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Author SHA1 Message Date
Zamil Majdy
1750c833ee fix(frontend): upgrade Docker Node.js from v21 (EOL) to v22 LTS (#12561)
## Summary
Upgrade the frontend **Docker image** from **Node.js v21** (EOL since
June 2024) to **Node.js v22 LTS** (supported through April 2027).

> **Scope:** This only affects the **Dockerfile** used for local
development (`docker compose`) and CI. It does **not** affect Vercel
(which manages its own Node.js runtime) or Kubernetes (the frontend Helm
chart was removed in Dec 2025 — the frontend is deployed exclusively via
Vercel).

## Why
- Node v21.7.3 has a **known TransformStream race condition bug**
causing `TypeError: controller[kState].transformAlgorithm is not a
function` — this is
[BUILDER-3KF](https://significant-gravitas.sentry.io/issues/BUILDER-3KF)
with **567,000+ Sentry events**
- The error is entirely in Node.js internals
(`node:internal/webstreams/transformstream`), zero first-party code
- Node 21 is **not an LTS release** and has been EOL since June 2024
- `package.json` already declares `"engines": { "node": "22.x" }` — the
Dockerfile was inconsistent
- Node 22.x LTS (v22.22.1) fixes the TransformStream bug
- Next.js 15.4.x requires Node 18.18+, so Node 22 is fully compatible

## Changes
- `autogpt_platform/frontend/Dockerfile`: `node:21-alpine` →
`node:22.22-alpine3.23` (both `base` and `prod` stages)

## Test plan
- [ ] Verify frontend Docker image builds successfully via `docker
compose`
- [ ] Verify frontend starts and serves pages correctly in local Docker
environment
- [ ] Monitor Sentry for BUILDER-3KF — should drop to zero for
Docker-based runs
2026-03-27 13:11:23 +07:00
2623 changed files with 825425 additions and 69899 deletions

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../.claude/skills

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@@ -1,10 +0,0 @@
{
"permissions": {
"allowedTools": [
"Read", "Grep", "Glob",
"Bash(ls:*)", "Bash(cat:*)", "Bash(grep:*)", "Bash(find:*)",
"Bash(git status:*)", "Bash(git diff:*)", "Bash(git log:*)", "Bash(git worktree:*)",
"Bash(tmux:*)", "Bash(sleep:*)", "Bash(branchlet:*)"
]
}
}

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@@ -1,106 +0,0 @@
---
name: open-pr
description: Open a pull request with proper PR template, test coverage, and review workflow. Guides agents through creating a PR that follows repo conventions, ensures existing behaviors aren't broken, covers new behaviors with tests, and handles review via bot when local testing isn't possible. TRIGGER when user asks to "open a PR", "create a PR", "make a PR", "submit a PR", "open pull request", "push and create PR", or any variation of opening/submitting a pull request.
user-invocable: true
args: "[base-branch] — optional target branch (defaults to dev)."
metadata:
author: autogpt-team
version: "1.0.0"
---
# Open a Pull Request
## Step 1: Pre-flight checks
Before opening the PR:
1. Ensure all changes are committed
2. Ensure the branch is pushed to the remote (`git push -u origin <branch>`)
3. Run linters/formatters across the whole repo (not just changed files) and commit any fixes
## Step 2: Test coverage
**This is critical.** Before opening the PR, verify:
### Existing behavior is not broken
- Identify which modules/components your changes touch
- Run the existing test suites for those areas
- If tests fail, fix them before opening the PR — do not open a PR with known regressions
### New behavior has test coverage
- Every new feature, endpoint, or behavior change needs tests
- If you added a new block, add tests for that block
- If you changed API behavior, add or update API tests
- If you changed frontend behavior, verify it doesn't break existing flows
If you cannot run the full test suite locally, note which tests you ran and which you couldn't in the test plan.
## Step 3: Create the PR using the repo template
Read the canonical PR template at `.github/PULL_REQUEST_TEMPLATE.md` and use it **verbatim** as your PR body:
1. Read the template: `cat .github/PULL_REQUEST_TEMPLATE.md`
2. Preserve the exact section titles and formatting, including:
- `### Why / What / How`
- `### Changes 🏗️`
- `### Checklist 📋`
3. Replace HTML comment prompts (`<!-- ... -->`) with actual content; do not leave them in
4. **Do not pre-check boxes** — leave all checkboxes as `- [ ]` until each step is actually completed
5. Do not alter the template structure, rename sections, or remove any checklist items
**PR title must use conventional commit format** (e.g., `feat(backend): add new block`, `fix(frontend): resolve routing bug`, `dx(skills): update PR workflow`). See CLAUDE.md for the full list of scopes.
Use `gh pr create` with the base branch (defaults to `dev` if no `[base-branch]` was provided). Use `--body-file` to avoid shell interpretation of backticks and special characters:
```bash
BASE_BRANCH="${BASE_BRANCH:-dev}"
PR_BODY=$(mktemp)
cat > "$PR_BODY" << 'PREOF'
<filled-in template from .github/PULL_REQUEST_TEMPLATE.md>
PREOF
gh pr create --base "$BASE_BRANCH" --title "<type>(scope): short description" --body-file "$PR_BODY"
rm "$PR_BODY"
```
## Step 4: Review workflow
### If you have a workspace that allows testing (docker, running backend, etc.)
- Run `/pr-test` to do E2E manual testing of the PR using docker compose, agent-browser, and API calls. This is the most thorough way to validate your changes before review.
- After testing, run `/pr-review` to self-review the PR for correctness, security, code quality, and testing gaps before requesting human review.
### If you do NOT have a workspace that allows testing
This is common for agents running in worktrees without a full stack. In this case:
1. Run `/pr-review` locally to catch obvious issues before pushing
2. **Comment `/review` on the PR** after creating it to trigger the review bot
3. **Poll for the review** rather than blindly waiting — check for new review comments every 30 seconds using `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` and the GraphQL inline threads query. The bot typically responds within 30 minutes, but polling lets the agent react as soon as it arrives.
4. Do NOT proceed or merge until the bot review comes back
5. Address any issues the bot raises — use `/pr-address` which has a full polling loop with CI + comment tracking
```bash
# After creating the PR:
PR_NUMBER=$(gh pr view --json number -q .number)
gh pr comment "$PR_NUMBER" --body "/review"
# Then use /pr-address to poll for and address the review when it arrives
```
## Step 5: Address review feedback
Once the review bot or human reviewers leave comments:
- Run `/pr-address` to address review comments. It will loop until CI is green and all comments are resolved.
- Do not merge without human approval.
## Related skills
| Skill | When to use |
|---|---|
| `/pr-test` | E2E testing with docker compose, agent-browser, API calls — use when you have a running workspace |
| `/pr-review` | Review for correctness, security, code quality — use before requesting human review |
| `/pr-address` | Address reviewer comments and loop until CI green — use after reviews come in |
## Step 6: Post-creation
After the PR is created and review is triggered:
- Share the PR URL with the user
- If waiting on the review bot, let the user know the expected wait time (~30 min)
- Do not merge without human approval

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@@ -1,195 +0,0 @@
---
name: setup-repo
description: Initialize a worktree-based repo layout for parallel development. Creates a main worktree, a reviews worktree for PR reviews, and N numbered work branches. Handles .env creation, dependency installation, and branchlet config. TRIGGER when user asks to set up the repo from scratch, initialize worktrees, bootstrap their dev environment, "setup repo", "setup worktrees", "initialize dev environment", "set up branches", or when a freshly cloned repo has no sibling worktrees.
user-invocable: true
args: "No arguments — interactive setup via prompts."
metadata:
author: autogpt-team
version: "1.0.0"
---
# Repository Setup
This skill sets up a worktree-based development layout from a freshly cloned repo. It creates:
- A **main** worktree (the primary checkout)
- A **reviews** worktree (for PR reviews)
- **N work branches** (branch1..branchN) for parallel development
## Step 1: Identify the repo
Determine the repo root and parent directory:
```bash
ROOT=$(git rev-parse --show-toplevel)
REPO_NAME=$(basename "$ROOT")
PARENT=$(dirname "$ROOT")
```
Detect if the repo is already inside a worktree layout by counting sibling worktrees (not just checking the directory name, which could be anything):
```bash
# Count worktrees that are siblings (live under $PARENT but aren't $ROOT itself)
SIBLING_COUNT=$(git worktree list --porcelain 2>/dev/null | grep "^worktree " | grep -c "$PARENT/" || true)
if [ "$SIBLING_COUNT" -gt 1 ]; then
echo "INFO: Existing worktree layout detected at $PARENT ($SIBLING_COUNT worktrees)"
# Use $ROOT as-is; skip renaming/restructuring
else
echo "INFO: Fresh clone detected, proceeding with setup"
fi
```
## Step 2: Ask the user questions
Use AskUserQuestion to gather setup preferences:
1. **How many parallel work branches do you need?** (Options: 4, 8, 16, or custom)
- These become `branch1` through `branchN`
2. **Which branch should be the base?** (Options: origin/master, origin/dev, or custom)
- All work branches and reviews will start from this
## Step 3: Fetch and set up branches
```bash
cd "$ROOT"
git fetch origin
# Create the reviews branch from base (skip if already exists)
if git show-ref --verify --quiet refs/heads/reviews; then
echo "INFO: Branch 'reviews' already exists, skipping"
else
git branch reviews <base-branch>
fi
# Create numbered work branches from base (skip if already exists)
for i in $(seq 1 "$COUNT"); do
if git show-ref --verify --quiet "refs/heads/branch$i"; then
echo "INFO: Branch 'branch$i' already exists, skipping"
else
git branch "branch$i" <base-branch>
fi
done
```
## Step 4: Create worktrees
Create worktrees as siblings to the main checkout:
```bash
if [ -d "$PARENT/reviews" ]; then
echo "INFO: Worktree '$PARENT/reviews' already exists, skipping"
else
git worktree add "$PARENT/reviews" reviews
fi
for i in $(seq 1 "$COUNT"); do
if [ -d "$PARENT/branch$i" ]; then
echo "INFO: Worktree '$PARENT/branch$i' already exists, skipping"
else
git worktree add "$PARENT/branch$i" "branch$i"
fi
done
```
## Step 5: Set up environment files
**Do NOT assume .env files exist.** For each worktree (including main if needed):
1. Check if `.env` exists in the source worktree for each path
2. If `.env` exists, copy it
3. If only `.env.default` or `.env.example` exists, copy that as `.env`
4. If neither exists, warn the user and list which env files are missing
Env file locations to check (same as the `/worktree` skill — keep these in sync):
- `autogpt_platform/.env`
- `autogpt_platform/backend/.env`
- `autogpt_platform/frontend/.env`
> **Note:** This env copying logic intentionally mirrors the `/worktree` skill's approach. If you update the path list or fallback logic here, update `/worktree` as well.
```bash
SOURCE="$ROOT"
WORKTREES="reviews"
for i in $(seq 1 "$COUNT"); do WORKTREES="$WORKTREES branch$i"; done
FOUND_ANY_ENV=0
for wt in $WORKTREES; do
TARGET="$PARENT/$wt"
for envpath in autogpt_platform autogpt_platform/backend autogpt_platform/frontend; do
if [ -f "$SOURCE/$envpath/.env" ]; then
FOUND_ANY_ENV=1
cp "$SOURCE/$envpath/.env" "$TARGET/$envpath/.env"
elif [ -f "$SOURCE/$envpath/.env.default" ]; then
FOUND_ANY_ENV=1
cp "$SOURCE/$envpath/.env.default" "$TARGET/$envpath/.env"
echo "NOTE: $wt/$envpath/.env was created from .env.default — you may need to edit it"
elif [ -f "$SOURCE/$envpath/.env.example" ]; then
FOUND_ANY_ENV=1
cp "$SOURCE/$envpath/.env.example" "$TARGET/$envpath/.env"
echo "NOTE: $wt/$envpath/.env was created from .env.example — you may need to edit it"
else
echo "WARNING: No .env, .env.default, or .env.example found at $SOURCE/$envpath/"
fi
done
done
if [ "$FOUND_ANY_ENV" -eq 0 ]; then
echo "WARNING: No environment files or templates were found in the source worktree."
# Use AskUserQuestion to confirm: "Continue setup without env files?"
# If the user declines, stop here and let them set up .env files first.
fi
```
## Step 6: Copy branchlet config
Copy `.branchlet.json` from main to each worktree so branchlet can manage sub-worktrees:
```bash
if [ -f "$ROOT/.branchlet.json" ]; then
for wt in $WORKTREES; do
cp "$ROOT/.branchlet.json" "$PARENT/$wt/.branchlet.json"
done
fi
```
## Step 7: Install dependencies
Install deps in all worktrees. Run these sequentially per worktree:
```bash
for wt in $WORKTREES; do
TARGET="$PARENT/$wt"
echo "=== Installing deps for $wt ==="
(cd "$TARGET/autogpt_platform/autogpt_libs" && poetry install) &&
(cd "$TARGET/autogpt_platform/backend" && poetry install && poetry run prisma generate) &&
(cd "$TARGET/autogpt_platform/frontend" && pnpm install) &&
echo "=== Done: $wt ===" ||
echo "=== FAILED: $wt ==="
done
```
This is slow. Run in background if possible and notify when complete.
## Step 8: Verify and report
After setup, verify and report to the user:
```bash
git worktree list
```
Summarize:
- Number of worktrees created
- Which env files were copied vs created from defaults vs missing
- Any warnings or errors encountered
## Final directory layout
```
parent/
main/ # Primary checkout (already exists)
reviews/ # PR review worktree
branch1/ # Work branch 1
branch2/ # Work branch 2
...
branchN/ # Work branch N
```

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@@ -6,19 +6,11 @@ on:
paths:
- '.github/workflows/classic-autogpt-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/direct_benchmark/**'
- 'classic/forge/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-autogpt-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/direct_benchmark/**'
- 'classic/forge/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
concurrency:
group: ${{ format('classic-autogpt-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -27,22 +19,47 @@ concurrency:
defaults:
run:
shell: bash
working-directory: classic
working-directory: classic/original_autogpt
jobs:
test:
permissions:
contents: read
timeout-minutes: 30
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
platform-os: [ubuntu, macos, macos-arm64, windows]
runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
steps:
- name: Start MinIO service
# Quite slow on macOS (2~4 minutes to set up Docker)
# - name: Set up Docker (macOS)
# if: runner.os == 'macOS'
# uses: crazy-max/ghaction-setup-docker@v3
- name: Start MinIO service (Linux)
if: runner.os == 'Linux'
working-directory: '.'
run: |
docker pull minio/minio:edge-cicd
docker run -d -p 9000:9000 minio/minio:edge-cicd
- name: Start MinIO service (macOS)
if: runner.os == 'macOS'
working-directory: ${{ runner.temp }}
run: |
brew install minio/stable/minio
mkdir data
minio server ./data &
# No MinIO on Windows:
# - Windows doesn't support running Linux Docker containers
# - It doesn't seem possible to start background processes on Windows. They are
# killed after the step returns.
# See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
- name: Checkout repository
uses: actions/checkout@v4
with:
@@ -54,23 +71,41 @@ jobs:
git config --global user.name "Auto-GPT-Bot"
git config --global user.email "github-bot@agpt.co"
- name: Set up Python 3.12
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: "3.12"
python-version: ${{ matrix.python-version }}
- id: get_date
name: Get date
run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
- name: Set up Python dependency cache
# On Windows, unpacking cached dependencies takes longer than just installing them
if: runner.os != 'Windows'
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
key: poetry-${{ runner.os }}-${{ hashFiles('classic/original_autogpt/poetry.lock') }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
if [ "${{ runner.os }}" = "macOS" ]; then
PATH="$HOME/.local/bin:$PATH"
echo "$HOME/.local/bin" >> $GITHUB_PATH
fi
- name: Install Poetry (Windows)
if: runner.os == 'Windows'
shell: pwsh
run: |
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
$env:PATH += ";$env:APPDATA\Python\Scripts"
echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
- name: Install Python dependencies
run: poetry install
@@ -81,13 +116,12 @@ jobs:
--cov=autogpt --cov-branch --cov-report term-missing --cov-report xml \
--numprocesses=logical --durations=10 \
--junitxml=junit.xml -o junit_family=legacy \
original_autogpt/tests/unit original_autogpt/tests/integration
tests/unit tests/integration
env:
CI: true
PLAIN_OUTPUT: True
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
S3_ENDPOINT_URL: http://127.0.0.1:9000
S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
AWS_ACCESS_KEY_ID: minioadmin
AWS_SECRET_ACCESS_KEY: minioadmin
@@ -101,11 +135,11 @@ jobs:
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: autogpt-agent
flags: autogpt-agent,${{ runner.os }}
- name: Upload logs to artifact
if: always()
uses: actions/upload-artifact@v4
with:
name: test-logs
path: classic/logs/
path: classic/original_autogpt/logs/

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@@ -148,7 +148,7 @@ jobs:
--entrypoint poetry ${{ env.IMAGE_NAME }} run \
pytest -v --cov=autogpt --cov-branch --cov-report term-missing \
--numprocesses=4 --durations=10 \
original_autogpt/tests/unit original_autogpt/tests/integration 2>&1 | tee test_output.txt
tests/unit tests/integration 2>&1 | tee test_output.txt
test_failure=${PIPESTATUS[0]}

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@@ -10,9 +10,10 @@ on:
- '.github/workflows/classic-autogpts-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- 'classic/benchmark/**'
- 'classic/run'
- 'classic/cli.py'
- 'classic/setup.py'
- '!**/*.md'
pull_request:
branches: [ master, dev, release-* ]
@@ -20,9 +21,10 @@ on:
- '.github/workflows/classic-autogpts-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- 'classic/benchmark/**'
- 'classic/run'
- 'classic/cli.py'
- 'classic/setup.py'
- '!**/*.md'
defaults:
@@ -33,9 +35,13 @@ defaults:
jobs:
serve-agent-protocol:
runs-on: ubuntu-latest
strategy:
matrix:
agent-name: [ original_autogpt ]
fail-fast: false
timeout-minutes: 20
env:
min-python-version: '3.12'
min-python-version: '3.10'
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -49,22 +55,22 @@ jobs:
python-version: ${{ env.min-python-version }}
- name: Install Poetry
working-directory: ./classic/${{ matrix.agent-name }}/
run: |
curl -sSL https://install.python-poetry.org | python -
- name: Install dependencies
run: poetry install
- name: Run smoke tests with direct-benchmark
- name: Run regression tests
run: |
poetry run direct-benchmark run \
--strategies one_shot \
--models claude \
--tests ReadFile,WriteFile \
--json
./run agent start ${{ matrix.agent-name }}
cd ${{ matrix.agent-name }}
poetry run agbenchmark --mock --test=BasicRetrieval --test=Battleship --test=WebArenaTask_0
poetry run agbenchmark --test=WriteFile
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
AGENT_NAME: ${{ matrix.agent-name }}
REQUESTS_CA_BUNDLE: /etc/ssl/certs/ca-certificates.crt
NONINTERACTIVE_MODE: "true"
CI: true
HELICONE_CACHE_ENABLED: false
HELICONE_PROPERTY_AGENT: ${{ matrix.agent-name }}
REPORTS_FOLDER: ${{ format('../../reports/{0}', matrix.agent-name) }}
TELEMETRY_ENVIRONMENT: autogpt-ci
TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}

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@@ -1,24 +1,18 @@
name: Classic - Direct Benchmark CI
name: Classic - AGBenchmark CI
on:
push:
branches: [ master, dev, ci-test* ]
paths:
- 'classic/direct_benchmark/**'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- '!classic/benchmark/reports/**'
- .github/workflows/classic-benchmark-ci.yml
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
pull_request:
branches: [ master, dev, release-* ]
paths:
- 'classic/direct_benchmark/**'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- '!classic/benchmark/reports/**'
- .github/workflows/classic-benchmark-ci.yml
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
concurrency:
group: ${{ format('benchmark-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -29,16 +23,23 @@ defaults:
shell: bash
env:
min-python-version: '3.12'
min-python-version: '3.10'
jobs:
benchmark-tests:
runs-on: ubuntu-latest
test:
permissions:
contents: read
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
platform-os: [ubuntu, macos, macos-arm64, windows]
runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
defaults:
run:
shell: bash
working-directory: classic
working-directory: classic/benchmark
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -46,88 +47,71 @@ jobs:
fetch-depth: 0
submodules: true
- name: Set up Python ${{ env.min-python-version }}
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ env.min-python-version }}
python-version: ${{ matrix.python-version }}
- name: Set up Python dependency cache
# On Windows, unpacking cached dependencies takes longer than just installing them
if: runner.os != 'Windows'
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
key: poetry-${{ runner.os }}-${{ hashFiles('classic/benchmark/poetry.lock') }}
- name: Install Poetry
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
- name: Install dependencies
if [ "${{ runner.os }}" = "macOS" ]; then
PATH="$HOME/.local/bin:$PATH"
echo "$HOME/.local/bin" >> $GITHUB_PATH
fi
- name: Install Poetry (Windows)
if: runner.os == 'Windows'
shell: pwsh
run: |
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
$env:PATH += ";$env:APPDATA\Python\Scripts"
echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
- name: Install Python dependencies
run: poetry install
- name: Run basic benchmark tests
- name: Run pytest with coverage
run: |
echo "Testing ReadFile challenge with one_shot strategy..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--tests ReadFile \
--json
echo "Testing WriteFile challenge..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--tests WriteFile \
--json
poetry run pytest -vv \
--cov=agbenchmark --cov-branch --cov-report term-missing --cov-report xml \
--durations=10 \
--junitxml=junit.xml -o junit_family=legacy \
tests
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
NONINTERACTIVE_MODE: "true"
- name: Test category filtering
run: |
echo "Testing coding category..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--categories coding \
--tests ReadFile,WriteFile \
--json
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
NONINTERACTIVE_MODE: "true"
- name: Upload test results to Codecov
if: ${{ !cancelled() }} # Run even if tests fail
uses: codecov/test-results-action@v1
with:
token: ${{ secrets.CODECOV_TOKEN }}
- name: Test multiple strategies
run: |
echo "Testing multiple strategies..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot,plan_execute \
--models claude \
--tests ReadFile \
--parallel 2 \
--json
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
NONINTERACTIVE_MODE: "true"
- name: Upload coverage reports to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: agbenchmark,${{ runner.os }}
# Run regression tests on maintain challenges
regression-tests:
self-test-with-agent:
runs-on: ubuntu-latest
timeout-minutes: 45
if: github.ref == 'refs/heads/master' || github.ref == 'refs/heads/dev'
defaults:
run:
shell: bash
working-directory: classic
strategy:
matrix:
agent-name: [forge]
fail-fast: false
timeout-minutes: 20
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -140,31 +124,53 @@ jobs:
with:
python-version: ${{ env.min-python-version }}
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
- name: Install Poetry
run: |
curl -sSL https://install.python-poetry.org | python3 -
- name: Install dependencies
run: poetry install
curl -sSL https://install.python-poetry.org | python -
- name: Run regression tests
working-directory: classic
run: |
echo "Running regression tests (previously beaten challenges)..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--maintain \
--parallel 4 \
--json
./run agent start ${{ matrix.agent-name }}
cd ${{ matrix.agent-name }}
set +e # Ignore non-zero exit codes and continue execution
echo "Running the following command: poetry run agbenchmark --maintain --mock"
poetry run agbenchmark --maintain --mock
EXIT_CODE=$?
set -e # Stop ignoring non-zero exit codes
# Check if the exit code was 5, and if so, exit with 0 instead
if [ $EXIT_CODE -eq 5 ]; then
echo "regression_tests.json is empty."
fi
echo "Running the following command: poetry run agbenchmark --mock"
poetry run agbenchmark --mock
echo "Running the following command: poetry run agbenchmark --mock --category=data"
poetry run agbenchmark --mock --category=data
echo "Running the following command: poetry run agbenchmark --mock --category=coding"
poetry run agbenchmark --mock --category=coding
# echo "Running the following command: poetry run agbenchmark --test=WriteFile"
# poetry run agbenchmark --test=WriteFile
cd ../benchmark
poetry install
echo "Adding the BUILD_SKILL_TREE environment variable. This will attempt to add new elements in the skill tree. If new elements are added, the CI fails because they should have been pushed"
export BUILD_SKILL_TREE=true
# poetry run agbenchmark --mock
# CHANGED=$(git diff --name-only | grep -E '(agbenchmark/challenges)|(../classic/frontend/assets)') || echo "No diffs"
# if [ ! -z "$CHANGED" ]; then
# echo "There are unstaged changes please run agbenchmark and commit those changes since they are needed."
# echo "$CHANGED"
# exit 1
# else
# echo "No unstaged changes."
# fi
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
NONINTERACTIVE_MODE: "true"
TELEMETRY_ENVIRONMENT: autogpt-benchmark-ci
TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}

View File

@@ -6,15 +6,13 @@ on:
paths:
- '.github/workflows/classic-forge-ci.yml'
- 'classic/forge/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- '!classic/forge/tests/vcr_cassettes'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-forge-ci.yml'
- 'classic/forge/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- '!classic/forge/tests/vcr_cassettes'
concurrency:
group: ${{ format('forge-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -23,60 +21,131 @@ concurrency:
defaults:
run:
shell: bash
working-directory: classic
working-directory: classic/forge
jobs:
test:
permissions:
contents: read
timeout-minutes: 30
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
platform-os: [ubuntu, macos, macos-arm64, windows]
runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
steps:
- name: Start MinIO service
# Quite slow on macOS (2~4 minutes to set up Docker)
# - name: Set up Docker (macOS)
# if: runner.os == 'macOS'
# uses: crazy-max/ghaction-setup-docker@v3
- name: Start MinIO service (Linux)
if: runner.os == 'Linux'
working-directory: '.'
run: |
docker pull minio/minio:edge-cicd
docker run -d -p 9000:9000 minio/minio:edge-cicd
- name: Start MinIO service (macOS)
if: runner.os == 'macOS'
working-directory: ${{ runner.temp }}
run: |
brew install minio/stable/minio
mkdir data
minio server ./data &
# No MinIO on Windows:
# - Windows doesn't support running Linux Docker containers
# - It doesn't seem possible to start background processes on Windows. They are
# killed after the step returns.
# See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true
- name: Set up Python 3.12
- name: Checkout cassettes
if: ${{ startsWith(github.event_name, 'pull_request') }}
env:
PR_BASE: ${{ github.event.pull_request.base.ref }}
PR_BRANCH: ${{ github.event.pull_request.head.ref }}
PR_AUTHOR: ${{ github.event.pull_request.user.login }}
run: |
cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
cassette_base_branch="${PR_BASE}"
cd tests/vcr_cassettes
if ! git ls-remote --exit-code --heads origin $cassette_base_branch ; then
cassette_base_branch="master"
fi
if git ls-remote --exit-code --heads origin $cassette_branch ; then
git fetch origin $cassette_branch
git fetch origin $cassette_base_branch
git checkout $cassette_branch
# Pick non-conflicting cassette updates from the base branch
git merge --no-commit --strategy-option=ours origin/$cassette_base_branch
echo "Using cassettes from mirror branch '$cassette_branch'," \
"synced to upstream branch '$cassette_base_branch'."
else
git checkout -b $cassette_branch
echo "Branch '$cassette_branch' does not exist in cassette submodule." \
"Using cassettes from '$cassette_base_branch'."
fi
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: "3.12"
python-version: ${{ matrix.python-version }}
- name: Set up Python dependency cache
# On Windows, unpacking cached dependencies takes longer than just installing them
if: runner.os != 'Windows'
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
key: poetry-${{ runner.os }}-${{ hashFiles('classic/forge/poetry.lock') }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
if [ "${{ runner.os }}" = "macOS" ]; then
PATH="$HOME/.local/bin:$PATH"
echo "$HOME/.local/bin" >> $GITHUB_PATH
fi
- name: Install Poetry (Windows)
if: runner.os == 'Windows'
shell: pwsh
run: |
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
$env:PATH += ";$env:APPDATA\Python\Scripts"
echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
- name: Install Python dependencies
run: poetry install
- name: Install Playwright browsers
run: poetry run playwright install chromium
- name: Run pytest with coverage
run: |
poetry run pytest -vv \
--cov=forge --cov-branch --cov-report term-missing --cov-report xml \
--durations=10 \
--junitxml=junit.xml -o junit_family=legacy \
forge/forge forge/tests
forge
env:
CI: true
PLAIN_OUTPUT: True
# API keys - tests that need these will skip if not available
# Secrets are not available to fork PRs (GitHub security feature)
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
S3_ENDPOINT_URL: http://127.0.0.1:9000
S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
AWS_ACCESS_KEY_ID: minioadmin
AWS_SECRET_ACCESS_KEY: minioadmin
@@ -90,11 +159,85 @@ jobs:
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: forge
flags: forge,${{ runner.os }}
- id: setup_git_auth
name: Set up git token authentication
# Cassettes may be pushed even when tests fail
if: success() || failure()
run: |
config_key="http.${{ github.server_url }}/.extraheader"
if [ "${{ runner.os }}" = 'macOS' ]; then
base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64)
else
base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64 -w0)
fi
git config "$config_key" \
"Authorization: Basic $base64_pat"
cd tests/vcr_cassettes
git config "$config_key" \
"Authorization: Basic $base64_pat"
echo "config_key=$config_key" >> $GITHUB_OUTPUT
- id: push_cassettes
name: Push updated cassettes
# For pull requests, push updated cassettes even when tests fail
if: github.event_name == 'push' || (! github.event.pull_request.head.repo.fork && (success() || failure()))
env:
PR_BRANCH: ${{ github.event.pull_request.head.ref }}
PR_AUTHOR: ${{ github.event.pull_request.user.login }}
run: |
if [ "${{ startsWith(github.event_name, 'pull_request') }}" = "true" ]; then
is_pull_request=true
cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
else
cassette_branch="${{ github.ref_name }}"
fi
cd tests/vcr_cassettes
# Commit & push changes to cassettes if any
if ! git diff --quiet; then
git add .
git commit -m "Auto-update cassettes"
git push origin HEAD:$cassette_branch
if [ ! $is_pull_request ]; then
cd ../..
git add tests/vcr_cassettes
git commit -m "Update cassette submodule"
git push origin HEAD:$cassette_branch
fi
echo "updated=true" >> $GITHUB_OUTPUT
else
echo "updated=false" >> $GITHUB_OUTPUT
echo "No cassette changes to commit"
fi
- name: Post Set up git token auth
if: steps.setup_git_auth.outcome == 'success'
run: |
git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
git submodule foreach git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
- name: Apply "behaviour change" label and comment on PR
if: ${{ startsWith(github.event_name, 'pull_request') }}
run: |
PR_NUMBER="${{ github.event.pull_request.number }}"
TOKEN="${{ secrets.PAT_REVIEW }}"
REPO="${{ github.repository }}"
if [[ "${{ steps.push_cassettes.outputs.updated }}" == "true" ]]; then
echo "Adding label and comment..."
echo $TOKEN | gh auth login --with-token
gh issue edit $PR_NUMBER --add-label "behaviour change"
gh issue comment $PR_NUMBER --body "You changed AutoGPT's behaviour on ${{ runner.os }}. The cassettes have been updated and will be merged to the submodule when this Pull Request gets merged."
fi
- name: Upload logs to artifact
if: always()
uses: actions/upload-artifact@v4
with:
name: test-logs
path: classic/logs/
path: classic/forge/logs/

View File

@@ -0,0 +1,60 @@
name: Classic - Frontend CI/CD
on:
push:
branches:
- master
- dev
- 'ci-test*' # This will match any branch that starts with "ci-test"
paths:
- 'classic/frontend/**'
- '.github/workflows/classic-frontend-ci.yml'
pull_request:
paths:
- 'classic/frontend/**'
- '.github/workflows/classic-frontend-ci.yml'
jobs:
build:
permissions:
contents: write
pull-requests: write
runs-on: ubuntu-latest
env:
BUILD_BRANCH: ${{ format('classic-frontend-build/{0}', github.ref_name) }}
steps:
- name: Checkout Repo
uses: actions/checkout@v4
- name: Setup Flutter
uses: subosito/flutter-action@v2
with:
flutter-version: '3.13.2'
- name: Build Flutter to Web
run: |
cd classic/frontend
flutter build web --base-href /app/
# - name: Commit and Push to ${{ env.BUILD_BRANCH }}
# if: github.event_name == 'push'
# run: |
# git config --local user.email "action@github.com"
# git config --local user.name "GitHub Action"
# git add classic/frontend/build/web
# git checkout -B ${{ env.BUILD_BRANCH }}
# git commit -m "Update frontend build to ${GITHUB_SHA:0:7}" -a
# git push -f origin ${{ env.BUILD_BRANCH }}
- name: Create PR ${{ env.BUILD_BRANCH }} -> ${{ github.ref_name }}
if: github.event_name == 'push'
uses: peter-evans/create-pull-request@v8
with:
add-paths: classic/frontend/build/web
base: ${{ github.ref_name }}
branch: ${{ env.BUILD_BRANCH }}
delete-branch: true
title: "Update frontend build in `${{ github.ref_name }}`"
body: "This PR updates the frontend build based on commit ${{ github.sha }}."
commit-message: "Update frontend build based on commit ${{ github.sha }}"

View File

@@ -7,9 +7,7 @@ on:
- '.github/workflows/classic-python-checks-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- 'classic/benchmark/**'
- '**.py'
- '!classic/forge/tests/vcr_cassettes'
pull_request:
@@ -18,9 +16,7 @@ on:
- '.github/workflows/classic-python-checks-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- 'classic/benchmark/**'
- '**.py'
- '!classic/forge/tests/vcr_cassettes'
@@ -31,13 +27,44 @@ concurrency:
defaults:
run:
shell: bash
working-directory: classic
jobs:
get-changed-parts:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- id: changes-in
name: Determine affected subprojects
uses: dorny/paths-filter@v3
with:
filters: |
original_autogpt:
- classic/original_autogpt/autogpt/**
- classic/original_autogpt/tests/**
- classic/original_autogpt/poetry.lock
forge:
- classic/forge/forge/**
- classic/forge/tests/**
- classic/forge/poetry.lock
benchmark:
- classic/benchmark/agbenchmark/**
- classic/benchmark/tests/**
- classic/benchmark/poetry.lock
outputs:
changed-parts: ${{ steps.changes-in.outputs.changes }}
lint:
needs: get-changed-parts
runs-on: ubuntu-latest
env:
min-python-version: "3.12"
min-python-version: "3.10"
strategy:
matrix:
sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
fail-fast: false
steps:
- name: Checkout repository
@@ -54,31 +81,42 @@ jobs:
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: ${{ runner.os }}-poetry-${{ hashFiles('classic/poetry.lock') }}
key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
- name: Install Python dependencies
run: poetry install
run: poetry -C classic/${{ matrix.sub-package }} install
# Lint
- name: Lint (isort)
run: poetry run isort --check .
working-directory: classic/${{ matrix.sub-package }}
- name: Lint (Black)
if: success() || failure()
run: poetry run black --check .
working-directory: classic/${{ matrix.sub-package }}
- name: Lint (Flake8)
if: success() || failure()
run: poetry run flake8 .
working-directory: classic/${{ matrix.sub-package }}
types:
needs: get-changed-parts
runs-on: ubuntu-latest
env:
min-python-version: "3.12"
min-python-version: "3.10"
strategy:
matrix:
sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
fail-fast: false
steps:
- name: Checkout repository
@@ -95,16 +133,19 @@ jobs:
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: ${{ runner.os }}-poetry-${{ hashFiles('classic/poetry.lock') }}
key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
- name: Install Python dependencies
run: poetry install
run: poetry -C classic/${{ matrix.sub-package }} install
# Typecheck
- name: Typecheck
if: success() || failure()
run: poetry run pyright
working-directory: classic/${{ matrix.sub-package }}

View File

@@ -269,14 +269,12 @@ jobs:
DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
- name: Run pytest with coverage
- name: Run pytest
run: |
if [[ "${{ runner.debug }}" == "1" ]]; then
poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG \
--cov=backend --cov-branch --cov-report term-missing --cov-report xml
poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG
else
poetry run pytest -s -vv \
--cov=backend --cov-branch --cov-report term-missing --cov-report xml
poetry run pytest -s -vv
fi
env:
LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
@@ -289,13 +287,11 @@ jobs:
REDIS_PORT: "6379"
ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
- name: Upload coverage reports to Codecov
if: ${{ !cancelled() }}
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: platform-backend
files: ./autogpt_platform/backend/coverage.xml
# - name: Upload coverage reports to Codecov
# uses: codecov/codecov-action@v4
# with:
# token: ${{ secrets.CODECOV_TOKEN }}
# flags: backend,${{ runner.os }}
env:
CI: true

View File

@@ -148,11 +148,3 @@ jobs:
- name: Run Integration Tests
run: pnpm test:unit
- name: Upload coverage reports to Codecov
if: ${{ !cancelled() }}
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: platform-frontend
files: ./autogpt_platform/frontend/coverage/cobertura-coverage.xml

10
.gitignore vendored
View File

@@ -3,7 +3,6 @@
classic/original_autogpt/keys.py
classic/original_autogpt/*.json
auto_gpt_workspace/*
.autogpt/
*.mpeg
.env
# Root .env files
@@ -17,7 +16,6 @@ log-ingestion.txt
/logs
*.log
*.mp3
!autogpt_platform/frontend/public/notification.mp3
mem.sqlite3
venvAutoGPT
@@ -161,10 +159,6 @@ CURRENT_BULLETIN.md
# AgBenchmark
classic/benchmark/agbenchmark/reports/
classic/reports/
classic/direct_benchmark/reports/
classic/.benchmark_workspaces/
classic/direct_benchmark/.benchmark_workspaces/
# Nodejs
package-lock.json
@@ -183,13 +177,9 @@ autogpt_platform/backend/settings.py
*.ign.*
.test-contents
**/.claude/settings.local.json
.claude/settings.local.json
CLAUDE.local.md
/autogpt_platform/backend/logs
# Test database
test.db
.next
# Implementation plans (generated by AI agents)
plans/

3
.gitmodules vendored Normal file
View File

@@ -0,0 +1,3 @@
[submodule "classic/forge/tests/vcr_cassettes"]
path = classic/forge/tests/vcr_cassettes
url = https://github.com/Significant-Gravitas/Auto-GPT-test-cassettes

View File

@@ -84,16 +84,51 @@ repos:
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic
alias: poetry-install-classic
name: Check & Install dependencies - Classic - AutoGPT
alias: poetry-install-classic-autogpt
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/poetry\.lock$" || exit 0;
poetry -C classic install
fi | grep -qE "^classic/(original_autogpt|forge)/poetry\.lock$" || exit 0;
poetry -C classic/original_autogpt install
'
# include forge source (since it's a path dependency)
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - Forge
alias: poetry-install-classic-forge
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/forge/poetry\.lock$" || exit 0;
poetry -C classic/forge install
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - Benchmark
alias: poetry-install-classic-benchmark
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/benchmark/poetry\.lock$" || exit 0;
poetry -C classic/benchmark install
'
always_run: true
language: system
@@ -188,10 +223,26 @@ repos:
language: system
- id: isort
name: Lint (isort) - Classic
alias: isort-classic
entry: bash -c 'cd classic && poetry run isort $(echo "$@" | sed "s|classic/||g")' --
files: ^classic/(original_autogpt|forge|direct_benchmark)/
name: Lint (isort) - Classic - AutoGPT
alias: isort-classic-autogpt
entry: poetry -P classic/original_autogpt run isort -p autogpt
files: ^classic/original_autogpt/
types: [file, python]
language: system
- id: isort
name: Lint (isort) - Classic - Forge
alias: isort-classic-forge
entry: poetry -P classic/forge run isort -p forge
files: ^classic/forge/
types: [file, python]
language: system
- id: isort
name: Lint (isort) - Classic - Benchmark
alias: isort-classic-benchmark
entry: poetry -P classic/benchmark run isort -p agbenchmark
files: ^classic/benchmark/
types: [file, python]
language: system
@@ -205,13 +256,26 @@ repos:
- repo: https://github.com/PyCQA/flake8
rev: 7.0.0
# Use consolidated flake8 config at classic/.flake8
# To have flake8 load the config of the individual subprojects, we have to call
# them separately.
hooks:
- id: flake8
name: Lint (Flake8) - Classic
alias: flake8-classic
files: ^classic/(original_autogpt|forge|direct_benchmark)/
args: [--config=classic/.flake8]
name: Lint (Flake8) - Classic - AutoGPT
alias: flake8-classic-autogpt
files: ^classic/original_autogpt/(autogpt|scripts|tests)/
args: [--config=classic/original_autogpt/.flake8]
- id: flake8
name: Lint (Flake8) - Classic - Forge
alias: flake8-classic-forge
files: ^classic/forge/(forge|tests)/
args: [--config=classic/forge/.flake8]
- id: flake8
name: Lint (Flake8) - Classic - Benchmark
alias: flake8-classic-benchmark
files: ^classic/benchmark/(agbenchmark|tests)/((?!reports).)*[/.]
args: [--config=classic/benchmark/.flake8]
- repo: local
hooks:
@@ -247,10 +311,29 @@ repos:
pass_filenames: false
- id: pyright
name: Typecheck - Classic
alias: pyright-classic
entry: poetry -C classic run pyright
files: ^classic/(original_autogpt|forge|direct_benchmark)/.*\.py$|^classic/poetry\.lock$
name: Typecheck - Classic - AutoGPT
alias: pyright-classic-autogpt
entry: poetry -C classic/original_autogpt run pyright
# include forge source (since it's a path dependency) but exclude *_test.py files:
files: ^(classic/original_autogpt/((autogpt|scripts|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
types: [file]
language: system
pass_filenames: false
- id: pyright
name: Typecheck - Classic - Forge
alias: pyright-classic-forge
entry: poetry -C classic/forge run pyright
files: ^classic/forge/(forge/|poetry\.lock$)
types: [file]
language: system
pass_filenames: false
- id: pyright
name: Typecheck - Classic - Benchmark
alias: pyright-classic-benchmark
entry: poetry -C classic/benchmark run pyright
files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
types: [file]
language: system
pass_filenames: false
@@ -277,9 +360,26 @@ repos:
# pass_filenames: false
# - id: pytest
# name: Run tests - Classic (excl. slow tests)
# alias: pytest-classic
# entry: bash -c 'cd classic && poetry run pytest -m "not slow"'
# files: ^classic/(original_autogpt|forge|direct_benchmark)/
# name: Run tests - Classic - AutoGPT (excl. slow tests)
# alias: pytest-classic-autogpt
# entry: bash -c 'cd classic/original_autogpt && poetry run pytest --cov=autogpt -m "not slow" tests/unit tests/integration'
# # include forge source (since it's a path dependency) but exclude *_test.py files:
# files: ^(classic/original_autogpt/((autogpt|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
# language: system
# pass_filenames: false
# - id: pytest
# name: Run tests - Classic - Forge (excl. slow tests)
# alias: pytest-classic-forge
# entry: bash -c 'cd classic/forge && poetry run pytest --cov=forge -m "not slow"'
# files: ^classic/forge/(forge/|tests/|poetry\.lock$)
# language: system
# pass_filenames: false
# - id: pytest
# name: Run tests - Classic - Benchmark
# alias: pytest-classic-benchmark
# entry: bash -c 'cd classic/benchmark && poetry run pytest --cov=benchmark'
# files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
# language: system
# pass_filenames: false

View File

@@ -1,6 +1,6 @@
# AutoGPT Platform Contribution Guide
This guide provides context for coding agents when updating the **autogpt_platform** folder.
This guide provides context for Codex when updating the **autogpt_platform** folder.
## Directory overview

View File

@@ -1 +0,0 @@
@AGENTS.md

View File

@@ -83,13 +83,13 @@ The AutoGPT frontend is where users interact with our powerful AI automation pla
**Agent Builder:** For those who want to customize, our intuitive, low-code interface allows you to design and configure your own AI agents.
**Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.
**Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.
**Deployment Controls:** Manage the lifecycle of your agents, from testing to production.
**Ready-to-Use Agents:** Don't want to build? Simply select from our library of pre-configured agents and put them to work immediately.
**Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.
**Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.
**Monitoring and Analytics:** Keep track of your agents' performance and gain insights to continually improve your automation processes.
@@ -130,7 +130,7 @@ These examples show just a glimpse of what you can achieve with AutoGPT! You can
All code and content within the `autogpt_platform` folder is licensed under the Polyform Shield License. This new project is our in-developlemt platform for building, deploying and managing agents.</br>_[Read more about this effort](https://agpt.co/blog/introducing-the-autogpt-platform)_
🦉 **MIT License:**
All other portions of the AutoGPT repository (i.e., everything outside the `autogpt_platform` folder) are licensed under the MIT License. This includes the original stand-alone AutoGPT Agent, along with projects such as [Forge](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/forge) and the [Direct Benchmark](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/direct_benchmark).</br>We also publish additional work under the MIT Licence in other repositories, such as [GravitasML](https://github.com/Significant-Gravitas/gravitasml) which is developed for and used in the AutoGPT Platform. See also our MIT Licenced [Code Ability](https://github.com/Significant-Gravitas/AutoGPT-Code-Ability) project.
All other portions of the AutoGPT repository (i.e., everything outside the `autogpt_platform` folder) are licensed under the MIT License. This includes the original stand-alone AutoGPT Agent, along with projects such as [Forge](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/forge), [agbenchmark](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/benchmark) and the [AutoGPT Classic GUI](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/frontend).</br>We also publish additional work under the MIT Licence in other repositories, such as [GravitasML](https://github.com/Significant-Gravitas/gravitasml) which is developed for and used in the AutoGPT Platform. See also our MIT Licenced [Code Ability](https://github.com/Significant-Gravitas/AutoGPT-Code-Ability) project.
---
### Mission
@@ -150,7 +150,7 @@ Be part of the revolution! **AutoGPT** is here to stay, at the forefront of AI i
## 🤖 AutoGPT Classic
> Below is information about the classic version of AutoGPT.
**🛠️ [Build your own Agent - Forge](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/forge)**
**🛠️ [Build your own Agent - Quickstart](classic/FORGE-QUICKSTART.md)**
### 🏗️ Forge
@@ -161,26 +161,46 @@ This guide will walk you through the process of creating your own agent and usin
📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/forge) about Forge
### 🎯 Direct Benchmark
### 🎯 Benchmark
**Measure your agent's performance!** The `direct_benchmark` harness tests agents directly without the agent protocol overhead. It supports multiple prompt strategies (one_shot, reflexion, plan_execute, tree_of_thoughts, etc.) and model configurations, with parallel execution and detailed reporting.
**Measure your agent's performance!** The `agbenchmark` can be used with any agent that supports the agent protocol, and the integration with the project's [CLI] makes it even easier to use with AutoGPT and forge-based agents. The benchmark offers a stringent testing environment. Our framework allows for autonomous, objective performance evaluations, ensuring your agents are primed for real-world action.
📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/direct_benchmark) about the Benchmark
<!-- TODO: insert visual demonstrating the benchmark -->
📦 [`agbenchmark`](https://pypi.org/project/agbenchmark/) on Pypi
&ensp;|&ensp;
📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/benchmark) about the Benchmark
### 💻 UI
**Makes agents easy to use!** The `frontend` gives you a user-friendly interface to control and monitor your agents. It connects to agents through the [agent protocol](#-agent-protocol), ensuring compatibility with many agents from both inside and outside of our ecosystem.
<!-- TODO: insert screenshot of front end -->
The frontend works out-of-the-box with all agents in the repo. Just use the [CLI] to run your agent of choice!
📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/frontend) about the Frontend
### ⌨️ CLI
[CLI]: #-cli
AutoGPT Classic is run via Poetry from the `classic/` directory:
To make it as easy as possible to use all of the tools offered by the repository, a CLI is included at the root of the repo:
```shell
cd classic
poetry install
poetry run autogpt # Interactive CLI mode
poetry run serve --debug # Agent Protocol server
$ ./run
Usage: cli.py [OPTIONS] COMMAND [ARGS]...
Options:
--help Show this message and exit.
Commands:
agent Commands to create, start and stop agents
benchmark Commands to start the benchmark and list tests and categories
setup Installs dependencies needed for your system.
```
See the [classic README](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic) for full setup instructions.
Just clone the repo, install dependencies with `./run setup`, and you should be good to go!
## 🤔 Questions? Problems? Suggestions?

View File

@@ -1,120 +0,0 @@
# AutoGPT Platform
This file provides guidance to coding agents when working with code in this repository.
## Repository Overview
AutoGPT Platform is a monorepo containing:
- **Backend** (`backend`): Python FastAPI server with async support
- **Frontend** (`frontend`): Next.js React application
- **Shared Libraries** (`autogpt_libs`): Common Python utilities
## Component Documentation
- **Backend**: See @backend/AGENTS.md for backend-specific commands, architecture, and development tasks
- **Frontend**: See @frontend/AGENTS.md for frontend-specific commands, architecture, and development patterns
## Key Concepts
1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
2. **Blocks**: Reusable components in `backend/backend/blocks/` that perform specific tasks
3. **Integrations**: OAuth and API connections stored per user
4. **Store**: Marketplace for sharing agent templates
5. **Virus Scanning**: ClamAV integration for file upload security
### Environment Configuration
#### Configuration Files
- **Backend**: `backend/.env.default` (defaults) → `backend/.env` (user overrides)
- **Frontend**: `frontend/.env.default` (defaults) → `frontend/.env` (user overrides)
- **Platform**: `.env.default` (Supabase/shared defaults) → `.env` (user overrides)
#### Docker Environment Loading Order
1. `.env.default` files provide base configuration (tracked in git)
2. `.env` files provide user-specific overrides (gitignored)
3. Docker Compose `environment:` sections provide service-specific overrides
4. Shell environment variables have highest precedence
#### Key Points
- All services use hardcoded defaults in docker-compose files (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
### Branching Strategy
- **`dev`** is the main development branch. All PRs should target `dev`.
- **`master`** is the production branch. Only used for production releases.
### Creating Pull Requests
- Create the PR against the `dev` branch of the repository.
- **Split PRs by concern** — each PR should have a single clear purpose. For example, "usage tracking" and "credit charging" should be separate PRs even if related. Combining multiple concerns makes it harder for reviewers to understand what belongs to what.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
- Use conventional commit messages (see below)
- **Structure the PR description with Why / What / How** — Why: the motivation (what problem it solves, what's broken/missing without it); What: high-level summary of changes; How: approach, key implementation details, or architecture decisions. Reviewers need all three to judge whether the approach fits the problem.
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description
- Always use `--body-file` to pass PR body — avoids shell interpretation of backticks and special characters:
```bash
PR_BODY=$(mktemp)
cat > "$PR_BODY" << 'PREOF'
## Summary
- use `backticks` freely here
PREOF
gh pr create --title "..." --body-file "$PR_BODY" --base dev
rm "$PR_BODY"
```
- Run the github pre-commit hooks to ensure code quality.
### Test-Driven Development (TDD)
When fixing a bug or adding a feature, follow a test-first approach:
1. **Write a failing test first** — create a test that reproduces the bug or validates the new behavior, marked with `@pytest.mark.xfail` (backend) or `.fixme` (Playwright). Run it to confirm it fails for the right reason.
2. **Implement the fix/feature** — write the minimal code to make the test pass.
3. **Remove the xfail marker** — once the test passes, remove the `xfail`/`.fixme` annotation and run the full test suite to confirm nothing else broke.
This ensures every change is covered by a test and that the test actually validates the intended behavior.
### Reviewing/Revising Pull Requests
Use `/pr-review` to review a PR or `/pr-address` to address comments.
When fetching comments manually:
- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` — top-level reviews
- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate` — inline review comments (always paginate to avoid missing comments beyond page 1)
- `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` — PR conversation comments
### Conventional Commits
Use this format for commit messages and Pull Request titles:
**Conventional Commit Types:**
- `feat`: Introduces a new feature to the codebase
- `fix`: Patches a bug in the codebase
- `refactor`: Code change that neither fixes a bug nor adds a feature; also applies to removing features
- `ci`: Changes to CI configuration
- `docs`: Documentation-only changes
- `dx`: Improvements to the developer experience
**Recommended Base Scopes:**
- `platform`: Changes affecting both frontend and backend
- `frontend`
- `backend`
- `infra`
- `blocks`: Modifications/additions of individual blocks
**Subscope Examples:**
- `backend/executor`
- `backend/db`
- `frontend/builder` (includes changes to the block UI component)
- `infra/prod`
Use these scopes and subscopes for clarity and consistency in commit messages.

View File

@@ -1 +1,120 @@
@AGENTS.md
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Repository Overview
AutoGPT Platform is a monorepo containing:
- **Backend** (`backend`): Python FastAPI server with async support
- **Frontend** (`frontend`): Next.js React application
- **Shared Libraries** (`autogpt_libs`): Common Python utilities
## Component Documentation
- **Backend**: See @backend/CLAUDE.md for backend-specific commands, architecture, and development tasks
- **Frontend**: See @frontend/CLAUDE.md for frontend-specific commands, architecture, and development patterns
## Key Concepts
1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
2. **Blocks**: Reusable components in `backend/backend/blocks/` that perform specific tasks
3. **Integrations**: OAuth and API connections stored per user
4. **Store**: Marketplace for sharing agent templates
5. **Virus Scanning**: ClamAV integration for file upload security
### Environment Configuration
#### Configuration Files
- **Backend**: `backend/.env.default` (defaults) → `backend/.env` (user overrides)
- **Frontend**: `frontend/.env.default` (defaults) → `frontend/.env` (user overrides)
- **Platform**: `.env.default` (Supabase/shared defaults) → `.env` (user overrides)
#### Docker Environment Loading Order
1. `.env.default` files provide base configuration (tracked in git)
2. `.env` files provide user-specific overrides (gitignored)
3. Docker Compose `environment:` sections provide service-specific overrides
4. Shell environment variables have highest precedence
#### Key Points
- All services use hardcoded defaults in docker-compose files (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
### Branching Strategy
- **`dev`** is the main development branch. All PRs should target `dev`.
- **`master`** is the production branch. Only used for production releases.
### Creating Pull Requests
- Create the PR against the `dev` branch of the repository.
- **Split PRs by concern** — each PR should have a single clear purpose. For example, "usage tracking" and "credit charging" should be separate PRs even if related. Combining multiple concerns makes it harder for reviewers to understand what belongs to what.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
- Use conventional commit messages (see below)
- **Structure the PR description with Why / What / How** — Why: the motivation (what problem it solves, what's broken/missing without it); What: high-level summary of changes; How: approach, key implementation details, or architecture decisions. Reviewers need all three to judge whether the approach fits the problem.
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description
- Always use `--body-file` to pass PR body — avoids shell interpretation of backticks and special characters:
```bash
PR_BODY=$(mktemp)
cat > "$PR_BODY" << 'PREOF'
## Summary
- use `backticks` freely here
PREOF
gh pr create --title "..." --body-file "$PR_BODY" --base dev
rm "$PR_BODY"
```
- Run the github pre-commit hooks to ensure code quality.
### Test-Driven Development (TDD)
When fixing a bug or adding a feature, follow a test-first approach:
1. **Write a failing test first** — create a test that reproduces the bug or validates the new behavior, marked with `@pytest.mark.xfail` (backend) or `.fixme` (Playwright). Run it to confirm it fails for the right reason.
2. **Implement the fix/feature** — write the minimal code to make the test pass.
3. **Remove the xfail marker** — once the test passes, remove the `xfail`/`.fixme` annotation and run the full test suite to confirm nothing else broke.
This ensures every change is covered by a test and that the test actually validates the intended behavior.
### Reviewing/Revising Pull Requests
Use `/pr-review` to review a PR or `/pr-address` to address comments.
When fetching comments manually:
- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` — top-level reviews
- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate` — inline review comments (always paginate to avoid missing comments beyond page 1)
- `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` — PR conversation comments
### Conventional Commits
Use this format for commit messages and Pull Request titles:
**Conventional Commit Types:**
- `feat`: Introduces a new feature to the codebase
- `fix`: Patches a bug in the codebase
- `refactor`: Code change that neither fixes a bug nor adds a feature; also applies to removing features
- `ci`: Changes to CI configuration
- `docs`: Documentation-only changes
- `dx`: Improvements to the developer experience
**Recommended Base Scopes:**
- `platform`: Changes affecting both frontend and backend
- `frontend`
- `backend`
- `infra`
- `blocks`: Modifications/additions of individual blocks
**Subscope Examples:**
- `backend/executor`
- `backend/db`
- `frontend/builder` (includes changes to the block UI component)
- `infra/prod`
Use these scopes and subscopes for clarity and consistency in commit messages.

View File

@@ -178,7 +178,6 @@ SMTP_USERNAME=
SMTP_PASSWORD=
# Business & Marketing Tools
AGENTMAIL_API_KEY=
APOLLO_API_KEY=
ENRICHLAYER_API_KEY=
AYRSHARE_API_KEY=

View File

@@ -1,227 +0,0 @@
# Backend
This file provides guidance to coding agents when working with the backend.
## Essential Commands
To run something with Python package dependencies you MUST use `poetry run ...`.
```bash
# Install dependencies
poetry install
# Run database migrations
poetry run prisma migrate dev
# Start all services (database, redis, rabbitmq, clamav)
docker compose up -d
# Run the backend as a whole
poetry run app
# Run tests
poetry run test
# Run specific test
poetry run pytest path/to/test_file.py::test_function_name
# Run block tests (tests that validate all blocks work correctly)
poetry run pytest backend/blocks/test/test_block.py -xvs
# Run tests for a specific block (e.g., GetCurrentTimeBlock)
poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs
# Lint and format
# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in @TESTING.md
### Creating/Updating Snapshots
When you first write a test or when the expected output changes:
```bash
poetry run pytest path/to/test.py --snapshot-update
```
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
## Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
- **Execution Engine**: Separate executor service processes agent workflows
- **Authentication**: JWT-based with Supabase integration
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
## Code Style
- **Top-level imports only** — no local/inner imports (lazy imports only for heavy optional deps like `openpyxl`)
- **Absolute imports** — use `from backend.module import ...` for cross-package imports. Single-dot relative (`from .sibling import ...`) is acceptable for sibling modules within the same package (e.g., blocks). Avoid double-dot relative imports (`from ..parent import ...`) — use the absolute path instead
- **No duck typing** — no `hasattr`/`getattr`/`isinstance` for type dispatch; use typed interfaces/unions/protocols
- **Pydantic models** over dataclass/namedtuple/dict for structured data
- **No linter suppressors** — no `# type: ignore`, `# noqa`, `# pyright: ignore`; fix the type/code
- **List comprehensions** over manual loop-and-append
- **Early return** — guard clauses first, avoid deep nesting
- **f-strings vs printf syntax in log statements** — Use `%s` for deferred interpolation in `debug` statements, f-strings elsewhere for readability: `logger.debug("Processing %s items", count)`, `logger.info(f"Processing {count} items")`
- **Sanitize error paths** — `os.path.basename()` in error messages to avoid leaking directory structure
- **TOCTOU awareness** — avoid check-then-act patterns for file access and credit charging
- **`Security()` vs `Depends()`** — use `Security()` for auth deps to get proper OpenAPI security spec
- **Redis pipelines** — `transaction=True` for atomicity on multi-step operations
- **`max(0, value)` guards** — for computed values that should never be negative
- **SSE protocol** — `data:` lines for frontend-parsed events (must match Zod schema), `: comment` lines for heartbeats/status
- **File length** — keep files under ~300 lines; if a file grows beyond this, split by responsibility (e.g. extract helpers, models, or a sub-module into a new file). Never keep appending to a long file.
- **Function length** — keep functions under ~40 lines; extract named helpers when a function grows longer. Long functions are a sign of mixed concerns, not complexity.
- **Top-down ordering** — define the main/public function or class first, then the helpers it uses below. A reader should encounter high-level logic before implementation details.
## Testing Approach
- Uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
- Mock at boundaries — mock where the symbol is **used**, not where it's **defined**
- After refactoring, update mock targets to match new module paths
- Use `AsyncMock` for async functions (`from unittest.mock import AsyncMock`)
### Test-Driven Development (TDD)
When fixing a bug or adding a feature, write the test **before** the implementation:
```python
# 1. Write a failing test marked xfail
@pytest.mark.xfail(reason="Bug #1234: widget crashes on empty input")
def test_widget_handles_empty_input():
result = widget.process("")
assert result == Widget.EMPTY_RESULT
# 2. Run it — confirm it fails (XFAIL)
# poetry run pytest path/to/test.py::test_widget_handles_empty_input -xvs
# 3. Implement the fix
# 4. Remove xfail, run again — confirm it passes
def test_widget_handles_empty_input():
result = widget.process("")
assert result == Widget.EMPTY_RESULT
```
This catches regressions and proves the fix actually works. **Every bug fix should include a test that would have caught it.**
## Database Schema
Key models (defined in `schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
- `AgentNode`: Individual nodes in a workflow
- `StoreListing`: Marketplace listings for sharing agents
## Environment Configuration
- **Backend**: `.env.default` (defaults) → `.env` (user overrides)
## Common Development Tasks
### Adding a new block
Follow the comprehensive [Block SDK Guide](@../../docs/platform/block-sdk-guide.md) which covers:
- Provider configuration with `ProviderBuilder`
- Block schema definition
- Authentication (API keys, OAuth, webhooks)
- Testing and validation
- File organization
Quick steps:
1. Create new file in `backend/blocks/`
2. Configure provider using `ProviderBuilder` in `_config.py`
3. Inherit from `Block` base class
4. Define input/output schemas using `BlockSchema`
5. Implement async `run` method
6. Generate unique block ID using `uuid.uuid4()`
7. Test with `poetry run pytest backend/blocks/test/test_block.py`
Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph-based editor or would they struggle to connect productively?
ex: do the inputs and outputs tie well together?
If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
#### Handling files in blocks with `store_media_file()`
When blocks need to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. The `return_format` parameter determines what you get back:
| Format | Use When | Returns |
|--------|----------|---------|
| `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
| `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
| `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |
**Examples:**
```python
# INPUT: Need to process file locally with ffmpeg
local_path = await store_media_file(
file=input_data.video,
execution_context=execution_context,
return_format="for_local_processing",
)
# local_path = "video.mp4" - use with Path/ffmpeg/etc
# INPUT: Need to send to external API like Replicate
image_b64 = await store_media_file(
file=input_data.image,
execution_context=execution_context,
return_format="for_external_api",
)
# image_b64 = "data:image/png;base64,iVBORw0..." - send to API
# OUTPUT: Returning result from block
result_url = await store_media_file(
file=generated_image_url,
execution_context=execution_context,
return_format="for_block_output",
)
yield "image_url", result_url
# In CoPilot: result_url = "workspace://abc123"
# In graphs: result_url = "data:image/png;base64,..."
```
**Key points:**
- `for_block_output` is the ONLY format that auto-adapts to execution context
- Always use `for_block_output` for block outputs unless you have a specific reason not to
- Never hardcode workspace checks - let `for_block_output` handle it
### Modifying the API
1. Update route in `backend/api/features/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
## Workspace & Media Files
**Read [Workspace & Media Architecture](../../docs/platform/workspace-media-architecture.md) when:**
- Working on CoPilot file upload/download features
- Building blocks that handle `MediaFileType` inputs/outputs
- Modifying `WorkspaceManager` or `store_media_file()`
- Debugging file persistence or virus scanning issues
Covers: `WorkspaceManager` (persistent storage with session scoping), `store_media_file()` (media normalization pipeline), and responsibility boundaries for virus scanning and persistence.
## Security Implementation
### Cache Protection Middleware
- Located in `backend/api/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
- Cacheable paths include: static assets (`static/*`, `_next/static/*`), health checks, public store pages, documentation
- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications

View File

@@ -1 +1,227 @@
@AGENTS.md
# CLAUDE.md - Backend
This file provides guidance to Claude Code when working with the backend.
## Essential Commands
To run something with Python package dependencies you MUST use `poetry run ...`.
```bash
# Install dependencies
poetry install
# Run database migrations
poetry run prisma migrate dev
# Start all services (database, redis, rabbitmq, clamav)
docker compose up -d
# Run the backend as a whole
poetry run app
# Run tests
poetry run test
# Run specific test
poetry run pytest path/to/test_file.py::test_function_name
# Run block tests (tests that validate all blocks work correctly)
poetry run pytest backend/blocks/test/test_block.py -xvs
# Run tests for a specific block (e.g., GetCurrentTimeBlock)
poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs
# Lint and format
# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in @TESTING.md
### Creating/Updating Snapshots
When you first write a test or when the expected output changes:
```bash
poetry run pytest path/to/test.py --snapshot-update
```
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
## Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
- **Execution Engine**: Separate executor service processes agent workflows
- **Authentication**: JWT-based with Supabase integration
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
## Code Style
- **Top-level imports only** — no local/inner imports (lazy imports only for heavy optional deps like `openpyxl`)
- **Absolute imports** — use `from backend.module import ...` for cross-package imports. Single-dot relative (`from .sibling import ...`) is acceptable for sibling modules within the same package (e.g., blocks). Avoid double-dot relative imports (`from ..parent import ...`) — use the absolute path instead
- **No duck typing** — no `hasattr`/`getattr`/`isinstance` for type dispatch; use typed interfaces/unions/protocols
- **Pydantic models** over dataclass/namedtuple/dict for structured data
- **No linter suppressors** — no `# type: ignore`, `# noqa`, `# pyright: ignore`; fix the type/code
- **List comprehensions** over manual loop-and-append
- **Early return** — guard clauses first, avoid deep nesting
- **f-strings vs printf syntax in log statements** — Use `%s` for deferred interpolation in `debug` statements, f-strings elsewhere for readability: `logger.debug("Processing %s items", count)`, `logger.info(f"Processing {count} items")`
- **Sanitize error paths** — `os.path.basename()` in error messages to avoid leaking directory structure
- **TOCTOU awareness** — avoid check-then-act patterns for file access and credit charging
- **`Security()` vs `Depends()`** — use `Security()` for auth deps to get proper OpenAPI security spec
- **Redis pipelines** — `transaction=True` for atomicity on multi-step operations
- **`max(0, value)` guards** — for computed values that should never be negative
- **SSE protocol** — `data:` lines for frontend-parsed events (must match Zod schema), `: comment` lines for heartbeats/status
- **File length** — keep files under ~300 lines; if a file grows beyond this, split by responsibility (e.g. extract helpers, models, or a sub-module into a new file). Never keep appending to a long file.
- **Function length** — keep functions under ~40 lines; extract named helpers when a function grows longer. Long functions are a sign of mixed concerns, not complexity.
- **Top-down ordering** — define the main/public function or class first, then the helpers it uses below. A reader should encounter high-level logic before implementation details.
## Testing Approach
- Uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
- Mock at boundaries — mock where the symbol is **used**, not where it's **defined**
- After refactoring, update mock targets to match new module paths
- Use `AsyncMock` for async functions (`from unittest.mock import AsyncMock`)
### Test-Driven Development (TDD)
When fixing a bug or adding a feature, write the test **before** the implementation:
```python
# 1. Write a failing test marked xfail
@pytest.mark.xfail(reason="Bug #1234: widget crashes on empty input")
def test_widget_handles_empty_input():
result = widget.process("")
assert result == Widget.EMPTY_RESULT
# 2. Run it — confirm it fails (XFAIL)
# poetry run pytest path/to/test.py::test_widget_handles_empty_input -xvs
# 3. Implement the fix
# 4. Remove xfail, run again — confirm it passes
def test_widget_handles_empty_input():
result = widget.process("")
assert result == Widget.EMPTY_RESULT
```
This catches regressions and proves the fix actually works. **Every bug fix should include a test that would have caught it.**
## Database Schema
Key models (defined in `schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
- `AgentNode`: Individual nodes in a workflow
- `StoreListing`: Marketplace listings for sharing agents
## Environment Configuration
- **Backend**: `.env.default` (defaults) → `.env` (user overrides)
## Common Development Tasks
### Adding a new block
Follow the comprehensive [Block SDK Guide](@../../docs/content/platform/block-sdk-guide.md) which covers:
- Provider configuration with `ProviderBuilder`
- Block schema definition
- Authentication (API keys, OAuth, webhooks)
- Testing and validation
- File organization
Quick steps:
1. Create new file in `backend/blocks/`
2. Configure provider using `ProviderBuilder` in `_config.py`
3. Inherit from `Block` base class
4. Define input/output schemas using `BlockSchema`
5. Implement async `run` method
6. Generate unique block ID using `uuid.uuid4()`
7. Test with `poetry run pytest backend/blocks/test/test_block.py`
Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph-based editor or would they struggle to connect productively?
ex: do the inputs and outputs tie well together?
If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
#### Handling files in blocks with `store_media_file()`
When blocks need to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. The `return_format` parameter determines what you get back:
| Format | Use When | Returns |
|--------|----------|---------|
| `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
| `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
| `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |
**Examples:**
```python
# INPUT: Need to process file locally with ffmpeg
local_path = await store_media_file(
file=input_data.video,
execution_context=execution_context,
return_format="for_local_processing",
)
# local_path = "video.mp4" - use with Path/ffmpeg/etc
# INPUT: Need to send to external API like Replicate
image_b64 = await store_media_file(
file=input_data.image,
execution_context=execution_context,
return_format="for_external_api",
)
# image_b64 = "data:image/png;base64,iVBORw0..." - send to API
# OUTPUT: Returning result from block
result_url = await store_media_file(
file=generated_image_url,
execution_context=execution_context,
return_format="for_block_output",
)
yield "image_url", result_url
# In CoPilot: result_url = "workspace://abc123"
# In graphs: result_url = "data:image/png;base64,..."
```
**Key points:**
- `for_block_output` is the ONLY format that auto-adapts to execution context
- Always use `for_block_output` for block outputs unless you have a specific reason not to
- Never hardcode workspace checks - let `for_block_output` handle it
### Modifying the API
1. Update route in `backend/api/features/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
## Workspace & Media Files
**Read [Workspace & Media Architecture](../../docs/platform/workspace-media-architecture.md) when:**
- Working on CoPilot file upload/download features
- Building blocks that handle `MediaFileType` inputs/outputs
- Modifying `WorkspaceManager` or `store_media_file()`
- Debugging file persistence or virus scanning issues
Covers: `WorkspaceManager` (persistent storage with session scoping), `store_media_file()` (media normalization pipeline), and responsibility boundaries for virus scanning and persistence.
## Security Implementation
### Cache Protection Middleware
- Located in `backend/api/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
- Cacheable paths include: static assets (`static/*`, `_next/static/*`), health checks, public store pages, documentation
- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications

View File

@@ -31,10 +31,7 @@ from backend.data.model import (
UserPasswordCredentials,
is_sdk_default,
)
from backend.integrations.credentials_store import (
is_system_credential,
provider_matches,
)
from backend.integrations.credentials_store import provider_matches
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
from backend.integrations.providers import ProviderName
@@ -621,11 +618,6 @@ async def delete_credential(
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if is_system_credential(cred_id):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="System-managed credentials cannot be deleted",
)
creds = await creds_manager.store.get_creds_by_id(auth.user_id, cred_id)
if not creds:
raise HTTPException(

View File

@@ -72,7 +72,7 @@ class RunAgentRequest(BaseModel):
def _create_ephemeral_session(user_id: str) -> ChatSession:
"""Create an ephemeral session for stateless API requests."""
return ChatSession.new(user_id, dry_run=False)
return ChatSession.new(user_id)
@tools_router.post(

View File

@@ -1,146 +0,0 @@
"""Admin endpoints for checking and resetting user CoPilot rate limit usage."""
import logging
from typing import Optional
from autogpt_libs.auth import get_user_id, requires_admin_user
from fastapi import APIRouter, Body, HTTPException, Security
from pydantic import BaseModel
from backend.copilot.config import ChatConfig
from backend.copilot.rate_limit import (
get_global_rate_limits,
get_usage_status,
reset_user_usage,
)
from backend.data.user import get_user_by_email, get_user_email_by_id
logger = logging.getLogger(__name__)
config = ChatConfig()
router = APIRouter(
prefix="/admin",
tags=["copilot", "admin"],
dependencies=[Security(requires_admin_user)],
)
class UserRateLimitResponse(BaseModel):
user_id: str
user_email: Optional[str] = None
daily_token_limit: int
weekly_token_limit: int
daily_tokens_used: int
weekly_tokens_used: int
async def _resolve_user_id(
user_id: Optional[str], email: Optional[str]
) -> tuple[str, Optional[str]]:
"""Resolve a user_id and email from the provided parameters.
Returns (user_id, email). Accepts either user_id or email; at least one
must be provided. When both are provided, ``email`` takes precedence.
"""
if email:
user = await get_user_by_email(email)
if not user:
raise HTTPException(
status_code=404, detail="No user found with the provided email."
)
return user.id, email
if not user_id:
raise HTTPException(
status_code=400,
detail="Either user_id or email query parameter is required.",
)
# We have a user_id; try to look up their email for display purposes.
# This is non-critical -- a failure should not block the response.
try:
resolved_email = await get_user_email_by_id(user_id)
except Exception:
logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
resolved_email = None
return user_id, resolved_email
@router.get(
"/rate_limit",
response_model=UserRateLimitResponse,
summary="Get User Rate Limit",
)
async def get_user_rate_limit(
user_id: Optional[str] = None,
email: Optional[str] = None,
admin_user_id: str = Security(get_user_id),
) -> UserRateLimitResponse:
"""Get a user's current usage and effective rate limits. Admin-only.
Accepts either ``user_id`` or ``email`` as a query parameter.
When ``email`` is provided the user is looked up by email first.
"""
resolved_id, resolved_email = await _resolve_user_id(user_id, email)
logger.info("Admin %s checking rate limit for user %s", admin_user_id, resolved_id)
daily_limit, weekly_limit = await get_global_rate_limits(
resolved_id, config.daily_token_limit, config.weekly_token_limit
)
usage = await get_usage_status(resolved_id, daily_limit, weekly_limit)
return UserRateLimitResponse(
user_id=resolved_id,
user_email=resolved_email,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_tokens_used=usage.daily.used,
weekly_tokens_used=usage.weekly.used,
)
@router.post(
"/rate_limit/reset",
response_model=UserRateLimitResponse,
summary="Reset User Rate Limit Usage",
)
async def reset_user_rate_limit(
user_id: str = Body(embed=True),
reset_weekly: bool = Body(False, embed=True),
admin_user_id: str = Security(get_user_id),
) -> UserRateLimitResponse:
"""Reset a user's daily usage counter (and optionally weekly). Admin-only."""
logger.info(
"Admin %s resetting rate limit for user %s (reset_weekly=%s)",
admin_user_id,
user_id,
reset_weekly,
)
try:
await reset_user_usage(user_id, reset_weekly=reset_weekly)
except Exception as e:
logger.exception("Failed to reset user usage")
raise HTTPException(status_code=500, detail="Failed to reset usage") from e
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
)
usage = await get_usage_status(user_id, daily_limit, weekly_limit)
try:
resolved_email = await get_user_email_by_id(user_id)
except Exception:
logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
resolved_email = None
return UserRateLimitResponse(
user_id=user_id,
user_email=resolved_email,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_tokens_used=usage.daily.used,
weekly_tokens_used=usage.weekly.used,
)

View File

@@ -1,263 +0,0 @@
import json
from types import SimpleNamespace
from unittest.mock import AsyncMock
import fastapi
import fastapi.testclient
import pytest
import pytest_mock
from autogpt_libs.auth.jwt_utils import get_jwt_payload
from pytest_snapshot.plugin import Snapshot
from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
from .rate_limit_admin_routes import router as rate_limit_admin_router
app = fastapi.FastAPI()
app.include_router(rate_limit_admin_router)
client = fastapi.testclient.TestClient(app)
_MOCK_MODULE = "backend.api.features.admin.rate_limit_admin_routes"
_TARGET_EMAIL = "target@example.com"
@pytest.fixture(autouse=True)
def setup_app_admin_auth(mock_jwt_admin):
"""Setup admin auth overrides for all tests in this module"""
app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
yield
app.dependency_overrides.clear()
def _mock_usage_status(
daily_used: int = 500_000, weekly_used: int = 3_000_000
) -> CoPilotUsageStatus:
from datetime import UTC, datetime, timedelta
now = datetime.now(UTC)
return CoPilotUsageStatus(
daily=UsageWindow(
used=daily_used, limit=2_500_000, resets_at=now + timedelta(hours=6)
),
weekly=UsageWindow(
used=weekly_used, limit=12_500_000, resets_at=now + timedelta(days=3)
),
)
def _patch_rate_limit_deps(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
daily_used: int = 500_000,
weekly_used: int = 3_000_000,
):
"""Patch the common rate-limit + user-lookup dependencies."""
mocker.patch(
f"{_MOCK_MODULE}.get_global_rate_limits",
new_callable=AsyncMock,
return_value=(2_500_000, 12_500_000),
)
mocker.patch(
f"{_MOCK_MODULE}.get_usage_status",
new_callable=AsyncMock,
return_value=_mock_usage_status(daily_used=daily_used, weekly_used=weekly_used),
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=_TARGET_EMAIL,
)
def test_get_rate_limit(
mocker: pytest_mock.MockerFixture,
configured_snapshot: Snapshot,
target_user_id: str,
) -> None:
"""Test getting rate limit and usage for a user."""
_patch_rate_limit_deps(mocker, target_user_id)
response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["user_email"] == _TARGET_EMAIL
assert data["daily_token_limit"] == 2_500_000
assert data["weekly_token_limit"] == 12_500_000
assert data["daily_tokens_used"] == 500_000
assert data["weekly_tokens_used"] == 3_000_000
configured_snapshot.assert_match(
json.dumps(data, indent=2, sort_keys=True) + "\n",
"get_rate_limit",
)
def test_get_rate_limit_by_email(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test looking up rate limits via email instead of user_id."""
_patch_rate_limit_deps(mocker, target_user_id)
mock_user = SimpleNamespace(id=target_user_id, email=_TARGET_EMAIL)
mocker.patch(
f"{_MOCK_MODULE}.get_user_by_email",
new_callable=AsyncMock,
return_value=mock_user,
)
response = client.get("/admin/rate_limit", params={"email": _TARGET_EMAIL})
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["user_email"] == _TARGET_EMAIL
assert data["daily_token_limit"] == 2_500_000
def test_get_rate_limit_by_email_not_found(
mocker: pytest_mock.MockerFixture,
) -> None:
"""Test that looking up a non-existent email returns 404."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_by_email",
new_callable=AsyncMock,
return_value=None,
)
response = client.get("/admin/rate_limit", params={"email": "nobody@example.com"})
assert response.status_code == 404
def test_get_rate_limit_no_params() -> None:
"""Test that omitting both user_id and email returns 400."""
response = client.get("/admin/rate_limit")
assert response.status_code == 400
def test_reset_user_usage_daily_only(
mocker: pytest_mock.MockerFixture,
configured_snapshot: Snapshot,
target_user_id: str,
) -> None:
"""Test resetting only daily usage (default behaviour)."""
mock_reset = mocker.patch(
f"{_MOCK_MODULE}.reset_user_usage",
new_callable=AsyncMock,
)
_patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=3_000_000)
response = client.post(
"/admin/rate_limit/reset",
json={"user_id": target_user_id},
)
assert response.status_code == 200
data = response.json()
assert data["daily_tokens_used"] == 0
# Weekly is untouched
assert data["weekly_tokens_used"] == 3_000_000
mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=False)
configured_snapshot.assert_match(
json.dumps(data, indent=2, sort_keys=True) + "\n",
"reset_user_usage_daily_only",
)
def test_reset_user_usage_daily_and_weekly(
mocker: pytest_mock.MockerFixture,
configured_snapshot: Snapshot,
target_user_id: str,
) -> None:
"""Test resetting both daily and weekly usage."""
mock_reset = mocker.patch(
f"{_MOCK_MODULE}.reset_user_usage",
new_callable=AsyncMock,
)
_patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=0)
response = client.post(
"/admin/rate_limit/reset",
json={"user_id": target_user_id, "reset_weekly": True},
)
assert response.status_code == 200
data = response.json()
assert data["daily_tokens_used"] == 0
assert data["weekly_tokens_used"] == 0
mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=True)
configured_snapshot.assert_match(
json.dumps(data, indent=2, sort_keys=True) + "\n",
"reset_user_usage_daily_and_weekly",
)
def test_reset_user_usage_redis_failure(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that Redis failure on reset returns 500."""
mocker.patch(
f"{_MOCK_MODULE}.reset_user_usage",
new_callable=AsyncMock,
side_effect=Exception("Redis connection refused"),
)
response = client.post(
"/admin/rate_limit/reset",
json={"user_id": target_user_id},
)
assert response.status_code == 500
def test_get_rate_limit_email_lookup_failure(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that failing to resolve a user email degrades gracefully."""
mocker.patch(
f"{_MOCK_MODULE}.get_global_rate_limits",
new_callable=AsyncMock,
return_value=(2_500_000, 12_500_000),
)
mocker.patch(
f"{_MOCK_MODULE}.get_usage_status",
new_callable=AsyncMock,
return_value=_mock_usage_status(),
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
side_effect=Exception("DB connection lost"),
)
response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["user_email"] is None
def test_admin_endpoints_require_admin_role(mock_jwt_user) -> None:
"""Test that rate limit admin endpoints require admin role."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
response = client.get("/admin/rate_limit", params={"user_id": "test"})
assert response.status_code == 403
response = client.post(
"/admin/rate_limit/reset",
json={"user_id": "test"},
)
assert response.status_code == 403

View File

@@ -11,7 +11,7 @@ from autogpt_libs import auth
from fastapi import APIRouter, HTTPException, Query, Response, Security
from fastapi.responses import StreamingResponse
from prisma.models import UserWorkspaceFile
from pydantic import BaseModel, ConfigDict, Field, field_validator
from pydantic import BaseModel, Field, field_validator
from backend.copilot import service as chat_service
from backend.copilot import stream_registry
@@ -20,7 +20,6 @@ from backend.copilot.executor.utils import enqueue_cancel_task, enqueue_copilot_
from backend.copilot.model import (
ChatMessage,
ChatSession,
ChatSessionMetadata,
append_and_save_message,
create_chat_session,
delete_chat_session,
@@ -31,14 +30,8 @@ from backend.copilot.model import (
from backend.copilot.rate_limit import (
CoPilotUsageStatus,
RateLimitExceeded,
acquire_reset_lock,
check_rate_limit,
get_daily_reset_count,
get_global_rate_limits,
get_usage_status,
increment_daily_reset_count,
release_reset_lock,
reset_daily_usage,
)
from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
from backend.copilot.tools.e2b_sandbox import kill_sandbox
@@ -66,16 +59,9 @@ from backend.copilot.tools.models import (
UnderstandingUpdatedResponse,
)
from backend.copilot.tracking import track_user_message
from backend.data.credit import UsageTransactionMetadata, get_user_credit_model
from backend.data.redis_client import get_redis_async
from backend.data.understanding import get_business_understanding
from backend.data.workspace import get_or_create_workspace
from backend.util.exceptions import InsufficientBalanceError, NotFoundError
from backend.util.settings import Settings
settings = Settings()
logger = logging.getLogger(__name__)
from backend.util.exceptions import NotFoundError
config = ChatConfig()
@@ -83,6 +69,8 @@ _UUID_RE = re.compile(
r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$", re.I
)
logger = logging.getLogger(__name__)
async def _validate_and_get_session(
session_id: str,
@@ -113,25 +101,12 @@ class StreamChatRequest(BaseModel):
) # Workspace file IDs attached to this message
class CreateSessionRequest(BaseModel):
"""Request model for creating a new chat session.
``dry_run`` is a **top-level** field — do not nest it inside ``metadata``.
Extra/unknown fields are rejected (422) to prevent silent mis-use.
"""
model_config = ConfigDict(extra="forbid")
dry_run: bool = False
class CreateSessionResponse(BaseModel):
"""Response model containing information on a newly created chat session."""
id: str
created_at: str
user_id: str | None
metadata: ChatSessionMetadata = ChatSessionMetadata()
class ActiveStreamInfo(BaseModel):
@@ -152,7 +127,6 @@ class SessionDetailResponse(BaseModel):
active_stream: ActiveStreamInfo | None = None # Present if stream is still active
total_prompt_tokens: int = 0
total_completion_tokens: int = 0
metadata: ChatSessionMetadata = ChatSessionMetadata()
class SessionSummaryResponse(BaseModel):
@@ -263,7 +237,6 @@ async def list_sessions(
)
async def create_session(
user_id: Annotated[str, Security(auth.get_user_id)],
request: CreateSessionRequest | None = None,
) -> CreateSessionResponse:
"""
Create a new chat session.
@@ -272,28 +245,22 @@ async def create_session(
Args:
user_id: The authenticated user ID parsed from the JWT (required).
request: Optional request body. When provided, ``dry_run=True``
forces run_block and run_agent calls to use dry-run simulation.
Returns:
CreateSessionResponse: Details of the created session.
"""
dry_run = request.dry_run if request else False
logger.info(
f"Creating session with user_id: "
f"...{user_id[-8:] if len(user_id) > 8 else '<redacted>'}"
f"{', dry_run=True' if dry_run else ''}"
)
session = await create_chat_session(user_id, dry_run=dry_run)
session = await create_chat_session(user_id)
return CreateSessionResponse(
id=session.session_id,
created_at=session.started_at.isoformat(),
user_id=session.user_id,
metadata=session.metadata,
)
@@ -442,7 +409,6 @@ async def get_session(
active_stream=active_stream_info,
total_prompt_tokens=total_prompt,
total_completion_tokens=total_completion,
metadata=session.metadata,
)
@@ -455,189 +421,11 @@ async def get_copilot_usage(
"""Get CoPilot usage status for the authenticated user.
Returns current token usage vs limits for daily and weekly windows.
Global defaults sourced from LaunchDarkly (falling back to config).
"""
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
)
return await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
rate_limit_reset_cost=config.rate_limit_reset_cost,
)
class RateLimitResetResponse(BaseModel):
"""Response from resetting the daily rate limit."""
success: bool
credits_charged: int = Field(description="Credits charged (in cents)")
remaining_balance: int = Field(description="Credit balance after charge (in cents)")
usage: CoPilotUsageStatus = Field(description="Updated usage status after reset")
@router.post(
"/usage/reset",
status_code=200,
responses={
400: {
"description": "Bad Request (feature disabled or daily limit not reached)"
},
402: {"description": "Payment Required (insufficient credits)"},
429: {
"description": "Too Many Requests (max daily resets exceeded or reset in progress)"
},
503: {
"description": "Service Unavailable (Redis reset failed; credits refunded or support needed)"
},
},
)
async def reset_copilot_usage(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> RateLimitResetResponse:
"""Reset the daily CoPilot rate limit by spending credits.
Allows users who have hit their daily token limit to spend credits
to reset their daily usage counter and continue working.
Returns 400 if the feature is disabled or the user is not over the limit.
Returns 402 if the user has insufficient credits.
"""
cost = config.rate_limit_reset_cost
if cost <= 0:
raise HTTPException(
status_code=400,
detail="Rate limit reset is not available.",
)
if not settings.config.enable_credit:
raise HTTPException(
status_code=400,
detail="Rate limit reset is not available (credit system is disabled).",
)
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
)
if daily_limit <= 0:
raise HTTPException(
status_code=400,
detail="No daily limit is configured — nothing to reset.",
)
# Check max daily resets. get_daily_reset_count returns None when Redis
# is unavailable; reject the reset in that case to prevent unlimited
# free resets when the counter store is down.
reset_count = await get_daily_reset_count(user_id)
if reset_count is None:
raise HTTPException(
status_code=503,
detail="Unable to verify reset eligibility — please try again later.",
)
if config.max_daily_resets > 0 and reset_count >= config.max_daily_resets:
raise HTTPException(
status_code=429,
detail=f"You've used all {config.max_daily_resets} resets for today.",
)
# Acquire a per-user lock to prevent TOCTOU races (concurrent resets).
if not await acquire_reset_lock(user_id):
raise HTTPException(
status_code=429,
detail="A reset is already in progress. Please try again.",
)
try:
# Verify the user is actually at or over their daily limit.
# (rate_limit_reset_cost intentionally omitted — this object is only
# used for limit checks, not returned to the client.)
usage_status = await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
)
if daily_limit > 0 and usage_status.daily.used < daily_limit:
raise HTTPException(
status_code=400,
detail="You have not reached your daily limit yet.",
)
# If the weekly limit is also exhausted, resetting the daily counter
# won't help — the user would still be blocked by the weekly limit.
if weekly_limit > 0 and usage_status.weekly.used >= weekly_limit:
raise HTTPException(
status_code=400,
detail="Your weekly limit is also reached. Resetting the daily limit won't help.",
)
# Charge credits.
credit_model = await get_user_credit_model(user_id)
try:
remaining = await credit_model.spend_credits(
user_id=user_id,
cost=cost,
metadata=UsageTransactionMetadata(
reason="CoPilot daily rate limit reset",
),
)
except InsufficientBalanceError as e:
raise HTTPException(
status_code=402,
detail="Insufficient credits to reset your rate limit.",
) from e
# Reset daily usage in Redis. If this fails, refund the credits
# so the user is not charged for a service they did not receive.
if not await reset_daily_usage(user_id, daily_token_limit=daily_limit):
# Compensate: refund the charged credits.
refunded = False
try:
await credit_model.top_up_credits(user_id, cost)
refunded = True
logger.warning(
"Refunded %d credits to user %s after Redis reset failure",
cost,
user_id[:8],
)
except Exception:
logger.error(
"CRITICAL: Failed to refund %d credits to user %s "
"after Redis reset failure — manual intervention required",
cost,
user_id[:8],
exc_info=True,
)
if refunded:
raise HTTPException(
status_code=503,
detail="Rate limit reset failed — please try again later. "
"Your credits have not been charged.",
)
raise HTTPException(
status_code=503,
detail="Rate limit reset failed and the automatic refund "
"also failed. Please contact support for assistance.",
)
# Track the reset count for daily cap enforcement.
await increment_daily_reset_count(user_id)
finally:
await release_reset_lock(user_id)
# Return updated usage status.
updated_usage = await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
rate_limit_reset_cost=config.rate_limit_reset_cost,
)
return RateLimitResetResponse(
success=True,
credits_charged=cost,
remaining_balance=remaining,
usage=updated_usage,
daily_token_limit=config.daily_token_limit,
weekly_token_limit=config.weekly_token_limit,
)
@@ -738,16 +526,12 @@ async def stream_chat_post(
# Pre-turn rate limit check (token-based).
# check_rate_limit short-circuits internally when both limits are 0.
# Global defaults sourced from LaunchDarkly, falling back to config.
if user_id:
try:
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
)
await check_rate_limit(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_token_limit=config.daily_token_limit,
weekly_token_limit=config.weekly_token_limit,
)
except RateLimitExceeded as e:
raise HTTPException(status_code=429, detail=str(e)) from e
@@ -1110,47 +894,6 @@ async def session_assign_user(
return {"status": "ok"}
# ========== Suggested Prompts ==========
class SuggestedTheme(BaseModel):
"""A themed group of suggested prompts."""
name: str
prompts: list[str]
class SuggestedPromptsResponse(BaseModel):
"""Response model for user-specific suggested prompts grouped by theme."""
themes: list[SuggestedTheme]
@router.get(
"/suggested-prompts",
dependencies=[Security(auth.requires_user)],
)
async def get_suggested_prompts(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> SuggestedPromptsResponse:
"""
Get LLM-generated suggested prompts grouped by theme.
Returns personalized quick-action prompts based on the user's
business understanding. Returns empty themes list if no custom
prompts are available.
"""
understanding = await get_business_understanding(user_id)
if understanding is None or not understanding.suggested_prompts:
return SuggestedPromptsResponse(themes=[])
themes = [
SuggestedTheme(name=name, prompts=prompts)
for name, prompts in understanding.suggested_prompts.items()
]
return SuggestedPromptsResponse(themes=themes)
# ========== Configuration ==========
@@ -1199,7 +942,7 @@ async def health_check() -> dict:
)
# Create and retrieve session to verify full data layer
session = await create_chat_session(health_check_user_id, dry_run=False)
session = await create_chat_session(health_check_user_id)
await get_chat_session(session.session_id, health_check_user_id)
return {

View File

@@ -1,7 +1,7 @@
"""Tests for chat API routes: session title update, file attachment validation, usage, and rate limiting."""
from datetime import UTC, datetime, timedelta
from unittest.mock import AsyncMock, MagicMock
from unittest.mock import AsyncMock
import fastapi
import fastapi.testclient
@@ -368,7 +368,6 @@ def test_usage_returns_daily_and_weekly(
user_id=test_user_id,
daily_token_limit=10000,
weekly_token_limit=50000,
rate_limit_reset_cost=chat_routes.config.rate_limit_reset_cost,
)
@@ -381,7 +380,6 @@ def test_usage_uses_config_limits(
mocker.patch.object(chat_routes.config, "daily_token_limit", 99999)
mocker.patch.object(chat_routes.config, "weekly_token_limit", 77777)
mocker.patch.object(chat_routes.config, "rate_limit_reset_cost", 500)
response = client.get("/usage")
@@ -390,7 +388,6 @@ def test_usage_uses_config_limits(
user_id=test_user_id,
daily_token_limit=99999,
weekly_token_limit=77777,
rate_limit_reset_cost=500,
)
@@ -403,126 +400,3 @@ def test_usage_rejects_unauthenticated_request() -> None:
response = unauthenticated_client.get("/usage")
assert response.status_code == 401
# ─── Suggested prompts endpoint ──────────────────────────────────────
def _mock_get_business_understanding(
mocker: pytest_mock.MockerFixture,
*,
return_value=None,
):
"""Mock get_business_understanding."""
return mocker.patch(
"backend.api.features.chat.routes.get_business_understanding",
new_callable=AsyncMock,
return_value=return_value,
)
def test_suggested_prompts_returns_themes(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""User with themed prompts gets them back as themes list."""
mock_understanding = MagicMock()
mock_understanding.suggested_prompts = {
"Learn": ["L1", "L2"],
"Create": ["C1"],
}
_mock_get_business_understanding(mocker, return_value=mock_understanding)
response = client.get("/suggested-prompts")
assert response.status_code == 200
data = response.json()
assert "themes" in data
themes_by_name = {t["name"]: t["prompts"] for t in data["themes"]}
assert themes_by_name["Learn"] == ["L1", "L2"]
assert themes_by_name["Create"] == ["C1"]
def test_suggested_prompts_no_understanding(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""User with no understanding gets empty themes list."""
_mock_get_business_understanding(mocker, return_value=None)
response = client.get("/suggested-prompts")
assert response.status_code == 200
assert response.json() == {"themes": []}
def test_suggested_prompts_empty_prompts(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""User with understanding but empty prompts gets empty themes list."""
mock_understanding = MagicMock()
mock_understanding.suggested_prompts = {}
_mock_get_business_understanding(mocker, return_value=mock_understanding)
response = client.get("/suggested-prompts")
assert response.status_code == 200
assert response.json() == {"themes": []}
# ─── Create session: dry_run contract ─────────────────────────────────
def _mock_create_chat_session(mocker: pytest_mock.MockerFixture):
"""Mock create_chat_session to return a fake session."""
from backend.copilot.model import ChatSession
async def _fake_create(user_id: str, *, dry_run: bool):
return ChatSession.new(user_id, dry_run=dry_run)
return mocker.patch(
"backend.api.features.chat.routes.create_chat_session",
new_callable=AsyncMock,
side_effect=_fake_create,
)
def test_create_session_dry_run_true(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""Sending ``{"dry_run": true}`` sets metadata.dry_run to True."""
_mock_create_chat_session(mocker)
response = client.post("/sessions", json={"dry_run": True})
assert response.status_code == 200
assert response.json()["metadata"]["dry_run"] is True
def test_create_session_dry_run_default_false(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""Empty body defaults dry_run to False."""
_mock_create_chat_session(mocker)
response = client.post("/sessions")
assert response.status_code == 200
assert response.json()["metadata"]["dry_run"] is False
def test_create_session_rejects_nested_metadata(
test_user_id: str,
) -> None:
"""Sending ``{"metadata": {"dry_run": true}}`` must return 422, not silently
default to ``dry_run=False``. This guards against the common mistake of
nesting dry_run inside metadata instead of providing it at the top level."""
response = client.post(
"/sessions",
json={"metadata": {"dry_run": True}},
)
assert response.status_code == 422

View File

@@ -40,15 +40,11 @@ from backend.data.onboarding import OnboardingStep, complete_onboarding_step
from backend.data.user import get_user_integrations
from backend.executor.utils import add_graph_execution
from backend.integrations.ayrshare import AyrshareClient, SocialPlatform
from backend.integrations.credentials_store import (
is_system_credential,
provider_matches,
)
from backend.integrations.credentials_store import provider_matches
from backend.integrations.creds_manager import (
IntegrationCredentialsManager,
create_mcp_oauth_handler,
)
from backend.integrations.managed_credentials import ensure_managed_credentials
from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
from backend.integrations.providers import ProviderName
from backend.integrations.webhooks import get_webhook_manager
@@ -114,7 +110,6 @@ class CredentialsMetaResponse(BaseModel):
default=None,
description="Host pattern for host-scoped or MCP server URL for MCP credentials",
)
is_managed: bool = False
@model_validator(mode="before")
@classmethod
@@ -153,7 +148,6 @@ def to_meta_response(cred: Credentials) -> CredentialsMetaResponse:
scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
username=cred.username if isinstance(cred, OAuth2Credentials) else None,
host=CredentialsMetaResponse.get_host(cred),
is_managed=cred.is_managed,
)
@@ -230,9 +224,6 @@ async def callback(
async def list_credentials(
user_id: Annotated[str, Security(get_user_id)],
) -> list[CredentialsMetaResponse]:
# Fire-and-forget: provision missing managed credentials in the background.
# The credential appears on the next page load; listing is never blocked.
asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
credentials = await creds_manager.store.get_all_creds(user_id)
return [
@@ -247,7 +238,6 @@ async def list_credentials_by_provider(
],
user_id: Annotated[str, Security(get_user_id)],
) -> list[CredentialsMetaResponse]:
asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
credentials = await creds_manager.store.get_creds_by_provider(user_id, provider)
return [
@@ -342,11 +332,6 @@ async def delete_credentials(
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if is_system_credential(cred_id):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="System-managed credentials cannot be deleted",
)
creds = await creds_manager.store.get_creds_by_id(user_id, cred_id)
if not creds:
raise HTTPException(
@@ -357,11 +342,6 @@ async def delete_credentials(
status_code=status.HTTP_404_NOT_FOUND,
detail="Credentials not found",
)
if creds.is_managed:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="AutoGPT-managed credentials cannot be deleted",
)
try:
await remove_all_webhooks_for_credentials(user_id, creds, force)

View File

@@ -1,7 +1,6 @@
"""Tests for credentials API security: no secret leakage, SDK defaults filtered."""
from contextlib import asynccontextmanager
from unittest.mock import AsyncMock, MagicMock, patch
from unittest.mock import AsyncMock, patch
import fastapi
import fastapi.testclient
@@ -277,294 +276,3 @@ class TestCreateCredentialNoSecretInResponse:
assert resp.status_code == 403
mock_mgr.create.assert_not_called()
class TestManagedCredentials:
"""AutoGPT-managed credentials cannot be deleted by users."""
def test_delete_is_managed_returns_403(self):
cred = APIKeyCredentials(
id="managed-cred-1",
provider="agent_mail",
title="AgentMail (managed by AutoGPT)",
api_key=SecretStr("sk-managed-key"),
is_managed=True,
)
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_creds_by_id = AsyncMock(return_value=cred)
resp = client.request("DELETE", "/agent_mail/credentials/managed-cred-1")
assert resp.status_code == 403
assert "AutoGPT-managed" in resp.json()["detail"]
def test_list_credentials_includes_is_managed_field(self):
managed = APIKeyCredentials(
id="managed-1",
provider="agent_mail",
title="AgentMail (managed)",
api_key=SecretStr("sk-key"),
is_managed=True,
)
regular = APIKeyCredentials(
id="regular-1",
provider="openai",
title="My Key",
api_key=SecretStr("sk-key"),
)
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_all_creds = AsyncMock(return_value=[managed, regular])
resp = client.get("/credentials")
assert resp.status_code == 200
data = resp.json()
managed_cred = next(c for c in data if c["id"] == "managed-1")
regular_cred = next(c for c in data if c["id"] == "regular-1")
assert managed_cred["is_managed"] is True
assert regular_cred["is_managed"] is False
# ---------------------------------------------------------------------------
# Managed credential provisioning infrastructure
# ---------------------------------------------------------------------------
def _make_managed_cred(
provider: str = "agent_mail", pod_id: str = "pod-abc"
) -> APIKeyCredentials:
return APIKeyCredentials(
id="managed-auto",
provider=provider,
title="AgentMail (managed by AutoGPT)",
api_key=SecretStr("sk-pod-key"),
is_managed=True,
metadata={"pod_id": pod_id},
)
def _make_store_mock(**kwargs) -> MagicMock:
"""Create a store mock with a working async ``locks()`` context manager."""
@asynccontextmanager
async def _noop_locked(key):
yield
locks_obj = MagicMock()
locks_obj.locked = _noop_locked
store = MagicMock(**kwargs)
store.locks = AsyncMock(return_value=locks_obj)
return store
class TestEnsureManagedCredentials:
"""Unit tests for the ensure/cleanup helpers in managed_credentials.py."""
@pytest.mark.asyncio
async def test_provisions_when_missing(self):
"""Provider.provision() is called when no managed credential exists."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
cred = _make_managed_cred()
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=True)
provider.provision = AsyncMock(return_value=cred)
store = _make_store_mock()
store.has_managed_credential = AsyncMock(return_value=False)
store.add_managed_credential = AsyncMock()
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
provider.provision.assert_awaited_once_with("user-1")
store.add_managed_credential.assert_awaited_once_with("user-1", cred)
@pytest.mark.asyncio
async def test_skips_when_already_exists(self):
"""Provider.provision() is NOT called when managed credential exists."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=True)
provider.provision = AsyncMock()
store = _make_store_mock()
store.has_managed_credential = AsyncMock(return_value=True)
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
provider.provision.assert_not_awaited()
@pytest.mark.asyncio
async def test_skips_when_unavailable(self):
"""Provider.provision() is NOT called when provider is not available."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=False)
provider.provision = AsyncMock()
store = _make_store_mock()
store.has_managed_credential = AsyncMock()
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
provider.provision.assert_not_awaited()
store.has_managed_credential.assert_not_awaited()
@pytest.mark.asyncio
async def test_provision_failure_does_not_propagate(self):
"""A failed provision is logged but does not raise."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=True)
provider.provision = AsyncMock(side_effect=RuntimeError("boom"))
store = _make_store_mock()
store.has_managed_credential = AsyncMock(return_value=False)
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
# No exception raised — provisioning failure is swallowed.
class TestCleanupManagedCredentials:
"""Unit tests for cleanup_managed_credentials."""
@pytest.mark.asyncio
async def test_calls_deprovision_for_managed_creds(self):
from backend.integrations.managed_credentials import (
_PROVIDERS,
cleanup_managed_credentials,
)
cred = _make_managed_cred()
provider = MagicMock()
provider.provider_name = "agent_mail"
provider.deprovision = AsyncMock()
store = MagicMock()
store.get_all_creds = AsyncMock(return_value=[cred])
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["agent_mail"] = provider
try:
await cleanup_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
provider.deprovision.assert_awaited_once_with("user-1", cred)
@pytest.mark.asyncio
async def test_skips_non_managed_creds(self):
from backend.integrations.managed_credentials import (
_PROVIDERS,
cleanup_managed_credentials,
)
regular = _make_api_key_cred()
provider = MagicMock()
provider.provider_name = "openai"
provider.deprovision = AsyncMock()
store = MagicMock()
store.get_all_creds = AsyncMock(return_value=[regular])
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["openai"] = provider
try:
await cleanup_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
provider.deprovision.assert_not_awaited()
@pytest.mark.asyncio
async def test_deprovision_failure_does_not_propagate(self):
from backend.integrations.managed_credentials import (
_PROVIDERS,
cleanup_managed_credentials,
)
cred = _make_managed_cred()
provider = MagicMock()
provider.provider_name = "agent_mail"
provider.deprovision = AsyncMock(side_effect=RuntimeError("boom"))
store = MagicMock()
store.get_all_creds = AsyncMock(return_value=[cred])
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["agent_mail"] = provider
try:
await cleanup_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
# No exception raised — cleanup failure is swallowed.

View File

@@ -17,6 +17,8 @@ from backend.data.includes import library_agent_include
from backend.util.exceptions import NotFoundError
from backend.util.json import SafeJson
from .db import get_library_agent_by_graph_id, update_library_agent
logger = logging.getLogger(__name__)
@@ -59,17 +61,28 @@ async def add_graph_to_library(
graph_model: GraphModel,
user_id: str,
) -> library_model.LibraryAgent:
"""Check existing / restore soft-deleted / create new LibraryAgent.
"""Check existing / restore soft-deleted / create new LibraryAgent."""
if existing := await get_library_agent_by_graph_id(
user_id, graph_model.id, graph_model.version
):
return existing
Uses a create-then-catch-UniqueViolationError-then-update pattern on
the (userId, agentGraphId, agentGraphVersion) composite unique constraint.
This is more robust than ``upsert`` because Prisma's upsert atomicity
guarantees are not well-documented for all versions.
"""
settings_json = SafeJson(GraphSettings.from_graph(graph_model).model_dump())
_include = library_agent_include(
user_id, include_nodes=False, include_executions=False
deleted_agent = await prisma.models.LibraryAgent.prisma().find_unique(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": user_id,
"agentGraphId": graph_model.id,
"agentGraphVersion": graph_model.version,
}
},
)
if deleted_agent and (deleted_agent.isDeleted or deleted_agent.isArchived):
return await update_library_agent(
deleted_agent.id,
user_id,
is_deleted=False,
is_archived=False,
)
try:
added_agent = await prisma.models.LibraryAgent.prisma().create(
@@ -85,32 +98,23 @@ async def add_graph_to_library(
},
"isCreatedByUser": False,
"useGraphIsActiveVersion": False,
"settings": settings_json,
"settings": SafeJson(
GraphSettings.from_graph(graph_model).model_dump()
),
},
include=_include,
include=library_agent_include(
user_id, include_nodes=False, include_executions=False
),
)
except prisma.errors.UniqueViolationError:
# Already exists — update to restore if previously soft-deleted/archived
added_agent = await prisma.models.LibraryAgent.prisma().update(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": user_id,
"agentGraphId": graph_model.id,
"agentGraphVersion": graph_model.version,
}
},
data={
"isDeleted": False,
"isArchived": False,
"settings": settings_json,
},
include=_include,
# Race condition: concurrent request created the row between our
# check and create. Re-read instead of crashing.
existing = await get_library_agent_by_graph_id(
user_id, graph_model.id, graph_model.version
)
if added_agent is None:
raise NotFoundError(
f"LibraryAgent for graph #{graph_model.id} "
f"v{graph_model.version} not found after UniqueViolationError"
)
if existing:
return existing
raise # Shouldn't happen, but don't swallow unexpected errors
logger.debug(
f"Added graph #{graph_model.id} v{graph_model.version} "

View File

@@ -1,80 +1,71 @@
from unittest.mock import AsyncMock, MagicMock, patch
import prisma.errors
import pytest
from ._add_to_library import add_graph_to_library
@pytest.mark.asyncio
async def test_add_graph_to_library_create_new_agent() -> None:
"""When no matching LibraryAgent exists, create inserts a new one."""
graph_model = MagicMock(id="graph-id", version=2, nodes=[])
created_agent = MagicMock(name="CreatedLibraryAgent")
converted_agent = MagicMock(name="ConvertedLibraryAgent")
async def test_add_graph_to_library_restores_archived_agent() -> None:
graph_model = MagicMock(id="graph-id", version=2)
archived_agent = MagicMock(id="library-agent-id", isDeleted=False, isArchived=True)
restored_agent = MagicMock(name="LibraryAgentModel")
with (
patch(
"backend.api.features.library._add_to_library.get_library_agent_by_graph_id",
new=AsyncMock(return_value=None),
),
patch(
"backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
) as mock_prisma,
patch(
"backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
return_value=converted_agent,
) as mock_from_db,
"backend.api.features.library._add_to_library.update_library_agent",
new=AsyncMock(return_value=restored_agent),
) as mock_update,
):
mock_prisma.return_value.create = AsyncMock(return_value=created_agent)
mock_prisma.return_value.find_unique = AsyncMock(return_value=archived_agent)
result = await add_graph_to_library("slv-id", graph_model, "user-id")
assert result is converted_agent
mock_from_db.assert_called_once_with(created_agent)
# Verify create was called with correct data
create_call = mock_prisma.return_value.create.call_args
create_data = create_call.kwargs["data"]
assert create_data["User"] == {"connect": {"id": "user-id"}}
assert create_data["AgentGraph"] == {
"connect": {"graphVersionId": {"id": "graph-id", "version": 2}}
}
assert create_data["isCreatedByUser"] is False
assert create_data["useGraphIsActiveVersion"] is False
assert result is restored_agent
mock_update.assert_awaited_once_with(
"library-agent-id",
"user-id",
is_deleted=False,
is_archived=False,
)
mock_prisma.return_value.create.assert_not_called()
@pytest.mark.asyncio
async def test_add_graph_to_library_unique_violation_updates_existing() -> None:
"""UniqueViolationError on create falls back to update."""
graph_model = MagicMock(id="graph-id", version=2, nodes=[])
updated_agent = MagicMock(name="UpdatedLibraryAgent")
converted_agent = MagicMock(name="ConvertedLibraryAgent")
async def test_add_graph_to_library_restores_deleted_agent() -> None:
graph_model = MagicMock(id="graph-id", version=2)
deleted_agent = MagicMock(id="library-agent-id", isDeleted=True, isArchived=False)
restored_agent = MagicMock(name="LibraryAgentModel")
with (
patch(
"backend.api.features.library._add_to_library.get_library_agent_by_graph_id",
new=AsyncMock(return_value=None),
),
patch(
"backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
) as mock_prisma,
patch(
"backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
return_value=converted_agent,
) as mock_from_db,
"backend.api.features.library._add_to_library.update_library_agent",
new=AsyncMock(return_value=restored_agent),
) as mock_update,
):
mock_prisma.return_value.create = AsyncMock(
side_effect=prisma.errors.UniqueViolationError(
MagicMock(), message="unique constraint"
)
)
mock_prisma.return_value.update = AsyncMock(return_value=updated_agent)
mock_prisma.return_value.find_unique = AsyncMock(return_value=deleted_agent)
result = await add_graph_to_library("slv-id", graph_model, "user-id")
assert result is converted_agent
mock_from_db.assert_called_once_with(updated_agent)
# Verify update was called with correct where and data
update_call = mock_prisma.return_value.update.call_args
assert update_call.kwargs["where"] == {
"userId_agentGraphId_agentGraphVersion": {
"userId": "user-id",
"agentGraphId": "graph-id",
"agentGraphVersion": 2,
}
}
update_data = update_call.kwargs["data"]
assert update_data["isDeleted"] is False
assert update_data["isArchived"] is False
assert result is restored_agent
mock_update.assert_awaited_once_with(
"library-agent-id",
"user-id",
is_deleted=False,
is_archived=False,
)
mock_prisma.return_value.create.assert_not_called()

View File

@@ -436,58 +436,32 @@ async def create_library_agent(
async with transaction() as tx:
library_agents = await asyncio.gather(
*(
prisma.models.LibraryAgent.prisma(tx).upsert(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": user_id,
"agentGraphId": graph_entry.id,
"agentGraphVersion": graph_entry.version,
}
},
data={
"create": prisma.types.LibraryAgentCreateInput(
isCreatedByUser=(user_id == graph.user_id),
useGraphIsActiveVersion=True,
User={"connect": {"id": user_id}},
AgentGraph={
"connect": {
"graphVersionId": {
"id": graph_entry.id,
"version": graph_entry.version,
}
prisma.models.LibraryAgent.prisma(tx).create(
data=prisma.types.LibraryAgentCreateInput(
isCreatedByUser=(user_id == user_id),
useGraphIsActiveVersion=True,
User={"connect": {"id": user_id}},
AgentGraph={
"connect": {
"graphVersionId": {
"id": graph_entry.id,
"version": graph_entry.version,
}
},
settings=SafeJson(
GraphSettings.from_graph(
graph_entry,
hitl_safe_mode=hitl_safe_mode,
sensitive_action_safe_mode=sensitive_action_safe_mode,
).model_dump()
),
**(
{"Folder": {"connect": {"id": folder_id}}}
if folder_id and graph_entry is graph
else {}
),
),
"update": {
"isDeleted": False,
"isArchived": False,
"useGraphIsActiveVersion": True,
"settings": SafeJson(
GraphSettings.from_graph(
graph_entry,
hitl_safe_mode=hitl_safe_mode,
sensitive_action_safe_mode=sensitive_action_safe_mode,
).model_dump()
),
**(
{"Folder": {"connect": {"id": folder_id}}}
if folder_id and graph_entry is graph
else {}
),
}
},
},
settings=SafeJson(
GraphSettings.from_graph(
graph_entry,
hitl_safe_mode=hitl_safe_mode,
sensitive_action_safe_mode=sensitive_action_safe_mode,
).model_dump()
),
**(
{"Folder": {"connect": {"id": folder_id}}}
if folder_id and graph_entry is graph
else {}
),
),
include=library_agent_include(
user_id, include_nodes=False, include_executions=False
),

View File

@@ -1,6 +1,4 @@
from contextlib import asynccontextmanager
from datetime import datetime
from unittest.mock import AsyncMock, MagicMock, patch
import prisma.enums
import prisma.models
@@ -87,6 +85,10 @@ async def test_get_library_agents(mocker):
async def test_add_agent_to_library(mocker):
await connect()
# Mock the transaction context
mock_transaction = mocker.patch("backend.api.features.library.db.transaction")
mock_transaction.return_value.__aenter__ = mocker.AsyncMock(return_value=None)
mock_transaction.return_value.__aexit__ = mocker.AsyncMock(return_value=None)
# Mock data
mock_store_listing_data = prisma.models.StoreListingVersion(
id="version123",
@@ -141,11 +143,13 @@ async def test_add_agent_to_library(mocker):
)
mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
mock_library_agent.return_value.find_unique = mocker.AsyncMock(return_value=None)
mock_library_agent.return_value.create = mocker.AsyncMock(
return_value=mock_library_agent_data
)
# Mock graph_db.get_graph function that's called in resolve_graph_for_library
# Mock graph_db.get_graph function that's called to check for HITL blocks
# (lives in _add_to_library.py after refactor, not db.py)
mock_graph_db = mocker.patch(
"backend.api.features.library._add_to_library.graph_db"
@@ -171,27 +175,37 @@ async def test_add_agent_to_library(mocker):
mock_store_listing_version.return_value.find_unique.assert_called_once_with(
where={"id": "version123"}, include={"AgentGraph": True}
)
mock_library_agent.return_value.find_unique.assert_called_once_with(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": "test-user",
"agentGraphId": "agent1",
"agentGraphVersion": 1,
}
},
)
# Check that create was called with the expected data including settings
create_call_args = mock_library_agent.return_value.create.call_args
assert create_call_args is not None
# Verify the create data structure
create_data = create_call_args.kwargs["data"]
expected_create = {
# Verify the main structure
expected_data = {
"User": {"connect": {"id": "test-user"}},
"AgentGraph": {"connect": {"graphVersionId": {"id": "agent1", "version": 1}}},
"isCreatedByUser": False,
"useGraphIsActiveVersion": False,
}
for key, value in expected_create.items():
assert create_data[key] == value
actual_data = create_call_args[1]["data"]
# Check that all expected fields are present
for key, value in expected_data.items():
assert actual_data[key] == value
# Check that settings field is present and is a SafeJson object
assert "settings" in create_data
assert hasattr(create_data["settings"], "__class__") # Should be a SafeJson object
assert "settings" in actual_data
assert hasattr(actual_data["settings"], "__class__") # Should be a SafeJson object
# Check include parameter
assert create_call_args.kwargs["include"] == library_agent_include(
assert create_call_args[1]["include"] == library_agent_include(
"test-user", include_nodes=False, include_executions=False
)
@@ -306,50 +320,3 @@ async def test_update_graph_in_library_allows_archived_library_agent(mocker):
include_archived=True,
)
mock_update_library_agent.assert_awaited_once_with("test-user", created_graph)
@pytest.mark.asyncio
async def test_create_library_agent_uses_upsert():
"""create_library_agent should use upsert (not create) to handle duplicates."""
mock_graph = MagicMock()
mock_graph.id = "graph-1"
mock_graph.version = 1
mock_graph.user_id = "user-1"
mock_graph.nodes = []
mock_graph.sub_graphs = []
mock_upserted = MagicMock(name="UpsertedLibraryAgent")
@asynccontextmanager
async def fake_tx():
yield None
with (
patch("backend.api.features.library.db.transaction", fake_tx),
patch("prisma.models.LibraryAgent.prisma") as mock_prisma,
patch(
"backend.api.features.library.db.add_generated_agent_image",
new=AsyncMock(),
),
patch(
"backend.api.features.library.model.LibraryAgent.from_db",
return_value=MagicMock(),
),
):
mock_prisma.return_value.upsert = AsyncMock(return_value=mock_upserted)
result = await db.create_library_agent(mock_graph, "user-1")
assert len(result) == 1
upsert_call = mock_prisma.return_value.upsert.call_args
assert upsert_call is not None
# Verify the upsert where clause uses the composite unique key
where = upsert_call.kwargs["where"]
assert "userId_agentGraphId_agentGraphVersion" in where
# Verify the upsert data has both create and update branches
data = upsert_call.kwargs["data"]
assert "create" in data
assert "update" in data
# Verify update branch restores soft-deleted/archived agents
assert data["update"]["isDeleted"] is False
assert data["update"]["isArchived"] is False

View File

@@ -12,7 +12,6 @@ Tests cover:
5. Complete OAuth flow end-to-end
"""
import asyncio
import base64
import hashlib
import secrets
@@ -59,27 +58,14 @@ async def test_user(server, test_user_id: str):
yield test_user_id
# Cleanup - delete in correct order due to foreign key constraints.
# Wrap in try/except because the event loop or Prisma engine may already
# be closed during session teardown on Python 3.12+.
try:
await asyncio.gather(
PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id}),
PrismaOAuthRefreshToken.prisma().delete_many(
where={"userId": test_user_id}
),
PrismaOAuthAuthorizationCode.prisma().delete_many(
where={"userId": test_user_id}
),
)
await asyncio.gather(
PrismaOAuthApplication.prisma().delete_many(
where={"ownerId": test_user_id}
),
PrismaUser.prisma().delete(where={"id": test_user_id}),
)
except RuntimeError:
pass
# Cleanup - delete in correct order due to foreign key constraints
await PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id})
await PrismaOAuthRefreshToken.prisma().delete_many(where={"userId": test_user_id})
await PrismaOAuthAuthorizationCode.prisma().delete_many(
where={"userId": test_user_id}
)
await PrismaOAuthApplication.prisma().delete_many(where={"ownerId": test_user_id})
await PrismaUser.prisma().delete(where={"id": test_user_id})
@pytest_asyncio.fixture

View File

@@ -1,61 +0,0 @@
from unittest.mock import AsyncMock
import fastapi
import fastapi.testclient
import pytest
from backend.api.features.v1 import v1_router
app = fastapi.FastAPI()
app.include_router(v1_router)
client = fastapi.testclient.TestClient(app)
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_user):
from autogpt_libs.auth.jwt_utils import get_jwt_payload
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
yield
app.dependency_overrides.clear()
def test_onboarding_profile_success(mocker):
mock_extract = mocker.patch(
"backend.api.features.v1.extract_business_understanding",
new_callable=AsyncMock,
)
mock_upsert = mocker.patch(
"backend.api.features.v1.upsert_business_understanding",
new_callable=AsyncMock,
)
from backend.data.understanding import BusinessUnderstandingInput
mock_extract.return_value = BusinessUnderstandingInput.model_construct(
user_name="John",
user_role="Founder/CEO",
pain_points=["Finding leads"],
suggested_prompts={"Learn": ["How do I automate lead gen?"]},
)
mock_upsert.return_value = AsyncMock()
response = client.post(
"/onboarding/profile",
json={
"user_name": "John",
"user_role": "Founder/CEO",
"pain_points": ["Finding leads", "Email & outreach"],
},
)
assert response.status_code == 200
mock_extract.assert_awaited_once()
mock_upsert.assert_awaited_once()
def test_onboarding_profile_missing_fields():
response = client.post(
"/onboarding/profile",
json={"user_name": "John"},
)
assert response.status_code == 422

View File

@@ -63,17 +63,12 @@ from backend.data.onboarding import (
UserOnboardingUpdate,
complete_onboarding_step,
complete_re_run_agent,
format_onboarding_for_extraction,
get_recommended_agents,
get_user_onboarding,
onboarding_enabled,
reset_user_onboarding,
update_user_onboarding,
)
from backend.data.tally import extract_business_understanding
from backend.data.understanding import (
BusinessUnderstandingInput,
upsert_business_understanding,
)
from backend.data.user import (
get_or_create_user,
get_user_by_id,
@@ -287,33 +282,35 @@ async def get_onboarding_agents(
return await get_recommended_agents(user_id)
class OnboardingProfileRequest(pydantic.BaseModel):
"""Request body for onboarding profile submission."""
user_name: str = pydantic.Field(min_length=1, max_length=100)
user_role: str = pydantic.Field(min_length=1, max_length=100)
pain_points: list[str] = pydantic.Field(default_factory=list, max_length=20)
class OnboardingStatusResponse(pydantic.BaseModel):
"""Response for onboarding completion check."""
"""Response for onboarding status check."""
is_completed: bool
is_onboarding_enabled: bool
is_chat_enabled: bool
@v1_router.get(
"/onboarding/completed",
summary="Check if onboarding is completed",
"/onboarding/enabled",
summary="Is onboarding enabled",
tags=["onboarding", "public"],
response_model=OnboardingStatusResponse,
dependencies=[Security(requires_user)],
)
async def is_onboarding_completed(
async def is_onboarding_enabled(
user_id: Annotated[str, Security(get_user_id)],
) -> OnboardingStatusResponse:
user_onboarding = await get_user_onboarding(user_id)
# Check if chat is enabled for user
is_chat_enabled = await is_feature_enabled(Flag.CHAT, user_id, False)
# If chat is enabled, skip legacy onboarding
if is_chat_enabled:
return OnboardingStatusResponse(
is_onboarding_enabled=False,
is_chat_enabled=True,
)
return OnboardingStatusResponse(
is_completed=OnboardingStep.VISIT_COPILOT in user_onboarding.completedSteps,
is_onboarding_enabled=await onboarding_enabled(),
is_chat_enabled=False,
)
@@ -328,38 +325,6 @@ async def reset_onboarding(user_id: Annotated[str, Security(get_user_id)]):
return await reset_user_onboarding(user_id)
@v1_router.post(
"/onboarding/profile",
summary="Submit onboarding profile",
tags=["onboarding"],
dependencies=[Security(requires_user)],
)
async def submit_onboarding_profile(
data: OnboardingProfileRequest,
user_id: Annotated[str, Security(get_user_id)],
):
formatted = format_onboarding_for_extraction(
user_name=data.user_name,
user_role=data.user_role,
pain_points=data.pain_points,
)
try:
understanding_input = await extract_business_understanding(formatted)
except Exception:
understanding_input = BusinessUnderstandingInput.model_construct()
# Ensure the direct fields are set even if LLM missed them
understanding_input.user_name = data.user_name
understanding_input.user_role = data.user_role
if not understanding_input.pain_points:
understanding_input.pain_points = data.pain_points
await upsert_business_understanding(user_id, understanding_input)
return {"status": "ok"}
########################################################
##################### Blocks ###########################
########################################################

View File

@@ -18,7 +18,6 @@ from prisma.errors import PrismaError
import backend.api.features.admin.credit_admin_routes
import backend.api.features.admin.execution_analytics_routes
import backend.api.features.admin.rate_limit_admin_routes
import backend.api.features.admin.store_admin_routes
import backend.api.features.builder
import backend.api.features.builder.routes
@@ -118,11 +117,6 @@ async def lifespan_context(app: fastapi.FastAPI):
AutoRegistry.patch_integrations()
# Register managed credential providers (e.g. AgentMail)
from backend.integrations.managed_providers import register_all
register_all()
await backend.data.block.initialize_blocks()
await backend.data.user.migrate_and_encrypt_user_integrations()
@@ -324,11 +318,6 @@ app.include_router(
tags=["v2", "admin"],
prefix="/api/executions",
)
app.include_router(
backend.api.features.admin.rate_limit_admin_routes.router,
tags=["v2", "admin"],
prefix="/api/copilot",
)
app.include_router(
backend.api.features.executions.review.routes.router,
tags=["v2", "executions", "review"],

View File

@@ -698,30 +698,13 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
if should_pause:
return
# Validate the input data (original or reviewer-modified) once.
# In dry-run mode, credential fields may contain sentinel None values
# that would fail JSON schema required checks. We still validate the
# non-credential fields so blocks that execute for real during dry-run
# (e.g. AgentExecutorBlock) get proper input validation.
is_dry_run = getattr(kwargs.get("execution_context"), "dry_run", False)
if is_dry_run:
cred_field_names = set(self.input_schema.get_credentials_fields().keys())
non_cred_data = {
k: v for k, v in input_data.items() if k not in cred_field_names
}
if error := self.input_schema.validate_data(non_cred_data):
raise BlockInputError(
message=f"Unable to execute block with invalid input data: {error}",
block_name=self.name,
block_id=self.id,
)
else:
if error := self.input_schema.validate_data(input_data):
raise BlockInputError(
message=f"Unable to execute block with invalid input data: {error}",
block_name=self.name,
block_id=self.id,
)
# Validate the input data (original or reviewer-modified) once
if error := self.input_schema.validate_data(input_data):
raise BlockInputError(
message=f"Unable to execute block with invalid input data: {error}",
block_name=self.name,
block_id=self.id,
)
# Use the validated input data
async for output_name, output_data in self.run(

View File

@@ -49,17 +49,11 @@ class AgentExecutorBlock(Block):
@classmethod
def get_missing_input(cls, data: BlockInput) -> set[str]:
required_fields = cls.get_input_schema(data).get("required", [])
# Check against the nested `inputs` dict, not the top-level node
# data — required fields like "topic" live inside data["inputs"],
# not at data["topic"].
provided = data.get("inputs", {})
return set(required_fields) - set(provided)
return set(required_fields) - set(data)
@classmethod
def get_mismatch_error(cls, data: BlockInput) -> str | None:
return validate_with_jsonschema(
cls.get_input_schema(data), data.get("inputs", {})
)
return validate_with_jsonschema(cls.get_input_schema(data), data)
class Output(BlockSchema):
# Use BlockSchema to avoid automatic error field that could clash with graph outputs
@@ -94,7 +88,6 @@ class AgentExecutorBlock(Block):
execution_context=execution_context.model_copy(
update={"parent_execution_id": graph_exec_id},
),
dry_run=execution_context.dry_run,
)
logger = execution_utils.LogMetadata(
@@ -156,19 +149,14 @@ class AgentExecutorBlock(Block):
ExecutionStatus.TERMINATED,
ExecutionStatus.FAILED,
]:
logger.info(
f"Execution {log_id} skipping event {event.event_type} status={event.status} "
f"node={getattr(event, 'node_exec_id', '?')}"
logger.debug(
f"Execution {log_id} received event {event.event_type} with status {event.status}"
)
continue
if event.event_type == ExecutionEventType.GRAPH_EXEC_UPDATE:
# If the graph execution is COMPLETED, TERMINATED, or FAILED,
# we can stop listening for further events.
logger.info(
f"Execution {log_id} graph completed with status {event.status}, "
f"yielded {len(yielded_node_exec_ids)} outputs"
)
self.merge_stats(
NodeExecutionStats(
extra_cost=event.stats.cost if event.stats else 0,

View File

@@ -1,4 +1,3 @@
import re
from typing import Any
from backend.blocks._base import (
@@ -20,33 +19,6 @@ from backend.blocks.llm import (
)
from backend.data.model import APIKeyCredentials, NodeExecutionStats, SchemaField
# Minimum max_output_tokens accepted by OpenAI-compatible APIs.
# A true/false answer fits comfortably within this budget.
MIN_LLM_OUTPUT_TOKENS = 16
def _parse_boolean_response(response_text: str) -> tuple[bool, str | None]:
"""Parse an LLM response into a boolean result.
Returns a ``(result, error)`` tuple. *error* is ``None`` when the
response is unambiguous; otherwise it contains a diagnostic message
and *result* defaults to ``False``.
"""
text = response_text.strip().lower()
if text == "true":
return True, None
if text == "false":
return False, None
# Fuzzy match use word boundaries to avoid false positives like "untrue".
tokens = set(re.findall(r"\b(true|false|yes|no|1|0)\b", text))
if tokens == {"true"} or tokens == {"yes"} or tokens == {"1"}:
return True, None
if tokens == {"false"} or tokens == {"no"} or tokens == {"0"}:
return False, None
return False, f"Unclear AI response: '{response_text}'"
class AIConditionBlock(AIBlockBase):
"""
@@ -190,26 +162,54 @@ class AIConditionBlock(AIBlockBase):
]
# Call the LLM
response = await self.llm_call(
credentials=credentials,
llm_model=input_data.model,
prompt=prompt,
max_tokens=MIN_LLM_OUTPUT_TOKENS,
)
# Extract the boolean result from the response
result, error = _parse_boolean_response(response.response)
if error:
yield "error", error
# Update internal stats
self.merge_stats(
NodeExecutionStats(
input_token_count=response.prompt_tokens,
output_token_count=response.completion_tokens,
try:
response = await self.llm_call(
credentials=credentials,
llm_model=input_data.model,
prompt=prompt,
max_tokens=10, # We only expect a true/false response
)
)
self.prompt = response.prompt
# Extract the boolean result from the response
response_text = response.response.strip().lower()
if response_text == "true":
result = True
elif response_text == "false":
result = False
else:
# If the response is not clear, try to interpret it using word boundaries
import re
# Use word boundaries to avoid false positives like 'untrue' or '10'
tokens = set(re.findall(r"\b(true|false|yes|no|1|0)\b", response_text))
if tokens == {"true"} or tokens == {"yes"} or tokens == {"1"}:
result = True
elif tokens == {"false"} or tokens == {"no"} or tokens == {"0"}:
result = False
else:
# Unclear or conflicting response - default to False and yield error
result = False
yield "error", f"Unclear AI response: '{response.response}'"
# Update internal stats
self.merge_stats(
NodeExecutionStats(
input_token_count=response.prompt_tokens,
output_token_count=response.completion_tokens,
)
)
self.prompt = response.prompt
except Exception as e:
# In case of any error, default to False to be safe
result = False
# Log the error but don't fail the block execution
import logging
logger = logging.getLogger(__name__)
logger.error(f"AI condition evaluation failed: {str(e)}")
yield "error", f"AI evaluation failed: {str(e)}"
# Yield results
yield "result", result

View File

@@ -1,147 +0,0 @@
"""Tests for AIConditionBlock regression coverage for max_tokens and error propagation."""
from __future__ import annotations
from typing import cast
import pytest
from backend.blocks.ai_condition import (
MIN_LLM_OUTPUT_TOKENS,
AIConditionBlock,
_parse_boolean_response,
)
from backend.blocks.llm import (
DEFAULT_LLM_MODEL,
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
AICredentials,
LLMResponse,
)
_TEST_AI_CREDENTIALS = cast(AICredentials, TEST_CREDENTIALS_INPUT)
# ---------------------------------------------------------------------------
# Helper to collect all yields from the async generator
# ---------------------------------------------------------------------------
async def _collect_outputs(block: AIConditionBlock, input_data, credentials):
outputs: dict[str, object] = {}
async for name, value in block.run(input_data, credentials=credentials):
outputs[name] = value
return outputs
def _make_input(**overrides) -> AIConditionBlock.Input:
defaults: dict = {
"input_value": "hello@example.com",
"condition": "the input is an email address",
"yes_value": "yes!",
"no_value": "no!",
"model": DEFAULT_LLM_MODEL,
"credentials": TEST_CREDENTIALS_INPUT,
}
defaults.update(overrides)
return AIConditionBlock.Input(**defaults)
def _mock_llm_response(response_text: str) -> LLMResponse:
return LLMResponse(
raw_response="",
prompt=[],
response=response_text,
tool_calls=None,
prompt_tokens=10,
completion_tokens=5,
reasoning=None,
)
# ---------------------------------------------------------------------------
# _parse_boolean_response unit tests
# ---------------------------------------------------------------------------
class TestParseBooleanResponse:
def test_true_exact(self):
assert _parse_boolean_response("true") == (True, None)
def test_false_exact(self):
assert _parse_boolean_response("false") == (False, None)
def test_true_with_whitespace(self):
assert _parse_boolean_response(" True ") == (True, None)
def test_yes_fuzzy(self):
assert _parse_boolean_response("Yes") == (True, None)
def test_no_fuzzy(self):
assert _parse_boolean_response("no") == (False, None)
def test_one_fuzzy(self):
assert _parse_boolean_response("1") == (True, None)
def test_zero_fuzzy(self):
assert _parse_boolean_response("0") == (False, None)
def test_unclear_response(self):
result, error = _parse_boolean_response("I'm not sure")
assert result is False
assert error is not None
assert "Unclear" in error
def test_conflicting_tokens(self):
result, error = _parse_boolean_response("true and false")
assert result is False
assert error is not None
# ---------------------------------------------------------------------------
# Regression: max_tokens is set to MIN_LLM_OUTPUT_TOKENS
# ---------------------------------------------------------------------------
class TestMaxTokensRegression:
@pytest.mark.asyncio
async def test_llm_call_receives_min_output_tokens(self):
"""max_tokens must be MIN_LLM_OUTPUT_TOKENS (16) the previous value
of 1 was too low and caused OpenAI to reject the request."""
block = AIConditionBlock()
captured_kwargs: dict = {}
async def spy_llm_call(**kwargs):
captured_kwargs.update(kwargs)
return _mock_llm_response("true")
block.llm_call = spy_llm_call # type: ignore[assignment]
input_data = _make_input()
await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)
assert captured_kwargs["max_tokens"] == MIN_LLM_OUTPUT_TOKENS
assert captured_kwargs["max_tokens"] == 16
# ---------------------------------------------------------------------------
# Regression: exceptions from llm_call must propagate
# ---------------------------------------------------------------------------
class TestExceptionPropagation:
@pytest.mark.asyncio
async def test_llm_call_exception_propagates(self):
"""If llm_call raises, the exception must NOT be swallowed.
Previously the block caught all exceptions and silently returned
result=False."""
block = AIConditionBlock()
async def boom(**kwargs):
raise RuntimeError("LLM provider error")
block.llm_call = boom # type: ignore[assignment]
input_data = _make_input()
with pytest.raises(RuntimeError, match="LLM provider error"):
await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)

View File

@@ -146,21 +146,6 @@ class AutoPilotBlock(Block):
advanced=True,
)
dry_run: bool = SchemaField(
description=(
"When enabled, run_block and run_agent tool calls in this "
"autopilot session are forced to use dry-run simulation mode. "
"No real API calls, side effects, or credits are consumed "
"by those tools. Useful for testing agent wiring and "
"previewing outputs. "
"Only applies when creating a new session (session_id is empty). "
"When reusing an existing session_id, the session's original "
"dry_run setting is preserved."
),
default=False,
advanced=True,
)
# timeout_seconds removed: the SDK manages its own heartbeat-based
# timeouts internally; wrapping with asyncio.timeout corrupts the
# SDK's internal stream (see service.py CRITICAL comment).
@@ -247,11 +232,11 @@ class AutoPilotBlock(Block):
},
)
async def create_session(self, user_id: str, *, dry_run: bool) -> str:
async def create_session(self, user_id: str) -> str:
"""Create a new chat session and return its ID (mockable for tests)."""
from backend.copilot.model import create_chat_session # avoid circular import
session = await create_chat_session(user_id, dry_run=dry_run)
session = await create_chat_session(user_id)
return session.session_id
async def execute_copilot(
@@ -382,9 +367,7 @@ class AutoPilotBlock(Block):
# even if the downstream stream fails (avoids orphaned sessions).
sid = input_data.session_id
if not sid:
sid = await self.create_session(
execution_context.user_id, dry_run=input_data.dry_run
)
sid = await self.create_session(execution_context.user_id)
# NOTE: No asyncio.timeout() here — the SDK manages its own
# heartbeat-based timeouts internally. Wrapping with asyncio.timeout

View File

@@ -73,7 +73,7 @@ class ReadDiscordMessagesBlock(Block):
id="df06086a-d5ac-4abb-9996-2ad0acb2eff7",
input_schema=ReadDiscordMessagesBlock.Input, # Assign input schema
output_schema=ReadDiscordMessagesBlock.Output, # Assign output schema
description="Reads new messages from a Discord channel using a bot token and triggers when a new message is posted",
description="Reads messages from a Discord channel using a bot token.",
categories={BlockCategory.SOCIAL},
test_input={
"continuous_read": False,

View File

@@ -1,6 +1,5 @@
import asyncio
import base64
import re
from abc import ABC
from email import encoders
from email.mime.base import MIMEBase
@@ -9,7 +8,7 @@ from email.mime.text import MIMEText
from email.policy import SMTP
from email.utils import getaddresses, parseaddr
from pathlib import Path
from typing import List, Literal, Optional, Protocol, runtime_checkable
from typing import List, Literal, Optional
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
@@ -43,52 +42,8 @@ NO_WRAP_POLICY = SMTP.clone(max_line_length=0)
def serialize_email_recipients(recipients: list[str]) -> str:
"""Serialize recipients list to comma-separated string.
Strips leading/trailing whitespace from each address to keep MIME
headers clean (mirrors the strip done in ``validate_email_recipients``).
"""
return ", ".join(addr.strip() for addr in recipients)
# RFC 5322 simplified pattern: local@domain where domain has at least one dot
_EMAIL_RE = re.compile(r"^[^@\s]+@[^@\s]+\.[^@\s]+$")
def validate_email_recipients(recipients: list[str], field_name: str = "to") -> None:
"""Validate that all recipients are plausible email addresses.
Raises ``ValueError`` with a user-friendly message listing every
invalid entry so the caller (or LLM) can correct them in one pass.
"""
invalid = [addr for addr in recipients if not _EMAIL_RE.match(addr.strip())]
if invalid:
formatted = ", ".join(f"'{a}'" for a in invalid)
raise ValueError(
f"Invalid email address(es) in '{field_name}': {formatted}. "
f"Each entry must be a valid email address (e.g. user@example.com)."
)
@runtime_checkable
class HasRecipients(Protocol):
to: list[str]
cc: list[str]
bcc: list[str]
def validate_all_recipients(input_data: HasRecipients) -> None:
"""Validate to/cc/bcc recipient fields on an input namespace.
Calls ``validate_email_recipients`` for ``to`` (required) and
``cc``/``bcc`` (when non-empty), raising ``ValueError`` on the
first field that contains an invalid address.
"""
validate_email_recipients(input_data.to, "to")
if input_data.cc:
validate_email_recipients(input_data.cc, "cc")
if input_data.bcc:
validate_email_recipients(input_data.bcc, "bcc")
"""Serialize recipients list to comma-separated string."""
return ", ".join(recipients)
def _make_mime_text(
@@ -145,16 +100,14 @@ async def create_mime_message(
) -> str:
"""Create a MIME message with attachments and return base64-encoded raw message."""
validate_all_recipients(input_data)
message = MIMEMultipart()
message["to"] = serialize_email_recipients(input_data.to)
message["subject"] = input_data.subject
if input_data.cc:
message["cc"] = serialize_email_recipients(input_data.cc)
message["cc"] = ", ".join(input_data.cc)
if input_data.bcc:
message["bcc"] = serialize_email_recipients(input_data.bcc)
message["bcc"] = ", ".join(input_data.bcc)
# Use the new helper function with content_type if available
content_type = getattr(input_data, "content_type", None)
@@ -1214,15 +1167,13 @@ async def _build_reply_message(
references.append(headers["message-id"])
# Create MIME message
validate_all_recipients(input_data)
msg = MIMEMultipart()
if input_data.to:
msg["To"] = serialize_email_recipients(input_data.to)
msg["To"] = ", ".join(input_data.to)
if input_data.cc:
msg["Cc"] = serialize_email_recipients(input_data.cc)
msg["Cc"] = ", ".join(input_data.cc)
if input_data.bcc:
msg["Bcc"] = serialize_email_recipients(input_data.bcc)
msg["Bcc"] = ", ".join(input_data.bcc)
msg["Subject"] = subject
if headers.get("message-id"):
msg["In-Reply-To"] = headers["message-id"]
@@ -1734,16 +1685,13 @@ To: {original_to}
else:
body = f"{forward_header}\n\n{original_body}"
# Validate all recipient lists before building the MIME message
validate_all_recipients(input_data)
# Create MIME message
msg = MIMEMultipart()
msg["To"] = serialize_email_recipients(input_data.to)
msg["To"] = ", ".join(input_data.to)
if input_data.cc:
msg["Cc"] = serialize_email_recipients(input_data.cc)
msg["Cc"] = ", ".join(input_data.cc)
if input_data.bcc:
msg["Bcc"] = serialize_email_recipients(input_data.bcc)
msg["Bcc"] = ", ".join(input_data.bcc)
msg["Subject"] = subject
# Add body with proper content type

View File

@@ -2,8 +2,6 @@ import copy
from datetime import date, time
from typing import Any, Optional
from pydantic import AliasChoices, Field
from backend.blocks._base import (
Block,
BlockCategory,
@@ -30,9 +28,9 @@ class AgentInputBlock(Block):
"""
This block is used to provide input to the graph.
It takes in a value, name, and description.
It takes in a value, name, description, default values list and bool to limit selection to default values.
It outputs the value passed as input.
It Outputs the value passed as input.
"""
class Input(BlockSchemaInput):
@@ -49,6 +47,12 @@ class AgentInputBlock(Block):
default=None,
advanced=True,
)
placeholder_values: list = SchemaField(
description="The placeholder values to be passed as input.",
default_factory=list,
advanced=True,
hidden=True,
)
advanced: bool = SchemaField(
description="Whether to show the input in the advanced section, if the field is not required.",
default=False,
@@ -61,7 +65,10 @@ class AgentInputBlock(Block):
)
def generate_schema(self):
return copy.deepcopy(self.get_field_schema("value"))
schema = copy.deepcopy(self.get_field_schema("value"))
if possible_values := self.placeholder_values:
schema["enum"] = possible_values
return schema
class Output(BlockSchema):
# Use BlockSchema to avoid automatic error field for interface definition
@@ -79,16 +86,18 @@ class AgentInputBlock(Block):
"value": "Hello, World!",
"name": "input_1",
"description": "Example test input.",
"placeholder_values": [],
},
{
"value": 42,
"value": "Hello, World!",
"name": "input_2",
"description": "Example numeric input.",
"description": "Example test input with placeholders.",
"placeholder_values": ["Hello, World!"],
},
],
"test_output": [
("result", "Hello, World!"),
("result", 42),
("result", "Hello, World!"),
],
"categories": {BlockCategory.INPUT, BlockCategory.BASIC},
"block_type": BlockType.INPUT,
@@ -236,11 +245,13 @@ class AgentShortTextInputBlock(AgentInputBlock):
"value": "Hello",
"name": "short_text_1",
"description": "Short text example 1",
"placeholder_values": [],
},
{
"value": "Quick test",
"name": "short_text_2",
"description": "Short text example 2",
"placeholder_values": ["Quick test", "Another option"],
},
],
test_output=[
@@ -274,11 +285,13 @@ class AgentLongTextInputBlock(AgentInputBlock):
"value": "Lorem ipsum dolor sit amet...",
"name": "long_text_1",
"description": "Long text example 1",
"placeholder_values": [],
},
{
"value": "Another multiline text input.",
"name": "long_text_2",
"description": "Long text example 2",
"placeholder_values": ["Another multiline text input."],
},
],
test_output=[
@@ -312,11 +325,13 @@ class AgentNumberInputBlock(AgentInputBlock):
"value": 42,
"name": "number_input_1",
"description": "Number example 1",
"placeholder_values": [],
},
{
"value": 314,
"name": "number_input_2",
"description": "Number example 2",
"placeholder_values": [314, 2718],
},
],
test_output=[
@@ -469,8 +484,7 @@ class AgentFileInputBlock(AgentInputBlock):
class AgentDropdownInputBlock(AgentInputBlock):
"""
A specialized text input block that presents a dropdown selector
restricted to a fixed set of values.
A specialized text input block that relies on placeholder_values to present a dropdown.
"""
class Input(AgentInputBlock.Input):
@@ -480,26 +494,13 @@ class AgentDropdownInputBlock(AgentInputBlock):
advanced=False,
title="Default Value",
)
# Use Field() directly (not SchemaField) to pass validation_alias,
# which handles backward compat for legacy "placeholder_values" across
# all construction paths (model_construct, __init__, model_validate).
options: list = Field(
placeholder_values: list = SchemaField(
description="Possible values for the dropdown.",
default_factory=list,
advanced=False,
title="Dropdown Options",
description=(
"If provided, renders the input as a dropdown selector "
"restricted to these values. Leave empty for free-text input."
),
validation_alias=AliasChoices("options", "placeholder_values"),
json_schema_extra={"advanced": False, "secret": False},
)
def generate_schema(self):
schema = super().generate_schema()
if possible_values := self.options:
schema["enum"] = possible_values
return schema
class Output(AgentInputBlock.Output):
result: str = SchemaField(description="Selected dropdown value.")
@@ -514,13 +515,13 @@ class AgentDropdownInputBlock(AgentInputBlock):
{
"value": "Option A",
"name": "dropdown_1",
"options": ["Option A", "Option B", "Option C"],
"placeholder_values": ["Option A", "Option B", "Option C"],
"description": "Dropdown example 1",
},
{
"value": "Option C",
"name": "dropdown_2",
"options": ["Option A", "Option B", "Option C"],
"placeholder_values": ["Option A", "Option B", "Option C"],
"description": "Dropdown example 2",
},
],

View File

@@ -104,18 +104,6 @@ class LlmModelMeta(EnumMeta):
class LlmModel(str, Enum, metaclass=LlmModelMeta):
@classmethod
def _missing_(cls, value: object) -> "LlmModel | None":
"""Handle provider-prefixed model names like 'anthropic/claude-sonnet-4-6'."""
if isinstance(value, str) and "/" in value:
stripped = value.split("/", 1)[1]
try:
return cls(stripped)
except ValueError:
return None
return None
# OpenAI models
O3_MINI = "o3-mini"
O3 = "o3-2025-04-16"
@@ -724,9 +712,6 @@ def convert_openai_tool_fmt_to_anthropic(
def extract_openai_reasoning(response) -> str | None:
"""Extract reasoning from OpenAI-compatible response if available."""
"""Note: This will likely not working since the reasoning is not present in another Response API"""
if not response.choices:
logger.warning("LLM response has empty choices in extract_openai_reasoning")
return None
reasoning = None
choice = response.choices[0]
if hasattr(choice, "reasoning") and getattr(choice, "reasoning", None):
@@ -742,9 +727,6 @@ def extract_openai_reasoning(response) -> str | None:
def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
"""Extract tool calls from OpenAI-compatible response."""
if not response.choices:
logger.warning("LLM response has empty choices in extract_openai_tool_calls")
return None
if response.choices[0].message.tool_calls:
return [
ToolContentBlock(
@@ -978,8 +960,6 @@ async def llm_call(
response_format=response_format, # type: ignore
max_tokens=max_tokens,
)
if not response.choices:
raise ValueError("Groq returned empty choices in response")
return LLMResponse(
raw_response=response.choices[0].message,
prompt=prompt,
@@ -1039,8 +1019,12 @@ async def llm_call(
parallel_tool_calls=parallel_tool_calls_param,
)
# If there's no response, raise an error
if not response.choices:
raise ValueError(f"OpenRouter returned empty choices: {response}")
if response:
raise ValueError(f"OpenRouter error: {response}")
else:
raise ValueError("No response from OpenRouter.")
tool_calls = extract_openai_tool_calls(response)
reasoning = extract_openai_reasoning(response)
@@ -1077,8 +1061,12 @@ async def llm_call(
parallel_tool_calls=parallel_tool_calls_param,
)
# If there's no response, raise an error
if not response.choices:
raise ValueError(f"Llama API returned empty choices: {response}")
if response:
raise ValueError(f"Llama API error: {response}")
else:
raise ValueError("No response from Llama API.")
tool_calls = extract_openai_tool_calls(response)
reasoning = extract_openai_reasoning(response)
@@ -1108,8 +1096,6 @@ async def llm_call(
messages=prompt, # type: ignore
max_tokens=max_tokens,
)
if not completion.choices:
raise ValueError("AI/ML API returned empty choices in response")
return LLMResponse(
raw_response=completion.choices[0].message,
@@ -1146,9 +1132,6 @@ async def llm_call(
parallel_tool_calls=parallel_tool_calls_param,
)
if not response.choices:
raise ValueError(f"v0 API returned empty choices: {response}")
tool_calls = extract_openai_tool_calls(response)
reasoning = extract_openai_reasoning(response)
@@ -2016,19 +1999,6 @@ class AIConversationBlock(AIBlockBase):
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
has_messages = any(
isinstance(m, dict)
and isinstance(m.get("content"), str)
and bool(m["content"].strip())
for m in (input_data.messages or [])
)
has_prompt = bool(input_data.prompt and input_data.prompt.strip())
if not has_messages and not has_prompt:
raise ValueError(
"Cannot call LLM with no messages and no prompt. "
"Provide at least one message or a non-empty prompt."
)
response = await self.llm_call(
AIStructuredResponseGeneratorBlock.Input(
prompt=input_data.prompt,

View File

@@ -89,12 +89,6 @@ class MCPToolBlock(Block):
default={},
hidden=True,
)
tool_description: str = SchemaField(
description="Description of the selected MCP tool. "
"Populated automatically when a tool is selected.",
default="",
hidden=True,
)
tool_arguments: dict[str, Any] = SchemaField(
description="Arguments to pass to the selected MCP tool. "

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@@ -1,323 +0,0 @@
import asyncio
from typing import Any, Literal
from pydantic import SecretStr
from sqlalchemy.engine.url import URL
from sqlalchemy.exc import DBAPIError, OperationalError, ProgrammingError
from backend.blocks._base import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.sql_query_helpers import (
_DATABASE_TYPE_DEFAULT_PORT,
_DATABASE_TYPE_TO_DRIVER,
DatabaseType,
_execute_query,
_sanitize_error,
_validate_query_is_read_only,
_validate_single_statement,
)
from backend.data.model import (
CredentialsField,
CredentialsMetaInput,
SchemaField,
UserPasswordCredentials,
)
from backend.integrations.providers import ProviderName
from backend.util.request import resolve_and_check_blocked
TEST_CREDENTIALS = UserPasswordCredentials(
id="01234567-89ab-cdef-0123-456789abcdef",
provider="database",
username=SecretStr("test_user"),
password=SecretStr("test_pass"),
title="Mock Database credentials",
)
TEST_CREDENTIALS_INPUT = {
"provider": TEST_CREDENTIALS.provider,
"id": TEST_CREDENTIALS.id,
"type": TEST_CREDENTIALS.type,
"title": TEST_CREDENTIALS.title,
}
DatabaseCredentials = UserPasswordCredentials
DatabaseCredentialsInput = CredentialsMetaInput[
Literal[ProviderName.DATABASE],
Literal["user_password"],
]
def DatabaseCredentialsField() -> DatabaseCredentialsInput:
return CredentialsField(
description="Database username and password",
)
class SQLQueryBlock(Block):
class Input(BlockSchemaInput):
database_type: DatabaseType = SchemaField(
default=DatabaseType.POSTGRES,
description="Database engine",
advanced=False,
)
host: SecretStr = SchemaField(
description=(
"Database hostname or IP address. "
"Treated as a secret to avoid leaking infrastructure details. "
"Private/internal IPs are blocked (SSRF protection)."
),
placeholder="db.example.com",
secret=True,
)
port: int | None = SchemaField(
default=None,
description=(
"Database port (leave empty for default: "
"PostgreSQL: 5432, MySQL: 3306, MSSQL: 1433)"
),
ge=1,
le=65535,
)
database: str = SchemaField(
description="Name of the database to connect to",
placeholder="my_database",
)
query: str = SchemaField(
description="SQL query to execute",
placeholder="SELECT * FROM analytics.daily_active_users LIMIT 10",
)
read_only: bool = SchemaField(
default=True,
description=(
"When enabled (default), only SELECT queries are allowed "
"and the database session is set to read-only mode. "
"Disable to allow write operations (INSERT, UPDATE, DELETE, etc.)."
),
)
timeout: int = SchemaField(
default=30,
description="Query timeout in seconds (max 120)",
ge=1,
le=120,
)
max_rows: int = SchemaField(
default=1000,
description="Maximum number of rows to return (max 10000)",
ge=1,
le=10000,
)
credentials: DatabaseCredentialsInput = DatabaseCredentialsField()
class Output(BlockSchemaOutput):
results: list[dict[str, Any]] = SchemaField(
description="Query results as a list of row dictionaries"
)
columns: list[str] = SchemaField(
description="Column names from the query result"
)
row_count: int = SchemaField(description="Number of rows returned")
truncated: bool = SchemaField(
description=(
"True when the result set was capped by max_rows, "
"indicating additional rows exist in the database"
)
)
affected_rows: int = SchemaField(
description="Number of rows affected by a write query (INSERT/UPDATE/DELETE)"
)
error: str = SchemaField(description="Error message if the query failed")
def __init__(self):
super().__init__(
id="4dc35c0f-4fd8-465e-9616-5a216f1ba2bc",
description=(
"Execute a SQL query. Read-only by default for safety "
"-- disable to allow write operations. "
"Supports PostgreSQL, MySQL, and MSSQL via SQLAlchemy."
),
categories={BlockCategory.DATA},
input_schema=SQLQueryBlock.Input,
output_schema=SQLQueryBlock.Output,
test_input={
"query": "SELECT 1 AS test_col",
"database_type": DatabaseType.POSTGRES,
"host": "localhost",
"database": "test_db",
"timeout": 30,
"max_rows": 1000,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_credentials=TEST_CREDENTIALS,
test_output=[
("results", [{"test_col": 1}]),
("columns", ["test_col"]),
("row_count", 1),
("truncated", False),
],
test_mock={
"execute_query": lambda *_args, **_kwargs: (
[{"test_col": 1}],
["test_col"],
-1,
False,
),
"check_host_allowed": lambda *_args, **_kwargs: ["127.0.0.1"],
},
)
@staticmethod
async def check_host_allowed(host: str) -> list[str]:
"""Validate that the given host is not a private/blocked address.
Returns the list of resolved IP addresses so the caller can pin the
connection to the validated IP (preventing DNS rebinding / TOCTOU).
Raises ValueError or OSError if the host is blocked.
Extracted as a method so it can be mocked during block tests.
"""
return await resolve_and_check_blocked(host)
@staticmethod
def execute_query(
connection_url: URL | str,
query: str,
timeout: int,
max_rows: int,
read_only: bool = True,
database_type: DatabaseType = DatabaseType.POSTGRES,
) -> tuple[list[dict[str, Any]], list[str], int, bool]:
"""Execute a SQL query and return (rows, columns, affected_rows, truncated).
Delegates to ``_execute_query`` in ``sql_query_helpers``.
Extracted as a method so it can be mocked during block tests.
"""
return _execute_query(
connection_url=connection_url,
query=query,
timeout=timeout,
max_rows=max_rows,
read_only=read_only,
database_type=database_type,
)
async def run(
self,
input_data: Input,
*,
credentials: DatabaseCredentials,
**_kwargs: Any,
) -> BlockOutput:
# Validate query structure and read-only constraints.
error = self._validate_query(input_data)
if error:
yield "error", error
return
# Validate host and resolve for SSRF protection.
host, pinned_host, error = await self._resolve_host(input_data)
if error:
yield "error", error
return
# Build connection URL and execute.
port = input_data.port or _DATABASE_TYPE_DEFAULT_PORT[input_data.database_type]
username = credentials.username.get_secret_value()
connection_url = URL.create(
drivername=_DATABASE_TYPE_TO_DRIVER[input_data.database_type],
username=username,
password=credentials.password.get_secret_value(),
host=pinned_host,
port=port,
database=input_data.database,
)
conn_str = connection_url.render_as_string(hide_password=True)
db_name = input_data.database
def _sanitize(err: Exception) -> str:
return _sanitize_error(
str(err).strip(),
conn_str,
host=pinned_host,
original_host=host,
username=username,
port=port,
database=db_name,
)
try:
results, columns, affected, truncated = await asyncio.to_thread(
self.execute_query,
connection_url=connection_url,
query=input_data.query,
timeout=input_data.timeout,
max_rows=input_data.max_rows,
read_only=input_data.read_only,
database_type=input_data.database_type,
)
yield "results", results
yield "columns", columns
yield "row_count", len(results)
yield "truncated", truncated
if affected >= 0:
yield "affected_rows", affected
except OperationalError as e:
yield (
"error",
self._classify_operational_error(
_sanitize(e),
input_data.timeout,
),
)
except ProgrammingError as e:
yield "error", f"SQL error: {_sanitize(e)}"
except DBAPIError as e:
yield "error", f"Database error: {_sanitize(e)}"
except ModuleNotFoundError:
yield (
"error",
(
f"Database driver not available for "
f"{input_data.database_type.value}. "
f"Please contact the platform administrator."
),
)
@staticmethod
def _validate_query(input_data: "SQLQueryBlock.Input") -> str | None:
"""Validate query structure and read-only constraints."""
stmt_error, parsed_stmt = _validate_single_statement(input_data.query)
if stmt_error:
return stmt_error
assert parsed_stmt is not None
if input_data.read_only:
return _validate_query_is_read_only(parsed_stmt)
return None
async def _resolve_host(
self, input_data: "SQLQueryBlock.Input"
) -> tuple[str, str, str | None]:
"""Validate and resolve the database host. Returns (host, pinned_ip, error)."""
host = input_data.host.get_secret_value().strip()
if not host:
return "", "", "Database host is required."
if host.startswith("/"):
return host, "", "Unix socket connections are not allowed."
try:
resolved_ips = await self.check_host_allowed(host)
except (ValueError, OSError) as e:
return host, "", f"Blocked host: {str(e).strip()}"
return host, resolved_ips[0], None
@staticmethod
def _classify_operational_error(sanitized_msg: str, timeout: int) -> str:
"""Classify an already-sanitized OperationalError for user display."""
lower = sanitized_msg.lower()
if "timeout" in lower or "cancel" in lower:
return f"Query timed out after {timeout}s."
if "connect" in lower:
return f"Failed to connect to database: {sanitized_msg}"
return f"Database error: {sanitized_msg}"

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@@ -1,430 +0,0 @@
import re
from datetime import date, datetime, time
from decimal import Decimal
from enum import Enum
from typing import Any
import sqlparse
from sqlalchemy import create_engine, text
from sqlalchemy.engine.url import URL
class DatabaseType(str, Enum):
POSTGRES = "postgres"
MYSQL = "mysql"
MSSQL = "mssql"
# Defense-in-depth: reject queries containing data-modifying keywords.
# These are checked against parsed SQL tokens (not raw text) so column names
# and string literals do not cause false positives.
_DISALLOWED_KEYWORDS = {
"INSERT",
"UPDATE",
"DELETE",
"DROP",
"ALTER",
"CREATE",
"TRUNCATE",
"GRANT",
"REVOKE",
"COPY",
"EXECUTE",
"CALL",
"SET",
"RESET",
"DISCARD",
"NOTIFY",
"DO",
# MySQL file exfiltration: LOAD DATA LOCAL INFILE reads server/client files
"LOAD",
# MySQL REPLACE is INSERT-or-UPDATE; data modification
"REPLACE",
# ANSI MERGE (UPSERT) modifies data
"MERGE",
# MSSQL BULK INSERT loads external files into tables
"BULK",
# MSSQL EXEC / EXEC sp_name runs stored procedures (arbitrary code)
"EXEC",
}
# Map DatabaseType enum values to the expected SQLAlchemy driver prefix.
_DATABASE_TYPE_TO_DRIVER = {
DatabaseType.POSTGRES: "postgresql",
DatabaseType.MYSQL: "mysql+pymysql",
DatabaseType.MSSQL: "mssql+pymssql",
}
# Connection timeout in seconds passed to the DBAPI driver (connect_timeout /
# login_timeout). This bounds how long the driver waits to establish a TCP
# connection to the database server. It is separate from the per-statement
# timeout configured via SET commands inside _configure_session().
_CONNECT_TIMEOUT_SECONDS = 10
# Default ports for each database type.
_DATABASE_TYPE_DEFAULT_PORT = {
DatabaseType.POSTGRES: 5432,
DatabaseType.MYSQL: 3306,
DatabaseType.MSSQL: 1433,
}
def _sanitize_error(
error_msg: str,
connection_string: str,
*,
host: str = "",
original_host: str = "",
username: str = "",
port: int = 0,
database: str = "",
) -> str:
"""Remove connection string, credentials, and infrastructure details
from error messages so they are safe to expose to the LLM.
Scrubs:
- The full connection string
- URL-embedded credentials (``://user:pass@``)
- ``password=<value>`` key-value pairs
- The database hostname / IP used for the connection
- The original (pre-resolution) hostname provided by the user
- Any IPv4 addresses that appear in the message
- Any bracketed IPv6 addresses (e.g. ``[::1]``, ``[fe80::1%eth0]``)
- The database username
- The database port number
- The database name
"""
sanitized = error_msg.replace(connection_string, "<connection_string>")
sanitized = re.sub(r"password=[^\s&]+", "password=***", sanitized)
sanitized = re.sub(r"://[^@]+@", "://***:***@", sanitized)
# Replace the known host (may be an IP already) before the generic IP pass.
# Also replace the original (pre-DNS-resolution) hostname if it differs.
if original_host and original_host != host:
sanitized = sanitized.replace(original_host, "<host>")
if host:
sanitized = sanitized.replace(host, "<host>")
# Replace any remaining IPv4 addresses (e.g. resolved IPs the driver logs)
sanitized = re.sub(r"\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}", "<ip>", sanitized)
# Replace bracketed IPv6 addresses (e.g. "[::1]", "[fe80::1%eth0]")
sanitized = re.sub(r"\[[0-9a-fA-F:]+(?:%[^\]]+)?\]", "<ip>", sanitized)
# Replace the database username (handles double-quoted, single-quoted,
# and unquoted formats across PostgreSQL, MySQL, and MSSQL error messages).
if username:
sanitized = re.sub(
r"""for user ["']?""" + re.escape(username) + r"""["']?""",
"for user <user>",
sanitized,
)
# Catch remaining bare occurrences in various quote styles:
# - PostgreSQL: "FATAL: role "myuser" does not exist"
# - MySQL: "Access denied for user 'myuser'@'host'"
# - MSSQL: "Login failed for user 'myuser'"
sanitized = sanitized.replace(f'"{username}"', "<user>")
sanitized = sanitized.replace(f"'{username}'", "<user>")
# Replace the port number (handles "port 5432" and ":5432" formats)
if port:
port_str = re.escape(str(port))
sanitized = re.sub(
r"(?:port |:)" + port_str + r"(?![0-9])",
lambda m: ("port " if m.group().startswith("p") else ":") + "<port>",
sanitized,
)
# Replace the database name to avoid leaking internal infrastructure names.
# Use word-boundary regex to prevent mangling when the database name is a
# common substring (e.g. "test", "data", "on").
if database:
sanitized = re.sub(r"\b" + re.escape(database) + r"\b", "<database>", sanitized)
return sanitized
def _extract_keyword_tokens(parsed: sqlparse.sql.Statement) -> list[str]:
"""Extract keyword tokens from a parsed SQL statement.
Uses sqlparse token type classification to collect Keyword/DML/DDL/DCL
tokens. String literals and identifiers have different token types, so
they are naturally excluded from the result.
"""
return [
token.normalized.upper()
for token in parsed.flatten()
if token.ttype
in (
sqlparse.tokens.Keyword,
sqlparse.tokens.Keyword.DML,
sqlparse.tokens.Keyword.DDL,
sqlparse.tokens.Keyword.DCL,
)
]
def _has_disallowed_into(stmt: sqlparse.sql.Statement) -> bool:
"""Check if a statement contains a disallowed ``INTO`` clause.
``SELECT ... INTO @variable`` is a valid read-only MySQL syntax that stores
a query result into a session-scoped user variable. All other forms of
``INTO`` are data-modifying or file-writing and must be blocked:
* ``SELECT ... INTO new_table`` (PostgreSQL / MSSQL creates a table)
* ``SELECT ... INTO OUTFILE`` (MySQL writes to the filesystem)
* ``SELECT ... INTO DUMPFILE`` (MySQL writes to the filesystem)
* ``INSERT INTO ...`` (already blocked by INSERT being in the
disallowed set, but we reject INTO as well for defense-in-depth)
Returns ``True`` if the statement contains a disallowed ``INTO``.
"""
flat = list(stmt.flatten())
for i, token in enumerate(flat):
if not (
token.ttype in (sqlparse.tokens.Keyword,)
and token.normalized.upper() == "INTO"
):
continue
# Look at the first non-whitespace token after INTO.
j = i + 1
while j < len(flat) and flat[j].ttype is sqlparse.tokens.Text.Whitespace:
j += 1
if j >= len(flat):
# INTO at the very end malformed, block it.
return True
next_token = flat[j]
# MySQL user variable: either a single Name starting with "@"
# (e.g. ``@total``) or a bare ``@`` Operator token followed by a Name.
if next_token.ttype is sqlparse.tokens.Name and next_token.value.startswith(
"@"
):
continue
if next_token.ttype is sqlparse.tokens.Operator and next_token.value == "@":
continue
# Everything else (table name, OUTFILE, DUMPFILE, etc.) is disallowed.
return True
return False
def _validate_query_is_read_only(stmt: sqlparse.sql.Statement) -> str | None:
"""Validate that a parsed SQL statement is read-only (SELECT/WITH only).
Accepts an already-parsed statement from ``_validate_single_statement``
to avoid re-parsing. Checks:
1. Statement type must be SELECT (sqlparse classifies WITH...SELECT as SELECT)
2. No disallowed keywords (INSERT, UPDATE, DELETE, DROP, etc.)
3. No disallowed INTO clauses (allows MySQL ``SELECT ... INTO @variable``)
Returns an error message if the query is not read-only, None otherwise.
"""
# sqlparse returns 'SELECT' for SELECT and WITH...SELECT queries
if stmt.get_type() != "SELECT":
return "Only SELECT queries are allowed."
# Defense-in-depth: check parsed keyword tokens for disallowed keywords
for kw in _extract_keyword_tokens(stmt):
# Normalize multi-word tokens (e.g. "SET LOCAL" -> "SET")
base_kw = kw.split()[0] if " " in kw else kw
if base_kw in _DISALLOWED_KEYWORDS:
return f"Disallowed SQL keyword: {kw}"
# Contextual check for INTO: allow MySQL @variable syntax, block everything else
if _has_disallowed_into(stmt):
return "Disallowed SQL keyword: INTO"
return None
def _validate_single_statement(
query: str,
) -> tuple[str | None, sqlparse.sql.Statement | None]:
"""Validate that the query contains exactly one non-empty SQL statement.
Returns (error_message, parsed_statement). If error_message is not None,
the query is invalid and parsed_statement will be None.
"""
stripped = query.strip().rstrip(";").strip()
if not stripped:
return "Query is empty.", None
# Parse the SQL using sqlparse for proper tokenization
statements = sqlparse.parse(stripped)
# Filter out empty statements and comment-only statements
statements = [
s
for s in statements
if s.tokens
and str(s).strip()
and not all(
t.is_whitespace or t.ttype in sqlparse.tokens.Comment for t in s.flatten()
)
]
if not statements:
return "Query is empty.", None
# Reject multiple statements -- prevents injection via semicolons
if len(statements) > 1:
return "Only single statements are allowed.", None
return None, statements[0]
def _serialize_value(value: Any) -> Any:
"""Convert database-specific types to JSON-serializable Python types."""
if isinstance(value, Decimal):
# NaN / Infinity are not valid JSON numbers; serialize as strings.
if value.is_nan() or value.is_infinite():
return str(value)
# Use int for whole numbers; use str for fractional to preserve exact
# precision (float would silently round high-precision analytics values).
if value == value.to_integral_value():
return int(value)
return str(value)
if isinstance(value, (datetime, date, time)):
return value.isoformat()
if isinstance(value, memoryview):
return bytes(value).hex()
if isinstance(value, bytes):
return value.hex()
return value
def _configure_session(
conn: Any,
dialect_name: str,
timeout_ms: str,
read_only: bool,
) -> None:
"""Set session-level timeout and read-only mode for the given dialect.
Timeout limitations by database:
* **PostgreSQL** ``statement_timeout`` reliably cancels any running
statement (SELECT or DML) after the configured duration.
* **MySQL** ``MAX_EXECUTION_TIME`` only applies to **read-only SELECT**
statements. DML (INSERT/UPDATE/DELETE) and DDL are *not* bounded by
this hint; they rely on the server's ``wait_timeout`` /
``interactive_timeout`` instead. There is no session-level setting in
MySQL that reliably cancels long-running writes.
* **MSSQL** ``SET LOCK_TIMEOUT`` only limits how long the server waits
to acquire a **lock**. CPU-bound queries (e.g. large scans, hash
joins) that do not block on locks will *not* be cancelled. MSSQL has
no session-level ``statement_timeout`` equivalent; the closest
mechanism is Resource Governor (requires sysadmin configuration) or
``CONTEXT_INFO``-based external monitoring.
Note: SQLite is not supported by this block. The ``_configure_session``
function is a no-op for unrecognised dialect names, so an SQLite engine
would skip all SET commands silently. The block's ``DatabaseType`` enum
intentionally excludes SQLite.
"""
if dialect_name == "postgresql":
conn.execute(text("SET statement_timeout = " + timeout_ms))
if read_only:
conn.execute(text("SET default_transaction_read_only = ON"))
elif dialect_name == "mysql":
# NOTE: MAX_EXECUTION_TIME only applies to SELECT statements.
# Write queries (INSERT/UPDATE/DELETE) are not bounded by this
# setting; they rely on the database's wait_timeout instead.
# See docstring above for full limitations.
conn.execute(text("SET SESSION MAX_EXECUTION_TIME = " + timeout_ms))
if read_only:
conn.execute(text("SET SESSION TRANSACTION READ ONLY"))
elif dialect_name == "mssql":
# MSSQL: SET LOCK_TIMEOUT limits lock-wait time (ms) only.
# CPU-bound queries without lock contention are NOT cancelled.
# See docstring above for full limitations.
conn.execute(text("SET LOCK_TIMEOUT " + timeout_ms))
# MSSQL lacks a session-level read-only mode like
# PostgreSQL/MySQL. Read-only enforcement is handled by
# the SQL validation layer (_validate_query_is_read_only)
# and the ROLLBACK in the finally block.
def _run_in_transaction(
conn: Any,
dialect_name: str,
query: str,
max_rows: int,
read_only: bool,
) -> tuple[list[dict[str, Any]], list[str], int, bool]:
"""Execute a query inside an explicit transaction, returning results.
Returns ``(rows, columns, affected_rows, truncated)`` where *truncated*
is ``True`` when ``fetchmany`` returned exactly ``max_rows`` rows,
indicating that additional rows may exist in the result set.
"""
# MSSQL uses T-SQL "BEGIN TRANSACTION"; others use "BEGIN".
begin_stmt = "BEGIN TRANSACTION" if dialect_name == "mssql" else "BEGIN"
conn.execute(text(begin_stmt))
try:
result = conn.execute(text(query))
affected = result.rowcount if not result.returns_rows else -1
columns = list(result.keys()) if result.returns_rows else []
rows = result.fetchmany(max_rows) if result.returns_rows else []
truncated = len(rows) == max_rows
results = [
{col: _serialize_value(val) for col, val in zip(columns, row)}
for row in rows
]
except Exception:
try:
conn.execute(text("ROLLBACK"))
except Exception:
pass
raise
else:
conn.execute(text("ROLLBACK" if read_only else "COMMIT"))
return results, columns, affected, truncated
def _execute_query(
connection_url: URL | str,
query: str,
timeout: int,
max_rows: int,
read_only: bool = True,
database_type: DatabaseType = DatabaseType.POSTGRES,
) -> tuple[list[dict[str, Any]], list[str], int, bool]:
"""Execute a SQL query and return (rows, columns, affected_rows, truncated).
Uses SQLAlchemy to connect to any supported database.
For SELECT queries, rows are limited to ``max_rows`` via DBAPI fetchmany.
``truncated`` is ``True`` when the result set was capped by ``max_rows``.
For write queries, affected_rows contains the rowcount from the driver.
When ``read_only`` is True, the database session is set to read-only
mode and the transaction is always rolled back.
"""
# Determine driver-specific connection timeout argument.
# pymssql uses "login_timeout", while PostgreSQL/MySQL use "connect_timeout".
timeout_key = (
"login_timeout" if database_type == DatabaseType.MSSQL else "connect_timeout"
)
engine = create_engine(
connection_url, connect_args={timeout_key: _CONNECT_TIMEOUT_SECONDS}
)
try:
with engine.connect() as conn:
# Use AUTOCOMMIT so SET commands take effect immediately.
conn = conn.execution_options(isolation_level="AUTOCOMMIT")
# Compute timeout in milliseconds. The value is Pydantic-validated
# (ge=1, le=120), but we use int() as defense-in-depth.
# NOTE: SET commands do not support bind parameters in most
# databases, so we use str(int(...)) for safe interpolation.
timeout_ms = str(int(timeout * 1000))
_configure_session(conn, engine.dialect.name, timeout_ms, read_only)
return _run_in_transaction(
conn, engine.dialect.name, query, max_rows, read_only
)
finally:
engine.dispose()

View File

@@ -4,8 +4,6 @@ import pytest
from backend.blocks import get_blocks
from backend.blocks._base import Block, BlockSchemaInput
from backend.blocks.io import AgentDropdownInputBlock, AgentInputBlock
from backend.data.graph import BaseGraph
from backend.data.model import SchemaField
from backend.util.test import execute_block_test
@@ -281,113 +279,3 @@ class TestAutoCredentialsFieldsValidation:
assert "Duplicate auto_credentials kwarg_name 'credentials'" in str(
exc_info.value
)
def test_agent_input_block_ignores_legacy_placeholder_values():
"""Verify AgentInputBlock.Input.model_construct tolerates extra placeholder_values
for backward compatibility with existing agent JSON."""
legacy_data = {
"name": "url",
"value": "",
"description": "Enter a URL",
"placeholder_values": ["https://example.com"],
}
instance = AgentInputBlock.Input.model_construct(**legacy_data)
schema = instance.generate_schema()
assert (
"enum" not in schema
), "AgentInputBlock should not produce enum from legacy placeholder_values"
def test_dropdown_input_block_produces_enum():
"""Verify AgentDropdownInputBlock.Input.generate_schema() produces enum
using the canonical 'options' field name."""
opts = ["Option A", "Option B"]
instance = AgentDropdownInputBlock.Input.model_construct(
name="choice", value=None, options=opts
)
schema = instance.generate_schema()
assert schema.get("enum") == opts
def test_dropdown_input_block_legacy_placeholder_values_produces_enum():
"""Verify backward compat: passing legacy 'placeholder_values' to
AgentDropdownInputBlock still produces enum via model_construct remap."""
opts = ["Option A", "Option B"]
instance = AgentDropdownInputBlock.Input.model_construct(
name="choice", value=None, placeholder_values=opts
)
schema = instance.generate_schema()
assert (
schema.get("enum") == opts
), "Legacy placeholder_values should be remapped to options"
def test_generate_schema_integration_legacy_placeholder_values():
"""Test the full Graph._generate_schema path with legacy placeholder_values
on AgentInputBlock — verifies no enum leaks through the graph loading path."""
legacy_input_default = {
"name": "url",
"value": "",
"description": "Enter a URL",
"placeholder_values": ["https://example.com"],
}
result = BaseGraph._generate_schema(
(AgentInputBlock.Input, legacy_input_default),
)
url_props = result["properties"]["url"]
assert (
"enum" not in url_props
), "Graph schema should not contain enum from AgentInputBlock placeholder_values"
def test_generate_schema_integration_dropdown_produces_enum():
"""Test the full Graph._generate_schema path with AgentDropdownInputBlock
— verifies enum IS produced for dropdown blocks using canonical field name."""
dropdown_input_default = {
"name": "color",
"value": None,
"options": ["Red", "Green", "Blue"],
}
result = BaseGraph._generate_schema(
(AgentDropdownInputBlock.Input, dropdown_input_default),
)
color_props = result["properties"]["color"]
assert color_props.get("enum") == [
"Red",
"Green",
"Blue",
], "Graph schema should contain enum from AgentDropdownInputBlock"
def test_generate_schema_integration_dropdown_legacy_placeholder_values():
"""Test the full Graph._generate_schema path with AgentDropdownInputBlock
using legacy 'placeholder_values' — verifies backward compat produces enum."""
legacy_dropdown_input_default = {
"name": "color",
"value": None,
"placeholder_values": ["Red", "Green", "Blue"],
}
result = BaseGraph._generate_schema(
(AgentDropdownInputBlock.Input, legacy_dropdown_input_default),
)
color_props = result["properties"]["color"]
assert color_props.get("enum") == [
"Red",
"Green",
"Blue",
], "Legacy placeholder_values should still produce enum via model_construct remap"
def test_dropdown_input_block_init_legacy_placeholder_values():
"""Verify backward compat: constructing AgentDropdownInputBlock.Input via
model_validate with legacy 'placeholder_values' correctly maps to 'options'."""
opts = ["Option A", "Option B"]
instance = AgentDropdownInputBlock.Input.model_validate(
{"name": "choice", "value": None, "placeholder_values": opts}
)
assert (
instance.options == opts
), "Legacy placeholder_values should be remapped to options via model_validate"
schema = instance.generate_schema()
assert schema.get("enum") == opts

View File

@@ -207,51 +207,6 @@ class TestXMLParserBlockSecurity:
pass
class TestXMLParserBlockSyntaxErrors:
"""XML syntax errors should raise ValueError (not SyntaxError).
This ensures the base Block.execute() wraps them as BlockExecutionError
(expected / user-caused) instead of BlockUnknownError (unexpected / alerts
Sentry).
"""
async def test_unclosed_tag_raises_value_error(self):
"""Unclosed tags should raise ValueError, not SyntaxError."""
block = XMLParserBlock()
bad_xml = "<root><unclosed>"
with pytest.raises(ValueError, match="Unclosed tag"):
async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
pass
async def test_unexpected_closing_tag_raises_value_error(self):
"""Extra closing tags should raise ValueError, not SyntaxError."""
block = XMLParserBlock()
bad_xml = "</unexpected>"
with pytest.raises(ValueError):
async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
pass
async def test_empty_xml_raises_value_error(self):
"""Empty XML input should raise ValueError."""
block = XMLParserBlock()
with pytest.raises(ValueError, match="XML input is empty"):
async for _ in block.run(XMLParserBlock.Input(input_xml="")):
pass
async def test_syntax_error_from_parser_becomes_value_error(self):
"""SyntaxErrors from gravitasml library become ValueError (BlockExecutionError)."""
block = XMLParserBlock()
# Malformed XML that might trigger a SyntaxError from the parser
bad_xml = "<root><child>no closing"
with pytest.raises(ValueError):
async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
pass
class TestStoreMediaFileSecurity:
"""Test file storage security limits."""

View File

@@ -488,154 +488,6 @@ class TestLLMStatsTracking:
assert outputs["response"] == {"result": "test"}
class TestAIConversationBlockValidation:
"""Test that AIConversationBlock validates inputs before calling the LLM."""
@pytest.mark.asyncio
async def test_empty_messages_and_empty_prompt_raises_error(self):
"""Empty messages with no prompt should raise ValueError, not a cryptic API error."""
block = llm.AIConversationBlock()
input_data = llm.AIConversationBlock.Input(
messages=[],
prompt="",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
with pytest.raises(ValueError, match="no messages and no prompt"):
async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
pass
@pytest.mark.asyncio
async def test_empty_messages_with_prompt_succeeds(self):
"""Empty messages but a non-empty prompt should proceed without error."""
block = llm.AIConversationBlock()
async def mock_llm_call(input_data, credentials):
return {"response": "OK"}
with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
input_data = llm.AIConversationBlock.Input(
messages=[],
prompt="Hello, how are you?",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
outputs = {}
async for name, data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[name] = data
assert outputs["response"] == "OK"
@pytest.mark.asyncio
async def test_nonempty_messages_with_empty_prompt_succeeds(self):
"""Non-empty messages with no prompt should proceed without error."""
block = llm.AIConversationBlock()
async def mock_llm_call(input_data, credentials):
return {"response": "response from conversation"}
with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
input_data = llm.AIConversationBlock.Input(
messages=[{"role": "user", "content": "Hello"}],
prompt="",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
outputs = {}
async for name, data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[name] = data
assert outputs["response"] == "response from conversation"
@pytest.mark.asyncio
async def test_messages_with_empty_content_raises_error(self):
"""Messages with empty content strings should be treated as no messages."""
block = llm.AIConversationBlock()
input_data = llm.AIConversationBlock.Input(
messages=[{"role": "user", "content": ""}],
prompt="",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
with pytest.raises(ValueError, match="no messages and no prompt"):
async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
pass
@pytest.mark.asyncio
async def test_messages_with_whitespace_content_raises_error(self):
"""Messages with whitespace-only content should be treated as no messages."""
block = llm.AIConversationBlock()
input_data = llm.AIConversationBlock.Input(
messages=[{"role": "user", "content": " "}],
prompt="",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
with pytest.raises(ValueError, match="no messages and no prompt"):
async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
pass
@pytest.mark.asyncio
async def test_messages_with_none_entry_raises_error(self):
"""Messages list containing None should be treated as no messages."""
block = llm.AIConversationBlock()
input_data = llm.AIConversationBlock.Input(
messages=[None],
prompt="",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
with pytest.raises(ValueError, match="no messages and no prompt"):
async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
pass
@pytest.mark.asyncio
async def test_messages_with_empty_dict_raises_error(self):
"""Messages list containing empty dict should be treated as no messages."""
block = llm.AIConversationBlock()
input_data = llm.AIConversationBlock.Input(
messages=[{}],
prompt="",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
with pytest.raises(ValueError, match="no messages and no prompt"):
async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
pass
@pytest.mark.asyncio
async def test_messages_with_none_content_raises_error(self):
"""Messages with content=None should not crash with AttributeError."""
block = llm.AIConversationBlock()
input_data = llm.AIConversationBlock.Input(
messages=[{"role": "user", "content": None}],
prompt="",
model=llm.DEFAULT_LLM_MODEL,
credentials=_TEST_AI_CREDENTIALS,
)
with pytest.raises(ValueError, match="no messages and no prompt"):
async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
pass
class TestAITextSummarizerValidation:
"""Test that AITextSummarizerBlock validates LLM responses are strings."""
@@ -957,33 +809,3 @@ class TestUserErrorStatusCodeHandling:
mock_warning.assert_called_once()
mock_exception.assert_not_called()
class TestLlmModelMissing:
"""Test that LlmModel handles provider-prefixed model names."""
def test_provider_prefixed_model_resolves(self):
"""Provider-prefixed model string should resolve to the correct enum member."""
assert (
llm.LlmModel("anthropic/claude-sonnet-4-6")
== llm.LlmModel.CLAUDE_4_6_SONNET
)
def test_bare_model_still_works(self):
"""Bare (non-prefixed) model string should still resolve correctly."""
assert llm.LlmModel("claude-sonnet-4-6") == llm.LlmModel.CLAUDE_4_6_SONNET
def test_invalid_prefixed_model_raises(self):
"""Unknown provider-prefixed model string should raise ValueError."""
with pytest.raises(ValueError):
llm.LlmModel("invalid/nonexistent-model")
def test_slash_containing_value_direct_lookup(self):
"""Enum values with '/' (e.g., OpenRouter models) should resolve via direct lookup, not _missing_."""
assert llm.LlmModel("google/gemini-2.5-pro") == llm.LlmModel.GEMINI_2_5_PRO
def test_double_prefixed_slash_model(self):
"""Double-prefixed value should still resolve by stripping first prefix."""
assert (
llm.LlmModel("extra/google/gemini-2.5-pro") == llm.LlmModel.GEMINI_2_5_PRO
)

View File

@@ -1,87 +0,0 @@
"""Tests for empty-choices guard in extract_openai_tool_calls() and extract_openai_reasoning()."""
from unittest.mock import MagicMock
from backend.blocks.llm import extract_openai_reasoning, extract_openai_tool_calls
class TestExtractOpenaiToolCallsEmptyChoices:
"""extract_openai_tool_calls() must return None when choices is empty."""
def test_returns_none_for_empty_choices(self):
response = MagicMock()
response.choices = []
assert extract_openai_tool_calls(response) is None
def test_returns_none_for_none_choices(self):
response = MagicMock()
response.choices = None
assert extract_openai_tool_calls(response) is None
def test_returns_tool_calls_when_choices_present(self):
tool = MagicMock()
tool.id = "call_1"
tool.type = "function"
tool.function.name = "my_func"
tool.function.arguments = '{"a": 1}'
message = MagicMock()
message.tool_calls = [tool]
choice = MagicMock()
choice.message = message
response = MagicMock()
response.choices = [choice]
result = extract_openai_tool_calls(response)
assert result is not None
assert len(result) == 1
assert result[0].function.name == "my_func"
def test_returns_none_when_no_tool_calls(self):
message = MagicMock()
message.tool_calls = None
choice = MagicMock()
choice.message = message
response = MagicMock()
response.choices = [choice]
assert extract_openai_tool_calls(response) is None
class TestExtractOpenaiReasoningEmptyChoices:
"""extract_openai_reasoning() must return None when choices is empty."""
def test_returns_none_for_empty_choices(self):
response = MagicMock()
response.choices = []
assert extract_openai_reasoning(response) is None
def test_returns_none_for_none_choices(self):
response = MagicMock()
response.choices = None
assert extract_openai_reasoning(response) is None
def test_returns_reasoning_from_choice(self):
choice = MagicMock()
choice.reasoning = "Step-by-step reasoning"
choice.message = MagicMock(spec=[]) # no 'reasoning' attr on message
response = MagicMock(spec=[]) # no 'reasoning' attr on response
response.choices = [choice]
result = extract_openai_reasoning(response)
assert result == "Step-by-step reasoning"
def test_returns_none_when_no_reasoning(self):
choice = MagicMock(spec=[]) # no 'reasoning' attr
choice.message = MagicMock(spec=[]) # no 'reasoning' attr
response = MagicMock(spec=[]) # no 'reasoning' attr
response.choices = [choice]
result = extract_openai_reasoning(response)
assert result is None

View File

@@ -1074,7 +1074,6 @@ async def test_orchestrator_uses_customized_name_for_blocks():
mock_node.block_id = StoreValueBlock().id
mock_node.metadata = {"customized_name": "My Custom Tool Name"}
mock_node.block = StoreValueBlock()
mock_node.input_default = {}
# Create a mock link
mock_link = MagicMock(spec=Link)
@@ -1106,7 +1105,6 @@ async def test_orchestrator_falls_back_to_block_name():
mock_node.block_id = StoreValueBlock().id
mock_node.metadata = {} # No customized_name
mock_node.block = StoreValueBlock()
mock_node.input_default = {}
# Create a mock link
mock_link = MagicMock(spec=Link)

View File

@@ -1,202 +0,0 @@
"""Tests for ExecutionMode enum and provider validation in the orchestrator.
Covers:
- ExecutionMode enum members exist and have stable values
- EXTENDED_THINKING provider validation (anthropic/open_router allowed, others rejected)
- EXTENDED_THINKING model-name validation (must start with "claude")
"""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from backend.blocks.llm import LlmModel
from backend.blocks.orchestrator import ExecutionMode, OrchestratorBlock
# ---------------------------------------------------------------------------
# ExecutionMode enum integrity
# ---------------------------------------------------------------------------
class TestExecutionModeEnum:
"""Guard against accidental renames or removals of enum members."""
def test_built_in_exists(self):
assert hasattr(ExecutionMode, "BUILT_IN")
assert ExecutionMode.BUILT_IN.value == "built_in"
def test_extended_thinking_exists(self):
assert hasattr(ExecutionMode, "EXTENDED_THINKING")
assert ExecutionMode.EXTENDED_THINKING.value == "extended_thinking"
def test_exactly_two_members(self):
"""If a new mode is added, this test should be updated intentionally."""
assert set(ExecutionMode.__members__.keys()) == {
"BUILT_IN",
"EXTENDED_THINKING",
}
def test_string_enum(self):
"""ExecutionMode is a str enum so it serialises cleanly to JSON."""
assert isinstance(ExecutionMode.BUILT_IN, str)
assert isinstance(ExecutionMode.EXTENDED_THINKING, str)
def test_round_trip_from_value(self):
"""Constructing from the string value should return the same member."""
assert ExecutionMode("built_in") is ExecutionMode.BUILT_IN
assert ExecutionMode("extended_thinking") is ExecutionMode.EXTENDED_THINKING
# ---------------------------------------------------------------------------
# Provider validation (inline in OrchestratorBlock.run)
# ---------------------------------------------------------------------------
def _make_model_stub(provider: str, value: str):
"""Create a lightweight stub that behaves like LlmModel for validation."""
metadata = MagicMock()
metadata.provider = provider
stub = MagicMock()
stub.metadata = metadata
stub.value = value
return stub
class TestExtendedThinkingProviderValidation:
"""The orchestrator rejects EXTENDED_THINKING for non-Anthropic providers."""
def test_anthropic_provider_accepted(self):
"""provider='anthropic' + claude model should not raise."""
model = _make_model_stub("anthropic", "claude-opus-4-6")
provider = model.metadata.provider
model_name = model.value
assert provider in ("anthropic", "open_router")
assert model_name.startswith("claude")
def test_open_router_provider_accepted(self):
"""provider='open_router' + claude model should not raise."""
model = _make_model_stub("open_router", "claude-sonnet-4-6")
provider = model.metadata.provider
model_name = model.value
assert provider in ("anthropic", "open_router")
assert model_name.startswith("claude")
def test_openai_provider_rejected(self):
"""provider='openai' should be rejected for EXTENDED_THINKING."""
model = _make_model_stub("openai", "gpt-4o")
provider = model.metadata.provider
assert provider not in ("anthropic", "open_router")
def test_groq_provider_rejected(self):
model = _make_model_stub("groq", "llama-3.3-70b-versatile")
provider = model.metadata.provider
assert provider not in ("anthropic", "open_router")
def test_non_claude_model_rejected_even_if_anthropic_provider(self):
"""A hypothetical non-Claude model with provider='anthropic' is rejected."""
model = _make_model_stub("anthropic", "not-a-claude-model")
model_name = model.value
assert not model_name.startswith("claude")
def test_real_gpt4o_model_rejected(self):
"""Verify a real LlmModel enum member (GPT4O) fails the provider check."""
model = LlmModel.GPT4O
provider = model.metadata.provider
assert provider not in ("anthropic", "open_router")
def test_real_claude_model_passes(self):
"""Verify a real LlmModel enum member (CLAUDE_4_6_SONNET) passes."""
model = LlmModel.CLAUDE_4_6_SONNET
provider = model.metadata.provider
model_name = model.value
assert provider in ("anthropic", "open_router")
assert model_name.startswith("claude")
# ---------------------------------------------------------------------------
# Integration-style: exercise the validation branch via OrchestratorBlock.run
# ---------------------------------------------------------------------------
def _make_input_data(model, execution_mode=ExecutionMode.EXTENDED_THINKING):
"""Build a minimal MagicMock that satisfies OrchestratorBlock.run's early path."""
inp = MagicMock()
inp.execution_mode = execution_mode
inp.model = model
inp.prompt = "test"
inp.sys_prompt = ""
inp.conversation_history = []
inp.last_tool_output = None
inp.prompt_values = {}
return inp
async def _collect_run_outputs(block, input_data, **kwargs):
"""Exhaust the OrchestratorBlock.run async generator, collecting outputs."""
outputs = []
async for item in block.run(input_data, **kwargs):
outputs.append(item)
return outputs
class TestExtendedThinkingValidationRaisesInBlock:
"""Call OrchestratorBlock.run far enough to trigger the ValueError."""
@pytest.mark.asyncio
async def test_non_anthropic_provider_raises_valueerror(self):
"""EXTENDED_THINKING + openai provider raises ValueError."""
block = OrchestratorBlock()
input_data = _make_input_data(model=LlmModel.GPT4O)
with (
patch.object(
block,
"_create_tool_node_signatures",
new_callable=AsyncMock,
return_value=[],
),
pytest.raises(ValueError, match="Anthropic-compatible"),
):
await _collect_run_outputs(
block,
input_data,
credentials=MagicMock(),
graph_id="g",
node_id="n",
graph_exec_id="ge",
node_exec_id="ne",
user_id="u",
graph_version=1,
execution_context=MagicMock(),
execution_processor=MagicMock(),
)
@pytest.mark.asyncio
async def test_non_claude_model_with_anthropic_provider_raises(self):
"""A model with anthropic provider but non-claude name raises ValueError."""
block = OrchestratorBlock()
fake_model = _make_model_stub("anthropic", "not-a-claude-model")
input_data = _make_input_data(model=fake_model)
with (
patch.object(
block,
"_create_tool_node_signatures",
new_callable=AsyncMock,
return_value=[],
),
pytest.raises(ValueError, match="only supports Claude models"),
):
await _collect_run_outputs(
block,
input_data,
credentials=MagicMock(),
graph_id="g",
node_id="n",
graph_exec_id="ge",
node_exec_id="ne",
user_id="u",
graph_version=1,
execution_context=MagicMock(),
execution_processor=MagicMock(),
)

View File

@@ -44,7 +44,7 @@ class XMLParserBlock(Block):
elif token.type == "TAG_CLOSE":
depth -= 1
if depth < 0:
raise ValueError("Unexpected closing tag in XML input.")
raise SyntaxError("Unexpected closing tag in XML input.")
elif token.type in {"TEXT", "ESCAPE"}:
if depth == 0 and token.value:
raise ValueError(
@@ -53,7 +53,7 @@ class XMLParserBlock(Block):
)
if depth != 0:
raise ValueError("Unclosed tag detected in XML input.")
raise SyntaxError("Unclosed tag detected in XML input.")
if not root_seen:
raise ValueError("XML must include a root element.")
@@ -76,7 +76,4 @@ class XMLParserBlock(Block):
except ValueError as val_e:
raise ValueError(f"Validation error for dict:{val_e}") from val_e
except SyntaxError as syn_e:
# Raise as ValueError so the base Block.execute() wraps it as
# BlockExecutionError (expected user-caused failure) instead of
# BlockUnknownError (unexpected platform error that alerts Sentry).
raise ValueError(f"Error in input xml syntax: {syn_e}") from syn_e
raise SyntaxError(f"Error in input xml syntax: {syn_e}") from syn_e

View File

@@ -9,16 +9,12 @@ shared tool registry as the SDK path.
import asyncio
import logging
import uuid
from collections.abc import AsyncGenerator, Sequence
from dataclasses import dataclass, field
from functools import partial
from typing import Any, cast
from collections.abc import AsyncGenerator
from typing import Any
import orjson
from langfuse import propagate_attributes
from openai.types.chat import ChatCompletionMessageParam, ChatCompletionToolParam
from backend.copilot.context import set_execution_context
from backend.copilot.model import (
ChatMessage,
ChatSession,
@@ -52,17 +48,7 @@ from backend.copilot.token_tracking import persist_and_record_usage
from backend.copilot.tools import execute_tool, get_available_tools
from backend.copilot.tracking import track_user_message
from backend.util.exceptions import NotFoundError
from backend.util.prompt import (
compress_context,
estimate_token_count,
estimate_token_count_str,
)
from backend.util.tool_call_loop import (
LLMLoopResponse,
LLMToolCall,
ToolCallResult,
tool_call_loop,
)
from backend.util.prompt import compress_context
logger = logging.getLogger(__name__)
@@ -73,247 +59,6 @@ _background_tasks: set[asyncio.Task[Any]] = set()
_MAX_TOOL_ROUNDS = 30
@dataclass
class _BaselineStreamState:
"""Mutable state shared between the tool-call loop callbacks.
Extracted from ``stream_chat_completion_baseline`` so that the callbacks
can be module-level functions instead of deeply nested closures.
"""
pending_events: list[StreamBaseResponse] = field(default_factory=list)
assistant_text: str = ""
text_block_id: str = field(default_factory=lambda: str(uuid.uuid4()))
text_started: bool = False
turn_prompt_tokens: int = 0
turn_completion_tokens: int = 0
async def _baseline_llm_caller(
messages: list[dict[str, Any]],
tools: Sequence[Any],
*,
state: _BaselineStreamState,
) -> LLMLoopResponse:
"""Stream an OpenAI-compatible response and collect results.
Extracted from ``stream_chat_completion_baseline`` for readability.
"""
state.pending_events.append(StreamStartStep())
round_text = ""
try:
client = _get_openai_client()
typed_messages = cast(list[ChatCompletionMessageParam], messages)
if tools:
typed_tools = cast(list[ChatCompletionToolParam], tools)
response = await client.chat.completions.create(
model=config.model,
messages=typed_messages,
tools=typed_tools,
stream=True,
stream_options={"include_usage": True},
)
else:
response = await client.chat.completions.create(
model=config.model,
messages=typed_messages,
stream=True,
stream_options={"include_usage": True},
)
tool_calls_by_index: dict[int, dict[str, str]] = {}
async for chunk in response:
if chunk.usage:
state.turn_prompt_tokens += chunk.usage.prompt_tokens or 0
state.turn_completion_tokens += chunk.usage.completion_tokens or 0
delta = chunk.choices[0].delta if chunk.choices else None
if not delta:
continue
if delta.content:
if not state.text_started:
state.pending_events.append(StreamTextStart(id=state.text_block_id))
state.text_started = True
round_text += delta.content
state.pending_events.append(
StreamTextDelta(id=state.text_block_id, delta=delta.content)
)
if delta.tool_calls:
for tc in delta.tool_calls:
idx = tc.index
if idx not in tool_calls_by_index:
tool_calls_by_index[idx] = {
"id": "",
"name": "",
"arguments": "",
}
entry = tool_calls_by_index[idx]
if tc.id:
entry["id"] = tc.id
if tc.function and tc.function.name:
entry["name"] = tc.function.name
if tc.function and tc.function.arguments:
entry["arguments"] += tc.function.arguments
# Close text block
if state.text_started:
state.pending_events.append(StreamTextEnd(id=state.text_block_id))
state.text_started = False
state.text_block_id = str(uuid.uuid4())
finally:
# Always persist partial text so the session history stays consistent,
# even when the stream is interrupted by an exception.
state.assistant_text += round_text
# Always emit StreamFinishStep to match the StreamStartStep,
# even if an exception occurred during streaming.
state.pending_events.append(StreamFinishStep())
# Convert to shared format
llm_tool_calls = [
LLMToolCall(
id=tc["id"],
name=tc["name"],
arguments=tc["arguments"] or "{}",
)
for tc in tool_calls_by_index.values()
]
return LLMLoopResponse(
response_text=round_text or None,
tool_calls=llm_tool_calls,
raw_response=None, # Not needed for baseline conversation updater
prompt_tokens=0, # Tracked via state accumulators
completion_tokens=0,
)
async def _baseline_tool_executor(
tool_call: LLMToolCall,
tools: Sequence[Any],
*,
state: _BaselineStreamState,
user_id: str | None,
session: ChatSession,
) -> ToolCallResult:
"""Execute a tool via the copilot tool registry.
Extracted from ``stream_chat_completion_baseline`` for readability.
"""
tool_call_id = tool_call.id
tool_name = tool_call.name
raw_args = tool_call.arguments or "{}"
try:
tool_args = orjson.loads(raw_args)
except orjson.JSONDecodeError as parse_err:
parse_error = f"Invalid JSON arguments for tool '{tool_name}': {parse_err}"
logger.warning("[Baseline] %s", parse_error)
state.pending_events.append(
StreamToolOutputAvailable(
toolCallId=tool_call_id,
toolName=tool_name,
output=parse_error,
success=False,
)
)
return ToolCallResult(
tool_call_id=tool_call_id,
tool_name=tool_name,
content=parse_error,
is_error=True,
)
state.pending_events.append(
StreamToolInputStart(toolCallId=tool_call_id, toolName=tool_name)
)
state.pending_events.append(
StreamToolInputAvailable(
toolCallId=tool_call_id,
toolName=tool_name,
input=tool_args,
)
)
try:
result: StreamToolOutputAvailable = await execute_tool(
tool_name=tool_name,
parameters=tool_args,
user_id=user_id,
session=session,
tool_call_id=tool_call_id,
)
state.pending_events.append(result)
tool_output = (
result.output if isinstance(result.output, str) else str(result.output)
)
return ToolCallResult(
tool_call_id=tool_call_id,
tool_name=tool_name,
content=tool_output,
)
except Exception as e:
error_output = f"Tool execution error: {e}"
logger.error(
"[Baseline] Tool %s failed: %s",
tool_name,
error_output,
exc_info=True,
)
state.pending_events.append(
StreamToolOutputAvailable(
toolCallId=tool_call_id,
toolName=tool_name,
output=error_output,
success=False,
)
)
return ToolCallResult(
tool_call_id=tool_call_id,
tool_name=tool_name,
content=error_output,
is_error=True,
)
def _baseline_conversation_updater(
messages: list[dict[str, Any]],
response: LLMLoopResponse,
tool_results: list[ToolCallResult] | None = None,
) -> None:
"""Update OpenAI message list with assistant response + tool results.
Extracted from ``stream_chat_completion_baseline`` for readability.
"""
if tool_results:
# Build assistant message with tool_calls
assistant_msg: dict[str, Any] = {"role": "assistant"}
if response.response_text:
assistant_msg["content"] = response.response_text
assistant_msg["tool_calls"] = [
{
"id": tc.id,
"type": "function",
"function": {"name": tc.name, "arguments": tc.arguments},
}
for tc in response.tool_calls
]
messages.append(assistant_msg)
for tr in tool_results:
messages.append(
{
"role": "tool",
"tool_call_id": tr.tool_call_id,
"content": tr.content,
}
)
else:
if response.response_text:
messages.append({"role": "assistant", "content": response.response_text})
async def _update_title_async(
session_id: str, message: str, user_id: str | None
) -> None:
@@ -458,9 +203,6 @@ async def stream_chat_completion_baseline(
tools = get_available_tools()
# Propagate execution context so tool handlers can read session-level flags.
set_execution_context(user_id, session)
yield StreamStart(messageId=message_id, sessionId=session_id)
# Propagate user/session context to Langfuse so all LLM calls within
@@ -477,32 +219,191 @@ async def stream_chat_completion_baseline(
except Exception:
logger.warning("[Baseline] Langfuse trace context setup failed")
assistant_text = ""
text_block_id = str(uuid.uuid4())
text_started = False
step_open = False
# Token usage accumulators — populated from streaming chunks
turn_prompt_tokens = 0
turn_completion_tokens = 0
_stream_error = False # Track whether an error occurred during streaming
state = _BaselineStreamState()
# Bind extracted module-level callbacks to this request's state/session
# using functools.partial so they satisfy the Protocol signatures.
_bound_llm_caller = partial(_baseline_llm_caller, state=state)
_bound_tool_executor = partial(
_baseline_tool_executor, state=state, user_id=user_id, session=session
)
try:
loop_result = None
async for loop_result in tool_call_loop(
messages=openai_messages,
tools=tools,
llm_call=_bound_llm_caller,
execute_tool=_bound_tool_executor,
update_conversation=_baseline_conversation_updater,
max_iterations=_MAX_TOOL_ROUNDS,
):
# Drain buffered events after each iteration (real-time streaming)
for evt in state.pending_events:
yield evt
state.pending_events.clear()
for _round in range(_MAX_TOOL_ROUNDS):
# Open a new step for each LLM round
yield StreamStartStep()
step_open = True
if loop_result and not loop_result.finished_naturally:
# Stream a response from the model
create_kwargs: dict[str, Any] = dict(
model=config.model,
messages=openai_messages,
stream=True,
stream_options={"include_usage": True},
)
if tools:
create_kwargs["tools"] = tools
response = await _get_openai_client().chat.completions.create(**create_kwargs) # type: ignore[arg-type] # dynamic kwargs
# Accumulate streamed response (text + tool calls)
round_text = ""
tool_calls_by_index: dict[int, dict[str, str]] = {}
async for chunk in response:
# Capture token usage from the streaming chunk.
# OpenRouter normalises all providers into OpenAI format
# where prompt_tokens already includes cached tokens
# (unlike Anthropic's native API). Use += to sum all
# tool-call rounds since each API call is independent.
# NOTE: stream_options={"include_usage": True} is not
# universally supported — some providers (Mistral, Llama
# via OpenRouter) always return chunk.usage=None. When
# that happens, tokens stay 0 and the tiktoken fallback
# below activates. Fail-open: one round is estimated.
if chunk.usage:
turn_prompt_tokens += chunk.usage.prompt_tokens or 0
turn_completion_tokens += chunk.usage.completion_tokens or 0
delta = chunk.choices[0].delta if chunk.choices else None
if not delta:
continue
# Text content
if delta.content:
if not text_started:
yield StreamTextStart(id=text_block_id)
text_started = True
round_text += delta.content
yield StreamTextDelta(id=text_block_id, delta=delta.content)
# Tool call fragments (streamed incrementally)
if delta.tool_calls:
for tc in delta.tool_calls:
idx = tc.index
if idx not in tool_calls_by_index:
tool_calls_by_index[idx] = {
"id": "",
"name": "",
"arguments": "",
}
entry = tool_calls_by_index[idx]
if tc.id:
entry["id"] = tc.id
if tc.function and tc.function.name:
entry["name"] = tc.function.name
if tc.function and tc.function.arguments:
entry["arguments"] += tc.function.arguments
# Close text block if we had one this round
if text_started:
yield StreamTextEnd(id=text_block_id)
text_started = False
text_block_id = str(uuid.uuid4())
# Accumulate text for session persistence
assistant_text += round_text
# No tool calls -> model is done
if not tool_calls_by_index:
yield StreamFinishStep()
step_open = False
break
# Close step before tool execution
yield StreamFinishStep()
step_open = False
# Append the assistant message with tool_calls to context.
assistant_msg: dict[str, Any] = {"role": "assistant"}
if round_text:
assistant_msg["content"] = round_text
assistant_msg["tool_calls"] = [
{
"id": tc["id"],
"type": "function",
"function": {
"name": tc["name"],
"arguments": tc["arguments"] or "{}",
},
}
for tc in tool_calls_by_index.values()
]
openai_messages.append(assistant_msg)
# Execute each tool call and stream events
for tc in tool_calls_by_index.values():
tool_call_id = tc["id"]
tool_name = tc["name"]
raw_args = tc["arguments"] or "{}"
try:
tool_args = orjson.loads(raw_args)
except orjson.JSONDecodeError as parse_err:
parse_error = (
f"Invalid JSON arguments for tool '{tool_name}': {parse_err}"
)
logger.warning("[Baseline] %s", parse_error)
yield StreamToolOutputAvailable(
toolCallId=tool_call_id,
toolName=tool_name,
output=parse_error,
success=False,
)
openai_messages.append(
{
"role": "tool",
"tool_call_id": tool_call_id,
"content": parse_error,
}
)
continue
yield StreamToolInputStart(toolCallId=tool_call_id, toolName=tool_name)
yield StreamToolInputAvailable(
toolCallId=tool_call_id,
toolName=tool_name,
input=tool_args,
)
# Execute via shared tool registry
try:
result: StreamToolOutputAvailable = await execute_tool(
tool_name=tool_name,
parameters=tool_args,
user_id=user_id,
session=session,
tool_call_id=tool_call_id,
)
yield result
tool_output = (
result.output
if isinstance(result.output, str)
else str(result.output)
)
except Exception as e:
error_output = f"Tool execution error: {e}"
logger.error(
"[Baseline] Tool %s failed: %s",
tool_name,
error_output,
exc_info=True,
)
yield StreamToolOutputAvailable(
toolCallId=tool_call_id,
toolName=tool_name,
output=error_output,
success=False,
)
tool_output = error_output
# Append tool result to context for next round
openai_messages.append(
{
"role": "tool",
"tool_call_id": tool_call_id,
"content": tool_output,
}
)
else:
# for-loop exhausted without break -> tool-round limit hit
limit_msg = (
f"Exceeded {_MAX_TOOL_ROUNDS} tool-call rounds "
"without a final response."
@@ -517,28 +418,11 @@ async def stream_chat_completion_baseline(
_stream_error = True
error_msg = str(e) or type(e).__name__
logger.error("[Baseline] Streaming error: %s", error_msg, exc_info=True)
# Close any open text block. The llm_caller's finally block
# already appended StreamFinishStep to pending_events, so we must
# insert StreamTextEnd *before* StreamFinishStep to preserve the
# protocol ordering:
# StreamStartStep -> StreamTextStart -> ...deltas... ->
# StreamTextEnd -> StreamFinishStep
# Appending (or yielding directly) would place it after
# StreamFinishStep, violating the protocol.
if state.text_started:
# Find the last StreamFinishStep and insert before it.
insert_pos = len(state.pending_events)
for i in range(len(state.pending_events) - 1, -1, -1):
if isinstance(state.pending_events[i], StreamFinishStep):
insert_pos = i
break
state.pending_events.insert(
insert_pos, StreamTextEnd(id=state.text_block_id)
)
# Drain pending events in correct order
for evt in state.pending_events:
yield evt
state.pending_events.clear()
# Close any open text/step before emitting error
if text_started:
yield StreamTextEnd(id=text_block_id)
if step_open:
yield StreamFinishStep()
yield StreamError(errorText=error_msg, code="baseline_error")
# Still persist whatever we got
finally:
@@ -558,21 +442,26 @@ async def stream_chat_completion_baseline(
# Skip fallback when an error occurred and no output was produced —
# charging rate-limit tokens for completely failed requests is unfair.
if (
state.turn_prompt_tokens == 0
and state.turn_completion_tokens == 0
and not (_stream_error and not state.assistant_text)
turn_prompt_tokens == 0
and turn_completion_tokens == 0
and not (_stream_error and not assistant_text)
):
state.turn_prompt_tokens = max(
from backend.util.prompt import (
estimate_token_count,
estimate_token_count_str,
)
turn_prompt_tokens = max(
estimate_token_count(openai_messages, model=config.model), 1
)
state.turn_completion_tokens = estimate_token_count_str(
state.assistant_text, model=config.model
turn_completion_tokens = estimate_token_count_str(
assistant_text, model=config.model
)
logger.info(
"[Baseline] No streaming usage reported; estimated tokens: "
"prompt=%d, completion=%d",
state.turn_prompt_tokens,
state.turn_completion_tokens,
turn_prompt_tokens,
turn_completion_tokens,
)
# Persist token usage to session and record for rate limiting.
@@ -582,15 +471,15 @@ async def stream_chat_completion_baseline(
await persist_and_record_usage(
session=session,
user_id=user_id,
prompt_tokens=state.turn_prompt_tokens,
completion_tokens=state.turn_completion_tokens,
prompt_tokens=turn_prompt_tokens,
completion_tokens=turn_completion_tokens,
log_prefix="[Baseline]",
)
# Persist assistant response
if state.assistant_text:
if assistant_text:
session.messages.append(
ChatMessage(role="assistant", content=state.assistant_text)
ChatMessage(role="assistant", content=assistant_text)
)
try:
await upsert_chat_session(session)
@@ -602,11 +491,11 @@ async def stream_chat_completion_baseline(
# aclose() — doing so raises RuntimeError on client disconnect.
# On GeneratorExit the client is already gone, so unreachable yields
# are harmless; on normal completion they reach the SSE stream.
if state.turn_prompt_tokens > 0 or state.turn_completion_tokens > 0:
if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
yield StreamUsage(
prompt_tokens=state.turn_prompt_tokens,
completion_tokens=state.turn_completion_tokens,
total_tokens=state.turn_prompt_tokens + state.turn_completion_tokens,
prompt_tokens=turn_prompt_tokens,
completion_tokens=turn_completion_tokens,
total_tokens=turn_prompt_tokens + turn_completion_tokens,
)
yield StreamFinish()

View File

@@ -31,7 +31,7 @@ async def test_baseline_multi_turn(setup_test_user, test_user_id):
if not api_key:
return pytest.skip("OPEN_ROUTER_API_KEY is not set, skipping test")
session = await create_chat_session(test_user_id, dry_run=False)
session = await create_chat_session(test_user_id)
session = await upsert_chat_session(session)
# --- Turn 1: send a message with a unique keyword ---

View File

@@ -20,10 +20,6 @@ class ChatConfig(BaseSettings):
default="openai/gpt-4o-mini",
description="Model to use for generating session titles (should be fast/cheap)",
)
simulation_model: str = Field(
default="google/gemini-2.5-flash",
description="Model for dry-run block simulation (should be fast/cheap with good JSON output)",
)
api_key: str | None = Field(default=None, description="OpenAI API key")
base_url: str | None = Field(
default=OPENROUTER_BASE_URL,
@@ -95,20 +91,6 @@ class ChatConfig(BaseSettings):
description="Max tokens per week, resets Monday 00:00 UTC (0 = unlimited)",
)
# Cost (in credits / cents) to reset the daily rate limit using credits.
# When a user hits their daily limit, they can spend this amount to reset
# the daily counter and keep working. Set to 0 to disable the feature.
rate_limit_reset_cost: int = Field(
default=500,
ge=0,
description="Credit cost (in cents) for resetting the daily rate limit. 0 = disabled.",
)
max_daily_resets: int = Field(
default=5,
ge=0,
description="Maximum number of credit-based rate limit resets per user per day. 0 = unlimited.",
)
# Claude Agent SDK Configuration
use_claude_agent_sdk: bool = Field(
default=True,
@@ -182,7 +164,7 @@ class ChatConfig(BaseSettings):
Single source of truth for "will the SDK route through OpenRouter?".
Checks the flag *and* that ``api_key`` + a valid ``base_url`` are
present — mirrors the fallback logic in ``build_sdk_env``.
present — mirrors the fallback logic in ``_build_sdk_env``.
"""
if not self.use_openrouter:
return False

View File

@@ -149,8 +149,7 @@ def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
Allowed:
- Files under *sdk_cwd* (``/tmp/copilot-<session>/``)
- Files under ``~/.claude/projects/<encoded-cwd>/<uuid>/tool-results/...``
or ``tool-outputs/...``.
- Files under ``~/.claude/projects/<encoded-cwd>/<uuid>/tool-results/...``.
The SDK nests tool-results under a conversation UUID directory;
the UUID segment is validated with ``_UUID_RE``.
"""
@@ -175,20 +174,17 @@ def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
# Defence-in-depth: ensure project_dir didn't escape the base.
if not project_dir.startswith(SDK_PROJECTS_DIR + os.sep):
return False
# Only allow: <encoded-cwd>/<uuid>/<tool-dir>/<file>
# Only allow: <encoded-cwd>/<uuid>/tool-results/<file>
# The SDK always creates a conversation UUID directory between
# the project dir and the tool directory.
# Accept both "tool-results" (SDK's persisted outputs) and
# "tool-outputs" (the model sometimes confuses workspace paths
# with filesystem paths and generates this variant).
# the project dir and tool-results/.
if resolved.startswith(project_dir + os.sep):
relative = resolved[len(project_dir) + 1 :]
parts = relative.split(os.sep)
# Require exactly: [<uuid>, "tool-results"|"tool-outputs", <file>, ...]
# Require exactly: [<uuid>, "tool-results", <file>, ...]
if (
len(parts) >= 3
and _UUID_RE.match(parts[0])
and parts[1] in ("tool-results", "tool-outputs")
and parts[1] == "tool-results"
):
return True

View File

@@ -134,21 +134,6 @@ def test_is_allowed_local_path_tool_results_with_uuid():
_current_project_dir.set("")
def test_is_allowed_local_path_tool_outputs_with_uuid():
"""Files under <encoded-cwd>/<uuid>/tool-outputs/ are also allowed."""
encoded = "test-encoded-dir"
conv_uuid = "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
path = os.path.join(
SDK_PROJECTS_DIR, encoded, conv_uuid, "tool-outputs", "output.json"
)
_current_project_dir.set(encoded)
try:
assert is_allowed_local_path(path, sdk_cwd=None)
finally:
_current_project_dir.set("")
def test_is_allowed_local_path_tool_results_without_uuid_rejected():
"""Direct <encoded-cwd>/tool-results/ (no UUID) is rejected."""
encoded = "test-encoded-dir"
@@ -174,7 +159,7 @@ def test_is_allowed_local_path_sibling_of_tool_results_is_rejected():
def test_is_allowed_local_path_valid_uuid_wrong_segment_name_rejected():
"""A valid UUID dir but non-'tool-results'/'tool-outputs' second segment is rejected."""
"""A valid UUID dir but non-'tool-results' second segment is rejected."""
encoded = "test-encoded-dir"
uuid_str = "12345678-1234-5678-9abc-def012345678"
path = os.path.join(

View File

@@ -18,13 +18,7 @@ from prisma.types import (
from backend.data import db
from backend.util.json import SafeJson, sanitize_string
from .model import (
ChatMessage,
ChatSession,
ChatSessionInfo,
ChatSessionMetadata,
invalidate_session_cache,
)
from .model import ChatMessage, ChatSession, ChatSessionInfo
logger = logging.getLogger(__name__)
@@ -41,7 +35,6 @@ async def get_chat_session(session_id: str) -> ChatSession | None:
async def create_chat_session(
session_id: str,
user_id: str,
metadata: ChatSessionMetadata | None = None,
) -> ChatSessionInfo:
"""Create a new chat session in the database."""
data = ChatSessionCreateInput(
@@ -50,7 +43,6 @@ async def create_chat_session(
credentials=SafeJson({}),
successfulAgentRuns=SafeJson({}),
successfulAgentSchedules=SafeJson({}),
metadata=SafeJson((metadata or ChatSessionMetadata()).model_dump()),
)
prisma_session = await PrismaChatSession.prisma().create(data=data)
return ChatSessionInfo.from_db(prisma_session)
@@ -65,12 +57,7 @@ async def update_chat_session(
total_completion_tokens: int | None = None,
title: str | None = None,
) -> ChatSession | None:
"""Update a chat session's mutable fields.
Note: ``metadata`` (which includes ``dry_run``) is intentionally omitted —
it is set once at creation time and treated as immutable for the lifetime
of the session.
"""
"""Update a chat session's metadata."""
data: ChatSessionUpdateInput = {"updatedAt": datetime.now(UTC)}
if credentials is not None:
@@ -230,9 +217,6 @@ async def add_chat_messages_batch(
if msg.get("function_call") is not None:
data["functionCall"] = SafeJson(msg["function_call"])
if msg.get("duration_ms") is not None:
data["durationMs"] = msg["duration_ms"]
messages_data.append(data)
# Run create_many and session update in parallel within transaction
@@ -375,22 +359,3 @@ async def update_tool_message_content(
f"tool_call_id {tool_call_id}: {e}"
)
return False
async def set_turn_duration(session_id: str, duration_ms: int) -> None:
"""Set durationMs on the last assistant message in a session.
Also invalidates the Redis session cache so the next GET returns
the updated duration.
"""
last_msg = await PrismaChatMessage.prisma().find_first(
where={"sessionId": session_id, "role": "assistant"},
order={"sequence": "desc"},
)
if last_msg:
await PrismaChatMessage.prisma().update(
where={"id": last_msg.id},
data={"durationMs": duration_ms},
)
# Invalidate cache so the session is re-fetched from DB with durationMs
await invalidate_session_cache(session_id)

View File

@@ -59,16 +59,6 @@ _null_cache: TTLCache[tuple[str, str], bool] = TTLCache(
maxsize=_CACHE_MAX_SIZE, ttl=_NULL_CACHE_TTL
)
# GitHub user identity caches (keyed by user_id only, not provider tuple).
# Declared here so invalidate_user_provider_cache() can reference them.
_GH_IDENTITY_CACHE_TTL = 600.0 # 10 min — profile data rarely changes
_gh_identity_cache: TTLCache[str, dict[str, str]] = TTLCache(
maxsize=_CACHE_MAX_SIZE, ttl=_GH_IDENTITY_CACHE_TTL
)
_gh_identity_null_cache: TTLCache[str, bool] = TTLCache(
maxsize=_CACHE_MAX_SIZE, ttl=_NULL_CACHE_TTL
)
def invalidate_user_provider_cache(user_id: str, provider: str) -> None:
"""Remove the cached entry for *user_id*/*provider* from both caches.
@@ -76,19 +66,11 @@ def invalidate_user_provider_cache(user_id: str, provider: str) -> None:
Call this after storing new credentials so that the next
``get_provider_token()`` call performs a fresh DB lookup instead of
serving a stale TTL-cached result.
For GitHub specifically, also clears the git-identity caches so that
``get_github_user_git_identity()`` re-fetches the user's profile on
the next call instead of serving stale identity data.
"""
key = (user_id, provider)
_token_cache.pop(key, None)
_null_cache.pop(key, None)
if provider == "github":
_gh_identity_cache.pop(user_id, None)
_gh_identity_null_cache.pop(user_id, None)
# Register this module's cache-bust function with the credentials manager so
# that any create/update/delete operation immediately evicts stale cache
@@ -141,7 +123,6 @@ async def get_provider_token(user_id: str, provider: str) -> str | None:
[c for c in creds_list if c.type == "oauth2"],
key=lambda c: 0 if "repo" in (cast(OAuth2Credentials, c).scopes or []) else 1,
)
refresh_failed = False
for creds in oauth2_creds:
if creds.type == "oauth2":
try:
@@ -160,7 +141,6 @@ async def get_provider_token(user_id: str, provider: str) -> str | None:
# Do NOT fall back to the stale token — it is likely expired
# or revoked. Returning None forces the caller to re-auth,
# preventing the LLM from receiving a non-functional token.
refresh_failed = True
continue
_token_cache[cache_key] = token
return token
@@ -172,12 +152,8 @@ async def get_provider_token(user_id: str, provider: str) -> str | None:
_token_cache[cache_key] = token
return token
# Only cache "not connected" when the user truly has no credentials for this
# provider. If we had OAuth credentials but refresh failed (e.g. transient
# network error, event-loop mismatch), do NOT cache the negative result —
# the next call should retry the refresh instead of being blocked for 60 s.
if not refresh_failed:
_null_cache[cache_key] = True
# No credentials found — cache to avoid repeated DB hits.
_null_cache[cache_key] = True
return None
@@ -195,76 +171,3 @@ async def get_integration_env_vars(user_id: str) -> dict[str, str]:
for var in var_names:
env[var] = token
return env
# ---------------------------------------------------------------------------
# GitHub user identity (for git committer env vars)
# ---------------------------------------------------------------------------
async def get_github_user_git_identity(user_id: str) -> dict[str, str] | None:
"""Fetch the GitHub user's name and email for git committer env vars.
Uses the ``/user`` GitHub API endpoint with the user's stored token.
Returns a dict with ``GIT_AUTHOR_NAME``, ``GIT_AUTHOR_EMAIL``,
``GIT_COMMITTER_NAME``, and ``GIT_COMMITTER_EMAIL`` if the user has a
connected GitHub account. Returns ``None`` otherwise.
Results are cached for 10 minutes; "not connected" results are cached for
60 s (same as null-token cache).
"""
if user_id in _gh_identity_null_cache:
return None
if cached := _gh_identity_cache.get(user_id):
return cached
token = await get_provider_token(user_id, "github")
if not token:
_gh_identity_null_cache[user_id] = True
return None
import aiohttp
try:
async with aiohttp.ClientSession() as session:
async with session.get(
"https://api.github.com/user",
headers={
"Authorization": f"token {token}",
"Accept": "application/vnd.github+json",
},
timeout=aiohttp.ClientTimeout(total=5),
) as resp:
if resp.status != 200:
logger.warning(
"[git-identity] GitHub /user returned %s for user %s",
resp.status,
user_id,
)
return None
data = await resp.json()
except Exception as exc:
logger.warning(
"[git-identity] Failed to fetch GitHub profile for user %s: %s",
user_id,
exc,
)
return None
name = data.get("name") or data.get("login") or "AutoGPT User"
# GitHub may return email=null if the user has set their email to private.
# Fall back to the noreply address GitHub generates for every account.
email = data.get("email")
if not email:
gh_id = data.get("id", "")
login = data.get("login", "user")
email = f"{gh_id}+{login}@users.noreply.github.com"
identity = {
"GIT_AUTHOR_NAME": name,
"GIT_AUTHOR_EMAIL": email,
"GIT_COMMITTER_NAME": name,
"GIT_COMMITTER_EMAIL": email,
}
_gh_identity_cache[user_id] = identity
return identity

View File

@@ -9,8 +9,6 @@ from backend.copilot.integration_creds import (
_NULL_CACHE_TTL,
_TOKEN_CACHE_TTL,
PROVIDER_ENV_VARS,
_gh_identity_cache,
_gh_identity_null_cache,
_null_cache,
_token_cache,
get_integration_env_vars,
@@ -51,13 +49,9 @@ def clear_caches():
"""Ensure clean caches before and after every test."""
_token_cache.clear()
_null_cache.clear()
_gh_identity_cache.clear()
_gh_identity_null_cache.clear()
yield
_token_cache.clear()
_null_cache.clear()
_gh_identity_cache.clear()
_gh_identity_null_cache.clear()
class TestInvalidateUserProviderCache:
@@ -83,34 +77,6 @@ class TestInvalidateUserProviderCache:
invalidate_user_provider_cache(_USER, _PROVIDER)
assert other_key in _token_cache
def test_clears_gh_identity_cache_for_github_provider(self):
"""When provider is 'github', identity caches must also be cleared."""
_gh_identity_cache[_USER] = {
"GIT_AUTHOR_NAME": "Old Name",
"GIT_AUTHOR_EMAIL": "old@example.com",
"GIT_COMMITTER_NAME": "Old Name",
"GIT_COMMITTER_EMAIL": "old@example.com",
}
invalidate_user_provider_cache(_USER, "github")
assert _USER not in _gh_identity_cache
def test_clears_gh_identity_null_cache_for_github_provider(self):
"""When provider is 'github', the identity null-cache must also be cleared."""
_gh_identity_null_cache[_USER] = True
invalidate_user_provider_cache(_USER, "github")
assert _USER not in _gh_identity_null_cache
def test_does_not_clear_gh_identity_cache_for_other_providers(self):
"""When provider is NOT 'github', identity caches must be left alone."""
_gh_identity_cache[_USER] = {
"GIT_AUTHOR_NAME": "Some Name",
"GIT_AUTHOR_EMAIL": "some@example.com",
"GIT_COMMITTER_NAME": "Some Name",
"GIT_COMMITTER_EMAIL": "some@example.com",
}
invalidate_user_provider_cache(_USER, "some-other-provider")
assert _USER in _gh_identity_cache
class TestGetProviderToken:
@pytest.mark.asyncio(loop_scope="session")
@@ -163,15 +129,8 @@ class TestGetProviderToken:
assert result == "oauth-tok"
@pytest.mark.asyncio(loop_scope="session")
async def test_oauth2_refresh_failure_returns_none_without_null_cache(self):
"""On refresh failure, return None but do NOT cache in null_cache.
The user has credentials — they just couldn't be refreshed right now
(e.g. transient network error or event-loop mismatch in the copilot
executor). Caching a negative result would block all credential
lookups for 60 s even though the creds exist and may refresh fine
on the next attempt.
"""
async def test_oauth2_refresh_failure_returns_none(self):
"""On refresh failure, return None instead of caching a stale token."""
oauth_creds = _make_oauth2_creds("stale-oauth-tok")
mock_manager = MagicMock()
mock_manager.store.get_creds_by_provider = AsyncMock(return_value=[oauth_creds])
@@ -182,8 +141,6 @@ class TestGetProviderToken:
# Stale tokens must NOT be returned — forces re-auth.
assert result is None
# Must NOT cache negative result when refresh failed — next call retries.
assert (_USER, _PROVIDER) not in _null_cache
@pytest.mark.asyncio(loop_scope="session")
async def test_no_credentials_caches_null_entry(self):
@@ -219,96 +176,6 @@ class TestGetProviderToken:
assert _NULL_CACHE_TTL < _TOKEN_CACHE_TTL
class TestThreadSafetyLocks:
"""Bug reproduction: shared AsyncRedisKeyedMutex across threads caused
'Future attached to a different loop' when copilot workers accessed
credentials from different event loops."""
@pytest.mark.asyncio(loop_scope="session")
async def test_store_locks_returns_per_thread_instance(self):
"""IntegrationCredentialsStore.locks() must return different instances
for different threads (via @thread_cached)."""
import asyncio
import concurrent.futures
from backend.integrations.credentials_store import IntegrationCredentialsStore
store = IntegrationCredentialsStore()
async def get_locks_id():
mock_redis = AsyncMock()
with patch(
"backend.integrations.credentials_store.get_redis_async",
return_value=mock_redis,
):
locks = await store.locks()
return id(locks)
# Get locks from main thread
main_id = await get_locks_id()
# Get locks from a worker thread
def run_in_thread():
loop = asyncio.new_event_loop()
try:
return loop.run_until_complete(get_locks_id())
finally:
loop.close()
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
worker_id = await asyncio.get_event_loop().run_in_executor(
pool, run_in_thread
)
assert main_id != worker_id, (
"Store.locks() returned the same instance across threads. "
"This would cause 'Future attached to a different loop' errors."
)
@pytest.mark.asyncio(loop_scope="session")
async def test_manager_delegates_to_store_locks(self):
"""IntegrationCredentialsManager.locks() should delegate to store."""
from backend.integrations.creds_manager import IntegrationCredentialsManager
manager = IntegrationCredentialsManager()
mock_redis = AsyncMock()
with patch(
"backend.integrations.credentials_store.get_redis_async",
return_value=mock_redis,
):
locks = await manager.locks()
# Should have gotten it from the store
assert locks is not None
class TestRefreshUnlockedPath:
"""Bug reproduction: copilot worker threads need lock-free refresh because
Redis-backed asyncio.Lock created on one event loop can't be used on another."""
@pytest.mark.asyncio(loop_scope="session")
async def test_refresh_if_needed_lock_false_skips_redis(self):
"""refresh_if_needed(lock=False) must not touch Redis locks at all."""
from backend.integrations.creds_manager import IntegrationCredentialsManager
manager = IntegrationCredentialsManager()
creds = _make_oauth2_creds()
mock_handler = MagicMock()
mock_handler.needs_refresh = MagicMock(return_value=False)
with patch(
"backend.integrations.creds_manager._get_provider_oauth_handler",
new_callable=AsyncMock,
return_value=mock_handler,
):
result = await manager.refresh_if_needed(_USER, creds, lock=False)
# Should return credentials without touching locks
assert result.id == creds.id
class TestGetIntegrationEnvVars:
@pytest.mark.asyncio(loop_scope="session")
async def test_injects_all_env_vars_for_provider(self):

View File

@@ -46,16 +46,6 @@ def _get_session_cache_key(session_id: str) -> str:
# ===================== Chat data models ===================== #
class ChatSessionMetadata(BaseModel):
"""Typed metadata stored in the ``metadata`` JSON column of ChatSession.
Add new session-level flags here instead of adding DB columns —
no migration required for new fields as long as a default is provided.
"""
dry_run: bool = False
class ChatMessage(BaseModel):
role: str
content: str | None = None
@@ -64,7 +54,6 @@ class ChatMessage(BaseModel):
refusal: str | None = None
tool_calls: list[dict] | None = None
function_call: dict | None = None
duration_ms: int | None = None
@staticmethod
def from_db(prisma_message: PrismaChatMessage) -> "ChatMessage":
@@ -77,7 +66,6 @@ class ChatMessage(BaseModel):
refusal=prisma_message.refusal,
tool_calls=_parse_json_field(prisma_message.toolCalls),
function_call=_parse_json_field(prisma_message.functionCall),
duration_ms=prisma_message.durationMs,
)
@@ -100,12 +88,6 @@ class ChatSessionInfo(BaseModel):
updated_at: datetime
successful_agent_runs: dict[str, int] = {}
successful_agent_schedules: dict[str, int] = {}
metadata: ChatSessionMetadata = ChatSessionMetadata()
@property
def dry_run(self) -> bool:
"""Convenience accessor for ``metadata.dry_run``."""
return self.metadata.dry_run
@classmethod
def from_db(cls, prisma_session: PrismaChatSession) -> Self:
@@ -119,10 +101,6 @@ class ChatSessionInfo(BaseModel):
prisma_session.successfulAgentSchedules, default={}
)
# Parse typed metadata from the JSON column.
raw_metadata = _parse_json_field(prisma_session.metadata, default={})
metadata = ChatSessionMetadata.model_validate(raw_metadata)
# Calculate usage from token counts.
# NOTE: Per-turn cache_read_tokens / cache_creation_tokens breakdown
# is lost after persistence — the DB only stores aggregate prompt and
@@ -148,7 +126,6 @@ class ChatSessionInfo(BaseModel):
updated_at=prisma_session.updatedAt,
successful_agent_runs=successful_agent_runs,
successful_agent_schedules=successful_agent_schedules,
metadata=metadata,
)
@@ -156,7 +133,7 @@ class ChatSession(ChatSessionInfo):
messages: list[ChatMessage]
@classmethod
def new(cls, user_id: str, *, dry_run: bool) -> Self:
def new(cls, user_id: str) -> Self:
return cls(
session_id=str(uuid.uuid4()),
user_id=user_id,
@@ -166,7 +143,6 @@ class ChatSession(ChatSessionInfo):
credentials={},
started_at=datetime.now(UTC),
updated_at=datetime.now(UTC),
metadata=ChatSessionMetadata(dry_run=dry_run),
)
@classmethod
@@ -554,7 +530,6 @@ async def _save_session_to_db(
await db.create_chat_session(
session_id=session.session_id,
user_id=session.user_id,
metadata=session.metadata,
)
existing_message_count = 0
@@ -632,27 +607,21 @@ async def append_and_save_message(session_id: str, message: ChatMessage) -> Chat
return session
async def create_chat_session(user_id: str, *, dry_run: bool) -> ChatSession:
async def create_chat_session(user_id: str) -> ChatSession:
"""Create a new chat session and persist it.
Args:
user_id: The authenticated user ID.
dry_run: When True, run_block and run_agent tool calls in this
session are forced to use dry-run simulation mode.
Raises:
DatabaseError: If the database write fails. We fail fast to ensure
callers never receive a non-persisted session that only exists
in cache (which would be lost when the cache expires).
"""
session = ChatSession.new(user_id, dry_run=dry_run)
session = ChatSession.new(user_id)
# Create in database first - fail fast if this fails
try:
await chat_db().create_chat_session(
session_id=session.session_id,
user_id=user_id,
metadata=session.metadata,
)
except Exception as e:
logger.error(f"Failed to create session {session.session_id} in database: {e}")

View File

@@ -46,7 +46,7 @@ messages = [
@pytest.mark.asyncio(loop_scope="session")
async def test_chatsession_serialization_deserialization():
s = ChatSession.new(user_id="abc123", dry_run=False)
s = ChatSession.new(user_id="abc123")
s.messages = messages
s.usage = [Usage(prompt_tokens=100, completion_tokens=200, total_tokens=300)]
serialized = s.model_dump_json()
@@ -57,7 +57,7 @@ async def test_chatsession_serialization_deserialization():
@pytest.mark.asyncio(loop_scope="session")
async def test_chatsession_redis_storage(setup_test_user, test_user_id):
s = ChatSession.new(user_id=test_user_id, dry_run=False)
s = ChatSession.new(user_id=test_user_id)
s.messages = messages
s = await upsert_chat_session(s)
@@ -75,7 +75,7 @@ async def test_chatsession_redis_storage_user_id_mismatch(
setup_test_user, test_user_id
):
s = ChatSession.new(user_id=test_user_id, dry_run=False)
s = ChatSession.new(user_id=test_user_id)
s.messages = messages
s = await upsert_chat_session(s)
@@ -90,7 +90,7 @@ async def test_chatsession_db_storage(setup_test_user, test_user_id):
from backend.data.redis_client import get_redis_async
# Create session with messages including assistant message
s = ChatSession.new(user_id=test_user_id, dry_run=False)
s = ChatSession.new(user_id=test_user_id)
s.messages = messages # Contains user, assistant, and tool messages
assert s.session_id is not None, "Session id is not set"
# Upsert to save to both cache and DB
@@ -241,7 +241,7 @@ _raw_tc2 = {
def test_add_tool_call_appends_to_existing_assistant():
"""When the last assistant is from the current turn, tool_call is added to it."""
session = ChatSession.new(user_id="u", dry_run=False)
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
ChatMessage(role="assistant", content="working on it"),
@@ -254,7 +254,7 @@ def test_add_tool_call_appends_to_existing_assistant():
def test_add_tool_call_creates_assistant_when_none_exists():
"""When there's no current-turn assistant, a new one is created."""
session = ChatSession.new(user_id="u", dry_run=False)
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
]
@@ -267,7 +267,7 @@ def test_add_tool_call_creates_assistant_when_none_exists():
def test_add_tool_call_does_not_cross_user_boundary():
"""A user message acts as a boundary — previous assistant is not modified."""
session = ChatSession.new(user_id="u", dry_run=False)
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="assistant", content="old turn"),
ChatMessage(role="user", content="new message"),
@@ -282,7 +282,7 @@ def test_add_tool_call_does_not_cross_user_boundary():
def test_add_tool_call_multiple_times():
"""Multiple long-running tool calls accumulate on the same assistant."""
session = ChatSession.new(user_id="u", dry_run=False)
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
ChatMessage(role="assistant", content="doing stuff"),
@@ -300,7 +300,7 @@ def test_add_tool_call_multiple_times():
def test_to_openai_messages_merges_split_assistants():
"""End-to-end: session with split assistants produces valid OpenAI messages."""
session = ChatSession.new(user_id="u", dry_run=False)
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="build agent"),
ChatMessage(role="assistant", content="Let me build that"),
@@ -352,7 +352,7 @@ async def test_concurrent_saves_collision_detection(setup_test_user, test_user_i
import asyncio
# Create a session with initial messages
session = ChatSession.new(user_id=test_user_id, dry_run=False)
session = ChatSession.new(user_id=test_user_id)
for i in range(3):
session.messages.append(
ChatMessage(

View File

@@ -66,7 +66,6 @@ from pydantic import BaseModel, PrivateAttr
ToolName = Literal[
# Platform tools (must match keys in TOOL_REGISTRY)
"add_understanding",
"ask_question",
"bash_exec",
"browser_act",
"browser_navigate",
@@ -103,7 +102,6 @@ ToolName = Literal[
"web_fetch",
"write_workspace_file",
# SDK built-ins
"Agent",
"Edit",
"Glob",
"Grep",

View File

@@ -544,7 +544,6 @@ class TestApplyToolPermissions:
class TestSdkBuiltinToolNames:
def test_expected_builtins_present(self):
expected = {
"Agent",
"Read",
"Write",
"Edit",

View File

@@ -18,18 +18,6 @@ After `write_workspace_file`, embed the `download_url` in Markdown:
- Image: `![chart](workspace://file_id#image/png)`
- Video: `![recording](workspace://file_id#video/mp4)`
### Handling binary/image data in tool outputs — CRITICAL
When a tool output contains base64-encoded binary data (images, PDFs, etc.):
1. **NEVER** try to inline or render the base64 content in your response.
2. **Save** the data to workspace using `write_workspace_file` (pass the base64 data URI as content).
3. **Show** the result via the workspace download URL in Markdown: `![image](workspace://file_id#image/png)`.
### Passing large data between tools — CRITICAL
When tool outputs produce large text that you need to feed into another tool:
- **NEVER** copy-paste the full text into the next tool call argument.
- **Save** the output to a file (workspace or local), then use `@@agptfile:` references.
- This avoids token limits and ensures data integrity.
### File references — @@agptfile:
Pass large file content to tools by reference: `@@agptfile:<uri>[<start>-<end>]`
- `workspace://<file_id>` or `workspace:///<path>` — workspace files
@@ -119,13 +107,6 @@ Do not re-fetch or re-generate data you already have from prior tool calls.
After building the file, reference it with `@@agptfile:` in other tools:
`@@agptfile:/home/user/report.md`
### Web search best practices
- If 3 similar web searches don't return the specific data you need, conclude
it isn't publicly available and work with what you have.
- Prefer fewer, well-targeted searches over many variations of the same query.
- When spawning sub-agents for research, ensure each has a distinct
non-overlapping scope to avoid redundant searches.
### Sub-agent tasks
- When using the Task tool, NEVER set `run_in_background` to true.
All tasks must run in the foreground.
@@ -150,11 +131,6 @@ parent autopilot handles orchestration.
# E2B-only notes — E2B has full internet access so gh CLI works there.
# Not shown in local (bubblewrap) mode: --unshare-net blocks all network.
_E2B_TOOL_NOTES = """
### SDK tool-result files in E2B
When you `Read` an SDK tool-result file, it is automatically copied into the
sandbox so `bash_exec` can access it for further processing.
The exact sandbox path is shown in the `[Sandbox copy available at ...]` note.
### GitHub CLI (`gh`) and git
- If the user has connected their GitHub account, both `gh` and `git` are
pre-authenticated — use them directly without any manual login step.
@@ -220,22 +196,18 @@ def _build_storage_supplement(
- Files here **survive across sessions indefinitely**
### Moving files between storages
- **{file_move_name_1_to_2}**: `write_workspace_file(filename="output.json", source_path="/path/to/local/file")`
- **{file_move_name_2_to_1}**: `read_workspace_file(path="tool-outputs/data.json", save_to_path="{working_dir}/data.json")`
- **{file_move_name_1_to_2}**: Copy to persistent workspace
- **{file_move_name_2_to_1}**: Download for processing
### File persistence
Important files (code, configs, outputs) should be saved to workspace to ensure they persist.
### SDK tool-result files
When tool outputs are large, the SDK truncates them and saves the full output to
a local file under `~/.claude/projects/.../tool-results/` (or `tool-outputs/`).
To read these files, use `Read` — it reads from the host filesystem.
### Large tool outputs saved to workspace
When a tool output contains `<tool-output-truncated workspace_path="...">`, the
full output is in workspace storage (NOT on the local filesystem). To access it:
- Use `read_workspace_file(path="...", offset=..., length=50000)` for reading sections.
- To process in the sandbox, use `read_workspace_file(path="...", save_to_path="{working_dir}/file.json")` first, then use `bash_exec` on the local copy.
a local file under `~/.claude/projects/.../tool-results/`. To read these files,
always use `read_file` or `Read` (NOT `read_workspace_file`).
`read_workspace_file` reads from cloud workspace storage, where SDK
tool-results are NOT stored.
{_SHARED_TOOL_NOTES}{extra_notes}"""

View File

@@ -1,28 +0,0 @@
"""Tests for agent generation guide — verifies clarification section."""
from pathlib import Path
class TestAgentGenerationGuideContainsClarifySection:
"""The agent generation guide must include the clarification section."""
def test_guide_includes_clarify_section(self):
guide_path = Path(__file__).parent / "sdk" / "agent_generation_guide.md"
content = guide_path.read_text(encoding="utf-8")
assert "Before or During Building" in content
def test_guide_mentions_find_block_for_clarification(self):
guide_path = Path(__file__).parent / "sdk" / "agent_generation_guide.md"
content = guide_path.read_text(encoding="utf-8")
clarify_section = content.split("Before or During Building")[1].split(
"### Workflow"
)[0]
assert "find_block" in clarify_section
def test_guide_mentions_ask_question_tool(self):
guide_path = Path(__file__).parent / "sdk" / "agent_generation_guide.md"
content = guide_path.read_text(encoding="utf-8")
clarify_section = content.split("Before or During Building")[1].split(
"### Workflow"
)[0]
assert "ask_question" in clarify_section

View File

@@ -36,10 +36,6 @@ class CoPilotUsageStatus(BaseModel):
daily: UsageWindow
weekly: UsageWindow
reset_cost: int = Field(
default=0,
description="Credit cost (in cents) to reset the daily limit. 0 = feature disabled.",
)
class RateLimitExceeded(Exception):
@@ -65,7 +61,6 @@ async def get_usage_status(
user_id: str,
daily_token_limit: int,
weekly_token_limit: int,
rate_limit_reset_cost: int = 0,
) -> CoPilotUsageStatus:
"""Get current usage status for a user.
@@ -73,7 +68,6 @@ async def get_usage_status(
user_id: The user's ID.
daily_token_limit: Max tokens per day (0 = unlimited).
weekly_token_limit: Max tokens per week (0 = unlimited).
rate_limit_reset_cost: Credit cost (cents) to reset daily limit (0 = disabled).
Returns:
CoPilotUsageStatus with current usage and limits.
@@ -103,7 +97,6 @@ async def get_usage_status(
limit=weekly_token_limit,
resets_at=_weekly_reset_time(now=now),
),
reset_cost=rate_limit_reset_cost,
)
@@ -148,111 +141,6 @@ async def check_rate_limit(
raise RateLimitExceeded("weekly", _weekly_reset_time(now=now))
async def reset_daily_usage(user_id: str, daily_token_limit: int = 0) -> bool:
"""Reset a user's daily token usage counter in Redis.
Called after a user pays credits to extend their daily limit.
Also reduces the weekly usage counter by ``daily_token_limit`` tokens
(clamped to 0) so the user effectively gets one extra day's worth of
weekly capacity.
Args:
user_id: The user's ID.
daily_token_limit: The configured daily token limit. When positive,
the weekly counter is reduced by this amount.
Returns False if Redis is unavailable so the caller can handle
compensation (fail-closed for billed operations, unlike the read-only
rate-limit checks which fail-open).
"""
now = datetime.now(UTC)
try:
redis = await get_redis_async()
# Use a MULTI/EXEC transaction so that DELETE (daily) and DECRBY
# (weekly) either both execute or neither does. This prevents the
# scenario where the daily counter is cleared but the weekly
# counter is not decremented — which would let the caller refund
# credits even though the daily limit was already reset.
d_key = _daily_key(user_id, now=now)
w_key = _weekly_key(user_id, now=now) if daily_token_limit > 0 else None
pipe = redis.pipeline(transaction=True)
pipe.delete(d_key)
if w_key is not None:
pipe.decrby(w_key, daily_token_limit)
results = await pipe.execute()
# Clamp negative weekly counter to 0 (best-effort; not critical).
if w_key is not None:
new_val = results[1] # DECRBY result
if new_val < 0:
await redis.set(w_key, 0, keepttl=True)
logger.info("Reset daily usage for user %s", user_id[:8])
return True
except (RedisError, ConnectionError, OSError):
logger.warning("Redis unavailable for resetting daily usage")
return False
_RESET_LOCK_PREFIX = "copilot:reset_lock"
_RESET_COUNT_PREFIX = "copilot:reset_count"
async def acquire_reset_lock(user_id: str, ttl_seconds: int = 10) -> bool:
"""Acquire a short-lived lock to serialize rate limit resets per user."""
try:
redis = await get_redis_async()
key = f"{_RESET_LOCK_PREFIX}:{user_id}"
return bool(await redis.set(key, "1", nx=True, ex=ttl_seconds))
except (RedisError, ConnectionError, OSError) as exc:
logger.warning("Redis unavailable for reset lock, rejecting reset: %s", exc)
return False
async def release_reset_lock(user_id: str) -> None:
"""Release the per-user reset lock."""
try:
redis = await get_redis_async()
await redis.delete(f"{_RESET_LOCK_PREFIX}:{user_id}")
except (RedisError, ConnectionError, OSError):
pass # Lock will expire via TTL
async def get_daily_reset_count(user_id: str) -> int | None:
"""Get how many times the user has reset today.
Returns None when Redis is unavailable so callers can fail-closed
for billed operations (as opposed to failing open for read-only
rate-limit checks).
"""
now = datetime.now(UTC)
try:
redis = await get_redis_async()
key = f"{_RESET_COUNT_PREFIX}:{user_id}:{now.strftime('%Y-%m-%d')}"
val = await redis.get(key)
return int(val or 0)
except (RedisError, ConnectionError, OSError):
logger.warning("Redis unavailable for reading daily reset count")
return None
async def increment_daily_reset_count(user_id: str) -> None:
"""Increment and track how many resets this user has done today."""
now = datetime.now(UTC)
try:
redis = await get_redis_async()
key = f"{_RESET_COUNT_PREFIX}:{user_id}:{now.strftime('%Y-%m-%d')}"
pipe = redis.pipeline(transaction=True)
pipe.incr(key)
seconds_until_reset = int((_daily_reset_time(now=now) - now).total_seconds())
pipe.expire(key, max(seconds_until_reset, 1))
await pipe.execute()
except (RedisError, ConnectionError, OSError):
logger.warning("Redis unavailable for tracking reset count")
async def record_token_usage(
user_id: str,
prompt_tokens: int,
@@ -343,67 +231,6 @@ async def record_token_usage(
)
async def get_global_rate_limits(
user_id: str,
config_daily: int,
config_weekly: int,
) -> tuple[int, int]:
"""Resolve global rate limits from LaunchDarkly, falling back to config.
Args:
user_id: User ID for LD flag evaluation context.
config_daily: Fallback daily limit from ChatConfig.
config_weekly: Fallback weekly limit from ChatConfig.
Returns:
(daily_token_limit, weekly_token_limit) tuple.
"""
# Lazy import to avoid circular dependency:
# rate_limit -> feature_flag -> settings -> ... -> rate_limit
from backend.util.feature_flag import Flag, get_feature_flag_value
daily_raw = await get_feature_flag_value(
Flag.COPILOT_DAILY_TOKEN_LIMIT.value, user_id, config_daily
)
weekly_raw = await get_feature_flag_value(
Flag.COPILOT_WEEKLY_TOKEN_LIMIT.value, user_id, config_weekly
)
try:
daily = max(0, int(daily_raw))
except (TypeError, ValueError):
logger.warning("Invalid LD value for daily token limit: %r", daily_raw)
daily = config_daily
try:
weekly = max(0, int(weekly_raw))
except (TypeError, ValueError):
logger.warning("Invalid LD value for weekly token limit: %r", weekly_raw)
weekly = config_weekly
return daily, weekly
async def reset_user_usage(user_id: str, *, reset_weekly: bool = False) -> None:
"""Reset a user's usage counters.
Always deletes the daily Redis key. When *reset_weekly* is ``True``,
the weekly key is deleted as well.
Unlike read paths (``get_usage_status``, ``check_rate_limit``) which
fail-open on Redis errors, resets intentionally re-raise so the caller
knows the operation did not succeed. A silent failure here would leave
the admin believing the counters were zeroed when they were not.
"""
now = datetime.now(UTC)
keys_to_delete = [_daily_key(user_id, now=now)]
if reset_weekly:
keys_to_delete.append(_weekly_key(user_id, now=now))
try:
redis = await get_redis_async()
await redis.delete(*keys_to_delete)
except (RedisError, ConnectionError, OSError):
logger.warning("Redis unavailable for resetting user usage")
raise
# ---------------------------------------------------------------------------
# Private helpers
# ---------------------------------------------------------------------------

View File

@@ -12,7 +12,6 @@ from .rate_limit import (
check_rate_limit,
get_usage_status,
record_token_usage,
reset_daily_usage,
)
_USER = "test-user-rl"
@@ -333,91 +332,3 @@ class TestRecordTokenUsage:
):
# Should not raise — fail-open
await record_token_usage(_USER, prompt_tokens=100, completion_tokens=50)
# ---------------------------------------------------------------------------
# reset_daily_usage
# ---------------------------------------------------------------------------
class TestResetDailyUsage:
@staticmethod
def _make_pipeline_mock(decrby_result: int = 0) -> MagicMock:
"""Create a pipeline mock that returns [delete_result, decrby_result]."""
pipe = MagicMock()
pipe.execute = AsyncMock(return_value=[1, decrby_result])
return pipe
@pytest.mark.asyncio
async def test_deletes_daily_key(self):
mock_pipe = self._make_pipeline_mock(decrby_result=0)
mock_redis = AsyncMock()
mock_redis.pipeline = lambda **_kw: mock_pipe
with patch(
"backend.copilot.rate_limit.get_redis_async",
return_value=mock_redis,
):
result = await reset_daily_usage(_USER, daily_token_limit=10000)
assert result is True
mock_pipe.delete.assert_called_once()
@pytest.mark.asyncio
async def test_reduces_weekly_usage_via_decrby(self):
"""Weekly counter should be reduced via DECRBY in the pipeline."""
mock_pipe = self._make_pipeline_mock(decrby_result=35000)
mock_redis = AsyncMock()
mock_redis.pipeline = lambda **_kw: mock_pipe
with patch(
"backend.copilot.rate_limit.get_redis_async",
return_value=mock_redis,
):
await reset_daily_usage(_USER, daily_token_limit=10000)
mock_pipe.decrby.assert_called_once()
mock_redis.set.assert_not_called() # 35000 > 0, no clamp needed
@pytest.mark.asyncio
async def test_clamps_negative_weekly_to_zero(self):
"""If DECRBY goes negative, SET to 0 (outside the pipeline)."""
mock_pipe = self._make_pipeline_mock(decrby_result=-5000)
mock_redis = AsyncMock()
mock_redis.pipeline = lambda **_kw: mock_pipe
with patch(
"backend.copilot.rate_limit.get_redis_async",
return_value=mock_redis,
):
await reset_daily_usage(_USER, daily_token_limit=10000)
mock_pipe.decrby.assert_called_once()
mock_redis.set.assert_called_once()
@pytest.mark.asyncio
async def test_no_weekly_reduction_when_daily_limit_zero(self):
"""When daily_token_limit is 0, weekly counter should not be touched."""
mock_pipe = self._make_pipeline_mock()
mock_pipe.execute = AsyncMock(return_value=[1]) # only delete result
mock_redis = AsyncMock()
mock_redis.pipeline = lambda **_kw: mock_pipe
with patch(
"backend.copilot.rate_limit.get_redis_async",
return_value=mock_redis,
):
await reset_daily_usage(_USER, daily_token_limit=0)
mock_pipe.delete.assert_called_once()
mock_pipe.decrby.assert_not_called()
@pytest.mark.asyncio
async def test_returns_false_when_redis_unavailable(self):
with patch(
"backend.copilot.rate_limit.get_redis_async",
side_effect=ConnectionError("Redis down"),
):
result = await reset_daily_usage(_USER, daily_token_limit=10000)
assert result is False

View File

@@ -1,330 +0,0 @@
"""Unit tests for the POST /usage/reset endpoint."""
from __future__ import annotations
from datetime import UTC, datetime, timedelta
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from fastapi import HTTPException
from backend.api.features.chat.routes import reset_copilot_usage
from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
from backend.util.exceptions import InsufficientBalanceError
# Minimal config mock matching ChatConfig fields used by the endpoint.
def _make_config(
rate_limit_reset_cost: int = 500,
daily_token_limit: int = 2_500_000,
weekly_token_limit: int = 12_500_000,
max_daily_resets: int = 5,
):
cfg = MagicMock()
cfg.rate_limit_reset_cost = rate_limit_reset_cost
cfg.daily_token_limit = daily_token_limit
cfg.weekly_token_limit = weekly_token_limit
cfg.max_daily_resets = max_daily_resets
return cfg
def _usage(daily_used: int = 3_000_000, daily_limit: int = 2_500_000):
return CoPilotUsageStatus(
daily=UsageWindow(
used=daily_used,
limit=daily_limit,
resets_at=datetime.now(UTC) + timedelta(hours=6),
),
weekly=UsageWindow(
used=5_000_000,
limit=12_500_000,
resets_at=datetime.now(UTC) + timedelta(days=3),
),
)
_MODULE = "backend.api.features.chat.routes"
def _mock_settings(enable_credit: bool = True):
"""Return a mock Settings object with the given enable_credit flag."""
mock = MagicMock()
mock.config.enable_credit = enable_credit
return mock
@pytest.mark.asyncio
class TestResetCopilotUsage:
async def test_feature_disabled_returns_400(self):
"""When rate_limit_reset_cost=0, endpoint returns 400."""
with patch(f"{_MODULE}.config", _make_config(rate_limit_reset_cost=0)):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 400
assert "not available" in exc_info.value.detail
async def test_no_daily_limit_returns_400(self):
"""When daily_token_limit=0 (unlimited), endpoint returns 400."""
with (
patch(f"{_MODULE}.config", _make_config(daily_token_limit=0)),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(0, 12_500_000)),
),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 400
assert "nothing to reset" in exc_info.value.detail.lower()
async def test_not_at_limit_returns_400(self):
"""When user hasn't hit their daily limit, returns 400."""
cfg = _make_config()
with (
patch(f"{_MODULE}.config", cfg),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
patch(
f"{_MODULE}.get_usage_status",
AsyncMock(return_value=_usage(daily_used=1_000_000)),
),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 400
assert "not reached" in exc_info.value.detail
mock_release.assert_awaited_once()
async def test_insufficient_credits_returns_402(self):
"""When user doesn't have enough credits, returns 402."""
mock_credit_model = AsyncMock()
mock_credit_model.spend_credits.side_effect = InsufficientBalanceError(
message="Insufficient balance",
user_id="user-1",
balance=50,
amount=200,
)
cfg = _make_config()
with (
patch(f"{_MODULE}.config", cfg),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
patch(
f"{_MODULE}.get_usage_status",
AsyncMock(return_value=_usage()),
),
patch(
f"{_MODULE}.get_user_credit_model",
AsyncMock(return_value=mock_credit_model),
),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 402
mock_release.assert_awaited_once()
async def test_happy_path(self):
"""Successful reset: charges credits, resets usage, returns response."""
mock_credit_model = AsyncMock()
mock_credit_model.spend_credits.return_value = 1500 # remaining balance
cfg = _make_config()
updated_usage = _usage(daily_used=0)
with (
patch(f"{_MODULE}.config", cfg),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
patch(
f"{_MODULE}.get_usage_status",
AsyncMock(side_effect=[_usage(), updated_usage]),
),
patch(
f"{_MODULE}.get_user_credit_model",
AsyncMock(return_value=mock_credit_model),
),
patch(
f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=True)
) as mock_reset,
patch(f"{_MODULE}.increment_daily_reset_count", AsyncMock()) as mock_incr,
):
result = await reset_copilot_usage(user_id="user-1")
assert result.success is True
assert result.credits_charged == 500
assert result.remaining_balance == 1500
mock_reset.assert_awaited_once()
mock_incr.assert_awaited_once()
async def test_max_daily_resets_exceeded(self):
"""When user has exhausted daily resets, returns 429."""
cfg = _make_config(max_daily_resets=3)
with (
patch(f"{_MODULE}.config", cfg),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=3)),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 429
async def test_credit_system_disabled_returns_400(self):
"""When enable_credit=False, endpoint returns 400."""
with (
patch(f"{_MODULE}.config", _make_config()),
patch(f"{_MODULE}.settings", _mock_settings(enable_credit=False)),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 400
assert "credit system is disabled" in exc_info.value.detail.lower()
async def test_weekly_limit_exhausted_returns_400(self):
"""When the weekly limit is also exhausted, resetting daily won't help."""
cfg = _make_config()
weekly_exhausted = CoPilotUsageStatus(
daily=UsageWindow(
used=3_000_000,
limit=2_500_000,
resets_at=datetime.now(UTC) + timedelta(hours=6),
),
weekly=UsageWindow(
used=12_500_000,
limit=12_500_000,
resets_at=datetime.now(UTC) + timedelta(days=3),
),
)
with (
patch(f"{_MODULE}.config", cfg),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
patch(
f"{_MODULE}.get_usage_status",
AsyncMock(return_value=weekly_exhausted),
),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 400
assert "weekly" in exc_info.value.detail.lower()
mock_release.assert_awaited_once()
async def test_redis_failure_for_reset_count_returns_503(self):
"""When Redis is unavailable for get_daily_reset_count, returns 503."""
with (
patch(f"{_MODULE}.config", _make_config()),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=None)),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 503
assert "verify" in exc_info.value.detail.lower()
async def test_redis_reset_failure_refunds_credits(self):
"""When reset_daily_usage fails, credits are refunded and 503 returned."""
mock_credit_model = AsyncMock()
mock_credit_model.spend_credits.return_value = 1500
cfg = _make_config()
with (
patch(f"{_MODULE}.config", cfg),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
patch(
f"{_MODULE}.get_usage_status",
AsyncMock(return_value=_usage()),
),
patch(
f"{_MODULE}.get_user_credit_model",
AsyncMock(return_value=mock_credit_model),
),
patch(f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=False)),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 503
assert "not been charged" in exc_info.value.detail
mock_credit_model.top_up_credits.assert_awaited_once()
async def test_redis_reset_failure_refund_also_fails(self):
"""When both reset and refund fail, error message reflects the truth."""
mock_credit_model = AsyncMock()
mock_credit_model.spend_credits.return_value = 1500
mock_credit_model.top_up_credits.side_effect = RuntimeError("db down")
cfg = _make_config()
with (
patch(f"{_MODULE}.config", cfg),
patch(f"{_MODULE}.settings", _mock_settings()),
patch(
f"{_MODULE}.get_global_rate_limits",
AsyncMock(return_value=(2_500_000, 12_500_000)),
),
patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
patch(
f"{_MODULE}.get_usage_status",
AsyncMock(return_value=_usage()),
),
patch(
f"{_MODULE}.get_user_credit_model",
AsyncMock(return_value=mock_credit_model),
),
patch(f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=False)),
):
with pytest.raises(HTTPException) as exc_info:
await reset_copilot_usage(user_id="user-1")
assert exc_info.value.status_code == 503
assert "contact support" in exc_info.value.detail.lower()

View File

@@ -3,55 +3,25 @@
You can create, edit, and customize agents directly. You ARE the brain —
generate the agent JSON yourself using block schemas, then validate and save.
### Clarifying — Before or During Building
Use `ask_question` whenever the user's intent is ambiguous — whether
that's before starting or midway through the workflow. Common moments:
- **Before building**: output format, delivery channel, data source, or
trigger is unspecified.
- **During block discovery**: multiple blocks could fit and the user
should choose.
- **During JSON generation**: a wiring decision depends on user
preference.
Steps:
1. Call `find_block` (or another discovery tool) to learn what the
platform actually supports for the ambiguous dimension.
2. Call `ask_question` with a concrete question listing the discovered
options (e.g. "The platform supports Gmail, Slack, and Google Docs —
which should the agent use for delivery?").
3. **Wait for the user's answer** before continuing.
**Skip this** when the goal already specifies all dimensions (e.g.
"scrape prices from Amazon and email me daily").
### Workflow for Creating/Editing Agents
1. **If editing**: First narrow to the specific agent by UUID, then fetch its
graph: `find_library_agent(query="<agent_id>", include_graph=true)`. This
returns the full graph structure (nodes + links). **Never edit blindly**
always inspect the current graph first so you know exactly what to change.
Avoid using `include_graph=true` with broad keyword searches, as fetching
multiple graphs at once is expensive and consumes LLM context budget.
2. **Discover blocks**: Call `find_block(query, include_schemas=true)` to
1. **Discover blocks**: Call `find_block(query, include_schemas=true)` to
search for relevant blocks. This returns block IDs, names, descriptions,
and full input/output schemas.
3. **Find library agents**: Call `find_library_agent` to discover reusable
2. **Find library agents**: Call `find_library_agent` to discover reusable
agents that can be composed as sub-agents via `AgentExecutorBlock`.
4. **Generate/modify JSON**: Build or modify the agent JSON using block schemas:
- Use block IDs from step 2 as `block_id` in nodes
3. **Generate JSON**: Build the agent JSON using block schemas:
- Use block IDs from step 1 as `block_id` in nodes
- Wire outputs to inputs using links
- Set design-time config in `input_default`
- Use `AgentInputBlock` for values the user provides at runtime
- When editing, apply targeted changes and preserve unchanged parts
5. **Write to workspace**: Save the JSON to a workspace file so the user
4. **Write to workspace**: Save the JSON to a workspace file so the user
can review it: `write_workspace_file(filename="agent.json", content=...)`
6. **Validate**: Call `validate_agent_graph` with the agent JSON to check
5. **Validate**: Call `validate_agent_graph` with the agent JSON to check
for errors
7. **Fix if needed**: Call `fix_agent_graph` to auto-fix common issues,
6. **Fix if needed**: Call `fix_agent_graph` to auto-fix common issues,
or fix manually based on the error descriptions. Iterate until valid.
8. **Save**: Call `create_agent` (new) or `edit_agent` (existing) with
7. **Save**: Call `create_agent` (new) or `edit_agent` (existing) with
the final `agent_json`
### Agent JSON Structure
@@ -97,17 +67,9 @@ These define the agent's interface — what it accepts and what it produces.
**AgentInputBlock** (ID: `c0a8e994-ebf1-4a9c-a4d8-89d09c86741b`):
- Defines a user-facing input field on the agent
- Required `input_default` fields: `name` (str), `value` (default: null)
- Optional: `title`, `description`
- Optional: `title`, `description`, `placeholder_values` (for dropdowns)
- Output: `result` — the user-provided value at runtime
- Create one AgentInputBlock per distinct input the agent needs
- For dropdown/select inputs, use **AgentDropdownInputBlock** instead (see below)
**AgentDropdownInputBlock** (ID: `655d6fdf-a334-421c-b733-520549c07cd1`):
- Specialized input block that presents a dropdown/select to the user
- Required `input_default` fields: `name` (str)
- Optional: `options` (list of dropdown values; when omitted/empty, input behaves as free-text), `title`, `description`, `value` (default selection)
- Output: `result` — the user-selected value at runtime
- Use this instead of AgentInputBlock when the user should pick from a fixed set of options
**AgentOutputBlock** (ID: `363ae599-353e-4804-937e-b2ee3cef3da4`):
- Defines a user-facing output displayed after the agent runs
@@ -260,17 +222,6 @@ real API calls, credentials, or credits:
3. **Iterate**: If the dry run reveals wiring issues or missing inputs, fix
the agent JSON and re-save before suggesting a real execution.
**Special block behaviour in dry-run mode:**
- **OrchestratorBlock** and **AgentExecutorBlock** execute for real so the
orchestrator can make LLM calls and agent executors can spawn child graphs.
Their downstream tool blocks and child-graph blocks are still simulated.
Note: real LLM inference calls are made (consuming API quota), even though
platform credits are not charged. Agent-mode iterations are capped at 1 in
dry-run to keep it fast.
- **MCPToolBlock** is simulated using the selected tool's name and JSON Schema
so the LLM can produce a realistic mock response without connecting to the
MCP server.
### Example: Simple AI Text Processor
A minimal agent with input, processing, and output:

View File

@@ -25,7 +25,7 @@ from backend.copilot.sdk.compaction import (
def _make_session() -> ChatSession:
return ChatSession.new(user_id="test-user", dry_run=False)
return ChatSession.new(user_id="test-user")
# ---------------------------------------------------------------------------

View File

@@ -2,30 +2,14 @@
from __future__ import annotations
from collections.abc import AsyncIterator
from unittest.mock import patch
from uuid import uuid4
import pytest
import pytest_asyncio
from backend.util import json
@pytest_asyncio.fixture(scope="session", loop_scope="session", name="server")
async def _server_noop() -> None:
"""No-op server stub — SDK tests don't need the full backend."""
return None
@pytest_asyncio.fixture(
scope="session", loop_scope="session", autouse=True, name="graph_cleanup"
)
async def _graph_cleanup_noop() -> AsyncIterator[None]:
"""No-op graph cleanup stub."""
yield
@pytest.fixture()
def mock_chat_config():
"""Mock ChatConfig so compact_transcript tests skip real config lookup."""
@@ -41,64 +25,24 @@ def build_test_transcript(pairs: list[tuple[str, str]]) -> str:
Use this helper in any copilot SDK test that needs a well-formed
transcript without hitting the real storage layer.
Delegates to ``build_structured_transcript`` — plain content strings
are automatically wrapped in ``[{"type": "text", "text": ...}]`` for
assistant messages.
"""
# Cast widening: tuple[str, str] is structurally compatible with
# tuple[str, str | list[dict]] but list invariance requires explicit
# annotation.
widened: list[tuple[str, str | list[dict]]] = list(pairs)
return build_structured_transcript(widened)
def build_structured_transcript(
entries: list[tuple[str, str | list[dict]]],
) -> str:
"""Build a JSONL transcript with structured content blocks.
Each entry is (role, content) where content is either a plain string
(for user messages) or a list of content block dicts (for assistant
messages with thinking/tool_use/text blocks).
Example::
build_structured_transcript([
("user", "Hello"),
("assistant", [
{"type": "thinking", "thinking": "...", "signature": "sig1"},
{"type": "text", "text": "Hi there"},
]),
])
"""
lines: list[str] = []
last_uuid: str | None = None
for role, content in entries:
for role, content in pairs:
uid = str(uuid4())
entry_type = "assistant" if role == "assistant" else "user"
if role == "assistant" and isinstance(content, list):
msg: dict = {
"role": "assistant",
"model": "claude-test",
"id": f"msg_{uid[:8]}",
"type": "message",
"content": content,
"stop_reason": "end_turn",
"stop_sequence": None,
}
elif role == "assistant":
msg = {
"role": "assistant",
"model": "claude-test",
"id": f"msg_{uid[:8]}",
"type": "message",
"content": [{"type": "text", "text": content}],
"stop_reason": "end_turn",
"stop_sequence": None,
}
else:
msg = {"role": role, "content": content}
msg: dict = {"role": role, "content": content}
if role == "assistant":
msg.update(
{
"model": "",
"id": f"msg_{uid[:8]}",
"type": "message",
"content": [{"type": "text", "text": content}],
"stop_reason": "end_turn",
"stop_sequence": None,
}
)
entry = {
"type": entry_type,
"uuid": uid,

View File

@@ -8,9 +8,6 @@ SDK-internal paths (``~/.claude/projects/…/tool-results/``) are handled
by the separate ``Read`` MCP tool registered in ``tool_adapter.py``.
"""
import asyncio
import base64
import hashlib
import itertools
import json
import logging
@@ -31,12 +28,6 @@ from backend.copilot.context import (
logger = logging.getLogger(__name__)
# Default number of lines returned by ``read_file`` when the caller does not
# specify a limit. Also used as the threshold in ``bridge_to_sandbox`` to
# decide whether the model is requesting the full file (and thus whether the
# bridge copy is worthwhile).
_DEFAULT_READ_LIMIT = 2000
async def _check_sandbox_symlink_escape(
sandbox: Any,
@@ -98,7 +89,7 @@ def _get_sandbox_and_path(
return sandbox, remote
async def _sandbox_write(sandbox: Any, path: str, content: str | bytes) -> None:
async def _sandbox_write(sandbox: Any, path: str, content: str) -> None:
"""Write *content* to *path* inside the sandbox.
The E2B filesystem API (``sandbox.files.write``) and the command API
@@ -111,14 +102,11 @@ async def _sandbox_write(sandbox: Any, path: str, content: str | bytes) -> None:
To work around this, writes targeting ``/tmp`` are performed via
``tee`` through the command API, which runs as the sandbox ``user``
and can therefore always overwrite user-owned files.
*content* may be ``str`` (text) or ``bytes`` (binary). Both paths
are handled correctly: text is encoded to bytes for the base64 shell
pipe, and raw bytes are passed through without any encoding.
"""
if path == "/tmp" or path.startswith("/tmp/"):
raw = content.encode() if isinstance(content, str) else content
encoded = base64.b64encode(raw).decode()
import base64 as _b64
encoded = _b64.b64encode(content.encode()).decode()
result = await sandbox.commands.run(
f"echo {shlex.quote(encoded)} | base64 -d > {shlex.quote(path)}",
cwd=E2B_WORKDIR,
@@ -140,25 +128,14 @@ async def _handle_read_file(args: dict[str, Any]) -> dict[str, Any]:
"""Read lines from a sandbox file, falling back to the local host for SDK-internal paths."""
file_path: str = args.get("file_path", "")
offset: int = max(0, int(args.get("offset", 0)))
limit: int = max(1, int(args.get("limit", _DEFAULT_READ_LIMIT)))
limit: int = max(1, int(args.get("limit", 2000)))
if not file_path:
return _mcp("file_path is required", error=True)
# SDK-internal paths (tool-results/tool-outputs, ephemeral working dir)
# stay on the host. When E2B is active, also copy the file into the
# sandbox so bash_exec can access it for further processing.
# SDK-internal paths (tool-results, ephemeral working dir) stay on the host.
if _is_allowed_local(file_path):
result = _read_local(file_path, offset, limit)
if not result.get("isError"):
sandbox = _get_sandbox()
if sandbox is not None:
annotation = await bridge_and_annotate(
sandbox, file_path, offset, limit
)
if annotation:
result["content"][0]["text"] += annotation
return result
return _read_local(file_path, offset, limit)
result = _get_sandbox_and_path(file_path)
if isinstance(result, dict):
@@ -325,103 +302,6 @@ async def _handle_grep(args: dict[str, Any]) -> dict[str, Any]:
return _mcp(output if output else "No matches found.")
# Bridging: copy SDK-internal files into E2B sandbox
# Files larger than this are written to /home/user/ via sandbox.files.write()
# instead of /tmp/ via shell base64, to avoid shell argument length limits
# and E2B command timeouts. Base64 expands content by ~33%, so keep this
# well under the typical Linux ARG_MAX (128 KB).
_BRIDGE_SHELL_MAX_BYTES = 32 * 1024 # 32 KB
# Files larger than this are skipped entirely to avoid excessive transfer times.
_BRIDGE_SKIP_BYTES = 50 * 1024 * 1024 # 50 MB
async def bridge_to_sandbox(
sandbox: Any, file_path: str, offset: int, limit: int
) -> str | None:
"""Best-effort copy of a host-side SDK file into the E2B sandbox.
When the model reads an SDK-internal file (e.g. tool-results), it often
wants to process the data with bash. Copying the file into the sandbox
under a stable name lets ``bash_exec`` access it without extra steps.
Only copies when offset=0 and limit is large enough to indicate the model
wants the full file. Errors are logged but never propagated.
Returns the sandbox path on success, or ``None`` on skip/failure.
Size handling:
- <= 32 KB: written to ``/tmp/<hash>-<basename>`` via shell base64
(``_sandbox_write``). Kept small to stay within ARG_MAX.
- 32 KB - 50 MB: written to ``/home/user/<hash>-<basename>`` via
``sandbox.files.write()`` to avoid shell argument length limits.
- > 50 MB: skipped entirely with a warning.
The sandbox filename is prefixed with a short hash of the full source
path to avoid collisions when different source files share the same
basename (e.g. multiple ``result.json`` files).
"""
if offset != 0 or limit < _DEFAULT_READ_LIMIT:
return None
try:
expanded = os.path.realpath(os.path.expanduser(file_path))
basename = os.path.basename(expanded)
source_id = hashlib.sha256(expanded.encode()).hexdigest()[:12]
unique_name = f"{source_id}-{basename}"
file_size = os.path.getsize(expanded)
if file_size > _BRIDGE_SKIP_BYTES:
logger.warning(
"[E2B] Skipping bridge for large file (%d bytes): %s",
file_size,
basename,
)
return None
def _read_bytes() -> bytes:
with open(expanded, "rb") as fh:
return fh.read()
raw_content = await asyncio.to_thread(_read_bytes)
try:
text_content: str | None = raw_content.decode("utf-8")
except UnicodeDecodeError:
text_content = None
data: str | bytes = text_content if text_content is not None else raw_content
if file_size <= _BRIDGE_SHELL_MAX_BYTES:
sandbox_path = f"/tmp/{unique_name}"
await _sandbox_write(sandbox, sandbox_path, data)
else:
sandbox_path = f"/home/user/{unique_name}"
await sandbox.files.write(sandbox_path, data)
logger.info(
"[E2B] Bridged SDK file to sandbox: %s -> %s", basename, sandbox_path
)
return sandbox_path
except Exception:
logger.warning(
"[E2B] Failed to bridge SDK file to sandbox: %s",
file_path,
exc_info=True,
)
return None
async def bridge_and_annotate(
sandbox: Any, file_path: str, offset: int, limit: int
) -> str | None:
"""Bridge a host file to the sandbox and return a newline-prefixed annotation.
Combines ``bridge_to_sandbox`` with the standard annotation suffix so
callers don't need to duplicate the pattern. Returns a string like
``"\\n[Sandbox copy available at /tmp/abc-file.txt]"`` on success, or
``None`` if bridging was skipped or failed.
"""
sandbox_path = await bridge_to_sandbox(sandbox, file_path, offset, limit)
if sandbox_path is None:
return None
return f"\n[Sandbox copy available at {sandbox_path}]"
# Local read (for SDK-internal paths)

View File

@@ -3,7 +3,6 @@
Pure unit tests with no external dependencies (no E2B, no sandbox).
"""
import hashlib
import os
import shutil
from types import SimpleNamespace
@@ -14,26 +13,12 @@ import pytest
from backend.copilot.context import E2B_WORKDIR, SDK_PROJECTS_DIR, _current_project_dir
from .e2b_file_tools import (
_BRIDGE_SHELL_MAX_BYTES,
_BRIDGE_SKIP_BYTES,
_DEFAULT_READ_LIMIT,
_check_sandbox_symlink_escape,
_read_local,
_sandbox_write,
bridge_and_annotate,
bridge_to_sandbox,
resolve_sandbox_path,
)
def _expected_bridge_path(file_path: str, prefix: str = "/tmp") -> str:
"""Compute the expected sandbox path for a bridged file."""
expanded = os.path.realpath(os.path.expanduser(file_path))
basename = os.path.basename(expanded)
source_id = hashlib.sha256(expanded.encode()).hexdigest()[:12]
return f"{prefix}/{source_id}-{basename}"
# ---------------------------------------------------------------------------
# resolve_sandbox_path — sandbox path normalisation & boundary enforcement
# ---------------------------------------------------------------------------
@@ -106,9 +91,9 @@ class TestResolveSandboxPath:
# ---------------------------------------------------------------------------
# _read_local — host filesystem reads with allowlist enforcement
#
# In E2B mode, _read_local only allows tool-results/tool-outputs paths
# (via is_allowed_local_path without sdk_cwd). Regular files live on
# the sandbox, not the host.
# In E2B mode, _read_local only allows tool-results paths (via
# is_allowed_local_path without sdk_cwd). Regular files live on the
# sandbox, not the host.
# ---------------------------------------------------------------------------
@@ -134,7 +119,7 @@ class TestReadLocal:
)
token = _current_project_dir.set(encoded)
try:
result = _read_local(filepath, offset=0, limit=_DEFAULT_READ_LIMIT)
result = _read_local(filepath, offset=0, limit=2000)
assert result["isError"] is False
assert "line 1" in result["content"][0]["text"]
assert "line 2" in result["content"][0]["text"]
@@ -142,25 +127,6 @@ class TestReadLocal:
_current_project_dir.reset(token)
os.unlink(filepath)
def test_read_tool_outputs_file(self):
"""Reading a tool-outputs file should also succeed."""
encoded = "-tmp-copilot-e2b-test-read-outputs"
tool_outputs_dir = os.path.join(
SDK_PROJECTS_DIR, encoded, self._CONV_UUID, "tool-outputs"
)
os.makedirs(tool_outputs_dir, exist_ok=True)
filepath = os.path.join(tool_outputs_dir, "sdk-abc123.json")
with open(filepath, "w") as f:
f.write('{"data": "test"}\n')
token = _current_project_dir.set(encoded)
try:
result = _read_local(filepath, offset=0, limit=_DEFAULT_READ_LIMIT)
assert result["isError"] is False
assert "test" in result["content"][0]["text"]
finally:
_current_project_dir.reset(token)
shutil.rmtree(os.path.join(SDK_PROJECTS_DIR, encoded), ignore_errors=True)
def test_read_disallowed_path_blocked(self):
"""Reading /etc/passwd should be blocked by the allowlist."""
result = _read_local("/etc/passwd", offset=0, limit=10)
@@ -369,199 +335,3 @@ class TestSandboxWrite:
encoded_in_cmd = call_args.split("echo ")[1].split(" |")[0].strip("'")
decoded = base64.b64decode(encoded_in_cmd).decode()
assert decoded == content
# ---------------------------------------------------------------------------
# bridge_to_sandbox — copy SDK-internal files into E2B sandbox
# ---------------------------------------------------------------------------
def _make_bridge_sandbox() -> SimpleNamespace:
"""Build a sandbox mock suitable for bridge_to_sandbox tests."""
run_result = SimpleNamespace(stdout="", stderr="", exit_code=0)
commands = SimpleNamespace(run=AsyncMock(return_value=run_result))
files = SimpleNamespace(write=AsyncMock())
return SimpleNamespace(commands=commands, files=files)
class TestBridgeToSandbox:
@pytest.mark.asyncio
async def test_happy_path_small_file(self, tmp_path):
"""A small file is bridged to /tmp/<hash>-<basename> via _sandbox_write."""
f = tmp_path / "result.json"
f.write_text('{"ok": true}')
sandbox = _make_bridge_sandbox()
result = await bridge_to_sandbox(
sandbox, str(f), offset=0, limit=_DEFAULT_READ_LIMIT
)
expected = _expected_bridge_path(str(f))
assert result == expected
sandbox.commands.run.assert_called_once()
cmd = sandbox.commands.run.call_args[0][0]
assert "result.json" in cmd
sandbox.files.write.assert_not_called()
@pytest.mark.asyncio
async def test_skip_when_offset_nonzero(self, tmp_path):
"""Bridging is skipped when offset != 0 (partial read)."""
f = tmp_path / "data.txt"
f.write_text("content")
sandbox = _make_bridge_sandbox()
result = await bridge_to_sandbox(
sandbox, str(f), offset=10, limit=_DEFAULT_READ_LIMIT
)
assert result is None
sandbox.commands.run.assert_not_called()
sandbox.files.write.assert_not_called()
@pytest.mark.asyncio
async def test_skip_when_limit_too_small(self, tmp_path):
"""Bridging is skipped when limit < _DEFAULT_READ_LIMIT (partial read)."""
f = tmp_path / "data.txt"
f.write_text("content")
sandbox = _make_bridge_sandbox()
await bridge_to_sandbox(sandbox, str(f), offset=0, limit=100)
sandbox.commands.run.assert_not_called()
sandbox.files.write.assert_not_called()
@pytest.mark.asyncio
async def test_nonexistent_file_does_not_raise(self, tmp_path):
"""Bridging a non-existent file logs but does not propagate errors."""
sandbox = _make_bridge_sandbox()
await bridge_to_sandbox(
sandbox, str(tmp_path / "ghost.txt"), offset=0, limit=_DEFAULT_READ_LIMIT
)
sandbox.commands.run.assert_not_called()
sandbox.files.write.assert_not_called()
@pytest.mark.asyncio
async def test_sandbox_write_failure_returns_none(self, tmp_path):
"""If sandbox write fails, returns None (best-effort)."""
f = tmp_path / "data.txt"
f.write_text("content")
sandbox = _make_bridge_sandbox()
sandbox.commands.run.side_effect = RuntimeError("E2B timeout")
result = await bridge_to_sandbox(
sandbox, str(f), offset=0, limit=_DEFAULT_READ_LIMIT
)
assert result is None
@pytest.mark.asyncio
async def test_large_file_uses_files_api(self, tmp_path):
"""Files > 32 KB but <= 50 MB are written to /home/user/ via files.write."""
f = tmp_path / "big.json"
f.write_bytes(b"x" * (_BRIDGE_SHELL_MAX_BYTES + 1))
sandbox = _make_bridge_sandbox()
result = await bridge_to_sandbox(
sandbox, str(f), offset=0, limit=_DEFAULT_READ_LIMIT
)
expected = _expected_bridge_path(str(f), prefix="/home/user")
assert result == expected
sandbox.files.write.assert_called_once()
call_args = sandbox.files.write.call_args[0]
assert call_args[0] == expected
sandbox.commands.run.assert_not_called()
@pytest.mark.asyncio
async def test_small_binary_file_preserves_bytes(self, tmp_path):
"""A small binary file is bridged to /tmp via base64 without corruption."""
binary_data = bytes(range(256))
f = tmp_path / "image.png"
f.write_bytes(binary_data)
sandbox = _make_bridge_sandbox()
result = await bridge_to_sandbox(
sandbox, str(f), offset=0, limit=_DEFAULT_READ_LIMIT
)
expected = _expected_bridge_path(str(f))
assert result == expected
sandbox.commands.run.assert_called_once()
cmd = sandbox.commands.run.call_args[0][0]
assert "base64" in cmd
sandbox.files.write.assert_not_called()
@pytest.mark.asyncio
async def test_large_binary_file_writes_raw_bytes(self, tmp_path):
"""A large binary file is bridged to /home/user/ as raw bytes."""
binary_data = bytes(range(256)) * 200
f = tmp_path / "photo.jpg"
f.write_bytes(binary_data)
sandbox = _make_bridge_sandbox()
result = await bridge_to_sandbox(
sandbox, str(f), offset=0, limit=_DEFAULT_READ_LIMIT
)
expected = _expected_bridge_path(str(f), prefix="/home/user")
assert result == expected
sandbox.files.write.assert_called_once()
call_args = sandbox.files.write.call_args[0]
assert call_args[0] == expected
assert call_args[1] == binary_data
sandbox.commands.run.assert_not_called()
@pytest.mark.asyncio
async def test_very_large_file_skipped(self, tmp_path):
"""Files > 50 MB are skipped entirely."""
f = tmp_path / "huge.bin"
# Create a sparse file to avoid actually writing 50 MB
with open(f, "wb") as fh:
fh.seek(_BRIDGE_SKIP_BYTES + 1)
fh.write(b"\0")
sandbox = _make_bridge_sandbox()
result = await bridge_to_sandbox(
sandbox, str(f), offset=0, limit=_DEFAULT_READ_LIMIT
)
assert result is None
sandbox.commands.run.assert_not_called()
sandbox.files.write.assert_not_called()
# ---------------------------------------------------------------------------
# bridge_and_annotate — shared helper wrapping bridge_to_sandbox + annotation
# ---------------------------------------------------------------------------
class TestBridgeAndAnnotate:
@pytest.mark.asyncio
async def test_returns_annotation_on_success(self, tmp_path):
"""On success, returns a newline-prefixed annotation with the sandbox path."""
f = tmp_path / "data.json"
f.write_text('{"ok": true}')
sandbox = _make_bridge_sandbox()
annotation = await bridge_and_annotate(
sandbox, str(f), offset=0, limit=_DEFAULT_READ_LIMIT
)
expected_path = _expected_bridge_path(str(f))
assert annotation == f"\n[Sandbox copy available at {expected_path}]"
@pytest.mark.asyncio
async def test_returns_none_when_skipped(self, tmp_path):
"""When bridging is skipped (e.g. offset != 0), returns None."""
f = tmp_path / "data.json"
f.write_text("content")
sandbox = _make_bridge_sandbox()
annotation = await bridge_and_annotate(
sandbox, str(f), offset=10, limit=_DEFAULT_READ_LIMIT
)
assert annotation is None

View File

@@ -275,7 +275,7 @@ class TestCompactionE2E:
# --- Step 7: CompactionTracker receives PreCompact hook ---
tracker = CompactionTracker()
session = ChatSession.new(user_id="test-user", dry_run=False)
session = ChatSession.new(user_id="test-user")
tracker.on_compact(str(session_file))
# --- Step 8: Next SDK message arrives → emit_start ---
@@ -376,7 +376,7 @@ class TestCompactionE2E:
monkeypatch.setenv("CLAUDE_CONFIG_DIR", str(config_dir))
tracker = CompactionTracker()
session = ChatSession.new(user_id="test", dry_run=False)
session = ChatSession.new(user_id="test")
builder = TranscriptBuilder()
# --- First query with compaction ---

View File

@@ -1,82 +0,0 @@
"""SDK environment variable builder — importable without circular deps.
Extracted from ``service.py`` so that ``backend.blocks.orchestrator``
can reuse the same subscription / OpenRouter / direct-Anthropic logic
without pulling in the full copilot service module (which would create a
circular import through ``executor`` → ``credit`` → ``block_cost_config``).
"""
from __future__ import annotations
from backend.copilot.config import ChatConfig
from backend.copilot.sdk.subscription import validate_subscription
# ChatConfig is stateless (reads env vars) — a separate instance is fine.
# A singleton would require importing service.py which causes the circular dep
# this module was created to avoid.
config = ChatConfig()
def build_sdk_env(
session_id: str | None = None,
user_id: str | None = None,
sdk_cwd: str | None = None,
) -> dict[str, str]:
"""Build env vars for the SDK CLI subprocess.
Three modes (checked in order):
1. **Subscription** — clears all keys; CLI uses ``claude login`` auth.
2. **Direct Anthropic** — returns ``{}``; subprocess inherits
``ANTHROPIC_API_KEY`` from the parent environment.
3. **OpenRouter** (default) — overrides base URL and auth token to
route through the proxy, with Langfuse trace headers.
When *sdk_cwd* is provided, ``CLAUDE_CODE_TMPDIR`` is set so that
the CLI writes temp/sub-agent output inside the per-session workspace
directory rather than an inaccessible system temp path.
"""
# --- Mode 1: Claude Code subscription auth ---
if config.use_claude_code_subscription:
validate_subscription()
env: dict[str, str] = {
"ANTHROPIC_API_KEY": "",
"ANTHROPIC_AUTH_TOKEN": "",
"ANTHROPIC_BASE_URL": "",
}
if sdk_cwd:
env["CLAUDE_CODE_TMPDIR"] = sdk_cwd
return env
# --- Mode 2: Direct Anthropic (no proxy hop) ---
if not config.openrouter_active:
env = {}
if sdk_cwd:
env["CLAUDE_CODE_TMPDIR"] = sdk_cwd
return env
# --- Mode 3: OpenRouter proxy ---
base = (config.base_url or "").rstrip("/")
if base.endswith("/v1"):
base = base[:-3]
env = {
"ANTHROPIC_BASE_URL": base,
"ANTHROPIC_AUTH_TOKEN": config.api_key or "",
"ANTHROPIC_API_KEY": "", # force CLI to use AUTH_TOKEN
}
# Inject broadcast headers so OpenRouter forwards traces to Langfuse.
def _safe(v: str) -> str:
return v.replace("\r", "").replace("\n", "").strip()[:128]
parts = []
if session_id:
parts.append(f"x-session-id: {_safe(session_id)}")
if user_id:
parts.append(f"x-user-id: {_safe(user_id)}")
if parts:
env["ANTHROPIC_CUSTOM_HEADERS"] = "\n".join(parts)
if sdk_cwd:
env["CLAUDE_CODE_TMPDIR"] = sdk_cwd
return env

View File

@@ -1,293 +0,0 @@
"""Tests for build_sdk_env() — the SDK subprocess environment builder."""
from unittest.mock import patch
import pytest
from backend.copilot.config import ChatConfig
# ---------------------------------------------------------------------------
# Helpers — build a ChatConfig with explicit field values so tests don't
# depend on real environment variables.
# ---------------------------------------------------------------------------
def _make_config(**overrides) -> ChatConfig:
"""Create a ChatConfig with safe defaults, applying *overrides*."""
defaults = {
"use_claude_code_subscription": False,
"use_openrouter": False,
"api_key": None,
"base_url": None,
}
defaults.update(overrides)
return ChatConfig(**defaults)
# ---------------------------------------------------------------------------
# Mode 1 — Subscription auth
# ---------------------------------------------------------------------------
class TestBuildSdkEnvSubscription:
"""When ``use_claude_code_subscription`` is True, keys are blanked."""
@patch("backend.copilot.sdk.env.validate_subscription")
def test_returns_blanked_keys(self, mock_validate):
"""Subscription mode clears API_KEY, AUTH_TOKEN, and BASE_URL."""
cfg = _make_config(use_claude_code_subscription=True)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
assert result == {
"ANTHROPIC_API_KEY": "",
"ANTHROPIC_AUTH_TOKEN": "",
"ANTHROPIC_BASE_URL": "",
}
mock_validate.assert_called_once()
@patch(
"backend.copilot.sdk.env.validate_subscription",
side_effect=RuntimeError("CLI not found"),
)
def test_propagates_validation_error(self, mock_validate):
"""If validate_subscription fails, the error bubbles up."""
cfg = _make_config(use_claude_code_subscription=True)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
with pytest.raises(RuntimeError, match="CLI not found"):
build_sdk_env()
# ---------------------------------------------------------------------------
# Mode 2 — Direct Anthropic (no OpenRouter)
# ---------------------------------------------------------------------------
class TestBuildSdkEnvDirectAnthropic:
"""When OpenRouter is inactive, return empty dict (inherit parent env)."""
def test_returns_empty_dict_when_openrouter_inactive(self):
cfg = _make_config(use_openrouter=False)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
assert result == {}
def test_returns_empty_dict_when_openrouter_flag_true_but_no_key(self):
"""OpenRouter flag is True but no api_key => openrouter_active is False."""
cfg = _make_config(use_openrouter=True, base_url="https://openrouter.ai/api/v1")
# Force api_key to None after construction (field_validator may pick up env vars)
object.__setattr__(cfg, "api_key", None)
assert not cfg.openrouter_active
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
assert result == {}
# ---------------------------------------------------------------------------
# Mode 3 — OpenRouter proxy
# ---------------------------------------------------------------------------
class TestBuildSdkEnvOpenRouter:
"""When OpenRouter is active, return proxy env vars."""
def _openrouter_config(self, **overrides):
defaults = {
"use_openrouter": True,
"api_key": "sk-or-test-key",
"base_url": "https://openrouter.ai/api/v1",
}
defaults.update(overrides)
return _make_config(**defaults)
def test_basic_openrouter_env(self):
cfg = self._openrouter_config()
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
assert result["ANTHROPIC_BASE_URL"] == "https://openrouter.ai/api"
assert result["ANTHROPIC_AUTH_TOKEN"] == "sk-or-test-key"
assert result["ANTHROPIC_API_KEY"] == ""
assert "ANTHROPIC_CUSTOM_HEADERS" not in result
def test_strips_trailing_v1(self):
"""The /v1 suffix is stripped from the base URL."""
cfg = self._openrouter_config(base_url="https://openrouter.ai/api/v1")
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
assert result["ANTHROPIC_BASE_URL"] == "https://openrouter.ai/api"
def test_strips_trailing_v1_and_slash(self):
"""Trailing slash before /v1 strip is handled."""
cfg = self._openrouter_config(base_url="https://openrouter.ai/api/v1/")
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
# rstrip("/") first, then remove /v1
assert result["ANTHROPIC_BASE_URL"] == "https://openrouter.ai/api"
def test_no_v1_suffix_left_alone(self):
"""A base URL without /v1 is used as-is."""
cfg = self._openrouter_config(base_url="https://custom-proxy.example.com")
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
assert result["ANTHROPIC_BASE_URL"] == "https://custom-proxy.example.com"
def test_session_id_header(self):
cfg = self._openrouter_config()
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(session_id="sess-123")
assert "ANTHROPIC_CUSTOM_HEADERS" in result
assert "x-session-id: sess-123" in result["ANTHROPIC_CUSTOM_HEADERS"]
def test_user_id_header(self):
cfg = self._openrouter_config()
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(user_id="user-456")
assert "x-user-id: user-456" in result["ANTHROPIC_CUSTOM_HEADERS"]
def test_both_headers(self):
cfg = self._openrouter_config()
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(session_id="s1", user_id="u2")
headers = result["ANTHROPIC_CUSTOM_HEADERS"]
assert "x-session-id: s1" in headers
assert "x-user-id: u2" in headers
# They should be newline-separated
assert "\n" in headers
def test_header_sanitisation_strips_newlines(self):
"""Newlines/carriage-returns in header values are stripped."""
cfg = self._openrouter_config()
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(session_id="bad\r\nvalue")
header_val = result["ANTHROPIC_CUSTOM_HEADERS"]
# The _safe helper removes \r and \n
assert "\r" not in header_val.split(": ", 1)[1]
assert "badvalue" in header_val
def test_header_value_truncated_to_128_chars(self):
"""Header values are truncated to 128 characters."""
cfg = self._openrouter_config()
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
long_id = "x" * 200
result = build_sdk_env(session_id=long_id)
# The value after "x-session-id: " should be at most 128 chars
header_line = result["ANTHROPIC_CUSTOM_HEADERS"]
value = header_line.split(": ", 1)[1]
assert len(value) == 128
# ---------------------------------------------------------------------------
# Mode priority
# ---------------------------------------------------------------------------
class TestBuildSdkEnvModePriority:
"""Subscription mode takes precedence over OpenRouter."""
@patch("backend.copilot.sdk.env.validate_subscription")
def test_subscription_overrides_openrouter(self, mock_validate):
cfg = _make_config(
use_claude_code_subscription=True,
use_openrouter=True,
api_key="sk-or-key",
base_url="https://openrouter.ai/api/v1",
)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env()
# Should get subscription result, not OpenRouter
assert result == {
"ANTHROPIC_API_KEY": "",
"ANTHROPIC_AUTH_TOKEN": "",
"ANTHROPIC_BASE_URL": "",
}
# ---------------------------------------------------------------------------
# CLAUDE_CODE_TMPDIR integration
# ---------------------------------------------------------------------------
class TestClaudeCodeTmpdir:
"""Verify build_sdk_env() sets CLAUDE_CODE_TMPDIR from *sdk_cwd*."""
def test_tmpdir_set_when_sdk_cwd_is_truthy(self):
"""CLAUDE_CODE_TMPDIR is set to sdk_cwd when sdk_cwd is truthy."""
cfg = _make_config(use_openrouter=False)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(sdk_cwd="/tmp/copilot-workspace")
assert result["CLAUDE_CODE_TMPDIR"] == "/tmp/copilot-workspace"
def test_tmpdir_not_set_when_sdk_cwd_is_none(self):
"""CLAUDE_CODE_TMPDIR is NOT in the env when sdk_cwd is None."""
cfg = _make_config(use_openrouter=False)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(sdk_cwd=None)
assert "CLAUDE_CODE_TMPDIR" not in result
def test_tmpdir_not_set_when_sdk_cwd_is_empty_string(self):
"""CLAUDE_CODE_TMPDIR is NOT in the env when sdk_cwd is empty string."""
cfg = _make_config(use_openrouter=False)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(sdk_cwd="")
assert "CLAUDE_CODE_TMPDIR" not in result
@patch("backend.copilot.sdk.env.validate_subscription")
def test_tmpdir_set_in_subscription_mode(self, mock_validate):
"""CLAUDE_CODE_TMPDIR is set even in subscription mode."""
cfg = _make_config(use_claude_code_subscription=True)
with patch("backend.copilot.sdk.env.config", cfg):
from backend.copilot.sdk.env import build_sdk_env
result = build_sdk_env(sdk_cwd="/tmp/sub-workspace")
assert result["CLAUDE_CODE_TMPDIR"] == "/tmp/sub-workspace"
assert result["ANTHROPIC_API_KEY"] == ""

View File

@@ -38,7 +38,7 @@ class TestFlattenAssistantContent:
def test_tool_use_blocks(self):
blocks = [{"type": "tool_use", "name": "read_file", "input": {}}]
assert _flatten_assistant_content(blocks) == ""
assert _flatten_assistant_content(blocks) == "[tool_use: read_file]"
def test_mixed_blocks(self):
blocks = [
@@ -47,22 +47,19 @@ class TestFlattenAssistantContent:
]
result = _flatten_assistant_content(blocks)
assert "Let me read that." in result
# tool_use blocks are dropped entirely to prevent model mimicry
assert "Read" not in result
assert "[tool_use: Read]" in result
def test_raw_strings(self):
assert _flatten_assistant_content(["hello", "world"]) == "hello\nworld"
def test_unknown_block_type_dropped(self):
def test_unknown_block_type_preserved_as_placeholder(self):
blocks = [
{"type": "text", "text": "See this image:"},
{"type": "image", "source": {"type": "base64", "data": "..."}},
]
result = _flatten_assistant_content(blocks)
assert "See this image:" in result
# Unknown block types are dropped to prevent model mimicry
assert "[__image__]" not in result
assert "base64" not in result
assert "[__image__]" in result
def test_empty(self):
assert _flatten_assistant_content([]) == ""
@@ -282,8 +279,7 @@ class TestTranscriptToMessages:
messages = _transcript_to_messages(content)
assert len(messages) == 2
assert "Let me check." in messages[0]["content"]
# tool_use blocks are dropped entirely to prevent model mimicry
assert "read_file" not in messages[0]["content"]
assert "[tool_use: read_file]" in messages[0]["content"]
assert messages[1]["content"] == "file contents"
@@ -446,11 +442,8 @@ class TestCompactTranscript:
assert result is not None
assert validate_transcript(result)
msgs = _transcript_to_messages(result)
# 3 messages: compressed prefix (2) + preserved last assistant (1)
assert len(msgs) == 3
assert len(msgs) == 2
assert msgs[1]["content"] == "Summarized response"
# The last assistant entry is preserved verbatim from original
assert msgs[2]["content"] == "Details"
@pytest.mark.asyncio
async def test_returns_none_on_compression_failure(self, mock_chat_config):

View File

@@ -49,22 +49,22 @@ def test_format_assistant_tool_calls():
)
]
result = _format_conversation_context(msgs)
# Assistant with no content and tool_calls omitted produces no lines
assert result is None
assert result is not None
assert 'You called tool: search({"q": "test"})' in result
def test_format_tool_result():
msgs = [ChatMessage(role="tool", content='{"result": "ok"}')]
result = _format_conversation_context(msgs)
assert result is not None
assert 'Tool output: {"result": "ok"}' in result
assert 'Tool result: {"result": "ok"}' in result
def test_format_tool_result_none_content():
msgs = [ChatMessage(role="tool", content=None)]
result = _format_conversation_context(msgs)
assert result is not None
assert "Tool output: " in result
assert "Tool result: " in result
def test_format_full_conversation():
@@ -84,8 +84,8 @@ def test_format_full_conversation():
assert result is not None
assert "User: find agents" in result
assert "You responded: I'll search for agents." in result
# tool_calls are omitted to prevent model mimicry
assert "Tool output:" in result
assert "You called tool: find_agents" in result
assert "Tool result:" in result
assert "You responded: Found Agent1." in result

View File

@@ -15,7 +15,6 @@ from claude_agent_sdk import (
ResultMessage,
SystemMessage,
TextBlock,
ThinkingBlock,
ToolResultBlock,
ToolUseBlock,
UserMessage,
@@ -27,7 +26,6 @@ from backend.copilot.response_model import (
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
StreamTextDelta,
@@ -77,12 +75,6 @@ class SDKResponseAdapter:
# Open the first step (matches non-SDK: StreamStart then StreamStartStep)
responses.append(StreamStartStep())
self.step_open = True
elif sdk_message.subtype == "task_progress":
# Emit a heartbeat so publish_chunk is called during long
# sub-agent runs. Without this, the Redis stream and meta
# key TTLs expire during gaps where no real chunks are
# produced (task_progress events were previously silent).
responses.append(StreamHeartbeat())
elif isinstance(sdk_message, AssistantMessage):
# Flush any SDK built-in tool calls that didn't get a UserMessage
@@ -108,11 +100,6 @@ class SDKResponseAdapter:
StreamTextDelta(id=self.text_block_id, delta=block.text)
)
elif isinstance(block, ThinkingBlock):
# Thinking blocks are preserved in the transcript but
# not streamed to the frontend — skip silently.
pass
elif isinstance(block, ToolUseBlock):
self._end_text_if_open(responses)

View File

@@ -18,7 +18,6 @@ from backend.copilot.response_model import (
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
StreamTextDelta,
@@ -29,7 +28,6 @@ from backend.copilot.response_model import (
StreamToolOutputAvailable,
)
from .compaction import compaction_events
from .response_adapter import SDKResponseAdapter
from .tool_adapter import MCP_TOOL_PREFIX
from .tool_adapter import _pending_tool_outputs as _pto
@@ -61,14 +59,6 @@ def test_system_non_init_emits_nothing():
assert results == []
def test_task_progress_emits_heartbeat():
"""task_progress events emit a StreamHeartbeat to keep Redis TTL alive."""
adapter = _adapter()
results = adapter.convert_message(SystemMessage(subtype="task_progress", data={}))
assert len(results) == 1
assert isinstance(results[0], StreamHeartbeat)
# -- AssistantMessage with TextBlock -----------------------------------------
@@ -690,102 +680,3 @@ def test_already_resolved_tool_skipped_in_user_message():
assert (
len(output_events) == 0
), "Already-resolved tool should not emit duplicate output"
# -- _end_text_if_open before compaction -------------------------------------
def test_end_text_if_open_emits_text_end_before_finish_step():
"""StreamTextEnd must be emitted before StreamFinishStep during compaction.
When ``emit_end_if_ready`` fires compaction events while a text block is
still open, ``_end_text_if_open`` must close it first. If StreamFinishStep
arrives before StreamTextEnd, the Vercel AI SDK clears ``activeTextParts``
and raises "Received text-end for missing text part".
"""
adapter = _adapter()
# Open a text block by processing an AssistantMessage with text
msg = AssistantMessage(content=[TextBlock(text="partial response")], model="test")
adapter.convert_message(msg)
assert adapter.has_started_text
assert not adapter.has_ended_text
# Simulate what service.py does before yielding compaction events
pre_close: list[StreamBaseResponse] = []
adapter._end_text_if_open(pre_close)
combined = pre_close + list(compaction_events("Compacted transcript"))
text_end_idx = next(
(i for i, e in enumerate(combined) if isinstance(e, StreamTextEnd)), None
)
finish_step_idx = next(
(i for i, e in enumerate(combined) if isinstance(e, StreamFinishStep)), None
)
assert text_end_idx is not None, "StreamTextEnd must be present"
assert finish_step_idx is not None, "StreamFinishStep must be present"
assert text_end_idx < finish_step_idx, (
f"StreamTextEnd (idx={text_end_idx}) must precede "
f"StreamFinishStep (idx={finish_step_idx}) — otherwise the Vercel AI SDK "
"clears activeTextParts before text-end arrives"
)
def test_step_open_must_reset_after_compaction_finish_step():
"""Adapter step_open must be reset when compaction emits StreamFinishStep.
Compaction events bypass the adapter, so service.py must explicitly clear
step_open after yielding a StreamFinishStep from compaction. Without this,
the next AssistantMessage skips StreamStartStep because the adapter still
thinks a step is open.
"""
adapter = _adapter()
# Open a step + text block via an AssistantMessage
msg = AssistantMessage(content=[TextBlock(text="thinking...")], model="test")
adapter.convert_message(msg)
assert adapter.step_open is True
# Simulate what service.py does: close text, then check compaction events
pre_close: list[StreamBaseResponse] = []
adapter._end_text_if_open(pre_close)
events = list(compaction_events("Compacted transcript"))
if any(isinstance(ev, StreamFinishStep) for ev in events):
adapter.step_open = False
assert (
adapter.step_open is False
), "step_open must be False after compaction emits StreamFinishStep"
# Next AssistantMessage must open a new step
msg2 = AssistantMessage(content=[TextBlock(text="continued")], model="test")
results = adapter.convert_message(msg2)
assert any(
isinstance(r, StreamStartStep) for r in results
), "A new StreamStartStep must be emitted after compaction closed the step"
def test_end_text_if_open_no_op_when_no_text_open():
"""_end_text_if_open emits nothing when no text block is open."""
adapter = _adapter()
results: list[StreamBaseResponse] = []
adapter._end_text_if_open(results)
assert results == []
def test_end_text_if_open_no_op_after_text_already_ended():
"""_end_text_if_open emits nothing when the text block is already closed."""
adapter = _adapter()
msg = AssistantMessage(content=[TextBlock(text="hello")], model="test")
adapter.convert_message(msg)
# Close it once
first: list[StreamBaseResponse] = []
adapter._end_text_if_open(first)
assert len(first) == 1
assert isinstance(first[0], StreamTextEnd)
# Second call must be a no-op
second: list[StreamBaseResponse] = []
adapter._end_text_if_open(second)
assert second == []

View File

@@ -124,11 +124,8 @@ class TestScenarioCompactAndRetry:
assert result != original # Must be different
assert validate_transcript(result)
msgs = _transcript_to_messages(result)
# 3 messages: compressed prefix (2) + preserved last assistant (1)
assert len(msgs) == 3
assert len(msgs) == 2
assert msgs[0]["content"] == "[summary of conversation]"
# Last assistant preserved verbatim
assert msgs[2]["content"] == "Long answer 2"
def test_compacted_transcript_loads_into_builder(self):
"""TranscriptBuilder can load a compacted transcript and continue."""
@@ -740,10 +737,7 @@ class TestRetryEdgeCases:
assert result is not None
assert result != transcript
msgs = _transcript_to_messages(result)
# 3 messages: compressed prefix (2) + preserved last assistant (1)
assert len(msgs) == 3
# Last assistant preserved verbatim
assert msgs[2]["content"] == "Answer 19"
assert len(msgs) == 2
def test_messages_to_transcript_roundtrip_preserves_content(self):
"""Verify messages → transcript → messages preserves all content."""
@@ -904,14 +898,14 @@ class TestTranscriptEdgeCases:
assert restored[1]["content"] == "Second"
def test_flatten_assistant_with_only_tool_use(self):
"""Assistant message with only tool_use blocks (no text) flattens to empty."""
"""Assistant message with only tool_use blocks (no text)."""
blocks = [
{"type": "tool_use", "name": "bash", "input": {"cmd": "ls"}},
{"type": "tool_use", "name": "read", "input": {"path": "/f"}},
]
result = _flatten_assistant_content(blocks)
# tool_use blocks are dropped entirely to prevent model mimicry
assert result == ""
assert "[tool_use: bash]" in result
assert "[tool_use: read]" in result
def test_flatten_tool_result_nested_image(self):
"""Tool result containing image blocks uses placeholder."""
@@ -1010,7 +1004,7 @@ def _make_sdk_patches(
(f"{_SVC}.create_security_hooks", dict(return_value=MagicMock())),
(f"{_SVC}.get_copilot_tool_names", dict(return_value=[])),
(f"{_SVC}.get_sdk_disallowed_tools", dict(return_value=[])),
(f"{_SVC}.build_sdk_env", dict(return_value={})),
(f"{_SVC}._build_sdk_env", dict(return_value=None)),
(f"{_SVC}._resolve_sdk_model", dict(return_value=None)),
(f"{_SVC}.set_execution_context", {}),
(
@@ -1414,261 +1408,3 @@ class TestStreamChatCompletionRetryIntegration:
# Verify user-friendly message (not raw SDK text)
assert "Authentication" in errors[0].errorText
assert any(isinstance(e, StreamStart) for e in events)
@pytest.mark.asyncio
async def test_result_message_prompt_too_long_triggers_compaction(self):
"""CLI returns ResultMessage(subtype="error") with "Prompt is too long".
When the Claude CLI rejects the prompt pre-API (model=<synthetic>,
duration_api_ms=0), it sends a ResultMessage with is_error=True
instead of raising a Python exception. The retry loop must still
detect this as a context-length error and trigger compaction.
"""
import contextlib
from claude_agent_sdk import ResultMessage
from backend.copilot.response_model import StreamError, StreamStart
from backend.copilot.sdk.service import stream_chat_completion_sdk
session = self._make_session()
success_result = self._make_result_message()
attempt_count = [0]
error_result = ResultMessage(
subtype="error",
result="Prompt is too long",
duration_ms=100,
duration_api_ms=0,
is_error=True,
num_turns=0,
session_id="test-session-id",
)
def _client_factory(*args, **kwargs):
attempt_count[0] += 1
if attempt_count[0] == 1:
# First attempt: CLI returns error ResultMessage
return self._make_client_mock(result_message=error_result)
# Second attempt (after compaction): succeeds
return self._make_client_mock(result_message=success_result)
original_transcript = _build_transcript(
[("user", "prior question"), ("assistant", "prior answer")]
)
compacted_transcript = _build_transcript(
[("user", "[summary]"), ("assistant", "summary reply")]
)
patches = _make_sdk_patches(
session,
original_transcript=original_transcript,
compacted_transcript=compacted_transcript,
client_side_effect=_client_factory,
)
events = []
with contextlib.ExitStack() as stack:
for target, kwargs in patches:
stack.enter_context(patch(target, **kwargs))
async for event in stream_chat_completion_sdk(
session_id="test-session-id",
message="hello",
is_user_message=True,
user_id="test-user",
session=session,
):
events.append(event)
assert attempt_count[0] == 2, (
f"Expected 2 SDK attempts (CLI error ResultMessage "
f"should trigger compaction retry), got {attempt_count[0]}"
)
errors = [e for e in events if isinstance(e, StreamError)]
assert not errors, f"Unexpected StreamError: {errors}"
assert any(isinstance(e, StreamStart) for e in events)
@pytest.mark.asyncio
async def test_result_message_success_subtype_prompt_too_long_triggers_compaction(
self,
):
"""CLI returns ResultMessage(subtype="success") with result="Prompt is too long".
The SDK internally compacts but the transcript is still too long. It
returns subtype="success" (process completed) with result="Prompt is
too long" (the actual rejection message). The retry loop must detect
this as a context-length error and trigger compaction — the subtype
"success" must not fool it into treating this as a real response.
"""
import contextlib
from claude_agent_sdk import ResultMessage
from backend.copilot.response_model import StreamError, StreamStart
from backend.copilot.sdk.service import stream_chat_completion_sdk
session = self._make_session()
success_result = self._make_result_message()
attempt_count = [0]
error_result = ResultMessage(
subtype="success",
result="Prompt is too long",
duration_ms=100,
duration_api_ms=0,
is_error=False,
num_turns=1,
session_id="test-session-id",
)
def _client_factory(*args, **kwargs):
attempt_count[0] += 1
async def _receive_error():
yield error_result
async def _receive_success():
yield success_result
client = MagicMock()
client._transport = MagicMock()
client._transport.write = AsyncMock()
client.query = AsyncMock()
if attempt_count[0] == 1:
client.receive_response = _receive_error
else:
client.receive_response = _receive_success
cm = AsyncMock()
cm.__aenter__.return_value = client
cm.__aexit__.return_value = None
return cm
original_transcript = _build_transcript(
[("user", "prior question"), ("assistant", "prior answer")]
)
compacted_transcript = _build_transcript(
[("user", "[summary]"), ("assistant", "summary reply")]
)
patches = _make_sdk_patches(
session,
original_transcript=original_transcript,
compacted_transcript=compacted_transcript,
client_side_effect=_client_factory,
)
events = []
with contextlib.ExitStack() as stack:
for target, kwargs in patches:
stack.enter_context(patch(target, **kwargs))
async for event in stream_chat_completion_sdk(
session_id="test-session-id",
message="hello",
is_user_message=True,
user_id="test-user",
session=session,
):
events.append(event)
assert attempt_count[0] == 2, (
f"Expected 2 SDK attempts (subtype='success' with 'Prompt is too long' "
f"result should trigger compaction retry), got {attempt_count[0]}"
)
errors = [e for e in events if isinstance(e, StreamError)]
assert not errors, f"Unexpected StreamError: {errors}"
assert any(isinstance(e, StreamStart) for e in events)
@pytest.mark.asyncio
async def test_assistant_message_error_content_prompt_too_long_triggers_compaction(
self,
):
"""AssistantMessage.error="invalid_request" with content "Prompt is too long".
The SDK returns error type "invalid_request" but puts the actual
rejection message ("Prompt is too long") in the content blocks.
The retry loop must detect this via content inspection (sdk_error
being set confirms it's an error message, not user content).
"""
import contextlib
from claude_agent_sdk import AssistantMessage, ResultMessage, TextBlock
from backend.copilot.response_model import StreamError, StreamStart
from backend.copilot.sdk.service import stream_chat_completion_sdk
session = self._make_session()
success_result = self._make_result_message()
attempt_count = [0]
def _client_factory(*args, **kwargs):
attempt_count[0] += 1
async def _receive_error():
# SDK returns invalid_request with "Prompt is too long" in content.
# ResultMessage.result is a non-PTL value ("done") to isolate
# the AssistantMessage content detection path exclusively.
yield AssistantMessage(
content=[TextBlock(text="Prompt is too long")],
model="<synthetic>",
error="invalid_request",
)
yield ResultMessage(
subtype="success",
result="done",
duration_ms=100,
duration_api_ms=0,
is_error=False,
num_turns=1,
session_id="test-session-id",
)
async def _receive_success():
yield success_result
client = MagicMock()
client._transport = MagicMock()
client._transport.write = AsyncMock()
client.query = AsyncMock()
if attempt_count[0] == 1:
client.receive_response = _receive_error
else:
client.receive_response = _receive_success
cm = AsyncMock()
cm.__aenter__.return_value = client
cm.__aexit__.return_value = None
return cm
original_transcript = _build_transcript(
[("user", "prior question"), ("assistant", "prior answer")]
)
compacted_transcript = _build_transcript(
[("user", "[summary]"), ("assistant", "summary reply")]
)
patches = _make_sdk_patches(
session,
original_transcript=original_transcript,
compacted_transcript=compacted_transcript,
client_side_effect=_client_factory,
)
events = []
with contextlib.ExitStack() as stack:
for target, kwargs in patches:
stack.enter_context(patch(target, **kwargs))
async for event in stream_chat_completion_sdk(
session_id="test-session-id",
message="hello",
is_user_message=True,
user_id="test-user",
session=session,
):
events.append(event)
assert attempt_count[0] == 2, (
f"Expected 2 SDK attempts (AssistantMessage error content 'Prompt is "
f"too long' should trigger compaction retry), got {attempt_count[0]}"
)
errors = [e for e in events if isinstance(e, StreamError)]
assert not errors, f"Unexpected StreamError: {errors}"
assert any(isinstance(e, StreamStart) for e in events)

View File

@@ -22,38 +22,6 @@ from .tool_adapter import (
logger = logging.getLogger(__name__)
# The SDK CLI uses "Task" in older versions and "Agent" in v2.x+.
# Shared across all sessions — used by security hooks for sub-agent detection.
_SUBAGENT_TOOLS: frozenset[str] = frozenset({"Task", "Agent"})
# Unicode ranges stripped by _sanitize():
# - BiDi overrides (U+202A-U+202E, U+2066-U+2069) can trick reviewers
# into misreading code/logs.
# - Zero-width characters (U+200B-U+200F, U+FEFF) can hide content.
_BIDI_AND_ZW_CHARS = set(
chr(c)
for r in (range(0x202A, 0x202F), range(0x2066, 0x206A), range(0x200B, 0x2010))
for c in r
) | {"\ufeff"}
def _sanitize(value: str, max_len: int = 200) -> str:
"""Strip control characters and truncate for safe logging.
Removes C0 (U+0000-U+001F), DEL (U+007F), C1 (U+0080-U+009F),
Unicode BiDi overrides, and zero-width characters to prevent
log injection and visual spoofing.
"""
cleaned = "".join(
c
for c in value
if c >= " "
and c != "\x7f"
and not ("\x80" <= c <= "\x9f")
and c not in _BIDI_AND_ZW_CHARS
)
return cleaned[:max_len]
def _deny(reason: str) -> dict[str, Any]:
"""Return a hook denial response."""
@@ -168,13 +136,11 @@ def create_security_hooks(
- PostToolUse: Log successful tool executions
- PostToolUseFailure: Log and handle failed tool executions
- PreCompact: Log context compaction events (SDK handles compaction automatically)
- SubagentStart: Log sub-agent lifecycle start
- SubagentStop: Log sub-agent lifecycle end
Args:
user_id: Current user ID for isolation validation
sdk_cwd: SDK working directory for workspace-scoped tool validation
max_subtasks: Maximum concurrent sub-agent spawns allowed per session
max_subtasks: Maximum concurrent Task (sub-agent) spawns allowed per session
on_compact: Callback invoked when SDK starts compacting context.
Receives the transcript_path from the hook input.
@@ -185,19 +151,9 @@ def create_security_hooks(
from claude_agent_sdk import HookMatcher
from claude_agent_sdk.types import HookContext, HookInput, SyncHookJSONOutput
# Per-session tracking for sub-agent concurrency.
# Per-session tracking for Task sub-agent concurrency.
# Set of tool_use_ids that consumed a slot — len() is the active count.
#
# LIMITATION: For background (async) agents the SDK returns the
# Agent/Task tool immediately with {isAsync: true}, which triggers
# PostToolUse and releases the slot while the agent is still running.
# SubagentStop fires later when the background process finishes but
# does not currently hold a slot. This means the concurrency limit
# only gates *launches*, not true concurrent execution. To fix this
# we would need to track background agent_ids separately and release
# in SubagentStop, but the SDK does not guarantee SubagentStop fires
# for every background agent (e.g. on session abort).
subagent_tool_use_ids: set[str] = set()
task_tool_use_ids: set[str] = set()
async def pre_tool_use_hook(
input_data: HookInput,
@@ -209,22 +165,29 @@ def create_security_hooks(
tool_name = cast(str, input_data.get("tool_name", ""))
tool_input = cast(dict[str, Any], input_data.get("tool_input", {}))
# Rate-limit sub-agent spawns per session.
# The SDK CLI renamed "Task" → "Agent" in v2.x; handle both.
if tool_name in _SUBAGENT_TOOLS:
# Background agents are allowed — the SDK returns immediately
# with {isAsync: true} and the model polls via TaskOutput.
# Still count them against the concurrency limit.
if len(subagent_tool_use_ids) >= max_subtasks:
# Rate-limit Task (sub-agent) spawns per session
if tool_name == "Task":
# Block background task execution first — denied calls
# should not consume a subtask slot.
if tool_input.get("run_in_background"):
logger.info(f"[SDK] Blocked background Task, user={user_id}")
return cast(
SyncHookJSONOutput,
_deny(
"Background task execution is not supported. "
"Run tasks in the foreground instead "
"(remove the run_in_background parameter)."
),
)
if len(task_tool_use_ids) >= max_subtasks:
logger.warning(
f"[SDK] Sub-agent limit reached ({max_subtasks}), "
f"user={user_id}"
f"[SDK] Task limit reached ({max_subtasks}), user={user_id}"
)
return cast(
SyncHookJSONOutput,
_deny(
f"Maximum {max_subtasks} concurrent sub-agents. "
"Wait for running sub-agents to finish, "
f"Maximum {max_subtasks} concurrent sub-tasks. "
"Wait for running sub-tasks to finish, "
"or continue in the main conversation."
),
)
@@ -245,20 +208,20 @@ def create_security_hooks(
if result:
return cast(SyncHookJSONOutput, result)
# Reserve the sub-agent slot only after all validations pass
if tool_name in _SUBAGENT_TOOLS and tool_use_id is not None:
subagent_tool_use_ids.add(tool_use_id)
# Reserve the Task slot only after all validations pass
if tool_name == "Task" and tool_use_id is not None:
task_tool_use_ids.add(tool_use_id)
logger.debug(f"[SDK] Tool start: {tool_name}, user={user_id}")
return cast(SyncHookJSONOutput, {})
def _release_subagent_slot(tool_name: str, tool_use_id: str | None) -> None:
"""Release a sub-agent concurrency slot if one was reserved."""
if tool_name in _SUBAGENT_TOOLS and tool_use_id in subagent_tool_use_ids:
subagent_tool_use_ids.discard(tool_use_id)
def _release_task_slot(tool_name: str, tool_use_id: str | None) -> None:
"""Release a Task concurrency slot if one was reserved."""
if tool_name == "Task" and tool_use_id in task_tool_use_ids:
task_tool_use_ids.discard(tool_use_id)
logger.info(
"[SDK] Sub-agent slot released, active=%d/%d, user=%s",
len(subagent_tool_use_ids),
"[SDK] Task slot released, active=%d/%d, user=%s",
len(task_tool_use_ids),
max_subtasks,
user_id,
)
@@ -278,14 +241,13 @@ def create_security_hooks(
_ = context
tool_name = cast(str, input_data.get("tool_name", ""))
_release_subagent_slot(tool_name, tool_use_id)
_release_task_slot(tool_name, tool_use_id)
is_builtin = not tool_name.startswith(MCP_TOOL_PREFIX)
safe_tool_use_id = _sanitize(str(tool_use_id or ""), max_len=12)
logger.info(
"[SDK] PostToolUse: %s (builtin=%s, tool_use_id=%s)",
tool_name,
is_builtin,
safe_tool_use_id,
(tool_use_id or "")[:12],
)
# Stash output for SDK built-in tools so the response adapter can
@@ -294,7 +256,7 @@ def create_security_hooks(
if is_builtin:
tool_response = input_data.get("tool_response")
if tool_response is not None:
resp_preview = _sanitize(str(tool_response), max_len=100)
resp_preview = str(tool_response)[:100]
logger.info(
"[SDK] Stashing builtin output for %s (%d chars): %s...",
tool_name,
@@ -318,17 +280,13 @@ def create_security_hooks(
"""Log failed tool executions for debugging."""
_ = context
tool_name = cast(str, input_data.get("tool_name", ""))
error = _sanitize(str(input_data.get("error", "Unknown error")))
safe_tool_use_id = _sanitize(str(tool_use_id or ""))
error = input_data.get("error", "Unknown error")
logger.warning(
"[SDK] Tool failed: %s, error=%s, user=%s, tool_use_id=%s",
tool_name,
error,
user_id,
safe_tool_use_id,
f"[SDK] Tool failed: {tool_name}, error={error}, "
f"user={user_id}, tool_use_id={tool_use_id}"
)
_release_subagent_slot(tool_name, tool_use_id)
_release_task_slot(tool_name, tool_use_id)
return cast(SyncHookJSONOutput, {})
@@ -343,17 +301,20 @@ def create_security_hooks(
This hook provides visibility into when compaction happens.
"""
_ = context, tool_use_id
trigger = _sanitize(str(input_data.get("trigger", "auto")), max_len=50)
trigger = input_data.get("trigger", "auto")
# Sanitize untrusted input: strip control chars for logging AND
# for the value passed downstream. read_compacted_entries()
# validates against _projects_base() as defence-in-depth, but
# sanitizing here prevents log injection and rejects obviously
# malformed paths early.
transcript_path = _sanitize(
str(input_data.get("transcript_path", "")), max_len=500
transcript_path = (
str(input_data.get("transcript_path", ""))
.replace("\n", "")
.replace("\r", "")
)
logger.info(
"[SDK] Context compaction triggered: %s, user=%s, transcript_path=%s",
"[SDK] Context compaction triggered: %s, user=%s, "
"transcript_path=%s",
trigger,
user_id,
transcript_path,
@@ -362,44 +323,6 @@ def create_security_hooks(
on_compact(transcript_path)
return cast(SyncHookJSONOutput, {})
async def subagent_start_hook(
input_data: HookInput,
tool_use_id: str | None,
context: HookContext,
) -> SyncHookJSONOutput:
"""Log when a sub-agent starts execution."""
_ = context, tool_use_id
agent_id = _sanitize(str(input_data.get("agent_id", "?")))
agent_type = _sanitize(str(input_data.get("agent_type", "?")))
logger.info(
"[SDK] SubagentStart: agent_id=%s, type=%s, user=%s",
agent_id,
agent_type,
user_id,
)
return cast(SyncHookJSONOutput, {})
async def subagent_stop_hook(
input_data: HookInput,
tool_use_id: str | None,
context: HookContext,
) -> SyncHookJSONOutput:
"""Log when a sub-agent stops."""
_ = context, tool_use_id
agent_id = _sanitize(str(input_data.get("agent_id", "?")))
agent_type = _sanitize(str(input_data.get("agent_type", "?")))
transcript = _sanitize(
str(input_data.get("agent_transcript_path", "")), max_len=500
)
logger.info(
"[SDK] SubagentStop: agent_id=%s, type=%s, user=%s, transcript=%s",
agent_id,
agent_type,
user_id,
transcript,
)
return cast(SyncHookJSONOutput, {})
hooks: dict[str, Any] = {
"PreToolUse": [HookMatcher(matcher="*", hooks=[pre_tool_use_hook])],
"PostToolUse": [HookMatcher(matcher="*", hooks=[post_tool_use_hook])],
@@ -407,8 +330,6 @@ def create_security_hooks(
HookMatcher(matcher="*", hooks=[post_tool_failure_hook])
],
"PreCompact": [HookMatcher(matcher="*", hooks=[pre_compact_hook])],
"SubagentStart": [HookMatcher(matcher="*", hooks=[subagent_start_hook])],
"SubagentStop": [HookMatcher(matcher="*", hooks=[subagent_stop_hook])],
}
return hooks

View File

@@ -5,18 +5,13 @@ They validate that the security hooks correctly block unauthorized paths,
tool access, and dangerous input patterns.
"""
import logging
import os
import pytest
from backend.copilot.context import _current_project_dir
from .security_hooks import (
_validate_tool_access,
_validate_user_isolation,
create_security_hooks,
)
from .security_hooks import _validate_tool_access, _validate_user_isolation
SDK_CWD = "/tmp/copilot-abc123"
@@ -137,20 +132,8 @@ def test_read_tool_results_allowed():
_current_project_dir.reset(token)
def test_read_tool_outputs_allowed():
"""tool-outputs/ paths should be allowed, same as tool-results/."""
home = os.path.expanduser("~")
path = f"{home}/.claude/projects/-tmp-copilot-abc123/a1b2c3d4-e5f6-7890-abcd-ef1234567890/tool-outputs/12345.txt"
token = _current_project_dir.set("-tmp-copilot-abc123")
try:
result = _validate_tool_access("Read", {"file_path": path}, sdk_cwd=SDK_CWD)
assert result == {}
finally:
_current_project_dir.reset(token)
def test_read_claude_projects_settings_json_denied():
"""SDK-internal artifacts like settings.json are NOT accessible — only tool-results/tool-outputs is."""
"""SDK-internal artifacts like settings.json are NOT accessible — only tool-results/ is."""
home = os.path.expanduser("~")
path = f"{home}/.claude/projects/-tmp-copilot-abc123/settings.json"
token = _current_project_dir.set("-tmp-copilot-abc123")
@@ -237,6 +220,8 @@ def test_bash_builtin_blocked_message_clarity():
@pytest.fixture()
def _hooks():
"""Create security hooks and return (pre, post, post_failure) handlers."""
from .security_hooks import create_security_hooks
hooks = create_security_hooks(user_id="u1", sdk_cwd=SDK_CWD, max_subtasks=2)
pre = hooks["PreToolUse"][0].hooks[0]
post = hooks["PostToolUse"][0].hooks[0]
@@ -246,15 +231,16 @@ def _hooks():
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_task_background_allowed(_hooks):
"""Task with run_in_background=true is allowed (SDK handles async lifecycle)."""
async def test_task_background_blocked(_hooks):
"""Task with run_in_background=true must be denied."""
pre, _, _ = _hooks
result = await pre(
{"tool_name": "Task", "tool_input": {"run_in_background": True, "prompt": "x"}},
tool_use_id="tu-bg-1",
tool_use_id=None,
context={},
)
assert not _is_denied(result)
assert _is_denied(result)
assert "foreground" in _reason(result).lower()
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@@ -368,303 +354,3 @@ async def test_task_slot_released_on_failure(_hooks):
context={},
)
assert not _is_denied(result)
# ---------------------------------------------------------------------------
# "Agent" tool name (SDK v2.x+ renamed "Task" → "Agent")
# ---------------------------------------------------------------------------
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_agent_background_allowed(_hooks):
"""Agent with run_in_background=true is allowed (SDK handles async lifecycle)."""
pre, _, _ = _hooks
result = await pre(
{
"tool_name": "Agent",
"tool_input": {"run_in_background": True, "prompt": "x"},
},
tool_use_id="tu-agent-bg-1",
context={},
)
assert not _is_denied(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_agent_foreground_allowed(_hooks):
"""Agent without run_in_background should be allowed."""
pre, _, _ = _hooks
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "do stuff"}},
tool_use_id="tu-agent-1",
context={},
)
assert not _is_denied(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_background_agent_counts_against_limit(_hooks):
"""Background agents still consume concurrency slots."""
pre, _, _ = _hooks
# Two background agents fill the limit
for i in range(2):
result = await pre(
{
"tool_name": "Agent",
"tool_input": {"run_in_background": True, "prompt": "bg"},
},
tool_use_id=f"tu-bglimit-{i}",
context={},
)
assert not _is_denied(result)
# Third (background or foreground) should be denied
result = await pre(
{
"tool_name": "Agent",
"tool_input": {"run_in_background": True, "prompt": "over"},
},
tool_use_id="tu-bglimit-2",
context={},
)
assert _is_denied(result)
assert "Maximum" in _reason(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_agent_limit_enforced(_hooks):
"""Agent spawns beyond max_subtasks should be denied."""
pre, _, _ = _hooks
# First two should pass
for i in range(2):
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "ok"}},
tool_use_id=f"tu-agent-limit-{i}",
context={},
)
assert not _is_denied(result)
# Third should be denied (limit=2)
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "over limit"}},
tool_use_id="tu-agent-limit-2",
context={},
)
assert _is_denied(result)
assert "Maximum" in _reason(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_agent_slot_released_on_completion(_hooks):
"""Completing an Agent should free a slot so new Agents can be spawned."""
pre, post, _ = _hooks
# Fill both slots
for i in range(2):
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "ok"}},
tool_use_id=f"tu-agent-comp-{i}",
context={},
)
assert not _is_denied(result)
# Third should be denied — at capacity
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "over"}},
tool_use_id="tu-agent-comp-2",
context={},
)
assert _is_denied(result)
# Complete first agent — frees a slot
await post(
{"tool_name": "Agent", "tool_input": {}},
tool_use_id="tu-agent-comp-0",
context={},
)
# Now a new Agent should be allowed
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "after release"}},
tool_use_id="tu-agent-comp-3",
context={},
)
assert not _is_denied(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_agent_slot_released_on_failure(_hooks):
"""A failed Agent should also free its concurrency slot."""
pre, _, post_failure = _hooks
# Fill both slots
for i in range(2):
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "ok"}},
tool_use_id=f"tu-agent-fail-{i}",
context={},
)
assert not _is_denied(result)
# At capacity
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "over"}},
tool_use_id="tu-agent-fail-2",
context={},
)
assert _is_denied(result)
# Fail first agent — should free a slot
await post_failure(
{"tool_name": "Agent", "tool_input": {}, "error": "something broke"},
tool_use_id="tu-agent-fail-0",
context={},
)
# New Agent should be allowed
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "after failure"}},
tool_use_id="tu-agent-fail-3",
context={},
)
assert not _is_denied(result)
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_mixed_task_agent_share_slots(_hooks):
"""Task and Agent share the same concurrency pool."""
pre, post, _ = _hooks
# Fill one slot with Task, one with Agent
result = await pre(
{"tool_name": "Task", "tool_input": {"prompt": "ok"}},
tool_use_id="tu-mix-task",
context={},
)
assert not _is_denied(result)
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "ok"}},
tool_use_id="tu-mix-agent",
context={},
)
assert not _is_denied(result)
# Third (either name) should be denied
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "over"}},
tool_use_id="tu-mix-over",
context={},
)
assert _is_denied(result)
# Release the Task slot
await post(
{"tool_name": "Task", "tool_input": {}},
tool_use_id="tu-mix-task",
context={},
)
# Now an Agent should be allowed
result = await pre(
{"tool_name": "Agent", "tool_input": {"prompt": "after task release"}},
tool_use_id="tu-mix-new",
context={},
)
assert not _is_denied(result)
# ---------------------------------------------------------------------------
# SubagentStart / SubagentStop hooks
# ---------------------------------------------------------------------------
@pytest.fixture()
def _subagent_hooks():
"""Create hooks and return (subagent_start, subagent_stop) handlers."""
hooks = create_security_hooks(user_id="u1", sdk_cwd=SDK_CWD, max_subtasks=2)
start = hooks["SubagentStart"][0].hooks[0]
stop = hooks["SubagentStop"][0].hooks[0]
return start, stop
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_subagent_start_hook_returns_empty(_subagent_hooks):
"""SubagentStart hook should return an empty dict (logging only)."""
start, _ = _subagent_hooks
result = await start(
{"agent_id": "sa-123", "agent_type": "research"},
tool_use_id=None,
context={},
)
assert result == {}
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_subagent_stop_hook_returns_empty(_subagent_hooks):
"""SubagentStop hook should return an empty dict (logging only)."""
_, stop = _subagent_hooks
result = await stop(
{
"agent_id": "sa-123",
"agent_type": "research",
"agent_transcript_path": "/tmp/transcript.txt",
},
tool_use_id=None,
context={},
)
assert result == {}
@pytest.mark.skipif(not _sdk_available(), reason="claude_agent_sdk not installed")
@pytest.mark.asyncio
async def test_subagent_hooks_sanitize_inputs(_subagent_hooks, caplog):
"""SubagentStart/Stop should sanitize control chars from inputs."""
start, stop = _subagent_hooks
# Inject control characters (C0, DEL, C1, BiDi overrides, zero-width)
# — hook should not raise AND logs must be clean
with caplog.at_level(logging.DEBUG, logger="backend.copilot.sdk.security_hooks"):
result = await start(
{
"agent_id": "sa\n-injected\r\x00\x7f",
"agent_type": "safe\x80_type\x9f\ttab",
},
tool_use_id=None,
context={},
)
assert result == {}
# Control chars must be stripped from the logged values
for record in caplog.records:
assert "\x00" not in record.message
assert "\r" not in record.message
assert "\n" not in record.message
assert "\x7f" not in record.message
assert "\x80" not in record.message
assert "\x9f" not in record.message
assert "safe_type" in caplog.text
caplog.clear()
with caplog.at_level(logging.DEBUG, logger="backend.copilot.sdk.security_hooks"):
result = await stop(
{
"agent_id": "sa\n-injected\x7f",
"agent_type": "type\r\x80\x9f",
"agent_transcript_path": "/tmp/\x00malicious\npath\u202a\u200b",
},
tool_use_id=None,
context={},
)
assert result == {}
for record in caplog.records:
assert "\x00" not in record.message
assert "\r" not in record.message
assert "\n" not in record.message
assert "\x7f" not in record.message
assert "\u202a" not in record.message
assert "\u200b" not in record.message
assert "/tmp/maliciouspath" in caplog.text

View File

@@ -59,14 +59,11 @@ from ..response_model import (
StreamBaseResponse,
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
StreamStatus,
StreamTextDelta,
StreamToolInputAvailable,
StreamToolInputStart,
StreamToolOutputAvailable,
StreamUsage,
)
@@ -80,13 +77,15 @@ from ..tools.e2b_sandbox import get_or_create_sandbox, pause_sandbox_direct
from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
from ..tracking import track_user_message
from .compaction import CompactionTracker, filter_compaction_messages
from .env import build_sdk_env # noqa: F401 — re-export for backward compat
from .response_adapter import SDKResponseAdapter
from .security_hooks import create_security_hooks
from .subscription import validate_subscription as _validate_claude_code_subscription
from .tool_adapter import (
cancel_pending_tool_tasks,
create_copilot_mcp_server,
get_copilot_tool_names,
get_sdk_disallowed_tools,
pre_launch_tool_call,
reset_stash_event,
reset_tool_failure_counters,
set_execution_context,
@@ -116,10 +115,9 @@ _MAX_STREAM_ATTEMPTS = 3
# Hard circuit breaker: abort the stream if the model sends this many
# consecutive tool calls with empty parameters (a sign of context
# saturation or serialization failure). The MCP wrapper now returns
# guidance on the first empty call, giving the model a chance to
# self-correct. The limit is generous to allow recovery attempts.
_EMPTY_TOOL_CALL_LIMIT = 5
# saturation or serialization failure). Empty input ({}) is never
# legitimate — even one is suspicious, three is conclusive.
_EMPTY_TOOL_CALL_LIMIT = 3
# User-facing error shown when the empty-tool-call circuit breaker trips.
_CIRCUIT_BREAKER_ERROR_MSG = (
@@ -187,24 +185,6 @@ def _is_prompt_too_long(err: BaseException) -> bool:
return False
def _is_sdk_disconnect_error(exc: BaseException) -> bool:
"""Return True if *exc* is an expected SDK cleanup error from client disconnect.
Two known patterns occur when ``GeneratorExit`` tears down the async
generator and the SDK's ``__aexit__`` runs in a different context/task:
* ``RuntimeError``: cancel scope exited in wrong task (anyio)
* ``ValueError``: ContextVar token created in a different Context (OTEL)
These are suppressed to avoid polluting Sentry with non-actionable noise.
"""
if isinstance(exc, RuntimeError) and "cancel scope" in str(exc):
return True
if isinstance(exc, ValueError) and "was created in a different Context" in str(exc):
return True
return False
def _is_tool_only_message(sdk_msg: object) -> bool:
"""Return True if *sdk_msg* is an AssistantMessage containing only ToolUseBlocks.
@@ -429,63 +409,6 @@ _HEARTBEAT_INTERVAL = 10.0 # seconds
STREAM_LOCK_PREFIX = "copilot:stream:lock:"
async def _safe_close_sdk_client(
sdk_client: ClaudeSDKClient,
log_prefix: str,
) -> None:
"""Close a ClaudeSDKClient, suppressing errors from client disconnect.
When the SSE client disconnects mid-stream, ``GeneratorExit`` propagates
through the async generator stack and causes ``ClaudeSDKClient.__aexit__``
to run in a different async context or task than where the client was
opened. This triggers two known error classes:
* ``ValueError``: ``<Token var=<ContextVar name='current_context'>>
was created in a different Context`` — OpenTelemetry's
``context.detach()`` fails because the OTEL context token was
created in the original generator coroutine but detach runs in
the GC / cleanup coroutine (Sentry: AUTOGPT-SERVER-8BT).
* ``RuntimeError``: ``Attempted to exit cancel scope in a different
task than it was entered in`` — anyio's ``TaskGroup.__aexit__``
detects that the cancel scope was entered in one task but is
being exited in another (Sentry: AUTOGPT-SERVER-8BW).
Both are harmless — the TCP connection is already dead and no
resources leak. Logging them at ``debug`` level keeps observability
without polluting Sentry.
"""
try:
await sdk_client.__aexit__(None, None, None)
except (ValueError, RuntimeError) as exc:
if _is_sdk_disconnect_error(exc):
# Expected during client disconnect — suppress to avoid Sentry noise.
logger.debug(
"%s SDK client cleanup error suppressed (client disconnect): %s: %s",
log_prefix,
type(exc).__name__,
exc,
)
else:
raise
except GeneratorExit:
# GeneratorExit can propagate through __aexit__ — suppress it here
# since the generator is already being torn down.
logger.debug(
"%s SDK client cleanup GeneratorExit suppressed (client disconnect)",
log_prefix,
)
except Exception:
# Unexpected cleanup error — log at error level so Sentry captures it
# (via its logging integration), but don't propagate since we're in
# teardown and the caller cannot meaningfully handle this.
logger.error(
"%s Unexpected SDK client cleanup error",
log_prefix,
exc_info=True,
)
async def _iter_sdk_messages(
client: ClaudeSDKClient,
) -> AsyncGenerator[Any, None]:
@@ -569,6 +492,60 @@ def _resolve_sdk_model() -> str | None:
return model
def _build_sdk_env(
session_id: str | None = None,
user_id: str | None = None,
) -> dict[str, str]:
"""Build env vars for the SDK CLI subprocess.
Three modes (checked in order):
1. **Subscription** — clears all keys; CLI uses `claude login` auth.
2. **Direct Anthropic** — returns `{}`; subprocess inherits
`ANTHROPIC_API_KEY` from the parent environment.
3. **OpenRouter** (default) — overrides base URL and auth token to
route through the proxy, with Langfuse trace headers.
"""
# --- Mode 1: Claude Code subscription auth ---
if config.use_claude_code_subscription:
_validate_claude_code_subscription()
return {
"ANTHROPIC_API_KEY": "",
"ANTHROPIC_AUTH_TOKEN": "",
"ANTHROPIC_BASE_URL": "",
}
# --- Mode 2: Direct Anthropic (no proxy hop) ---
# `openrouter_active` checks the flag *and* credential presence.
if not config.openrouter_active:
return {}
# --- Mode 3: OpenRouter proxy ---
# Strip /v1 suffix — SDK expects the base URL without a version path.
base = (config.base_url or "").rstrip("/")
if base.endswith("/v1"):
base = base[:-3]
env: dict[str, str] = {
"ANTHROPIC_BASE_URL": base,
"ANTHROPIC_AUTH_TOKEN": config.api_key or "",
"ANTHROPIC_API_KEY": "", # force CLI to use AUTH_TOKEN
}
# Inject broadcast headers so OpenRouter forwards traces to Langfuse.
def _safe(v: str) -> str:
"""Sanitise a header value: strip newlines/whitespace and cap length."""
return v.replace("\r", "").replace("\n", "").strip()[:128]
parts = []
if session_id:
parts.append(f"x-session-id: {_safe(session_id)}")
if user_id:
parts.append(f"x-user-id: {_safe(user_id)}")
if parts:
env["ANTHROPIC_CUSTOM_HEADERS"] = "\n".join(parts)
return env
def _make_sdk_cwd(session_id: str) -> str:
"""Create a safe, session-specific working directory path.
@@ -618,9 +595,7 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
"""Convert SDK content blocks to transcript format.
Handles TextBlock, ToolUseBlock, ToolResultBlock, and ThinkingBlock.
Raw dicts (e.g. ``redacted_thinking`` blocks that the SDK may not have
a typed class for) are passed through verbatim to preserve them in the
transcript. Unknown typed block objects are logged and skipped.
Unknown block types are logged and skipped.
"""
result: list[dict[str, Any]] = []
for block in blocks or []:
@@ -652,9 +627,6 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
"signature": block.signature,
}
)
elif isinstance(block, dict) and "type" in block:
# Preserve raw dict blocks (e.g. redacted_thinking) verbatim.
result.append(block)
else:
logger.warning(
f"[SDK] Unknown content block type: {type(block).__name__}. "
@@ -748,11 +720,15 @@ def _format_conversation_context(messages: list[ChatMessage]) -> str | None:
elif msg.role == "assistant":
if msg.content:
lines.append(f"You responded: {msg.content}")
# Omit tool_calls — any text representation gets mimicked
# by the model. Tool results below provide the context.
if msg.tool_calls:
for tc in msg.tool_calls:
func = tc.get("function", {})
tool_name = func.get("name", "unknown")
tool_args = func.get("arguments", "")
lines.append(f"You called tool: {tool_name}({tool_args})")
elif msg.role == "tool":
content = msg.content or ""
lines.append(f"Tool output: {content[:500]}")
lines.append(f"Tool result: {content}")
if not lines:
return None
@@ -1212,25 +1188,7 @@ async def _run_stream_attempt(
consecutive_empty_tool_calls = 0
# --- Intermediate persistence tracking ---
# Flush session messages to DB periodically so page reloads show progress
# during long-running turns (see incident d2f7cba3: 82-min turn lost on refresh).
_last_flush_time = time.monotonic()
_msgs_since_flush = 0
_FLUSH_INTERVAL_SECONDS = 30.0
_FLUSH_MESSAGE_THRESHOLD = 10
# Use manual __aenter__/__aexit__ instead of ``async with`` so we can
# suppress SDK cleanup errors that occur when the SSE client disconnects
# mid-stream. GeneratorExit causes the SDK's ``__aexit__`` to run in a
# different async context/task than where the client was opened, which
# triggers:
# - ValueError: ContextVar token mismatch (AUTOGPT-SERVER-8BT)
# - RuntimeError: cancel scope in wrong task (AUTOGPT-SERVER-8BW)
# Both are harmless — the TCP connection is already dead.
sdk_client = ClaudeSDKClient(options=state.options)
client = await sdk_client.__aenter__()
try:
async with ClaudeSDKClient(options=state.options) as client:
logger.info(
"%s Sending query — resume=%s, total_msgs=%d, "
"query_len=%d, attached_files=%d, image_blocks=%d",
@@ -1306,27 +1264,6 @@ async def _run_stream_attempt(
error_preview,
)
# Intercept prompt-too-long errors surfaced as
# AssistantMessage.error (not as a Python exception).
# Re-raise so the outer retry loop can compact the
# transcript and retry with reduced context.
# Check both error_text and error_preview: sdk_error
# being set confirms this is an error message (not user
# content), so checking content is safe. The actual
# error description (e.g. "Prompt is too long") may be
# in the content, not the error type field
# (e.g. error="invalid_request", content="Prompt is
# too long").
if _is_prompt_too_long(Exception(error_text)) or _is_prompt_too_long(
Exception(error_preview)
):
logger.warning(
"%s Prompt-too-long detected via AssistantMessage "
"error — raising for retry",
ctx.log_prefix,
)
raise RuntimeError("Prompt is too long")
# Intercept transient API errors (socket closed,
# ECONNRESET) — replace the raw message with a
# user-friendly error text and use the retryable
@@ -1354,17 +1291,28 @@ async def _run_stream_attempt(
ended_with_stream_error = True
break
# Determine if the message is a tool-only batch (all content
# Parallel tool execution: pre-launch every ToolUseBlock as an
# asyncio.Task the moment its AssistantMessage arrives. The SDK
# sends one AssistantMessage per tool call when issuing parallel
# calls, so each message is pre-launched independently. The MCP
# handlers will await the already-running task instead of executing
# fresh, making all concurrent tool calls run in parallel.
#
# Also determine if the message is a tool-only batch (all content
# items are ToolUseBlocks) — such messages have no text output yet,
# so we skip the wait_for_stash flush below.
#
# Note: parallel execution of tools is handled natively by the
# SDK CLI via readOnlyHint annotations on tool definitions.
is_tool_only = False
if isinstance(sdk_msg, AssistantMessage) and sdk_msg.content:
is_tool_only = all(
isinstance(item, ToolUseBlock) for item in sdk_msg.content
)
is_tool_only = True
# NOTE: Pre-launches are sequential (each await completes
# file-ref expansion before the next starts). This is fine
# since expansion is typically sub-ms; a future optimisation
# could gather all pre-launches concurrently.
for tool_use in sdk_msg.content:
if isinstance(tool_use, ToolUseBlock):
await pre_launch_tool_call(tool_use.name, tool_use.input)
else:
is_tool_only = False
# Race-condition fix: SDK hooks (PostToolUse) are
# executed asynchronously via start_soon() — the next
@@ -1421,16 +1369,6 @@ async def _run_stream_attempt(
sdk_msg.result or "(no error message provided)",
)
# Check for prompt-too-long regardless of subtype — the
# SDK may return subtype="success" with result="Prompt is
# too long" when the CLI rejects the prompt before calling
# the API (cost_usd=0, no tokens consumed). If we only
# check the "error" subtype path, the stream appears to
# complete normally, the synthetic error text is stored
# in the transcript, and the session grows without bound.
if _is_prompt_too_long(RuntimeError(sdk_msg.result or "")):
raise RuntimeError("Prompt is too long")
# Capture token usage from ResultMessage.
# Anthropic reports cached tokens separately:
# input_tokens = uncached only
@@ -1462,23 +1400,6 @@ async def _run_stream_attempt(
# Emit compaction end if SDK finished compacting.
# Sync TranscriptBuilder with the CLI's active context.
compact_result = await ctx.compaction.emit_end_if_ready(ctx.session)
if compact_result.events:
# Compaction events end with StreamFinishStep, which maps to
# Vercel AI SDK's "finish-step" — that clears activeTextParts.
# Close any open text block BEFORE the compaction events so
# the text-end arrives before finish-step, preventing
# "text-end for missing text part" errors on the frontend.
pre_close: list[StreamBaseResponse] = []
state.adapter._end_text_if_open(pre_close)
# Compaction events bypass the adapter, so sync step state
# when a StreamFinishStep is present — otherwise the adapter
# will skip StreamStartStep on the next AssistantMessage.
if any(
isinstance(ev, StreamFinishStep) for ev in compact_result.events
):
state.adapter.step_open = False
for r in pre_close:
yield r
for ev in compact_result.events:
yield ev
entries_replaced = False
@@ -1525,38 +1446,8 @@ async def _run_stream_attempt(
model=sdk_msg.model,
)
# --- Intermediate persistence ---
# Flush session messages to DB periodically so page reloads
# show progress during long-running turns.
_msgs_since_flush += 1
now = time.monotonic()
if (
_msgs_since_flush >= _FLUSH_MESSAGE_THRESHOLD
or (now - _last_flush_time) >= _FLUSH_INTERVAL_SECONDS
):
try:
await asyncio.shield(upsert_chat_session(ctx.session))
logger.debug(
"%s Intermediate flush: %d messages "
"(msgs_since=%d, elapsed=%.1fs)",
ctx.log_prefix,
len(ctx.session.messages),
_msgs_since_flush,
now - _last_flush_time,
)
except Exception as flush_err:
logger.warning(
"%s Intermediate flush failed: %s",
ctx.log_prefix,
flush_err,
)
_last_flush_time = now
_msgs_since_flush = 0
if acc.stream_completed:
break
finally:
await _safe_close_sdk_client(sdk_client, ctx.log_prefix)
# --- Post-stream processing (only on success) ---
if state.adapter.has_unresolved_tool_calls:
@@ -1884,10 +1775,7 @@ async def stream_chat_completion_sdk(
)
# Fail fast when no API credentials are available at all.
# sdk_cwd routes the CLI's temp dir into the per-session workspace
# so sub-agent output files land inside sdk_cwd (see build_sdk_env).
sdk_env = build_sdk_env(session_id=session_id, user_id=user_id, sdk_cwd=sdk_cwd)
sdk_env = _build_sdk_env(session_id=session_id, user_id=user_id)
if not config.api_key and not config.use_claude_code_subscription:
raise RuntimeError(
"No API key configured. Set OPEN_ROUTER_API_KEY, "
@@ -2082,22 +1970,13 @@ async def stream_chat_completion_sdk(
try:
async for event in _run_stream_attempt(stream_ctx, state):
if not isinstance(
event,
(
StreamHeartbeat,
# Compaction UI events are cosmetic and must not
# block retry — they're emitted before the SDK
# query on compacted attempts.
StreamStartStep,
StreamFinishStep,
StreamToolInputStart,
StreamToolInputAvailable,
StreamToolOutputAvailable,
),
):
if not isinstance(event, StreamHeartbeat):
events_yielded += 1
yield event
# Cancel any pre-launched tasks that were never dispatched
# by the SDK (e.g. edge-case SDK behaviour changes). Symmetric
# with the three error-path await cancel_pending_tool_tasks() calls.
await cancel_pending_tool_tasks()
break # Stream completed — exit retry loop
except asyncio.CancelledError:
logger.warning(
@@ -2106,6 +1985,9 @@ async def stream_chat_completion_sdk(
attempt + 1,
_MAX_STREAM_ATTEMPTS,
)
# Cancel any pre-launched tasks so they don't continue executing
# against a rolled-back or abandoned session.
await cancel_pending_tool_tasks()
raise
except _HandledStreamError as exc:
# _run_stream_attempt already yielded a StreamError and
@@ -2137,6 +2019,8 @@ async def stream_chat_completion_sdk(
retryable=True,
)
ended_with_stream_error = True
# Cancel any pre-launched tasks from the failed attempt.
await cancel_pending_tool_tasks()
break
except Exception as e:
stream_err = e
@@ -2153,6 +2037,9 @@ async def stream_chat_completion_sdk(
exc_info=True,
)
session.messages = session.messages[:pre_attempt_msg_count]
# Cancel any pre-launched tasks from the failed attempt so they
# don't continue executing against the rolled-back session.
await cancel_pending_tool_tasks()
if events_yielded > 0:
# Events were already sent to the frontend and cannot be
# unsent. Retrying would produce duplicate/inconsistent
@@ -2282,16 +2169,9 @@ async def stream_chat_completion_sdk(
error_msg = "Operation cancelled"
else:
error_msg = str(e) or type(e).__name__
# SDK cleanup errors are expected during client disconnect —
# log as warning rather than error to reduce Sentry noise.
# These are normally caught by _safe_close_sdk_client but
# can escape in edge cases (e.g. GeneratorExit timing).
if _is_sdk_disconnect_error(e):
logger.warning(
"%s SDK cleanup error (client disconnect): %s",
log_prefix,
error_msg,
)
# SDK cleanup RuntimeError is expected during cancellation, log as warning
if isinstance(e, RuntimeError) and "cancel scope" in str(e):
logger.warning("%s SDK cleanup error: %s", log_prefix, error_msg)
else:
logger.error("%s Error: %s", log_prefix, error_msg, exc_info=True)
@@ -2313,11 +2193,10 @@ async def stream_chat_completion_sdk(
)
# Yield StreamError for immediate feedback (only for non-cancellation errors)
# Skip for CancelledError and SDK disconnect cleanup errors — these
# are not actionable by the user and the SSE connection is already dead.
is_cancellation = isinstance(
e, asyncio.CancelledError
) or _is_sdk_disconnect_error(e)
# Skip for CancelledError and RuntimeError cleanup issues (both are cancellations)
is_cancellation = isinstance(e, asyncio.CancelledError) or (
isinstance(e, RuntimeError) and "cancel scope" in str(e)
)
if not is_cancellation:
yield StreamError(errorText=display_msg, code=code)

View File

@@ -8,12 +8,7 @@ from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from .service import (
_is_sdk_disconnect_error,
_prepare_file_attachments,
_resolve_sdk_model,
_safe_close_sdk_client,
)
from .service import _prepare_file_attachments, _resolve_sdk_model
@dataclass
@@ -504,111 +499,3 @@ class TestResolveSdkModel:
)
monkeypatch.setattr("backend.copilot.sdk.service.config", cfg)
assert _resolve_sdk_model() == "claude-opus-4-6"
# ---------------------------------------------------------------------------
# _is_sdk_disconnect_error — classify client disconnect cleanup errors
# ---------------------------------------------------------------------------
class TestIsSdkDisconnectError:
"""Tests for _is_sdk_disconnect_error — identifies expected SDK cleanup errors."""
def test_cancel_scope_runtime_error(self):
"""RuntimeError about cancel scope in wrong task is a disconnect error."""
exc = RuntimeError(
"Attempted to exit cancel scope in a different task than it was entered in"
)
assert _is_sdk_disconnect_error(exc) is True
def test_context_var_value_error(self):
"""ValueError about ContextVar token mismatch is a disconnect error."""
exc = ValueError(
"<Token var=<ContextVar name='current_context'>> "
"was created in a different Context"
)
assert _is_sdk_disconnect_error(exc) is True
def test_unrelated_runtime_error(self):
"""Unrelated RuntimeError should NOT be classified as disconnect error."""
exc = RuntimeError("something else went wrong")
assert _is_sdk_disconnect_error(exc) is False
def test_unrelated_value_error(self):
"""Unrelated ValueError should NOT be classified as disconnect error."""
exc = ValueError("invalid argument")
assert _is_sdk_disconnect_error(exc) is False
def test_other_exception_types(self):
"""Non-RuntimeError/ValueError should NOT be classified as disconnect error."""
assert _is_sdk_disconnect_error(TypeError("bad type")) is False
assert _is_sdk_disconnect_error(OSError("network down")) is False
assert _is_sdk_disconnect_error(asyncio.CancelledError()) is False
# ---------------------------------------------------------------------------
# _safe_close_sdk_client — suppress cleanup errors during disconnect
# ---------------------------------------------------------------------------
class TestSafeCloseSdkClient:
"""Tests for _safe_close_sdk_client — suppresses expected SDK cleanup errors."""
@pytest.mark.asyncio
async def test_clean_exit(self):
"""Normal __aexit__ (no error) should succeed silently."""
client = AsyncMock()
client.__aexit__ = AsyncMock(return_value=None)
await _safe_close_sdk_client(client, "[test]")
client.__aexit__.assert_awaited_once_with(None, None, None)
@pytest.mark.asyncio
async def test_cancel_scope_runtime_error_suppressed(self):
"""RuntimeError from cancel scope mismatch should be suppressed."""
client = AsyncMock()
client.__aexit__ = AsyncMock(
side_effect=RuntimeError(
"Attempted to exit cancel scope in a different task"
)
)
# Should NOT raise
await _safe_close_sdk_client(client, "[test]")
@pytest.mark.asyncio
async def test_context_var_value_error_suppressed(self):
"""ValueError from ContextVar token mismatch should be suppressed."""
client = AsyncMock()
client.__aexit__ = AsyncMock(
side_effect=ValueError(
"<Token var=<ContextVar name='current_context'>> "
"was created in a different Context"
)
)
# Should NOT raise
await _safe_close_sdk_client(client, "[test]")
@pytest.mark.asyncio
async def test_unexpected_exception_suppressed_with_error_log(self):
"""Unexpected exceptions should be caught (not propagated) but logged at error."""
client = AsyncMock()
client.__aexit__ = AsyncMock(side_effect=OSError("unexpected"))
# Should NOT raise — unexpected errors are also suppressed to
# avoid crashing the generator during teardown. Logged at error
# level so Sentry captures them via its logging integration.
await _safe_close_sdk_client(client, "[test]")
@pytest.mark.asyncio
async def test_unrelated_runtime_error_propagates(self):
"""Non-cancel-scope RuntimeError should propagate (not suppressed)."""
client = AsyncMock()
client.__aexit__ = AsyncMock(side_effect=RuntimeError("something unrelated"))
with pytest.raises(RuntimeError, match="something unrelated"):
await _safe_close_sdk_client(client, "[test]")
@pytest.mark.asyncio
async def test_unrelated_value_error_propagates(self):
"""Non-disconnect ValueError should propagate (not suppressed)."""
client = AsyncMock()
client.__aexit__ = AsyncMock(side_effect=ValueError("invalid argument"))
with pytest.raises(ValueError, match="invalid argument"):
await _safe_close_sdk_client(client, "[test]")

View File

@@ -1,823 +0,0 @@
"""Tests for thinking/redacted_thinking block preservation.
Validates the fix for the Anthropic API error:
"thinking or redacted_thinking blocks in the latest assistant message
cannot be modified. These blocks must remain as they were in the
original response."
The API requires that thinking blocks in the LAST assistant message are
preserved value-identical. Older assistant messages may have thinking blocks
stripped entirely. This test suite covers:
1. _flatten_assistant_content — strips thinking from older messages
2. compact_transcript — preserves last assistant's thinking blocks
3. response_adapter — handles ThinkingBlock without error
4. _format_sdk_content_blocks — preserves redacted_thinking blocks
"""
from __future__ import annotations
from unittest.mock import AsyncMock, patch
import pytest
from claude_agent_sdk import AssistantMessage, TextBlock, ThinkingBlock
from backend.copilot.response_model import (
StreamStartStep,
StreamTextDelta,
StreamTextStart,
)
from backend.util import json
from .conftest import build_structured_transcript
from .response_adapter import SDKResponseAdapter
from .service import _format_sdk_content_blocks
from .transcript import (
_find_last_assistant_entry,
_flatten_assistant_content,
_messages_to_transcript,
_rechain_tail,
_transcript_to_messages,
compact_transcript,
validate_transcript,
)
# ---------------------------------------------------------------------------
# Fixtures: realistic thinking block content
# ---------------------------------------------------------------------------
THINKING_BLOCK = {
"type": "thinking",
"thinking": "Let me analyze the user's request carefully...",
"signature": "ErUBCkYIAxgCIkD0V2MsRXPkuGolGexaW9V1kluijxXGF",
}
REDACTED_THINKING_BLOCK = {
"type": "redacted_thinking",
"data": "EmwKAhgBEgy2VEE8PJaS2oLJCPkaT...",
}
def _make_thinking_transcript() -> str:
"""Build a transcript with thinking blocks in multiple assistant turns.
Layout:
User 1 → Assistant 1 (thinking + text + tool_use)
User 2 (tool_result) → Assistant 2 (thinking + text)
User 3 → Assistant 3 (thinking + redacted_thinking + text) ← LAST
"""
return build_structured_transcript(
[
("user", "What files are in this project?"),
(
"assistant",
[
{
"type": "thinking",
"thinking": "I should list the files.",
"signature": "sig_old_1",
},
{"type": "text", "text": "Let me check the files."},
{
"type": "tool_use",
"id": "tu1",
"name": "list_files",
"input": {"path": "/"},
},
],
),
("user", "Here are the files: a.py, b.py"),
(
"assistant",
[
{
"type": "thinking",
"thinking": "Good, I see two Python files.",
"signature": "sig_old_2",
},
{"type": "text", "text": "I found a.py and b.py."},
],
),
("user", "Tell me about a.py"),
(
"assistant",
[
THINKING_BLOCK,
REDACTED_THINKING_BLOCK,
{"type": "text", "text": "a.py contains the main entry point."},
],
),
]
)
def _last_assistant_content(transcript_jsonl: str) -> list[dict] | None:
"""Extract the content blocks of the last assistant entry in a transcript."""
last_content = None
for line in transcript_jsonl.strip().split("\n"):
entry = json.loads(line)
msg = entry.get("message", {})
if msg.get("role") == "assistant":
last_content = msg.get("content")
return last_content
# ---------------------------------------------------------------------------
# _find_last_assistant_entry — unit tests
# ---------------------------------------------------------------------------
class TestFindLastAssistantEntry:
def test_splits_at_last_assistant(self):
"""Prefix contains everything before last assistant; tail starts at it."""
transcript = build_structured_transcript(
[
("user", "Hello"),
("assistant", [{"type": "text", "text": "Hi"}]),
("user", "More"),
("assistant", [{"type": "text", "text": "Details"}]),
]
)
prefix, tail = _find_last_assistant_entry(transcript)
# 3 entries in prefix (user, assistant, user), 1 in tail (last assistant)
assert len(prefix) == 3
assert len(tail) == 1
def test_no_assistant_returns_all_in_prefix(self):
"""When there's no assistant, all lines are in prefix, tail is empty."""
transcript = build_structured_transcript(
[("user", "Hello"), ("user", "Another question")]
)
prefix, tail = _find_last_assistant_entry(transcript)
assert len(prefix) == 2
assert tail == []
def test_assistant_at_index_zero(self):
"""When assistant is the first entry, prefix is empty."""
transcript = build_structured_transcript(
[("assistant", [{"type": "text", "text": "Start"}])]
)
prefix, tail = _find_last_assistant_entry(transcript)
assert prefix == []
assert len(tail) == 1
def test_trailing_user_included_in_tail(self):
"""User message after last assistant is part of the tail."""
transcript = build_structured_transcript(
[
("user", "Q1"),
("assistant", [{"type": "text", "text": "A1"}]),
("user", "Q2"),
]
)
prefix, tail = _find_last_assistant_entry(transcript)
assert len(prefix) == 1 # first user
assert len(tail) == 2 # last assistant + trailing user
def test_multi_entry_turn_fully_preserved(self):
"""An assistant turn spanning multiple JSONL entries (same message.id)
must be entirely in the tail, not split across prefix and tail."""
# Build manually because build_structured_transcript generates unique ids
lines = [
json.dumps(
{
"type": "user",
"uuid": "u1",
"parentUuid": "",
"message": {"role": "user", "content": "Hello"},
}
),
json.dumps(
{
"type": "assistant",
"uuid": "a1-think",
"parentUuid": "u1",
"message": {
"role": "assistant",
"id": "msg_same_turn",
"type": "message",
"content": [THINKING_BLOCK],
"stop_reason": None,
"stop_sequence": None,
},
}
),
json.dumps(
{
"type": "assistant",
"uuid": "a1-tool",
"parentUuid": "u1",
"message": {
"role": "assistant",
"id": "msg_same_turn",
"type": "message",
"content": [
{
"type": "tool_use",
"id": "tu1",
"name": "Bash",
"input": {},
},
],
"stop_reason": "tool_use",
"stop_sequence": None,
},
}
),
]
transcript = "\n".join(lines) + "\n"
prefix, tail = _find_last_assistant_entry(transcript)
# Both assistant entries share msg_same_turn → both in tail
assert len(prefix) == 1 # only the user entry
assert len(tail) == 2 # both assistant entries (thinking + tool_use)
def test_no_message_id_preserves_last_assistant(self):
"""When the last assistant entry has no message.id, it should still
be preserved in the tail (fail closed) rather than being compressed."""
lines = [
json.dumps(
{
"type": "user",
"uuid": "u1",
"parentUuid": "",
"message": {"role": "user", "content": "Hello"},
}
),
json.dumps(
{
"type": "assistant",
"uuid": "a1",
"parentUuid": "u1",
"message": {
"role": "assistant",
"content": [THINKING_BLOCK, {"type": "text", "text": "Hi"}],
},
}
),
]
transcript = "\n".join(lines) + "\n"
prefix, tail = _find_last_assistant_entry(transcript)
assert len(prefix) == 1 # user entry
assert len(tail) == 1 # assistant entry preserved
# ---------------------------------------------------------------------------
# _rechain_tail — UUID chain patching
# ---------------------------------------------------------------------------
class TestRechainTail:
def test_patches_first_entry_parentuuid(self):
"""First tail entry's parentUuid should point to last prefix uuid."""
prefix = _messages_to_transcript(
[
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi"},
]
)
# Get the last uuid from the prefix
last_prefix_uuid = None
for line in prefix.strip().split("\n"):
entry = json.loads(line)
last_prefix_uuid = entry.get("uuid")
tail_lines = [
json.dumps(
{
"type": "assistant",
"uuid": "tail-a1",
"parentUuid": "old-parent",
"message": {
"role": "assistant",
"content": [{"type": "text", "text": "Tail msg"}],
},
}
)
]
result = _rechain_tail(prefix, tail_lines)
entry = json.loads(result.strip())
assert entry["parentUuid"] == last_prefix_uuid
assert entry["uuid"] == "tail-a1" # uuid preserved
def test_chains_multiple_tail_entries(self):
"""Subsequent tail entries chain to each other."""
prefix = _messages_to_transcript([{"role": "user", "content": "Hi"}])
tail_lines = [
json.dumps(
{
"type": "assistant",
"uuid": "t1",
"parentUuid": "old1",
"message": {"role": "assistant", "content": []},
}
),
json.dumps(
{
"type": "user",
"uuid": "t2",
"parentUuid": "old2",
"message": {"role": "user", "content": "Follow-up"},
}
),
]
result = _rechain_tail(prefix, tail_lines)
entries = [json.loads(ln) for ln in result.strip().split("\n")]
assert len(entries) == 2
# Second entry's parentUuid should be first entry's uuid
assert entries[1]["parentUuid"] == "t1"
def test_empty_tail_returns_empty(self):
"""No tail entries → empty string."""
prefix = _messages_to_transcript([{"role": "user", "content": "Hi"}])
assert _rechain_tail(prefix, []) == ""
def test_preserves_message_content_verbatim(self):
"""Tail message content (including thinking blocks) must not be modified."""
prefix = _messages_to_transcript([{"role": "user", "content": "Hi"}])
original_content = [
THINKING_BLOCK,
REDACTED_THINKING_BLOCK,
{"type": "text", "text": "Response"},
]
tail_lines = [
json.dumps(
{
"type": "assistant",
"uuid": "t1",
"parentUuid": "old",
"message": {
"role": "assistant",
"content": original_content,
},
}
)
]
result = _rechain_tail(prefix, tail_lines)
entry = json.loads(result.strip())
assert entry["message"]["content"] == original_content
# ---------------------------------------------------------------------------
# _flatten_assistant_content — thinking blocks
# ---------------------------------------------------------------------------
class TestFlattenThinkingBlocks:
def test_thinking_blocks_are_stripped(self):
"""Thinking blocks should not appear in flattened text for compression."""
blocks = [
{"type": "thinking", "thinking": "secret thoughts", "signature": "sig"},
{"type": "text", "text": "Hello user"},
]
result = _flatten_assistant_content(blocks)
assert "secret thoughts" not in result
assert "Hello user" in result
def test_redacted_thinking_blocks_are_stripped(self):
"""Redacted thinking blocks should not appear in flattened text."""
blocks = [
{"type": "redacted_thinking", "data": "encrypted_data"},
{"type": "text", "text": "Response text"},
]
result = _flatten_assistant_content(blocks)
assert "encrypted_data" not in result
assert "Response text" in result
def test_thinking_only_message_flattens_to_empty(self):
"""A message with only thinking blocks flattens to empty string."""
blocks = [
{"type": "thinking", "thinking": "just thinking...", "signature": "sig"},
]
result = _flatten_assistant_content(blocks)
assert result == ""
def test_mixed_thinking_text_tool(self):
"""Mixed blocks: only text survives flattening; thinking and tool_use dropped."""
blocks = [
{"type": "thinking", "thinking": "hmm", "signature": "sig"},
{"type": "redacted_thinking", "data": "xyz"},
{"type": "text", "text": "I'll read the file."},
{"type": "tool_use", "name": "Read", "input": {"path": "/x"}},
]
result = _flatten_assistant_content(blocks)
assert "hmm" not in result
assert "xyz" not in result
assert "I'll read the file." in result
# tool_use blocks are dropped entirely to prevent model mimicry
assert "Read" not in result
# ---------------------------------------------------------------------------
# compact_transcript — thinking block preservation
# ---------------------------------------------------------------------------
class TestCompactTranscriptThinkingBlocks:
"""Verify that compact_transcript preserves thinking blocks in the
last assistant message while stripping them from older messages."""
@pytest.mark.asyncio
async def test_last_assistant_thinking_blocks_preserved(self, mock_chat_config):
"""After compaction, the last assistant entry must retain its
original thinking and redacted_thinking blocks verbatim."""
transcript = _make_thinking_transcript()
compacted_msgs = [
{"role": "user", "content": "[conversation summary]"},
{"role": "assistant", "content": "Summarized response"},
]
mock_result = type(
"CompressResult",
(),
{
"was_compacted": True,
"messages": compacted_msgs,
"original_token_count": 800,
"token_count": 200,
"messages_summarized": 4,
"messages_dropped": 0,
},
)()
with patch(
"backend.copilot.sdk.transcript._run_compression",
new_callable=AsyncMock,
return_value=mock_result,
):
result = await compact_transcript(transcript, model="test-model")
assert result is not None
assert validate_transcript(result)
last_content = _last_assistant_content(result)
assert last_content is not None, "No assistant entry found"
assert isinstance(last_content, list)
# The last assistant must have the thinking blocks preserved
block_types = [b["type"] for b in last_content]
assert (
"thinking" in block_types
), "thinking block missing from last assistant message"
assert (
"redacted_thinking" in block_types
), "redacted_thinking block missing from last assistant message"
assert "text" in block_types
# Verify the thinking block content is value-identical
thinking_blocks = [b for b in last_content if b["type"] == "thinking"]
assert len(thinking_blocks) == 1
assert thinking_blocks[0]["thinking"] == THINKING_BLOCK["thinking"]
assert thinking_blocks[0]["signature"] == THINKING_BLOCK["signature"]
redacted_blocks = [b for b in last_content if b["type"] == "redacted_thinking"]
assert len(redacted_blocks) == 1
assert redacted_blocks[0]["data"] == REDACTED_THINKING_BLOCK["data"]
@pytest.mark.asyncio
async def test_older_assistant_thinking_blocks_stripped(self, mock_chat_config):
"""Older assistant messages should NOT retain thinking blocks
after compaction (they're compressed into summaries)."""
transcript = _make_thinking_transcript()
# The compressor will receive messages where older assistant
# entries have already had thinking blocks stripped.
captured_messages: list[dict] = []
async def mock_compression(messages, model, log_prefix):
captured_messages.extend(messages)
return type(
"CompressResult",
(),
{
"was_compacted": True,
"messages": messages,
"original_token_count": 800,
"token_count": 400,
"messages_summarized": 2,
"messages_dropped": 0,
},
)()
with patch(
"backend.copilot.sdk.transcript._run_compression",
side_effect=mock_compression,
):
await compact_transcript(transcript, model="test-model")
# Check that the messages sent to compression don't contain
# thinking content from older assistant messages
for msg in captured_messages:
if msg["role"] == "assistant":
content = msg.get("content", "")
assert (
"I should list the files." not in content
), "Old thinking block content leaked into compression input"
assert (
"Good, I see two Python files." not in content
), "Old thinking block content leaked into compression input"
@pytest.mark.asyncio
async def test_trailing_user_message_after_last_assistant(self, mock_chat_config):
"""When the last entry is a user message, the last *assistant*
message's thinking blocks should still be preserved."""
transcript = build_structured_transcript(
[
("user", "Hello"),
(
"assistant",
[
THINKING_BLOCK,
{"type": "text", "text": "Hi there"},
],
),
("user", "Follow-up question"),
]
)
# The compressor only receives the prefix (1 user message); the
# tail (assistant + trailing user) is preserved verbatim.
compacted_msgs = [
{"role": "user", "content": "Hello"},
]
mock_result = type(
"CompressResult",
(),
{
"was_compacted": True,
"messages": compacted_msgs,
"original_token_count": 400,
"token_count": 100,
"messages_summarized": 0,
"messages_dropped": 0,
},
)()
with patch(
"backend.copilot.sdk.transcript._run_compression",
new_callable=AsyncMock,
return_value=mock_result,
):
result = await compact_transcript(transcript, model="test-model")
assert result is not None
last_content = _last_assistant_content(result)
assert last_content is not None
assert isinstance(last_content, list)
block_types = [b["type"] for b in last_content]
assert (
"thinking" in block_types
), "thinking block lost from last assistant despite trailing user msg"
@pytest.mark.asyncio
async def test_single_assistant_with_thinking_preserved(self, mock_chat_config):
"""When there's only one assistant message (which is also the last),
its thinking blocks must be preserved."""
transcript = build_structured_transcript(
[
("user", "Hello"),
(
"assistant",
[
THINKING_BLOCK,
{"type": "text", "text": "World"},
],
),
]
)
compacted_msgs = [
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "World"},
]
mock_result = type(
"CompressResult",
(),
{
"was_compacted": True,
"messages": compacted_msgs,
"original_token_count": 200,
"token_count": 100,
"messages_summarized": 0,
"messages_dropped": 0,
},
)()
with patch(
"backend.copilot.sdk.transcript._run_compression",
new_callable=AsyncMock,
return_value=mock_result,
):
result = await compact_transcript(transcript, model="test-model")
assert result is not None
last_content = _last_assistant_content(result)
assert last_content is not None
assert isinstance(last_content, list)
block_types = [b["type"] for b in last_content]
assert "thinking" in block_types
@pytest.mark.asyncio
async def test_tail_parentuuid_rewired_to_prefix(self, mock_chat_config):
"""After compaction, the first tail entry's parentUuid must point to
the last entry in the compressed prefix — not its original parent."""
transcript = _make_thinking_transcript()
compacted_msgs = [
{"role": "user", "content": "[conversation summary]"},
{"role": "assistant", "content": "Summarized response"},
]
mock_result = type(
"CompressResult",
(),
{
"was_compacted": True,
"messages": compacted_msgs,
"original_token_count": 800,
"token_count": 200,
"messages_summarized": 4,
"messages_dropped": 0,
},
)()
with patch(
"backend.copilot.sdk.transcript._run_compression",
new_callable=AsyncMock,
return_value=mock_result,
):
result = await compact_transcript(transcript, model="test-model")
assert result is not None
lines = [ln for ln in result.strip().split("\n") if ln.strip()]
entries = [json.loads(ln) for ln in lines]
# Find the boundary: the compressed prefix ends just before the
# first tail entry (last assistant in original transcript).
tail_start = None
for i, entry in enumerate(entries):
msg = entry.get("message", {})
if isinstance(msg.get("content"), list):
# Structured content = preserved tail entry
tail_start = i
break
assert tail_start is not None, "Could not find preserved tail entry"
assert tail_start > 0, "Tail should not be the first entry"
# The tail entry's parentUuid must be the uuid of the preceding entry
prefix_last_uuid = entries[tail_start - 1]["uuid"]
tail_first_parent = entries[tail_start]["parentUuid"]
assert tail_first_parent == prefix_last_uuid, (
f"Tail parentUuid {tail_first_parent!r} != "
f"last prefix uuid {prefix_last_uuid!r}"
)
@pytest.mark.asyncio
async def test_no_thinking_blocks_still_works(self, mock_chat_config):
"""Compaction should still work normally when there are no thinking
blocks in the transcript."""
transcript = build_structured_transcript(
[
("user", "Hello"),
("assistant", [{"type": "text", "text": "Hi"}]),
("user", "More"),
("assistant", [{"type": "text", "text": "Details"}]),
]
)
compacted_msgs = [
{"role": "user", "content": "[summary]"},
{"role": "assistant", "content": "Summary"},
]
mock_result = type(
"CompressResult",
(),
{
"was_compacted": True,
"messages": compacted_msgs,
"original_token_count": 200,
"token_count": 50,
"messages_summarized": 2,
"messages_dropped": 0,
},
)()
with patch(
"backend.copilot.sdk.transcript._run_compression",
new_callable=AsyncMock,
return_value=mock_result,
):
result = await compact_transcript(transcript, model="test-model")
assert result is not None
assert validate_transcript(result)
# Verify last assistant content is preserved even without thinking blocks
last_content = _last_assistant_content(result)
assert last_content is not None
assert last_content == [{"type": "text", "text": "Details"}]
# ---------------------------------------------------------------------------
# _transcript_to_messages — thinking block handling
# ---------------------------------------------------------------------------
class TestTranscriptToMessagesThinking:
def test_thinking_blocks_excluded_from_flattened_content(self):
"""When _transcript_to_messages flattens content, thinking block
text should not leak into the message content string."""
transcript = build_structured_transcript(
[
("user", "Hello"),
(
"assistant",
[
{
"type": "thinking",
"thinking": "SECRET_THOUGHT",
"signature": "sig",
},
{"type": "text", "text": "Visible response"},
],
),
]
)
messages = _transcript_to_messages(transcript)
assistant_msg = [m for m in messages if m["role"] == "assistant"][0]
assert "SECRET_THOUGHT" not in assistant_msg["content"]
assert "Visible response" in assistant_msg["content"]
# ---------------------------------------------------------------------------
# response_adapter — ThinkingBlock handling
# ---------------------------------------------------------------------------
class TestResponseAdapterThinkingBlock:
def test_thinking_block_does_not_crash(self):
"""ThinkingBlock in AssistantMessage should not cause an error."""
adapter = SDKResponseAdapter(message_id="msg-1", session_id="sess-1")
msg = AssistantMessage(
content=[
ThinkingBlock(
thinking="Let me think about this...",
signature="sig_test_123",
),
TextBlock(text="Here is my response."),
],
model="claude-test",
)
results = adapter.convert_message(msg)
# Should produce stream events for text only, no crash
types = [type(r) for r in results]
assert StreamStartStep in types
assert StreamTextStart in types or StreamTextDelta in types
def test_thinking_block_does_not_emit_stream_events(self):
"""ThinkingBlock should NOT produce any StreamTextDelta events
containing thinking content."""
adapter = SDKResponseAdapter(message_id="msg-1", session_id="sess-1")
msg = AssistantMessage(
content=[
ThinkingBlock(
thinking="My secret thoughts",
signature="sig_test_456",
),
TextBlock(text="Public response"),
],
model="claude-test",
)
results = adapter.convert_message(msg)
text_deltas = [r for r in results if isinstance(r, StreamTextDelta)]
for delta in text_deltas:
assert "secret thoughts" not in (delta.delta or "")
# ---------------------------------------------------------------------------
# _format_sdk_content_blocks — redacted_thinking handling
# ---------------------------------------------------------------------------
class TestFormatSdkContentBlocks:
def test_thinking_block_preserved(self):
"""ThinkingBlock should be serialized with type, thinking, and signature."""
blocks = [
ThinkingBlock(thinking="My thoughts", signature="sig123"),
TextBlock(text="Response"),
]
result = _format_sdk_content_blocks(blocks)
assert len(result) == 2
assert result[0] == {
"type": "thinking",
"thinking": "My thoughts",
"signature": "sig123",
}
assert result[1] == {"type": "text", "text": "Response"}
def test_raw_dict_redacted_thinking_preserved(self):
"""Raw dict blocks (e.g. redacted_thinking) pass through unchanged."""
raw_block = {"type": "redacted_thinking", "data": "EmwKAh...encrypted"}
blocks = [
raw_block,
TextBlock(text="Response"),
]
result = _format_sdk_content_blocks(blocks)
assert len(result) == 2
assert result[0] == raw_block
assert result[1] == {"type": "text", "text": "Response"}

View File

@@ -14,7 +14,6 @@ from contextvars import ContextVar
from typing import TYPE_CHECKING, Any
from claude_agent_sdk import create_sdk_mcp_server, tool
from mcp.types import ToolAnnotations
from backend.copilot.context import (
_current_permissions,
@@ -38,7 +37,7 @@ from backend.copilot.tools import TOOL_REGISTRY
from backend.copilot.tools.base import BaseTool
from backend.util.truncate import truncate
from .e2b_file_tools import E2B_FILE_TOOL_NAMES, E2B_FILE_TOOLS, bridge_and_annotate
from .e2b_file_tools import E2B_FILE_TOOL_NAMES, E2B_FILE_TOOLS
if TYPE_CHECKING:
from e2b import AsyncSandbox
@@ -54,6 +53,14 @@ _MCP_MAX_CHARS = 500_000
MCP_SERVER_NAME = "copilot"
MCP_TOOL_PREFIX = f"mcp__{MCP_SERVER_NAME}__"
# Map from tool_name -> Queue of pre-launched (task, args) pairs.
# Initialised per-session in set_execution_context() so concurrent sessions
# never share the same dict.
_TaskQueueItem = tuple[asyncio.Task[dict[str, Any]], dict[str, Any]]
_tool_task_queues: ContextVar[dict[str, asyncio.Queue[_TaskQueueItem]] | None] = (
ContextVar("_tool_task_queues", default=None)
)
# Stash for MCP tool outputs before the SDK potentially truncates them.
# Keyed by tool_name → full output string. Consumed (popped) by the
# response adapter when it builds StreamToolOutputAvailable.
@@ -108,6 +115,7 @@ def set_execution_context(
_current_permissions.set(permissions)
_pending_tool_outputs.set({})
_stash_event.set(asyncio.Event())
_tool_task_queues.set({})
_consecutive_tool_failures.set({})
@@ -124,6 +132,48 @@ def reset_stash_event() -> None:
event.clear()
async def cancel_pending_tool_tasks() -> None:
"""Cancel all queued pre-launched tasks for the current execution context.
Call this when a stream attempt aborts (error, cancellation) to prevent
pre-launched tasks from continuing to execute against a rolled-back session.
Tasks that are already done are skipped; in-flight tasks are cancelled and
awaited so that any cleanup (``finally`` blocks, DB rollbacks) completes
before the next retry starts.
"""
queues = _tool_task_queues.get()
if not queues:
return
cancelled_tasks: list[asyncio.Task] = []
for tool_name, queue in list(queues.items()):
cancelled = 0
while not queue.empty():
task, _args = queue.get_nowait()
if not task.done():
task.cancel()
cancelled_tasks.append(task)
cancelled += 1
if cancelled:
logger.debug(
"Cancelled %d pre-launched task(s) for tool '%s'", cancelled, tool_name
)
queues.clear()
# Await all cancelled tasks so their cleanup (finally blocks, DB rollbacks)
# completes before the next retry attempt starts new pre-launches.
# Use a timeout to prevent hanging indefinitely if a task's cleanup is stuck.
if cancelled_tasks:
try:
await asyncio.wait_for(
asyncio.gather(*cancelled_tasks, return_exceptions=True),
timeout=5.0,
)
except TimeoutError:
logger.warning(
"Timed out waiting for %d cancelled task(s) to clean up",
len(cancelled_tasks),
)
def reset_tool_failure_counters() -> None:
"""Reset all tool-level circuit breaker counters.
@@ -199,6 +249,10 @@ async def wait_for_stash(timeout: float = 2.0) -> bool:
Uses ``asyncio.Event.wait()`` so it returns the instant the hook signals —
the timeout is purely a safety net for the case where the hook never fires.
Returns ``True`` if the stash signal was received, ``False`` on timeout.
The 2.0 s default was chosen to accommodate slower tool startup in cloud
sandboxes while still failing fast when the hook genuinely will not fire.
With the parallel pre-launch path, hooks typically fire well under 1 ms.
"""
event = _stash_event.get(None)
if event is None:
@@ -217,13 +271,95 @@ async def wait_for_stash(timeout: float = 2.0) -> bool:
return False
async def pre_launch_tool_call(tool_name: str, args: dict[str, Any]) -> None:
"""Pre-launch a tool as a background task so parallel calls run concurrently.
Called when an AssistantMessage with ToolUseBlocks is received, before the
SDK dispatches the MCP tool/call requests. The tool_handler will await the
pre-launched task instead of executing fresh.
The tool_name may include an MCP prefix (e.g. ``mcp__copilot__run_block``);
the prefix is stripped automatically before looking up the tool.
Ordering guarantee: the Claude Agent SDK dispatches MCP ``tools/call`` requests
in the same order as the ToolUseBlocks appear in the AssistantMessage.
Pre-launched tasks are queued FIFO per tool name, so the N-th handler for a
given tool name dequeues the N-th pre-launched task — result and args always
correspond when the SDK preserves order (which it does in the current SDK).
"""
queues = _tool_task_queues.get()
if queues is None:
return
# Strip the MCP server prefix (e.g. "mcp__copilot__") to get the bare tool name.
# Use removeprefix so tool names that themselves contain "__" are handled correctly.
bare_name = tool_name.removeprefix(MCP_TOOL_PREFIX)
base_tool = TOOL_REGISTRY.get(bare_name)
if base_tool is None:
return
user_id, session = get_execution_context()
if session is None:
return
# Expand @@agptfile: references before launching the task.
# The _truncating wrapper (which normally handles expansion) runs AFTER
# pre_launch_tool_call — the pre-launched task would otherwise receive raw
# @@agptfile: tokens and fail to resolve them inside _execute_tool_sync.
# Use _build_input_schema (same path as _truncating) for schema-aware expansion.
input_schema: dict[str, Any] | None
try:
input_schema = _build_input_schema(base_tool)
except Exception:
input_schema = None # schema unavailable — skip schema-aware expansion
try:
args = await expand_file_refs_in_args(
args, user_id, session, input_schema=input_schema
)
except FileRefExpansionError as exc:
logger.warning(
"pre_launch_tool_call: @@agptfile expansion failed for %s: %s — skipping pre-launch",
bare_name,
exc,
)
return
task = asyncio.create_task(_execute_tool_sync(base_tool, user_id, session, args))
# Log unhandled exceptions so "Task exception was never retrieved" warnings
# do not pollute stderr when a task is pre-launched but never dequeued.
task.add_done_callback(
lambda t, name=bare_name: (
logger.warning(
"Pre-launched task for %s raised unhandled: %s",
name,
t.exception(),
)
if not t.cancelled() and t.exception()
else None
)
)
if bare_name not in queues:
queues[bare_name] = asyncio.Queue[_TaskQueueItem]()
# Store (task, args) so the handler can log a warning if the SDK dispatches
# calls in a different order than the ToolUseBlocks appeared in the message.
queues[bare_name].put_nowait((task, args))
async def _execute_tool_sync(
base_tool: BaseTool,
user_id: str | None,
session: ChatSession,
args: dict[str, Any],
) -> dict[str, Any]:
"""Execute a tool synchronously and return MCP-formatted response."""
"""Execute a tool synchronously and return MCP-formatted response.
Note: ``@@agptfile:`` expansion should be performed by the caller before
invoking this function. For the normal (non-parallel) path it is handled
by the ``_truncating`` wrapper; for the pre-launched parallel path it is
handled in :func:`pre_launch_tool_call` before the task is created.
"""
effective_id = f"sdk-{uuid.uuid4().hex[:12]}"
result = await base_tool.execute(
user_id=user_id,
@@ -319,7 +455,83 @@ def create_tool_handler(base_tool: BaseTool):
"""
async def tool_handler(args: dict[str, Any]) -> dict[str, Any]:
"""Execute the wrapped tool and return MCP-formatted response."""
"""Execute the wrapped tool and return MCP-formatted response.
If a pre-launched task exists (from parallel tool pre-launch in the
message loop), await it instead of executing fresh.
"""
queues = _tool_task_queues.get()
if queues and base_tool.name in queues:
queue = queues[base_tool.name]
if not queue.empty():
task, launch_args = queue.get_nowait()
# Sanity-check: warn if the args don't match — this can happen
# if the SDK dispatches tool calls in a different order than the
# ToolUseBlocks appeared in the AssistantMessage (unlikely but
# could occur in future SDK versions or with SDK bugs).
# We compare full values (not just keys) so that two run_block
# calls with different block_id values are caught even though
# both have the same key set.
if launch_args != args:
logger.warning(
"Pre-launched task for %s: arg mismatch "
"(launch_keys=%s, call_keys=%s) — cancelling "
"pre-launched task and falling back to direct execution",
base_tool.name,
(
sorted(launch_args.keys())
if isinstance(launch_args, dict)
else type(launch_args).__name__
),
(
sorted(args.keys())
if isinstance(args, dict)
else type(args).__name__
),
)
if not task.done():
task.cancel()
# Await cancellation to prevent duplicate concurrent
# execution for blocks with side effects.
try:
await task
except (asyncio.CancelledError, Exception):
pass
# Fall through to the direct-execution path below.
else:
# Args match — await the pre-launched task.
try:
result = await task
except asyncio.CancelledError:
# Re-raise: CancelledError may be propagating from the
# outer streaming loop being cancelled — swallowing it
# would mask the cancellation and prevent proper cleanup.
logger.warning(
"Pre-launched tool %s was cancelled — re-raising",
base_tool.name,
)
raise
except Exception as e:
logger.error(
"Pre-launched tool %s failed: %s",
base_tool.name,
e,
exc_info=True,
)
return _mcp_error(
f"Failed to execute {base_tool.name}. "
"Check server logs for details."
)
# Pre-truncate the result so the _truncating wrapper (which
# wraps this handler) receives an already-within-budget
# value. _truncating handles stashing — we must NOT stash
# here or the output will be appended twice to the FIFO
# queue and pop_pending_tool_output would return a duplicate
# entry on the second call for the same tool.
return truncate(result, _MCP_MAX_CHARS)
# No pre-launched task — execute directly (fallback for non-parallel calls).
user_id, session = get_execution_context()
if session is None:
@@ -387,16 +599,7 @@ async def _read_file_handler(args: dict[str, Any]) -> dict[str, Any]:
selected = list(itertools.islice(f, offset, offset + limit))
# Cleanup happens in _cleanup_sdk_tool_results after session ends;
# don't delete here — the SDK may read in multiple chunks.
#
# When E2B is active, also copy the file into the sandbox so
# bash_exec can process it (the model often uses Read then bash).
text = "".join(selected)
sandbox = _current_sandbox.get(None)
if sandbox is not None:
annotation = await bridge_and_annotate(sandbox, resolved, offset, limit)
if annotation:
text += annotation
return _mcp_ok(text)
return _mcp_ok("".join(selected))
except FileNotFoundError:
return _mcp_err(f"File not found: {file_path}")
except Exception as e:
@@ -445,19 +648,9 @@ def _text_from_mcp_result(result: dict[str, Any]) -> str:
)
_PARALLEL_ANNOTATION = ToolAnnotations(readOnlyHint=True)
def create_copilot_mcp_server(*, use_e2b: bool = False):
"""Create an in-process MCP server configuration for CoPilot tools.
All tools are annotated with ``readOnlyHint=True`` so the SDK CLI
dispatches concurrent tool calls in parallel rather than sequentially.
This is a deliberate override: even side-effect tools use the hint
because the MCP tools are already individually sandboxed and the
pre-launch duplicate-execution bug (SECRT-2204) is worse than
sequential dispatch.
When *use_e2b* is True, five additional MCP file tools are registered
that route directly to the E2B sandbox filesystem, and the caller should
disable the corresponding SDK built-in tools via
@@ -475,28 +668,6 @@ def create_copilot_mcp_server(*, use_e2b: bool = False):
Applied once to every registered tool."""
async def wrapper(args: dict[str, Any]) -> dict[str, Any]:
# Empty tool args = model's output was truncated by the API's
# max_tokens limit. Instead of letting the tool fail with a
# confusing error (and eventually tripping the circuit breaker),
# return clear guidance so the model can self-correct.
if not args and input_schema and input_schema.get("required"):
logger.warning(
"[MCP] %s called with empty args (likely output "
"token truncation) — returning guidance",
tool_name,
)
return _mcp_error(
f"Your call to {tool_name} had empty arguments — "
f"this means your previous response was too long and "
f"the tool call input was truncated by the API. "
f"To fix this: break your work into smaller steps. "
f"For large content, first write it to a file using "
f"bash_exec with cat >> (append section by section), "
f"then pass it via @@agptfile:filename reference. "
f"Do NOT retry with the same approach — it will "
f"be truncated again."
)
# Circuit breaker: stop infinite retry loops with identical args.
# Use the original (pre-expansion) args for fingerprinting so
# check and record always use the same key — @@agptfile:
@@ -547,35 +718,24 @@ def create_copilot_mcp_server(*, use_e2b: bool = False):
for tool_name, base_tool in TOOL_REGISTRY.items():
handler = create_tool_handler(base_tool)
schema = _build_input_schema(base_tool)
# All tools annotated readOnlyHint=True to enable parallel dispatch.
# The SDK CLI uses this hint to dispatch concurrent tool calls in
# parallel rather than sequentially. Side-effect safety is ensured
# by the tool implementations themselves (idempotency, credentials).
decorated = tool(
tool_name,
base_tool.description,
schema,
annotations=_PARALLEL_ANNOTATION,
)(_truncating(handler, tool_name, input_schema=schema))
sdk_tools.append(decorated)
# E2B file tools replace SDK built-in Read/Write/Edit/Glob/Grep.
if use_e2b:
for name, desc, schema, handler in E2B_FILE_TOOLS:
decorated = tool(
name,
desc,
schema,
annotations=_PARALLEL_ANNOTATION,
)(_truncating(handler, name))
decorated = tool(name, desc, schema)(_truncating(handler, name))
sdk_tools.append(decorated)
# Read tool for SDK-truncated tool results (always needed, read-only).
# Read tool for SDK-truncated tool results (always needed).
read_tool = tool(
_READ_TOOL_NAME,
_READ_TOOL_DESCRIPTION,
_READ_TOOL_SCHEMA,
annotations=_PARALLEL_ANNOTATION,
)(_truncating(_read_file_handler, _READ_TOOL_NAME))
sdk_tools.append(read_tool)
@@ -590,14 +750,13 @@ def create_copilot_mcp_server(*, use_e2b: bool = False):
# Security hooks validate that file paths stay within sdk_cwd.
# Bash is NOT included — use the sandboxed MCP bash_exec tool instead,
# which provides kernel-level network isolation via unshare --net.
# Task/Agent allows spawning sub-agents (rate-limited by security hooks).
# The CLI renamed "Task" → "Agent" in v2.x; both are listed for compat.
# Task allows spawning sub-agents (rate-limited by security hooks).
# WebSearch uses Brave Search via Anthropic's API — safe, no SSRF risk.
# TodoWrite manages the task checklist shown in the UI — no security concern.
# In E2B mode, all five are disabled — MCP equivalents provide direct sandbox
# access. read_file also handles local tool-results and ephemeral reads.
_SDK_BUILTIN_FILE_TOOLS = ["Read", "Write", "Edit", "Glob", "Grep"]
_SDK_BUILTIN_ALWAYS = ["Task", "Agent", "WebSearch", "TodoWrite"]
_SDK_BUILTIN_ALWAYS = ["Task", "WebSearch", "TodoWrite"]
_SDK_BUILTIN_TOOLS = [*_SDK_BUILTIN_FILE_TOOLS, *_SDK_BUILTIN_ALWAYS]
# SDK built-in tools that must be explicitly blocked.

View File

@@ -1,21 +1,22 @@
"""Tests for tool_adapter: truncation, stash, context vars, readOnlyHint annotations."""
"""Tests for tool_adapter helpers: truncation, stash, context vars, parallel pre-launch."""
import asyncio
from unittest.mock import AsyncMock, MagicMock
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from mcp.types import ToolAnnotations
from backend.copilot.context import get_sdk_cwd
from backend.copilot.response_model import StreamToolOutputAvailable
from backend.copilot.sdk.file_ref import FileRefExpansionError
from backend.util.truncate import truncate
from .tool_adapter import (
_MCP_MAX_CHARS,
SDK_DISALLOWED_TOOLS,
_text_from_mcp_result,
cancel_pending_tool_tasks,
create_tool_handler,
pop_pending_tool_output,
pre_launch_tool_call,
reset_stash_event,
set_execution_context,
stash_pending_tool_output,
@@ -243,7 +244,7 @@ class TestTruncationAndStashIntegration:
# ---------------------------------------------------------------------------
# create_tool_handler (direct execution, no pre-launch)
# Parallel pre-launch infrastructure
# ---------------------------------------------------------------------------
@@ -276,18 +277,169 @@ def _init_ctx(session=None):
)
class TestCreateToolHandler:
"""Tests for create_tool_handler — direct tool execution."""
class TestPreLaunchToolCall:
"""Tests for pre_launch_tool_call and the queue-based parallel dispatch."""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.asyncio
async def test_handler_executes_tool_directly(self):
"""Handler executes the tool and returns MCP-formatted result."""
async def test_unknown_tool_is_silently_ignored(self):
"""pre_launch_tool_call does nothing for tools not in TOOL_REGISTRY."""
# Should not raise even if the tool name is completely unknown
await pre_launch_tool_call("nonexistent_tool", {})
@pytest.mark.asyncio
async def test_mcp_prefix_stripped_before_registry_lookup(self):
"""mcp__copilot__run_block is looked up as 'run_block'."""
mock_tool = _make_mock_tool("run_block")
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("mcp__copilot__run_block", {"block_id": "b1"})
# The task was enqueued — mock_tool.execute should be called once
# (may not complete immediately but should start)
await asyncio.sleep(0) # yield to event loop
mock_tool.execute.assert_awaited_once()
@pytest.mark.asyncio
async def test_bare_tool_name_without_prefix(self):
"""Tool names without __ separator are looked up as-is."""
mock_tool = _make_mock_tool("run_block")
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "b1"})
await asyncio.sleep(0)
mock_tool.execute.assert_awaited_once()
@pytest.mark.asyncio
async def test_task_enqueued_fifo_for_same_tool(self):
"""Two pre-launched calls for the same tool name are enqueued FIFO."""
results = []
async def slow_execute(*args, **kwargs):
results.append(len(results))
return StreamToolOutputAvailable(
toolCallId="id",
output=str(len(results) - 1),
toolName="t",
success=True,
)
mock_tool = _make_mock_tool("t")
mock_tool.execute = AsyncMock(side_effect=slow_execute)
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"t": mock_tool},
):
await pre_launch_tool_call("t", {"n": 1})
await pre_launch_tool_call("t", {"n": 2})
await asyncio.sleep(0)
assert mock_tool.execute.await_count == 2
@pytest.mark.asyncio
async def test_file_ref_expansion_failure_skips_pre_launch(self):
"""When @@agptfile: expansion fails, pre_launch_tool_call skips the task.
The handler should then fall back to direct execution (which will also
fail with a proper MCP error via _truncating's own expansion).
"""
mock_tool = _make_mock_tool("run_block", output="should-not-execute")
with (
patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
),
patch(
"backend.copilot.sdk.tool_adapter.expand_file_refs_in_args",
AsyncMock(side_effect=FileRefExpansionError("@@agptfile:missing.txt")),
),
):
# Should not raise — expansion failure is handled gracefully
await pre_launch_tool_call("run_block", {"text": "@@agptfile:missing.txt"})
await asyncio.sleep(0)
# No task was pre-launched — execute was not called
mock_tool.execute.assert_not_awaited()
class TestCreateToolHandlerParallel:
"""Tests for create_tool_handler using pre-launched tasks."""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.asyncio
async def test_handler_uses_prelaunched_task(self):
"""Handler pops and awaits the pre-launched task rather than re-executing."""
mock_tool = _make_mock_tool("run_block", output="pre-launched result")
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "b1"})
await asyncio.sleep(0) # let task start
handler = create_tool_handler(mock_tool)
result = await handler({"block_id": "b1"})
assert result["isError"] is False
text = result["content"][0]["text"]
assert "pre-launched result" in text
# Should only have been called once (the pre-launched task), not twice
mock_tool.execute.assert_awaited_once()
@pytest.mark.asyncio
async def test_handler_does_not_double_stash_for_prelaunched_task(self):
"""Pre-launched task result must NOT be stashed by tool_handler directly.
The _truncating wrapper wraps tool_handler and handles stashing after
tool_handler returns. If tool_handler also stashed, the output would be
appended twice to the FIFO queue and pop_pending_tool_output would return
a duplicate on the second call.
This test calls tool_handler directly (without _truncating) and asserts
that nothing was stashed — confirming stashing is deferred to _truncating.
"""
mock_tool = _make_mock_tool("run_block", output="stash-me")
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "b1"})
await asyncio.sleep(0)
handler = create_tool_handler(mock_tool)
result = await handler({"block_id": "b1"})
assert result["isError"] is False
assert "stash-me" in result["content"][0]["text"]
# tool_handler must NOT stash — _truncating (which wraps handler) does it.
# Calling pop here (without going through _truncating) should return None.
not_stashed = pop_pending_tool_output("run_block")
assert not_stashed is None, (
"tool_handler must not stash directly — _truncating handles stashing "
"to prevent double-stash in the FIFO queue"
)
@pytest.mark.asyncio
async def test_handler_falls_back_when_queue_empty(self):
"""When no pre-launched task exists, handler executes directly."""
mock_tool = _make_mock_tool("run_block", output="direct result")
# Don't call pre_launch_tool_call — queue is empty
handler = create_tool_handler(mock_tool)
result = await handler({"block_id": "b1"})
@@ -297,9 +449,104 @@ class TestCreateToolHandler:
mock_tool.execute.assert_awaited_once()
@pytest.mark.asyncio
async def test_handler_returns_error_on_no_session(self):
"""When session is None, handler returns MCP error."""
async def test_handler_cancelled_error_propagates(self):
"""CancelledError from a pre-launched task is re-raised to preserve cancellation semantics."""
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=asyncio.CancelledError())
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "b1"})
await asyncio.sleep(0)
handler = create_tool_handler(mock_tool)
with pytest.raises(asyncio.CancelledError):
await handler({"block_id": "b1"})
@pytest.mark.asyncio
async def test_handler_exception_returns_mcp_error(self):
"""Exception from a pre-launched task is caught and returned as MCP error."""
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=RuntimeError("block exploded"))
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "b1"})
await asyncio.sleep(0)
handler = create_tool_handler(mock_tool)
result = await handler({"block_id": "b1"})
assert result["isError"] is True
assert "Failed to execute run_block" in result["content"][0]["text"]
@pytest.mark.asyncio
async def test_two_same_tool_calls_dispatched_in_order(self):
"""Two pre-launched tasks for the same tool are consumed in FIFO order."""
call_order = []
async def execute_with_tag(*args, **kwargs):
tag = kwargs.get("block_id", "?")
call_order.append(tag)
return StreamToolOutputAvailable(
toolCallId="id", output=f"out-{tag}", toolName="run_block", success=True
)
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=execute_with_tag)
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "first"})
await pre_launch_tool_call("run_block", {"block_id": "second"})
await asyncio.sleep(0)
handler = create_tool_handler(mock_tool)
r1 = await handler({"block_id": "first"})
r2 = await handler({"block_id": "second"})
assert "out-first" in r1["content"][0]["text"]
assert "out-second" in r2["content"][0]["text"]
assert call_order == [
"first",
"second",
], f"Expected FIFO dispatch order but got {call_order}"
@pytest.mark.asyncio
async def test_arg_mismatch_falls_back_to_direct_execution(self):
"""When pre-launched args differ from SDK args, handler cancels pre-launched
task and falls back to direct execution with the correct args."""
mock_tool = _make_mock_tool("run_block", output="direct-result")
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
# Pre-launch with args {"block_id": "wrong"}
await pre_launch_tool_call("run_block", {"block_id": "wrong"})
await asyncio.sleep(0)
# SDK dispatches with different args
handler = create_tool_handler(mock_tool)
result = await handler({"block_id": "correct"})
assert result["isError"] is False
# The tool was called twice: once by pre-launch (wrong args), once by
# direct fallback (correct args). The result should come from the
# direct execution path.
assert mock_tool.execute.await_count == 2
@pytest.mark.asyncio
async def test_no_session_falls_back_gracefully(self):
"""When session is None and no pre-launched task, handler returns MCP error."""
mock_tool = _make_mock_tool("run_block")
# session=None means get_execution_context returns (user_id, None)
set_execution_context(user_id="u", session=None, sandbox=None) # type: ignore[arg-type]
handler = create_tool_handler(mock_tool)
@@ -308,406 +555,220 @@ class TestCreateToolHandler:
assert result["isError"] is True
assert "session" in result["content"][0]["text"].lower()
# ---------------------------------------------------------------------------
# cancel_pending_tool_tasks
# ---------------------------------------------------------------------------
class TestCancelPendingToolTasks:
"""Tests for cancel_pending_tool_tasks — the stream-abort cleanup helper."""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.asyncio
async def test_handler_returns_error_on_exception(self):
"""Exception from tool execution is caught and returned as MCP error."""
async def test_cancels_queued_tasks(self):
"""Queued tasks are cancelled and the queue is cleared."""
ran = False
async def never_run(*_args, **_kwargs):
nonlocal ran
await asyncio.sleep(10) # long enough to still be pending
ran = True
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=RuntimeError("block exploded"))
mock_tool.execute = AsyncMock(side_effect=never_run)
handler = create_tool_handler(mock_tool)
result = await handler({"block_id": "b1"})
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "b1"})
await asyncio.sleep(0) # let task start
await cancel_pending_tool_tasks()
await asyncio.sleep(0) # let cancellation propagate
assert result["isError"] is True
assert "Failed to execute run_block" in result["content"][0]["text"]
assert not ran, "Task should have been cancelled before completing"
@pytest.mark.asyncio
async def test_handler_executes_once_per_call(self):
"""Each handler call executes the tool exactly once — no duplicate execution."""
mock_tool = _make_mock_tool("run_block", output="single-execution")
async def test_noop_when_no_tasks_queued(self):
"""cancel_pending_tool_tasks does not raise when queues are empty."""
await cancel_pending_tool_tasks() # should not raise
handler = create_tool_handler(mock_tool)
await handler({"block_id": "b1"})
await handler({"block_id": "b2"})
@pytest.mark.asyncio
async def test_handler_does_not_find_cancelled_task(self):
"""After cancel, tool_handler falls back to direct execution."""
mock_tool = _make_mock_tool("run_block", output="direct-fallback")
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"run_block": mock_tool},
):
await pre_launch_tool_call("run_block", {"block_id": "b1"})
await asyncio.sleep(0)
await cancel_pending_tool_tasks()
# Queue is now empty — handler should execute directly
handler = create_tool_handler(mock_tool)
result = await handler({"block_id": "b1"})
assert result["isError"] is False
assert "direct-fallback" in result["content"][0]["text"]
# ---------------------------------------------------------------------------
# Concurrent / parallel pre-launch scenarios
# ---------------------------------------------------------------------------
class TestAllParallelToolsPrelaunchedIndependently:
"""Simulate SDK sending N separate AssistantMessages for the same tool concurrently."""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.asyncio
async def test_all_parallel_tools_prelaunched_independently(self):
"""5 pre-launches for the same tool all enqueue independently and run concurrently.
Each task sleeps for PER_TASK_S seconds. If they ran sequentially the total
wall time would be ~5*PER_TASK_S. Running concurrently it should finish in
roughly PER_TASK_S (plus scheduling overhead).
"""
PER_TASK_S = 0.05
N = 5
started: list[int] = []
finished: list[int] = []
async def slow_execute(*args, **kwargs):
idx = len(started)
started.append(idx)
await asyncio.sleep(PER_TASK_S)
finished.append(idx)
return StreamToolOutputAvailable(
toolCallId=f"id-{idx}",
output=f"result-{idx}",
toolName="bash_exec",
success=True,
)
mock_tool = _make_mock_tool("bash_exec")
mock_tool.execute = AsyncMock(side_effect=slow_execute)
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"bash_exec": mock_tool},
):
for i in range(N):
await pre_launch_tool_call("bash_exec", {"cmd": f"echo {i}"})
# Measure only the concurrent execution window, not pre-launch overhead.
# Starting the timer here avoids false failures on slow CI runners where
# the pre_launch_tool_call setup takes longer than the concurrent sleep.
t0 = asyncio.get_running_loop().time()
await asyncio.sleep(PER_TASK_S * 2)
elapsed = asyncio.get_running_loop().time() - t0
assert mock_tool.execute.await_count == N
assert len(finished) == N
# Wall time of the sleep window should be well under N * PER_TASK_S
# (sequential would be ~0.25s; concurrent finishes in ~PER_TASK_S = 0.05s)
assert elapsed < N * PER_TASK_S, (
f"Expected concurrent execution (<{N * PER_TASK_S:.2f}s) "
f"but sleep window took {elapsed:.2f}s"
)
class TestHandlerReturnsResultFromCorrectPrelaunchedTask:
"""Pop pre-launched tasks in order and verify each returns its own result."""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.asyncio
async def test_handler_returns_result_from_correct_prelaunched_task(self):
"""Two pre-launches for the same tool: first handler gets first result, second gets second."""
async def execute_with_cmd(*args, **kwargs):
cmd = kwargs.get("cmd", "?")
return StreamToolOutputAvailable(
toolCallId="id",
output=f"output-for-{cmd}",
toolName="bash_exec",
success=True,
)
mock_tool = _make_mock_tool("bash_exec")
mock_tool.execute = AsyncMock(side_effect=execute_with_cmd)
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"bash_exec": mock_tool},
):
await pre_launch_tool_call("bash_exec", {"cmd": "alpha"})
await pre_launch_tool_call("bash_exec", {"cmd": "beta"})
await asyncio.sleep(0) # let both tasks start
handler = create_tool_handler(mock_tool)
r1 = await handler({"cmd": "alpha"})
r2 = await handler({"cmd": "beta"})
text1 = r1["content"][0]["text"]
text2 = r2["content"][0]["text"]
assert "output-for-alpha" in text1, f"Expected alpha result, got: {text1}"
assert "output-for-beta" in text2, f"Expected beta result, got: {text2}"
assert mock_tool.execute.await_count == 2
# ---------------------------------------------------------------------------
# Regression tests: bugs fixed by removing pre-launch mechanism
#
# Each test class includes a _buggy_handler fixture that reproduces the old
# pre-launch implementation inline. Tests run against BOTH the buggy handler
# (xfail — proves the bug exists) and the current clean handler (must pass).
# ---------------------------------------------------------------------------
def _make_execute_fn(tool_name: str = "run_block"):
"""Return (execute_fn, call_log) — execute_fn records every call."""
call_log: list[dict] = []
async def execute_fn(*args, **kwargs):
call_log.append(kwargs)
return StreamToolOutputAvailable(
toolCallId=f"id-{len(call_log)}",
output=f"result-{len(call_log)}",
toolName=tool_name,
success=True,
)
return execute_fn, call_log
async def _buggy_prelaunch_handler(mock_tool, pre_launch_args, dispatch_args):
"""Simulate the OLD buggy pre-launch flow.
1. pre_launch_tool_call fires _execute_tool_sync with pre_launch_args
2. SDK dispatches handler with dispatch_args
3. Handler compares args — on mismatch, cancels + re-executes (BUG)
Returns the handler result.
"""
from backend.copilot.sdk.tool_adapter import _execute_tool_sync
user_id, session = "user-1", _make_mock_session()
# Step 1: pre-launch fires immediately (speculative)
task = asyncio.create_task(
_execute_tool_sync(mock_tool, user_id, session, pre_launch_args)
)
await asyncio.sleep(0) # let task start
# Step 2: SDK dispatches with (potentially different) args
if pre_launch_args != dispatch_args:
# Arg mismatch path: cancel pre-launched task + re-execute
if not task.done():
task.cancel()
try:
await task
except (asyncio.CancelledError, Exception):
pass
# Fall through to direct execution (duplicate!)
return await _execute_tool_sync(mock_tool, user_id, session, dispatch_args)
else:
return await task
class TestBug1DuplicateExecution:
"""Bug 1 (SECRT-2204): arg mismatch causes duplicate execution.
Pre-launch fires with raw args, SDK dispatches with normalised args.
Mismatch → cancel (too late) + re-execute → 2 API calls.
"""
class TestFiveConcurrentPrelaunchAllComplete:
"""Pre-launch 5 tasks; consume all 5 via handlers; assert all succeed."""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.xfail(reason="Old pre-launch code causes duplicate execution")
@pytest.mark.asyncio
async def test_old_code_duplicates_on_arg_mismatch(self):
"""OLD CODE: pre-launch with args A, dispatch with args B → 2 calls."""
execute_fn, call_log = _make_execute_fn()
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=execute_fn)
async def test_five_concurrent_prelaunch_all_complete(self):
"""All 5 pre-launched tasks complete and return successful results."""
N = 5
call_count = 0
pre_launch_args = {"block_id": "b1", "input_data": {"title": "Test"}}
dispatch_args = {
"block_id": "b1",
"input_data": {"title": "Test", "priority": None},
}
await _buggy_prelaunch_handler(mock_tool, pre_launch_args, dispatch_args)
# BUG: pre-launch executed once + fallback executed again = 2
assert len(call_log) == 1, (
f"Expected 1 execution but got {len(call_log)}"
f"duplicate execution bug!"
)
@pytest.mark.asyncio
async def test_current_code_no_duplicate(self):
"""FIXED: handler executes exactly once regardless of arg shape."""
execute_fn, call_log = _make_execute_fn()
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=execute_fn)
handler = create_tool_handler(mock_tool)
await handler({"block_id": "b1", "input_data": {"title": "Test"}})
assert len(call_log) == 1, f"Expected 1 execution but got {len(call_log)}"
class TestBug2FIFODesync:
"""Bug 2: FIFO desync when security hook denies a tool.
Pre-launch queues [task_A, task_B]. Tool A denied (no MCP dispatch).
Tool B's handler dequeues task_A → returns wrong result.
"""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.xfail(reason="Old FIFO queue returns wrong result on denial")
@pytest.mark.asyncio
async def test_old_code_fifo_desync_on_denial(self):
"""OLD CODE: denied tool's task stays in queue, next tool gets wrong result."""
from backend.copilot.sdk.tool_adapter import _execute_tool_sync
call_log: list[str] = []
async def tagged_execute(*args, **kwargs):
tag = kwargs.get("block_id", "?")
call_log.append(tag)
async def counting_execute(*args, **kwargs):
nonlocal call_count
call_count += 1
n = call_count
return StreamToolOutputAvailable(
toolCallId="id",
output=f"result-for-{tag}",
toolName="run_block",
toolCallId=f"id-{n}",
output=f"done-{n}",
toolName="bash_exec",
success=True,
)
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=tagged_execute)
user_id, session = "user-1", _make_mock_session()
mock_tool = _make_mock_tool("bash_exec")
mock_tool.execute = AsyncMock(side_effect=counting_execute)
# Simulate old FIFO queue
queue: asyncio.Queue = asyncio.Queue()
with patch(
"backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
{"bash_exec": mock_tool},
):
for i in range(N):
await pre_launch_tool_call("bash_exec", {"cmd": f"task-{i}"})
# Pre-launch for tool A and tool B
task_a = asyncio.create_task(
_execute_tool_sync(mock_tool, user_id, session, {"block_id": "A"})
)
task_b = asyncio.create_task(
_execute_tool_sync(mock_tool, user_id, session, {"block_id": "B"})
)
queue.put_nowait(task_a)
queue.put_nowait(task_b)
await asyncio.sleep(0) # let both tasks run
await asyncio.sleep(0) # let all tasks start
# Tool A is DENIED by security hook — no MCP dispatch, no dequeue
# Tool B's handler dequeues from FIFO → gets task_A!
dequeued_task = queue.get_nowait()
result = await dequeued_task
result_text = result["content"][0]["text"]
handler = create_tool_handler(mock_tool)
results = []
for i in range(N):
results.append(await handler({"cmd": f"task-{i}"}))
# BUG: handler for B got task_A's result
assert "result-for-B" in result_text, (
f"Expected result for B but got: {result_text}"
f"FIFO desync: B got A's result!"
)
@pytest.mark.asyncio
async def test_current_code_no_fifo_desync(self):
"""FIXED: each handler call executes independently, no shared queue."""
call_log: list[str] = []
async def tagged_execute(*args, **kwargs):
tag = kwargs.get("block_id", "?")
call_log.append(tag)
return StreamToolOutputAvailable(
toolCallId="id",
output=f"result-for-{tag}",
toolName="run_block",
success=True,
)
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=tagged_execute)
handler = create_tool_handler(mock_tool)
# Tool A denied (never called). Tool B dispatched normally.
result_b = await handler({"block_id": "B"})
assert "result-for-B" in result_b["content"][0]["text"]
assert call_log == ["B"]
class TestBug3CancelRace:
"""Bug 3: cancel race — task completes before cancel arrives.
Pre-launch fires fast HTTP call (< 1s). By the time handler detects
mismatch and calls task.cancel(), the API call already completed.
Side effect (Linear issue created) is irreversible.
"""
@pytest.fixture(autouse=True)
def _init(self):
_init_ctx(session=_make_mock_session())
@pytest.mark.xfail(reason="Old code: cancel arrives after task completes")
@pytest.mark.asyncio
async def test_old_code_cancel_arrives_too_late(self):
"""OLD CODE: fast task completes before cancel, side effect persists."""
side_effects: list[str] = []
async def fast_execute_with_side_effect(*args, **kwargs):
# Side effect happens immediately (like an HTTP POST to Linear)
side_effects.append("created-issue")
return StreamToolOutputAvailable(
toolCallId="id",
output="issue-created",
toolName="run_block",
success=True,
)
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=fast_execute_with_side_effect)
# Pre-launch fires immediately
pre_launch_args = {"block_id": "b1"}
dispatch_args = {"block_id": "b1", "extra": "normalised"}
await _buggy_prelaunch_handler(mock_tool, pre_launch_args, dispatch_args)
# BUG: side effect happened TWICE (pre-launch + fallback)
assert len(side_effects) == 1, (
f"Expected 1 side effect but got {len(side_effects)}"
f"cancel race: pre-launch completed before cancel!"
)
@pytest.mark.asyncio
async def test_current_code_single_side_effect(self):
"""FIXED: no speculative execution, exactly 1 side effect per call."""
side_effects: list[str] = []
async def execute_with_side_effect(*args, **kwargs):
side_effects.append("created-issue")
return StreamToolOutputAvailable(
toolCallId="id",
output="issue-created",
toolName="run_block",
success=True,
)
mock_tool = _make_mock_tool("run_block")
mock_tool.execute = AsyncMock(side_effect=execute_with_side_effect)
handler = create_tool_handler(mock_tool)
await handler({"block_id": "b1"})
assert len(side_effects) == 1
# ---------------------------------------------------------------------------
# readOnlyHint annotations
# ---------------------------------------------------------------------------
class TestReadOnlyAnnotations:
"""Tests that all tools get readOnlyHint=True for parallel dispatch."""
def test_parallel_annotation_constant(self):
"""_PARALLEL_ANNOTATION is a ToolAnnotations with readOnlyHint=True."""
from .tool_adapter import _PARALLEL_ANNOTATION
assert isinstance(_PARALLEL_ANNOTATION, ToolAnnotations)
assert _PARALLEL_ANNOTATION.readOnlyHint is True
# ---------------------------------------------------------------------------
# SDK_DISALLOWED_TOOLS
# ---------------------------------------------------------------------------
class TestSDKDisallowedTools:
"""Verify that dangerous SDK built-in tools are in the disallowed list."""
def test_bash_tool_is_disallowed(self):
assert "Bash" in SDK_DISALLOWED_TOOLS
def test_webfetch_tool_is_disallowed(self):
"""WebFetch is disallowed due to SSRF risk."""
assert "WebFetch" in SDK_DISALLOWED_TOOLS
# ---------------------------------------------------------------------------
# _read_file_handler — bridge_and_annotate integration
# ---------------------------------------------------------------------------
class TestReadFileHandlerBridge:
"""Verify that _read_file_handler calls bridge_and_annotate when a sandbox is active."""
@pytest.fixture(autouse=True)
def _init_context(self):
set_execution_context(
user_id="test",
session=None, # type: ignore[arg-type]
sandbox=None,
sdk_cwd="/tmp/copilot-bridge-test",
)
@pytest.mark.asyncio
async def test_bridge_called_when_sandbox_active(self, tmp_path, monkeypatch):
"""When a sandbox is set, bridge_and_annotate is called and its annotation appended."""
from backend.copilot.context import _current_sandbox
from .tool_adapter import _read_file_handler
test_file = tmp_path / "tool-results" / "data.json"
test_file.parent.mkdir(parents=True, exist_ok=True)
test_file.write_text('{"ok": true}\n')
monkeypatch.setattr(
"backend.copilot.sdk.tool_adapter.is_allowed_local_path",
lambda path, cwd: True,
)
fake_sandbox = object()
token = _current_sandbox.set(fake_sandbox) # type: ignore[arg-type]
try:
bridge_calls: list[tuple] = []
async def fake_bridge_and_annotate(sandbox, file_path, offset, limit):
bridge_calls.append((sandbox, file_path, offset, limit))
return "\n[Sandbox copy available at /tmp/abc-data.json]"
monkeypatch.setattr(
"backend.copilot.sdk.tool_adapter.bridge_and_annotate",
fake_bridge_and_annotate,
)
result = await _read_file_handler(
{"file_path": str(test_file), "offset": 0, "limit": 2000}
)
assert result["isError"] is False
assert len(bridge_calls) == 1
assert bridge_calls[0][0] is fake_sandbox
assert "/tmp/abc-data.json" in result["content"][0]["text"]
finally:
_current_sandbox.reset(token)
@pytest.mark.asyncio
async def test_bridge_not_called_without_sandbox(self, tmp_path, monkeypatch):
"""When no sandbox is set, bridge_and_annotate is not called."""
from .tool_adapter import _read_file_handler
test_file = tmp_path / "tool-results" / "data.json"
test_file.parent.mkdir(parents=True, exist_ok=True)
test_file.write_text('{"ok": true}\n')
monkeypatch.setattr(
"backend.copilot.sdk.tool_adapter.is_allowed_local_path",
lambda path, cwd: True,
)
bridge_calls: list[tuple] = []
async def fake_bridge_and_annotate(sandbox, file_path, offset, limit):
bridge_calls.append((sandbox, file_path, offset, limit))
return "\n[Sandbox copy available at /tmp/abc-data.json]"
monkeypatch.setattr(
"backend.copilot.sdk.tool_adapter.bridge_and_annotate",
fake_bridge_and_annotate,
)
result = await _read_file_handler(
{"file_path": str(test_file), "offset": 0, "limit": 2000}
)
assert result["isError"] is False
assert len(bridge_calls) == 0
assert "Sandbox copy" not in result["content"][0]["text"]
assert (
mock_tool.execute.await_count == N
), f"Expected {N} execute calls, got {mock_tool.execute.await_count}"
for i, result in enumerate(results):
assert result["isError"] is False, f"Result {i} should not be an error"
text = result["content"][0]["text"]
assert "done-" in text, f"Result {i} missing expected output: {text}"

View File

@@ -43,10 +43,6 @@ STRIPPABLE_TYPES = frozenset(
{"progress", "file-history-snapshot", "queue-operation", "summary", "pr-link"}
)
# Thinking block types that can be stripped from non-last assistant entries.
# The Anthropic API only requires these in the *last* assistant message.
_THINKING_BLOCK_TYPES = frozenset({"thinking", "redacted_thinking"})
@dataclass
class TranscriptDownload:
@@ -454,83 +450,6 @@ def _build_meta_storage_path(user_id: str, session_id: str, backend: object) ->
)
def strip_stale_thinking_blocks(content: str) -> str:
"""Remove thinking/redacted_thinking blocks from non-last assistant entries.
The Anthropic API only requires thinking blocks in the **last** assistant
message to be value-identical to the original response. Older assistant
entries carry stale thinking blocks that consume significant tokens
(often 10-50K each) without providing useful context for ``--resume``.
Stripping them before upload prevents the CLI from triggering compaction
every turn just to compress away the stale thinking bloat.
"""
lines = content.strip().split("\n")
if not lines:
return content
parsed: list[tuple[str, dict | None]] = []
for line in lines:
parsed.append((line, json.loads(line, fallback=None)))
# Reverse scan to find the last assistant message ID and index.
last_asst_msg_id: str | None = None
last_asst_idx: int | None = None
for i in range(len(parsed) - 1, -1, -1):
_line, entry = parsed[i]
if not isinstance(entry, dict):
continue
msg = entry.get("message", {})
if msg.get("role") == "assistant":
last_asst_msg_id = msg.get("id")
last_asst_idx = i
break
if last_asst_idx is None:
return content
result_lines: list[str] = []
stripped_count = 0
for i, (line, entry) in enumerate(parsed):
if not isinstance(entry, dict):
result_lines.append(line)
continue
msg = entry.get("message", {})
# Only strip from assistant entries that are NOT the last turn.
# Use msg_id matching when available; fall back to index for entries
# without an id field.
is_last_turn = (
last_asst_msg_id is not None and msg.get("id") == last_asst_msg_id
) or (last_asst_msg_id is None and i == last_asst_idx)
if (
msg.get("role") == "assistant"
and not is_last_turn
and isinstance(msg.get("content"), list)
):
content_blocks = msg["content"]
filtered = [
b
for b in content_blocks
if not (isinstance(b, dict) and b.get("type") in _THINKING_BLOCK_TYPES)
]
if len(filtered) < len(content_blocks):
stripped_count += len(content_blocks) - len(filtered)
entry = {**entry, "message": {**msg, "content": filtered}}
result_lines.append(json.dumps(entry, separators=(",", ":")))
continue
result_lines.append(line)
if stripped_count:
logger.info(
"[Transcript] Stripped %d stale thinking block(s) from non-last entries",
stripped_count,
)
return "\n".join(result_lines) + "\n"
async def upload_transcript(
user_id: str,
session_id: str,
@@ -553,9 +472,6 @@ async def upload_transcript(
# Strip metadata entries (progress, file-history-snapshot, etc.)
# Note: SDK-built transcripts shouldn't have these, but strip for safety
stripped = strip_progress_entries(content)
# Strip stale thinking blocks from older assistant entries — these consume
# significant tokens and trigger unnecessary CLI compaction every turn.
stripped = strip_stale_thinking_blocks(stripped)
if not validate_transcript(stripped):
# Log entry types for debugging — helps identify why validation failed
entry_types = [
@@ -693,35 +609,24 @@ def _flatten_assistant_content(blocks: list) -> str:
"""Flatten assistant content blocks into a single plain-text string.
Structured ``tool_use`` blocks are converted to ``[tool_use: name]``
placeholders. ``thinking`` and ``redacted_thinking`` blocks are
silently dropped — they carry no useful context for compression
summaries and must not leak into compacted transcripts (the Anthropic
API requires thinking blocks in the last assistant message to be
value-identical to the original response; including stale thinking
text would violate that constraint).
This is intentional: ``compress_context`` requires plain text for
token counting and LLM summarization. The structural loss is
acceptable because compaction only runs when the original transcript
was already too large for the model.
placeholders. This is intentional: ``compress_context`` requires plain
text for token counting and LLM summarization. The structural loss is
acceptable because compaction only runs when the original transcript was
already too large for the model — a summarized plain-text version is
better than no context at all.
"""
parts: list[str] = []
for block in blocks:
if isinstance(block, dict):
btype = block.get("type", "")
if btype in _THINKING_BLOCK_TYPES:
continue
if btype == "text":
parts.append(block.get("text", ""))
elif btype == "tool_use":
# Drop tool_use entirely — any text representation gets
# mimicked by the model as plain text instead of actual
# structured tool calls. The tool results (in the
# following user/tool_result entry) provide sufficient
# context about what happened.
continue
parts.append(f"[tool_use: {block.get('name', '?')}]")
else:
continue
# Preserve non-text blocks (e.g. image) as placeholders.
# Use __prefix__ to distinguish from literal user text.
parts.append(f"[__{btype}__]")
elif isinstance(block, str):
parts.append(block)
return "\n".join(parts) if parts else ""
@@ -900,68 +805,6 @@ async def _run_compression(
)
def _find_last_assistant_entry(
content: str,
) -> tuple[list[str], list[str]]:
"""Split JSONL lines into (compressible_prefix, preserved_tail).
The tail starts at the **first** entry of the last assistant turn and
includes everything after it (typically trailing user messages). An
assistant turn can span multiple consecutive JSONL entries sharing the
same ``message.id`` (e.g., a thinking entry followed by a tool_use
entry). All entries of the turn are preserved verbatim.
The Anthropic API requires that ``thinking`` and ``redacted_thinking``
blocks in the **last** assistant message remain value-identical to the
original response (the API validates parsed signature values, not raw
JSON bytes). By excluding the entire turn from compression we
guarantee those blocks are never altered.
Returns ``(all_lines, [])`` when no assistant entry is found.
"""
lines = [ln for ln in content.strip().split("\n") if ln.strip()]
# Parse all lines once to avoid double JSON deserialization.
# json.loads with fallback=None returns Any; non-dict entries are
# safely skipped by the isinstance(entry, dict) guards below.
parsed: list = [json.loads(ln, fallback=None) for ln in lines]
# Reverse scan: find the message.id and index of the last assistant entry.
last_asst_msg_id: str | None = None
last_asst_idx: int | None = None
for i in range(len(parsed) - 1, -1, -1):
entry = parsed[i]
if not isinstance(entry, dict):
continue
msg = entry.get("message", {})
if msg.get("role") == "assistant":
last_asst_idx = i
last_asst_msg_id = msg.get("id")
break
if last_asst_idx is None:
return lines, []
# If the assistant entry has no message.id, fall back to preserving
# from that single entry onward — safer than compressing everything.
if last_asst_msg_id is None:
return lines[:last_asst_idx], lines[last_asst_idx:]
# Forward scan: find the first entry of this turn (same message.id).
first_turn_idx: int | None = None
for i, entry in enumerate(parsed):
if not isinstance(entry, dict):
continue
msg = entry.get("message", {})
if msg.get("role") == "assistant" and msg.get("id") == last_asst_msg_id:
first_turn_idx = i
break
if first_turn_idx is None:
return lines, []
return lines[:first_turn_idx], lines[first_turn_idx:]
async def compact_transcript(
content: str,
*,
@@ -973,50 +816,42 @@ async def compact_transcript(
Converts transcript entries to plain messages, runs ``compress_context``
(the same compressor used for pre-query history), and rebuilds JSONL.
The **last assistant entry** (and any entries after it) are preserved
verbatim — never flattened or compressed. The Anthropic API requires
``thinking`` and ``redacted_thinking`` blocks in the latest assistant
message to be value-identical to the original response (the API
validates parsed signature values, not raw JSON bytes); compressing
them would destroy the cryptographic signatures and cause
``invalid_request_error``.
Structured content (``tool_use`` blocks, ``tool_result`` nesting, images)
is flattened to plain text for compression. This matches the fidelity of
the Plan C (DB compression) fallback path, where
``_format_conversation_context`` similarly renders tool calls as
``You called tool: name(args)`` and results as ``Tool result: ...``.
Neither path preserves structured API content blocks — the compacted
context serves as text history for the LLM, which creates proper
structured tool calls going forward.
Structured content in *older* assistant entries (``tool_use`` blocks,
``thinking`` blocks, ``tool_result`` nesting, images) is flattened to
plain text for compression. This matches the fidelity of the Plan C
(DB compression) fallback path.
Images are per-turn attachments loaded from workspace storage by file ID
(via ``_prepare_file_attachments``), not part of the conversation history.
They are re-attached each turn and are unaffected by compaction.
Returns the compacted JSONL string, or ``None`` on failure.
See also:
``_compress_messages`` in ``service.py`` — compresses ``ChatMessage``
lists for pre-query DB history.
lists for pre-query DB history. Both share ``compress_context()``
but operate on different input formats (JSONL transcript entries
here vs. ChatMessage dicts there).
"""
prefix_lines, tail_lines = _find_last_assistant_entry(content)
# Build the JSONL string for the compressible prefix
prefix_content = "\n".join(prefix_lines) + "\n" if prefix_lines else ""
messages = _transcript_to_messages(prefix_content) if prefix_content else []
if len(messages) + len(tail_lines) < 2:
total = len(messages) + len(tail_lines)
logger.warning("%s Too few messages to compact (%d)", log_prefix, total)
return None
if not messages:
logger.warning("%s Nothing to compress (only tail entries remain)", log_prefix)
messages = _transcript_to_messages(content)
if len(messages) < 2:
logger.warning("%s Too few messages to compact (%d)", log_prefix, len(messages))
return None
try:
result = await _run_compression(messages, model, log_prefix)
if not result.was_compacted:
# Compressor says it's within budget, but the SDK rejected it.
# Return None so the caller falls through to DB fallback.
logger.warning(
"%s Compressor reports within budget but SDK rejected — "
"signalling failure",
log_prefix,
)
return None
if not result.messages:
logger.warning("%s Compressor returned empty messages", log_prefix)
return None
logger.info(
"%s Compacted transcript: %d->%d tokens (%d summarized, %d dropped)",
log_prefix,
@@ -1025,29 +860,7 @@ async def compact_transcript(
result.messages_summarized,
result.messages_dropped,
)
compressed_part = _messages_to_transcript(result.messages)
# Re-append the preserved tail (last assistant + trailing entries)
# with parentUuid patched to chain onto the compressed prefix.
tail_part = _rechain_tail(compressed_part, tail_lines)
compacted = compressed_part + tail_part
if len(compacted) >= len(content):
# Byte count can increase due to preserved tail entries
# (thinking blocks, JSON overhead) even when token count
# decreased. Log a warning but still return — the API
# validates tokens not bytes, and the caller falls through
# to DB fallback if the transcript is still too large.
logger.warning(
"%s Compacted transcript (%d bytes) is not smaller than "
"original (%d bytes) — may still reduce token count",
log_prefix,
len(compacted),
len(content),
)
# Authoritative validation — the caller (_reduce_context) also
# validates, but this is the canonical check that guarantees we
# never return a malformed transcript from this function.
compacted = _messages_to_transcript(result.messages)
if not validate_transcript(compacted):
logger.warning("%s Compacted transcript failed validation", log_prefix)
return None
@@ -1057,43 +870,3 @@ async def compact_transcript(
"%s Transcript compaction failed: %s", log_prefix, e, exc_info=True
)
return None
def _rechain_tail(compressed_prefix: str, tail_lines: list[str]) -> str:
"""Patch tail entries so their parentUuid chain links to the compressed prefix.
The first tail entry's ``parentUuid`` is set to the ``uuid`` of the
last entry in the compressed prefix. Subsequent tail entries are
rechained to point to their predecessor in the tail — their original
``parentUuid`` values may reference entries that were compressed away.
"""
if not tail_lines:
return ""
# Find the last uuid in the compressed prefix
last_prefix_uuid = ""
for line in reversed(compressed_prefix.strip().split("\n")):
if not line.strip():
continue
entry = json.loads(line, fallback=None)
if isinstance(entry, dict) and "uuid" in entry:
last_prefix_uuid = entry["uuid"]
break
result_lines: list[str] = []
prev_uuid: str | None = None
for i, line in enumerate(tail_lines):
entry = json.loads(line, fallback=None)
if not isinstance(entry, dict):
# Safety guard: _find_last_assistant_entry already filters empty
# lines, and well-formed JSONL always parses to dicts. Non-dict
# lines are passed through unchanged; prev_uuid is intentionally
# NOT updated so the next dict entry chains to the last known uuid.
result_lines.append(line)
continue
if i == 0:
entry["parentUuid"] = last_prefix_uuid
elif prev_uuid is not None:
entry["parentUuid"] = prev_uuid
prev_uuid = entry.get("uuid")
result_lines.append(json.dumps(entry, separators=(",", ":")))
return "\n".join(result_lines) + "\n"

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