fix(backend/copilot): fix logging, token counting, and compaction edge cases

- Convert all remaining f-string logger calls to %-style across SDK files
- Fix _msg_tokens not counting Anthropic text blocks (underestimated tokens)
- Fix _truncate_middle_tokens producing wrong output when max_tok < 3
- Fix CompactionTracker.reset_for_query not clearing _compact_start event
- Add cycle guard to strip_progress_entries reparenting loop
- Replace bare except with logged exception in transcript metadata loading

.claude/skills/backend-check/SKILL.md

@@ -0,0 +1,17 @@
+---
+name: backend-check
+description: Run the full backend formatting, linting, and test suite. Ensures code quality before commits and PRs. TRIGGER when backend Python code has been modified and needs validation.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Backend Check
+
+## Steps
+
+1. **Format**: `poetry run format` — runs formatting AND linting. NEVER run ruff/black/isort individually
+2. **Fix** any remaining errors manually, re-run until clean
+3. **Test**: `poetry run test` (runs DB setup + pytest). For specific files: `poetry run pytest -s -vvv <test_files>`
+4. **Snapshots** (if needed): `poetry run pytest path/to/test.py --snapshot-update` — review with `git diff`

.claude/skills/code-style/SKILL.md

@@ -0,0 +1,35 @@
+---
+name: code-style
+description: Python code style preferences for the AutoGPT backend. Apply when writing or reviewing Python code. TRIGGER when writing new Python code, reviewing PRs, or refactoring backend code.
+user-invocable: false
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Code Style
+
+## Imports
+
+- **Top-level only** — no local/inner imports. Move all imports to the top of the file.
+
+## Typing
+
+- **No duck typing** — avoid `hasattr`, `getattr`, `isinstance` for type dispatch. Use proper typed interfaces, unions, or protocols.
+- **Pydantic models** over dataclass, namedtuple, or raw dict for structured data.
+- **No linter suppressors** — avoid `# type: ignore`, `# noqa`, `# pyright: ignore` etc. 99% of the time the right fix is fixing the type/code, not silencing the tool.
+
+## Code Structure
+
+- **List comprehensions** over manual loop-and-append.
+- **Early return** — guard clauses first, avoid deep nesting.
+- **Flatten inline** — prefer short, concise expressions. Reduce `if/else` chains with direct returns or ternaries when readable.
+- **Modular functions** — break complex logic into small, focused functions rather than long blocks with nested conditionals.
+
+## Review Checklist
+
+Before finishing, always ask:
+- Can any function be split into smaller pieces?
+- Is there unnecessary nesting that an early return would eliminate?
+- Can any loop be a comprehension?
+- Is there a simpler way to express this logic?

.claude/skills/frontend-check/SKILL.md

@@ -0,0 +1,16 @@
+---
+name: frontend-check
+description: Run the full frontend formatting, linting, and type checking suite. Ensures code quality before commits and PRs. TRIGGER when frontend TypeScript/React code has been modified and needs validation.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Frontend Check
+
+## Steps (in order)
+
+1. **Format**: `pnpm format` — NEVER run individual formatters
+2. **Lint**: `pnpm lint` — fix errors, re-run until clean
+3. **Types**: `pnpm types` — if it keeps failing after multiple attempts, stop and ask the user

.claude/skills/new-block/SKILL.md

@@ -0,0 +1,29 @@
+---
+name: new-block
+description: Create a new backend block following the Block SDK Guide. Guides through provider configuration, schema definition, authentication, and testing. TRIGGER when user asks to create a new block, add a new integration, or build a new node for the graph editor.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# New Block Creation
+
+Read `docs/platform/block-sdk-guide.md` first for the full guide.
+
+## Steps
+
+1. **Provider config** (if external service): create `_config.py` with `ProviderBuilder`
+2. **Block file** in `backend/blocks/` (from `autogpt_platform/backend/`):
+   - Generate a UUID once with `uuid.uuid4()`, then **hard-code that string** as `id` (IDs must be stable across imports)
+   - `Input(BlockSchema)` and `Output(BlockSchema)` classes
+   - `async def run` that `yield`s output fields
+3. **Files**: use `store_media_file()` with `"for_block_output"` for outputs
+4. **Test**: `poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[MyBlock]' -xvs`
+5. **Format**: `poetry run format`
+
+## Rules
+
+- Analyze interfaces: do inputs/outputs connect well with other blocks in a graph?
+- Use top-level imports, avoid duck typing
+- Always use `for_block_output` for block outputs

.claude/skills/openapi-regen/SKILL.md

@@ -0,0 +1,28 @@
+---
+name: openapi-regen
+description: Regenerate the OpenAPI spec and frontend API client. Starts the backend REST server, fetches the spec, and regenerates the typed frontend hooks. TRIGGER when API routes change, new endpoints are added, or frontend API types are stale.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# OpenAPI Spec Regeneration
+
+## Steps
+
+1. **Run end-to-end** in a single shell block (so `REST_PID` persists):
+   ```bash
+   cd autogpt_platform/backend && poetry run rest &
+   REST_PID=$!
+   WAIT=0; until curl -sf http://localhost:8006/health > /dev/null 2>&1; do sleep 1; WAIT=$((WAIT+1)); [ $WAIT -ge 60 ] && echo "Timed out" && kill $REST_PID && exit 1; done
+   cd ../frontend && pnpm generate:api:force
+   kill $REST_PID
+   pnpm types && pnpm lint && pnpm format
+   ```
+
+## Rules
+
+- Always use `pnpm generate:api:force` (not `pnpm generate:api`)
+- Don't manually edit files in `src/app/api/__generated__/`
+- Generated hooks follow: `use{Method}{Version}{OperationName}`

.claude/skills/pr-address/SKILL.md

@@ -1,79 +0,0 @@
----
-name: pr-address
-description: Address PR review comments and loop until CI green and all comments resolved. TRIGGER when user asks to address comments, fix PR feedback, respond to reviewers, or babysit/monitor a PR.
-user-invocable: true
-args: "[PR number or URL] — if omitted, finds PR for current branch."
-metadata:
-  author: autogpt-team
-  version: "1.0.0"
----
-
-# PR Address
-
-## Find the PR
-
-```bash
-gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT
-gh pr view {N}
-```
-
-## Fetch comments (all sources)
-
-```bash
-gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews       # top-level reviews
-gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments      # inline review comments
-gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments     # PR conversation comments
-```
-
-**Bots to watch for:**
-- `autogpt-reviewer` — posts "Blockers", "Should Fix", "Nice to Have". Address ALL of them.
-- `sentry[bot]` — bug predictions. Fix real bugs, explain false positives.
-- `coderabbitai[bot]` — automated review. Address actionable items.
-
-## For each unaddressed comment
-
-Address comments **one at a time**: fix → commit → push → inline reply → next.
-
-1. Read the referenced code, make the fix (or reply explaining why it's not needed)
-2. Commit and push the fix
-3. Reply **inline** (not as a new top-level comment) referencing the fixing commit — this is what resolves the conversation for bot reviewers (coderabbitai, sentry):
-
-| Comment type | How to reply |
-|---|---|
-| Inline review (`pulls/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID}/replies -f body="Fixed in <commit-sha>: <description>"` |
-| Conversation (`issues/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments -f body="Fixed in <commit-sha>: <description>"` |
-
-## Format and commit
-
-After fixing, format the changed code:
-
-- **Backend** (from `autogpt_platform/backend/`): `poetry run format`
-- **Frontend** (from `autogpt_platform/frontend/`): `pnpm format && pnpm lint && pnpm types`
-
-If API routes changed, regenerate the frontend client:
-```bash
-cd autogpt_platform/backend && poetry run rest &
-REST_PID=$!
-trap "kill $REST_PID 2>/dev/null" EXIT
-WAIT=0; until curl -sf http://localhost:8006/health > /dev/null 2>&1; do sleep 1; WAIT=$((WAIT+1)); [ $WAIT -ge 60 ] && echo "Timed out" && exit 1; done
-cd ../frontend && pnpm generate:api:force
-kill $REST_PID 2>/dev/null; trap - EXIT
-```
-Never manually edit files in `src/app/api/__generated__/`.
-
-Then commit and **push immediately** — never batch commits without pushing.
-
-For backend commits in worktrees: `poetry run git commit` (pre-commit hooks).
-
-## The loop
-
-```text
-address comments → format → commit → push
-→ re-check comments → fix new ones → push
-→ wait for CI → re-check comments after CI settles
-→ repeat until: all comments addressed AND CI green AND no new comments arriving
-```
-
-While CI runs, stay productive: run local tests, address remaining comments.
-
-**The loop ends when:** CI fully green + all comments addressed + no new comments since CI settled.

.claude/skills/pr-create/SKILL.md

@@ -0,0 +1,31 @@
+---
+name: pr-create
+description: Create a pull request for the current branch. TRIGGER when user asks to create a PR, open a pull request, push changes for review, or submit work for merging.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Create Pull Request
+
+## Steps
+
+1. **Check for existing PR**: `gh pr view --json url -q .url 2>/dev/null` — if a PR already exists, output its URL and stop
+2. **Understand changes**: `git status`, `git diff dev...HEAD`, `git log dev..HEAD --oneline`
+3. **Read PR template**: `.github/PULL_REQUEST_TEMPLATE.md`
+4. **Draft PR title**: Use conventional commits format (see CLAUDE.md for types and scopes)
+5. **Fill out PR template** as the body — be thorough in the Changes section
+6. **Format first** (if relevant changes exist):
+   - Backend: `cd autogpt_platform/backend && poetry run format`
+   - Frontend: `cd autogpt_platform/frontend && pnpm format`
+   - Fix any lint errors, then commit formatting changes before pushing
+7. **Push**: `git push -u origin HEAD`
+8. **Create PR**: `gh pr create --base dev`
+9. **Output** the PR URL
+
+## Rules
+
+- Always target `dev` branch
+- Do NOT run tests — CI will handle that
+- Use the PR template from `.github/PULL_REQUEST_TEMPLATE.md`

.claude/skills/pr-review/SKILL.md

@@ -1,74 +1,51 @@
 ---
 name: pr-review
-description: Review a PR for correctness, security, code quality, and testing issues. TRIGGER when user asks to review a PR, check PR quality, or give feedback on a PR.
+description: Address all open PR review comments systematically. Fetches comments, addresses each one, reacts +1/-1, and replies when clarification is needed. Keeps iterating until all comments are addressed and CI is green. TRIGGER when user shares a PR URL, asks to address review comments, fix PR feedback, or respond to reviewer comments.
 user-invocable: true
-args: "[PR number or URL] — if omitted, finds PR for current branch."
 metadata:
   author: autogpt-team
   version: "1.0.0"
 ---
 
-# PR Review
+# PR Review Comment Workflow
 
-## Find the PR
+## Steps
 
-```bash
-gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT
-gh pr view {N}
-```
+1. **Find PR**: `gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT`
+2. **Fetch comments** (all three sources):
+   - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews` (top-level reviews)
+   - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments` (inline review comments)
+   - `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` (PR conversation comments)
+3. **Skip** comments already reacted to by PR author
+4. **For each unreacted comment**:
+   - Read referenced code, make the fix (or reply if you disagree/need info)
+   - **Inline review comments** (`pulls/{N}/comments`):
+     - React: `gh api repos/.../pulls/comments/{ID}/reactions -f content="+1"` (or `-1`)
+     - Reply: `gh api repos/.../pulls/{N}/comments/{ID}/replies -f body="..."`
+   - **PR conversation comments** (`issues/{N}/comments`):
+     - React: `gh api repos/.../issues/comments/{ID}/reactions -f content="+1"` (or `-1`)
+     - No threaded replies — post a new issue comment if needed
+   - **Top-level reviews**: no reaction API — address in code, reply via issue comment if needed
+5. **Include autogpt-reviewer bot fixes** too
+6. **Format**: `cd autogpt_platform/backend && poetry run format`, `cd autogpt_platform/frontend && pnpm format`
+7. **Commit & push**
+8. **Re-fetch comments** immediately — address any new unreacted ones before waiting on CI
+9. **Stay productive while CI runs** — don't idle. In priority order:
+   - Run any pending local tests (`poetry run pytest`, e2e, etc.) and fix failures
+   - Address any remaining comments
+   - Only poll `gh pr checks {N}` as the last resort when there's truly nothing left to do
+10. **If CI fails** — fix, go back to step 6
+11. **Re-fetch comments again** after CI is green — address anything that appeared while CI was running
+12. **Done** only when: all comments reacted AND CI is green.
 
-## Read the diff
+## CRITICAL: Do Not Stop
 
-```bash
-gh pr diff {N}
-```
+**Loop is: address → format → commit → push → re-check comments → run local tests → wait CI → re-check comments → repeat.**
 
-## Fetch existing review comments
+Never idle. If CI is running and you have nothing to address, run local tests. Waiting on CI is the last resort.
 
-Before posting anything, fetch existing inline comments to avoid duplicates:
+## Rules
 
-```bash
-gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments
-gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews
-```
-
-## What to check
-
-**Correctness:** logic errors, off-by-one, missing edge cases, race conditions (TOCTOU in file access, credit charging), error handling gaps, async correctness (missing `await`, unclosed resources).
-
-**Security:** input validation at boundaries, no injection (command, XSS, SQL), secrets not logged, file paths sanitized (`os.path.basename()` in error messages).
-
-**Code quality:** apply rules from backend/frontend CLAUDE.md files.
-
-**Architecture:** DRY, single responsibility, modular functions. `Security()` vs `Depends()` for FastAPI auth. `data:` for SSE events, `: comment` for heartbeats. `transaction=True` for Redis pipelines.
-
-**Testing:** edge cases covered, colocated `*_test.py` (backend) / `__tests__/` (frontend), mocks target where symbol is **used** not defined, `AsyncMock` for async.
-
-## Output format
-
-Every comment **must** be prefixed with `🤖` and a criticality badge:
-
-| Tier | Badge | Meaning |
-|---|---|---|
-| Blocker | `🔴 **Blocker**` | Must fix before merge |
-| Should Fix | `🟠 **Should Fix**` | Important improvement |
-| Nice to Have | `🟡 **Nice to Have**` | Minor suggestion |
-| Nit | `🔵 **Nit**` | Style / wording |
-
-Example: `🤖 🔴 **Blocker**: Missing error handling for X — suggest wrapping in try/except.`
-
-## Post inline comments
-
-For each finding, post an inline comment on the PR (do not just write a local report):
-
-```bash
-# Get the latest commit SHA for the PR
-COMMIT_SHA=$(gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.head.sha')
-
-# Post an inline comment on a specific file/line
-gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments \
-  -f body="🤖 🔴 **Blocker**: <description>" \
-  -f commit_id="$COMMIT_SHA" \
-  -f path="<file path>" \
-  -F line=<line number>
-```
+- One todo per comment
+- For inline review comments: reply on existing threads. For PR conversation comments: post a new issue comment (API doesn't support threaded replies)
+- React to every comment: +1 addressed, -1 disagreed (with explanation)

.claude/skills/worktree-setup/SKILL.md

@@ -0,0 +1,45 @@
+---
+name: worktree-setup
+description: Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, generates Prisma client, and optionally starts the app (with port conflict resolution) or runs tests. TRIGGER when user asks to set up a worktree, work on a branch in isolation, or needs a separate environment for a branch or PR.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Worktree Setup
+
+## Preferred: Use Branchlet
+
+The repo has a `.branchlet.json` config — it handles env file copying, dependency installation, and Prisma generation automatically.
+
+```bash
+npm install -g branchlet                                      # install once
+branchlet create -n <name> -s <source-branch> -b <new-branch>
+branchlet list --json   # list all worktrees
+```
+
+## Manual Fallback
+
+If branchlet isn't available:
+
+1. `git worktree add ../<RepoName><N> <branch-name>`
+2. Copy `.env` files: `backend/.env`, `frontend/.env`, `autogpt_platform/.env`, `db/docker/.env`
+3. Install deps:
+   - `cd autogpt_platform/backend && poetry install && poetry run prisma generate`
+   - `cd autogpt_platform/frontend && pnpm install`
+
+## Running the App
+
+Free ports first — backend uses: 8001, 8002, 8003, 8005, 8006, 8007, 8008.
+
+```bash
+for port in 8001 8002 8003 8005 8006 8007 8008; do
+  lsof -ti :$port | xargs kill -9 2>/dev/null || true
+done
+cd <worktree>/autogpt_platform/backend && poetry run app
+```
+
+## CoPilot Testing Gotcha
+
+SDK mode spawns a Claude subprocess — **won't work inside Claude Code**. Set `CHAT_USE_CLAUDE_AGENT_SDK=false` in `backend/.env` to use baseline mode.

.claude/skills/worktree/SKILL.md

@@ -1,85 +0,0 @@
----
-name: worktree
-description: Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, and generates Prisma client. TRIGGER when user asks to set up a worktree, work on a branch in isolation, or needs a separate environment for a branch or PR.
-user-invocable: true
-args: "[name] — optional worktree name (e.g., 'AutoGPT7'). If omitted, uses next available AutoGPT<N>."
-metadata:
-  author: autogpt-team
-  version: "3.0.0"
----
-
-# Worktree Setup
-
-## Create the worktree
-
-Derive paths from the git toplevel. If a name is provided as argument, use it. Otherwise, check `git worktree list` and pick the next `AutoGPT<N>`.
-
-```bash
-ROOT=$(git rev-parse --show-toplevel)
-PARENT=$(dirname "$ROOT")
-
-# From an existing branch
-git worktree add "$PARENT/<NAME>" <branch-name>
-
-# From a new branch off dev
-git worktree add -b <new-branch> "$PARENT/<NAME>" dev
-```
-
-## Copy environment files
-
-Copy `.env` from the root worktree. Falls back to `.env.default` if `.env` doesn't exist.
-
-```bash
-ROOT=$(git rev-parse --show-toplevel)
-TARGET="$(dirname "$ROOT")/<NAME>"
-
-for envpath in autogpt_platform/backend autogpt_platform/frontend autogpt_platform; do
-  if [ -f "$ROOT/$envpath/.env" ]; then
-    cp "$ROOT/$envpath/.env" "$TARGET/$envpath/.env"
-  elif [ -f "$ROOT/$envpath/.env.default" ]; then
-    cp "$ROOT/$envpath/.env.default" "$TARGET/$envpath/.env"
-  fi
-done
-```
-
-## Install dependencies
-
-```bash
-TARGET="$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
-cd "$TARGET/autogpt_platform/autogpt_libs" && poetry install
-cd "$TARGET/autogpt_platform/backend" && poetry install && poetry run prisma generate
-cd "$TARGET/autogpt_platform/frontend" && pnpm install
-```
-
-Replace `<NAME>` with the actual worktree name (e.g., `AutoGPT7`).
-
-## Running the app (optional)
-
-Backend uses ports: 8001, 8002, 8003, 8005, 8006, 8007, 8008. Free them first if needed:
-
-```bash
-TARGET="$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
-for port in 8001 8002 8003 8005 8006 8007 8008; do
-  lsof -ti :$port | xargs kill -9 2>/dev/null || true
-done
-cd "$TARGET/autogpt_platform/backend" && poetry run app
-```
-
-## CoPilot testing
-
-SDK mode spawns a Claude subprocess — won't work inside Claude Code. Set `CHAT_USE_CLAUDE_AGENT_SDK=false` in `backend/.env` to use baseline mode.
-
-## Cleanup
-
-```bash
-# Replace <NAME> with the actual worktree name (e.g., AutoGPT7)
-git worktree remove "$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
-```
-
-## Alternative: Branchlet (optional)
-
-If [branchlet](https://www.npmjs.com/package/branchlet) is installed:
-
-```bash
-branchlet create -n <name> -s <source-branch> -b <new-branch>
-```

.github/workflows/platform-backend-ci.yml

@@ -5,14 +5,12 @@ on:
     branches: [master, dev, ci-test*]
     paths:
       - ".github/workflows/platform-backend-ci.yml"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/backend/**"
       - "autogpt_platform/autogpt_libs/**"
   pull_request:
     branches: [master, dev, release-*]
     paths:
       - ".github/workflows/platform-backend-ci.yml"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/backend/**"
       - "autogpt_platform/autogpt_libs/**"
   merge_group:

.github/workflows/platform-frontend-ci.yml

@@ -120,6 +120,175 @@ jobs:
           token: ${{ secrets.GITHUB_TOKEN }}
           exitOnceUploaded: true
 
+  e2e_test:
+    name: end-to-end tests
+    runs-on: big-boi
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          submodules: recursive
+
+      - name: Set up Platform - Copy default supabase .env
+        run: |
+          cp ../.env.default ../.env
+
+      - name: Set up Platform - Copy backend .env and set OpenAI API key
+        run: |
+          cp ../backend/.env.default ../backend/.env
+          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
+        env:
+          # Used by E2E test data script to generate embeddings for approved store agents
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+
+      - name: Set up Platform - Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+        with:
+          driver: docker-container
+          driver-opts: network=host
+
+      - name: Set up Platform - Expose GHA cache to docker buildx CLI
+        uses: crazy-max/ghaction-github-runtime@v4
+
+      - name: Set up Platform - Build Docker images (with cache)
+        working-directory: autogpt_platform
+        run: |
+          pip install pyyaml
+
+          # Resolve extends and generate a flat compose file that bake can understand
+          docker compose -f docker-compose.yml config > docker-compose.resolved.yml
+
+          # Add cache configuration to the resolved compose file
+          python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
+            --source docker-compose.resolved.yml \
+            --cache-from "type=gha" \
+            --cache-to "type=gha,mode=max" \
+            --backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend') }}" \
+            --frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src') }}" \
+            --git-ref "${{ github.ref }}"
+
+          # Build with bake using the resolved compose file (now includes cache config)
+          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Cache E2E test data
+        id: e2e-data-cache
+        uses: actions/cache@v5
+        with:
+          path: /tmp/e2e_test_data.sql
+          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-frontend-ci.yml') }}
+
+      - name: Set up Platform - Start Supabase DB + Auth
+        run: |
+          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
+          echo "Waiting for database to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
+          echo "Waiting for auth service to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
+
+      - name: Set up Platform - Run migrations
+        run: |
+          echo "Running migrations..."
+          docker compose -f ../docker-compose.resolved.yml run --rm migrate
+          echo "✅ Migrations completed"
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Load cached E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
+        run: |
+          echo "✅ Found cached E2E test data, restoring..."
+          {
+            echo "SET session_replication_role = 'replica';"
+            cat /tmp/e2e_test_data.sql
+            echo "SET session_replication_role = 'origin';"
+          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
+          # Refresh materialized views after restore
+          docker compose -f ../docker-compose.resolved.yml exec -T db \
+            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
+
+          echo "✅ E2E test data restored from cache"
+
+      - name: Set up Platform - Start (all other services)
+        run: |
+          docker compose -f ../docker-compose.resolved.yml up -d --no-build
+          echo "Waiting for rest_server to be ready..."
+          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Create E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
+        run: |
+          echo "Creating E2E test data..."
+          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
+          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
+            echo "❌ E2E test data creation failed!"
+            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
+            exit 1
+          }
+
+          # Dump auth.users + platform schema for cache (two separate dumps)
+          echo "Dumping database for cache..."
+          {
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --table='auth.users' postgres
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --schema=platform \
+              --exclude-table='platform._prisma_migrations' \
+              --exclude-table='platform.apscheduler_jobs' \
+              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
+              postgres
+          } > /tmp/e2e_test_data.sql
+
+          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
+
+      - name: Set up tests - Enable corepack
+        run: corepack enable
+
+      - name: Set up tests - Set up Node
+        uses: actions/setup-node@v6
+        with:
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Set up tests - Install dependencies
+        run: pnpm install --frozen-lockfile
+
+      - name: Set up tests - Install browser 'chromium'
+        run: pnpm playwright install --with-deps chromium
+
+      - name: Run Playwright tests
+        run: pnpm test:no-build
+        continue-on-error: false
+
+      - name: Upload Playwright report
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: playwright-report
+          path: playwright-report
+          if-no-files-found: ignore
+          retention-days: 3
+
+      - name: Upload Playwright test results
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: playwright-test-results
+          path: test-results
+          if-no-files-found: ignore
+          retention-days: 3
+
+      - name: Print Final Docker Compose logs
+        if: always()
+        run: docker compose -f ../docker-compose.resolved.yml logs
+
   integration_test:
     runs-on: ubuntu-latest
     needs: setup

.github/workflows/platform-fullstack-ci.yml

@@ -1,18 +1,14 @@
-name: AutoGPT Platform - Full-stack CI
+name: AutoGPT Platform - Frontend CI
 
 on:
   push:
     branches: [master, dev]
     paths:
       - ".github/workflows/platform-fullstack-ci.yml"
-      - ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/**"
   pull_request:
     paths:
       - ".github/workflows/platform-fullstack-ci.yml"
-      - ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/**"
   merge_group:
 
@@ -28,28 +24,42 @@ defaults:
 jobs:
   setup:
     runs-on: ubuntu-latest
+    outputs:
+      cache-key: ${{ steps.cache-key.outputs.key }}
 
     steps:
       - name: Checkout repository
         uses: actions/checkout@v6
 
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Install dependencies to populate cache
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Generate cache key
+        id: cache-key
+        run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
+
+      - name: Cache dependencies
+        uses: actions/cache@v5
+        with:
+          path: ~/.pnpm-store
+          key: ${{ steps.cache-key.outputs.key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
+            ${{ runner.os }}-pnpm-
+
+      - name: Install dependencies
         run: pnpm install --frozen-lockfile
 
-  check-api-types:
-    name: check API types
-    runs-on: ubuntu-latest
+  types:
+    runs-on: big-boi
     needs: setup
+    strategy:
+      fail-fast: false
 
     steps:
       - name: Checkout repository
@@ -57,256 +67,70 @@ jobs:
         with:
           submodules: recursive
 
-      # ------------------------ Backend setup ------------------------
-
-      - name: Set up Backend - Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.12"
-
-      - name: Set up Backend - Install Poetry
-        working-directory: autogpt_platform/backend
-        run: |
-          POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
-          echo "Installing Poetry version ${POETRY_VERSION}"
-          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$POETRY_VERSION python3 -
-
-      - name: Set up Backend - Set up dependency cache
-        uses: actions/cache@v5
-        with:
-          path: ~/.cache/pypoetry
-          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
-
-      - name: Set up Backend - Install dependencies
-        working-directory: autogpt_platform/backend
-        run: poetry install
-
-      - name: Set up Backend - Generate Prisma client
-        working-directory: autogpt_platform/backend
-        run: poetry run prisma generate && poetry run gen-prisma-stub
-
-      - name: Set up Frontend - Export OpenAPI schema from Backend
-        working-directory: autogpt_platform/backend
-        run: poetry run export-api-schema --output ../frontend/src/app/api/openapi.json
-
-      # ------------------------ Frontend setup ------------------------
-
-      - name: Set up Frontend - Enable corepack
-        run: corepack enable
-
-      - name: Set up Frontend - Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Set up Frontend - Install dependencies
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Copy default supabase .env
+        run: |
+          cp ../.env.default ../.env
+
+      - name: Copy backend .env
+        run: |
+          cp ../backend/.env.default ../backend/.env
+
+      - name: Run docker compose
+        run: |
+          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v5
+        with:
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-
+
+      - name: Install dependencies
         run: pnpm install --frozen-lockfile
 
-      - name: Set up Frontend - Format OpenAPI schema
-        id: format-schema
-        run: pnpm prettier --write ./src/app/api/openapi.json
+      - name: Setup .env
+        run: cp .env.default .env
+
+      - name: Wait for services to be ready
+        run: |
+          echo "Waiting for rest_server to be ready..."
+          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
+          echo "Waiting for database to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
+
+      - name: Generate API queries
+        run: pnpm generate:api:force
 
       - name: Check for API schema changes
         run: |
           if ! git diff --exit-code src/app/api/openapi.json; then
             echo "❌ API schema changes detected in src/app/api/openapi.json"
             echo ""
-            echo "The openapi.json file has been modified after exporting the API schema."
+            echo "The openapi.json file has been modified after running 'pnpm generate:api-all'."
             echo "This usually means changes have been made in the BE endpoints without updating the Frontend."
             echo "The API schema is now out of sync with the Front-end queries."
             echo ""
             echo "To fix this:"
-            echo "\nIn the backend directory:"
-            echo "1. Run 'poetry run export-api-schema --output ../frontend/src/app/api/openapi.json'"
-            echo "\nIn the frontend directory:"
-            echo "2. Run 'pnpm prettier --write src/app/api/openapi.json'"
-            echo "3. Run 'pnpm generate:api'"
-            echo "4. Run 'pnpm types'"
-            echo "5. Fix any TypeScript errors that may have been introduced"
-            echo "6. Commit and push your changes"
+            echo "1. Pull the backend 'docker compose pull && docker compose up -d --build --force-recreate'"
+            echo "2. Run 'pnpm generate:api' locally"
+            echo "3. Run 'pnpm types' locally"
+            echo "4. Fix any TypeScript errors that may have been introduced"
+            echo "5. Commit and push your changes"
             echo ""
             exit 1
           else
             echo "✅ No API schema changes detected"
           fi
 
-      - name: Set up Frontend - Generate API client
-        id: generate-api-client
-        run: pnpm orval --config ./orval.config.ts
-        # Continue with type generation & check even if there are schema changes
-        if: success() || (steps.format-schema.outcome == 'success')
-
-      - name: Check for TypeScript errors
+      - name: Run Typescript checks
         run: pnpm types
-        if: success() || (steps.generate-api-client.outcome == 'success')
-
-  e2e_test:
-    name: end-to-end tests
-    runs-on: big-boi
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v6
-        with:
-          submodules: recursive
-
-      - name: Set up Platform - Copy default supabase .env
-        run: |
-          cp ../.env.default ../.env
-
-      - name: Set up Platform - Copy backend .env and set OpenAI API key
-        run: |
-          cp ../backend/.env.default ../backend/.env
-          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
-        env:
-          # Used by E2E test data script to generate embeddings for approved store agents
-          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-
-      - name: Set up Platform - Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-        with:
-          driver: docker-container
-          driver-opts: network=host
-
-      - name: Set up Platform - Expose GHA cache to docker buildx CLI
-        uses: crazy-max/ghaction-github-runtime@v4
-
-      - name: Set up Platform - Build Docker images (with cache)
-        working-directory: autogpt_platform
-        run: |
-          pip install pyyaml
-
-          # Resolve extends and generate a flat compose file that bake can understand
-          docker compose -f docker-compose.yml config > docker-compose.resolved.yml
-
-          # Add cache configuration to the resolved compose file
-          python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
-            --source docker-compose.resolved.yml \
-            --cache-from "type=gha" \
-            --cache-to "type=gha,mode=max" \
-            --backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend/**') }}" \
-            --frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src/**') }}" \
-            --git-ref "${{ github.ref }}"
-
-          # Build with bake using the resolved compose file (now includes cache config)
-          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Cache E2E test data
-        id: e2e-data-cache
-        uses: actions/cache@v5
-        with:
-          path: /tmp/e2e_test_data.sql
-          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-fullstack-ci.yml') }}
-
-      - name: Set up Platform - Start Supabase DB + Auth
-        run: |
-          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
-          echo "Waiting for database to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
-          echo "Waiting for auth service to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
-
-      - name: Set up Platform - Run migrations
-        run: |
-          echo "Running migrations..."
-          docker compose -f ../docker-compose.resolved.yml run --rm migrate
-          echo "✅ Migrations completed"
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Load cached E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
-        run: |
-          echo "✅ Found cached E2E test data, restoring..."
-          {
-            echo "SET session_replication_role = 'replica';"
-            cat /tmp/e2e_test_data.sql
-            echo "SET session_replication_role = 'origin';"
-          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
-          # Refresh materialized views after restore
-          docker compose -f ../docker-compose.resolved.yml exec -T db \
-            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
-
-          echo "✅ E2E test data restored from cache"
-
-      - name: Set up Platform - Start (all other services)
-        run: |
-          docker compose -f ../docker-compose.resolved.yml up -d --no-build
-          echo "Waiting for rest_server to be ready..."
-          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Create E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
-        run: |
-          echo "Creating E2E test data..."
-          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
-          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
-            echo "❌ E2E test data creation failed!"
-            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
-            exit 1
-          }
-
-          # Dump auth.users + platform schema for cache (two separate dumps)
-          echo "Dumping database for cache..."
-          {
-            docker compose -f ../docker-compose.resolved.yml exec -T db \
-              pg_dump -U postgres --data-only --column-inserts \
-              --table='auth.users' postgres
-            docker compose -f ../docker-compose.resolved.yml exec -T db \
-              pg_dump -U postgres --data-only --column-inserts \
-              --schema=platform \
-              --exclude-table='platform._prisma_migrations' \
-              --exclude-table='platform.apscheduler_jobs' \
-              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
-              postgres
-          } > /tmp/e2e_test_data.sql
-
-          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
-
-      - name: Set up tests - Enable corepack
-        run: corepack enable
-
-      - name: Set up tests - Set up Node
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-
-      - name: Set up tests - Install dependencies
-        run: pnpm install --frozen-lockfile
-
-      - name: Set up tests - Install browser 'chromium'
-        run: pnpm playwright install --with-deps chromium
-
-      - name: Run Playwright tests
-        run: pnpm test:no-build
-        continue-on-error: false
-
-      - name: Upload Playwright report
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: playwright-report
-          path: playwright-report
-          if-no-files-found: ignore
-          retention-days: 3
-
-      - name: Upload Playwright test results
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: playwright-test-results
-          path: test-results
-          if-no-files-found: ignore
-          retention-days: 3
-
-      - name: Print Final Docker Compose logs
-        if: always()
-        run: docker compose -f ../docker-compose.resolved.yml logs

autogpt_platform/CLAUDE.md

@@ -60,12 +60,9 @@ AutoGPT Platform is a monorepo containing:
 
 ### 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` — top-level reviews
-- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments` — inline review comments
-- `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` — PR conversation comments
+- When the user runs /pr-comments or tries to fetch them, also run gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews to get the reviews
+- Use gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews/[review_id]/comments to get the review contents
+- Use gh api /repos/Significant-Gravitas/AutoGPT/issues/9924/comments to get the pr specific comments
 
 ### Conventional Commits
 

autogpt_platform/backend/CLAUDE.md

@@ -58,31 +58,10 @@ poetry run pytest path/to/test.py --snapshot-update
 - **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`)
-- **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
-- **Lazy `%s` logging** — `logger.info("Processing %s items", count)` not `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.
-
 ## 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`)
 
 ## Database Schema
 

autogpt_platform/backend/backend/api/features/chat/routes.py

@@ -8,7 +8,7 @@ from typing import Annotated
 from uuid import uuid4
 
 from autogpt_libs import auth
-from fastapi import APIRouter, HTTPException, Query, Response, Security
+from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
 from prisma.models import UserWorkspaceFile
 from pydantic import BaseModel, Field, field_validator
@@ -215,7 +215,7 @@ async def list_sessions(
             }
         except Exception:
             logger.warning(
-                "Failed to fetch processing status from Redis; defaulting to empty"
+                "Failed to fetch processing status from Redis; " "defaulting to empty"
             )
 
     return ListSessionsResponse(
@@ -237,7 +237,7 @@ async def list_sessions(
     "/sessions",
 )
 async def create_session(
-    user_id: Annotated[str, Security(auth.get_user_id)],
+    user_id: Annotated[str, Depends(auth.get_user_id)],
 ) -> CreateSessionResponse:
     """
     Create a new chat session.
@@ -356,7 +356,7 @@ async def update_session_title_route(
 )
 async def get_session(
     session_id: str,
-    user_id: Annotated[str, Security(auth.get_user_id)],
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
 ) -> SessionDetailResponse:
     """
     Retrieve the details of a specific chat session.
@@ -413,16 +413,17 @@ async def get_session(
     )
 
 
-@router.get(
-    "/usage",
-)
+@router.get("/usage")
 async def get_copilot_usage(
-    user_id: Annotated[str, Security(auth.get_user_id)],
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
 ) -> CoPilotUsageStatus:
     """Get CoPilot usage status for the authenticated user.
 
     Returns current token usage vs limits for daily and weekly windows.
     """
+    if not user_id:
+        raise HTTPException(status_code=401, detail="Authentication required")
+
     return await get_usage_status(
         user_id=user_id,
         daily_token_limit=config.daily_token_limit,
@@ -436,7 +437,7 @@ async def get_copilot_usage(
 )
 async def cancel_session_task(
     session_id: str,
-    user_id: Annotated[str, Security(auth.get_user_id)],
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
 ) -> CancelSessionResponse:
     """Cancel the active streaming task for a session.
 
@@ -481,7 +482,7 @@ async def cancel_session_task(
 async def stream_chat_post(
     session_id: str,
     request: StreamChatRequest,
-    user_id: str = Security(auth.get_user_id),
+    user_id: str | None = Depends(auth.get_user_id),
 ):
     """
     Stream chat responses for a session (POST with context support).
@@ -498,7 +499,7 @@ async def stream_chat_post(
     Args:
         session_id: The chat session identifier to associate with the streamed messages.
         request: Request body containing message, is_user_message, and optional context.
-        user_id: Authenticated user ID.
+        user_id: Optional authenticated user ID.
     Returns:
         StreamingResponse: SSE-formatted response chunks.
 
@@ -507,7 +508,9 @@ async def stream_chat_post(
     import time
 
     stream_start_time = time.perf_counter()
-    log_meta = {"component": "ChatStream", "session_id": session_id, "user_id": user_id}
+    log_meta = {"component": "ChatStream", "session_id": session_id}
+    if user_id:
+        log_meta["user_id"] = user_id
 
     logger.info(
         f"[TIMING] stream_chat_post STARTED, session={session_id}, "
@@ -525,9 +528,8 @@ async def stream_chat_post(
         },
     )
 
-    # Pre-turn rate limit check (token-based).
-    # check_rate_limit short-circuits internally when both limits are 0.
-    if user_id:
+    # Pre-turn rate limit check (token-based)
+    if user_id and (config.daily_token_limit > 0 or config.weekly_token_limit > 0):
         try:
             await check_rate_limit(
                 user_id=user_id,
@@ -771,7 +773,7 @@ async def stream_chat_post(
 )
 async def resume_session_stream(
     session_id: str,
-    user_id: str = Security(auth.get_user_id),
+    user_id: str | None = Depends(auth.get_user_id),
 ):
     """
     Resume an active stream for a session.

autogpt_platform/backend/backend/api/features/chat/routes_test.py

@@ -1,4 +1,4 @@
-"""Tests for chat API routes: session title update, file attachment validation, usage, rate limiting, and suggested prompts."""
+"""Tests for chat API routes: session title update, file attachment validation, usage, and suggested prompts."""
 
 from datetime import UTC, datetime, timedelta
 from unittest.mock import AsyncMock, MagicMock
@@ -252,77 +252,6 @@ def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
     assert call_kwargs["where"]["isDeleted"] is False
 
 
-# ─── Rate limit → 429 ─────────────────────────────────────────────────
-
-
-def test_stream_chat_returns_429_on_daily_rate_limit(mocker: pytest_mock.MockFixture):
-    """When check_rate_limit raises RateLimitExceeded for daily limit the endpoint returns 429."""
-    from backend.copilot.rate_limit import RateLimitExceeded
-
-    _mock_stream_internals(mocker)
-    # Ensure the rate-limit branch is entered by setting a non-zero limit.
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
-    mocker.patch(
-        "backend.api.features.chat.routes.check_rate_limit",
-        side_effect=RateLimitExceeded("daily", datetime.now(UTC) + timedelta(hours=1)),
-    )
-
-    response = client.post(
-        "/sessions/sess-1/stream",
-        json={"message": "hello"},
-    )
-    assert response.status_code == 429
-    assert "daily" in response.json()["detail"].lower()
-
-
-def test_stream_chat_returns_429_on_weekly_rate_limit(mocker: pytest_mock.MockFixture):
-    """When check_rate_limit raises RateLimitExceeded for weekly limit the endpoint returns 429."""
-    from backend.copilot.rate_limit import RateLimitExceeded
-
-    _mock_stream_internals(mocker)
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
-    resets_at = datetime.now(UTC) + timedelta(days=3)
-    mocker.patch(
-        "backend.api.features.chat.routes.check_rate_limit",
-        side_effect=RateLimitExceeded("weekly", resets_at),
-    )
-
-    response = client.post(
-        "/sessions/sess-1/stream",
-        json={"message": "hello"},
-    )
-    assert response.status_code == 429
-    detail = response.json()["detail"].lower()
-    assert "weekly" in detail
-    assert "resets in" in detail
-
-
-def test_stream_chat_429_includes_reset_time(mocker: pytest_mock.MockFixture):
-    """The 429 response detail should include the human-readable reset time."""
-    from backend.copilot.rate_limit import RateLimitExceeded
-
-    _mock_stream_internals(mocker)
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
-    mocker.patch(
-        "backend.api.features.chat.routes.check_rate_limit",
-        side_effect=RateLimitExceeded(
-            "daily", datetime.now(UTC) + timedelta(hours=2, minutes=30)
-        ),
-    )
-
-    response = client.post(
-        "/sessions/sess-1/stream",
-        json={"message": "hello"},
-    )
-    assert response.status_code == 429
-    detail = response.json()["detail"]
-    assert "2h" in detail
-    assert "Resets in" in detail
-
-
 # ─── Usage endpoint ───────────────────────────────────────────────────
 
 
@@ -391,17 +320,6 @@ def test_usage_uses_config_limits(
     )
 
 
-def test_usage_rejects_unauthenticated_request() -> None:
-    """GET /usage should return 401 when no valid JWT is provided."""
-    unauthenticated_app = fastapi.FastAPI()
-    unauthenticated_app.include_router(chat_routes.router)
-    unauthenticated_client = fastapi.testclient.TestClient(unauthenticated_app)
-
-    response = unauthenticated_client.get("/usage")
-
-    assert response.status_code == 401
-
-
 # ─── Suggested prompts endpoint ──────────────────────────────────────
 
 

autogpt_platform/backend/backend/blocks/github/commits.py

@@ -11,10 +11,7 @@ from backend.blocks._base import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
-from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
-from backend.util.file import parse_data_uri, resolve_media_content
-from backend.util.type import MediaFileType
 
 from ._api import get_api
 from ._auth import (
@@ -181,8 +178,7 @@ class FileOperation(StrEnum):
 
 class FileOperationInput(TypedDict):
     path: str
-    # MediaFileType is a str NewType — no runtime breakage for existing callers.
-    content: MediaFileType
+    content: str
     operation: FileOperation
 
 
@@ -279,11 +275,11 @@ class GithubMultiFileCommitBlock(Block):
         base_tree_sha = commit_data["tree"]["sha"]
 
         # 3. Build tree entries for each file operation (blobs created concurrently)
-        async def _create_blob(content: str, encoding: str = "utf-8") -> str:
+        async def _create_blob(content: str) -> str:
             blob_url = repo_url + "/git/blobs"
             blob_response = await api.post(
                 blob_url,
-                json={"content": content, "encoding": encoding},
+                json={"content": content, "encoding": "utf-8"},
             )
             return blob_response.json()["sha"]
 
@@ -305,19 +301,10 @@ class GithubMultiFileCommitBlock(Block):
             else:
                 upsert_files.append((path, file_op.get("content", "")))
 
-        # Create all blobs concurrently. Data URIs (from store_media_file)
-        # are sent as base64 blobs to preserve binary content.
+        # Create all blobs concurrently
         if upsert_files:
-
-            async def _make_blob(content: str) -> str:
-                parsed = parse_data_uri(content)
-                if parsed is not None:
-                    _, b64_payload = parsed
-                    return await _create_blob(b64_payload, encoding="base64")
-                return await _create_blob(content)
-
             blob_shas = await asyncio.gather(
-                *[_make_blob(content) for _, content in upsert_files]
+                *[_create_blob(content) for _, content in upsert_files]
             )
             for (path, _), blob_sha in zip(upsert_files, blob_shas):
                 tree_entries.append(
@@ -371,36 +358,15 @@ class GithubMultiFileCommitBlock(Block):
         input_data: Input,
         *,
         credentials: GithubCredentials,
-        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         try:
-            # Resolve media references (workspace://, data:, URLs) to data
-            # URIs so _make_blob can send binary content correctly.
-            resolved_files: list[FileOperationInput] = []
-            for file_op in input_data.files:
-                content = file_op.get("content", "")
-                operation = FileOperation(file_op.get("operation", "upsert"))
-                if operation != FileOperation.DELETE:
-                    content = await resolve_media_content(
-                        MediaFileType(content),
-                        execution_context,
-                        return_format="for_external_api",
-                    )
-                resolved_files.append(
-                    FileOperationInput(
-                        path=file_op["path"],
-                        content=MediaFileType(content),
-                        operation=operation,
-                    )
-                )
-
             sha, url = await self.multi_file_commit(
                 credentials,
                 input_data.repo_url,
                 input_data.branch,
                 input_data.commit_message,
-                resolved_files,
+                input_data.files,
             )
             yield "sha", sha
             yield "url", url

autogpt_platform/backend/backend/blocks/github/test_github_blocks.py

@@ -8,7 +8,6 @@ from backend.blocks.github.pull_requests import (
     GithubMergePullRequestBlock,
     prepare_pr_api_url,
 )
-from backend.data.execution import ExecutionContext
 from backend.util.exceptions import BlockExecutionError
 
 # ── prepare_pr_api_url tests ──
@@ -98,11 +97,7 @@ async def test_multi_file_commit_error_path():
         "credentials": TEST_CREDENTIALS_INPUT,
     }
     with pytest.raises(BlockExecutionError, match="ref update failed"):
-        async for _ in block.execute(
-            input_data,
-            credentials=TEST_CREDENTIALS,
-            execution_context=ExecutionContext(),
-        ):
+        async for _ in block.execute(input_data, credentials=TEST_CREDENTIALS):
             pass
 
 

autogpt_platform/backend/backend/copilot/baseline/service.py

@@ -18,11 +18,13 @@ from langfuse import propagate_attributes
 from backend.copilot.model import (
     ChatMessage,
     ChatSession,
+    Usage,
     get_chat_session,
     update_session_title,
     upsert_chat_session,
 )
 from backend.copilot.prompting import get_baseline_supplement
+from backend.copilot.rate_limit import record_token_usage
 from backend.copilot.response_model import (
     StreamBaseResponse,
     StreamError,
@@ -41,14 +43,17 @@ from backend.copilot.response_model import (
 from backend.copilot.service import (
     _build_system_prompt,
     _generate_session_title,
-    _get_openai_client,
+    client,
     config,
 )
-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
+from backend.util.prompt import (
+    compress_context,
+    estimate_token_count,
+    estimate_token_count_str,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -91,7 +96,7 @@ async def _compress_session_messages(
         result = await compress_context(
             messages=messages_dict,
             model=config.model,
-            client=_get_openai_client(),
+            client=client,
         )
     except Exception as e:
         logger.warning("[Baseline] Context compression with LLM failed: %s", e)
@@ -226,7 +231,6 @@ async def stream_chat_completion_baseline(
     # 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
     try:
         for _round in range(_MAX_TOOL_ROUNDS):
             # Open a new step for each LLM round
@@ -242,7 +246,7 @@ async def stream_chat_completion_baseline(
             )
             if tools:
                 create_kwargs["tools"] = tools
-            response = await _get_openai_client().chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
+            response = await client.chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
 
             # Accumulate streamed response (text + tool calls)
             round_text = ""
@@ -254,16 +258,13 @@ async def stream_chat_completion_baseline(
                 # 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 chunk.choices:
+                    continue
+                delta = chunk.choices[0].delta
                 if not delta:
                     continue
 
@@ -415,7 +416,6 @@ async def stream_chat_completion_baseline(
             )
 
     except Exception as e:
-        _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/step before emitting error
@@ -437,25 +437,12 @@ async def stream_chat_completion_baseline(
         # not honour stream_options={"include_usage": True}.
         # Count the full message list (system + history + turn) since
         # each API call sends the complete context window.
-        # NOTE: This estimates one round's prompt tokens. Multi-round tool-calling
-        # turns consume prompt tokens on each API call, so the total is underestimated.
-        # Skip fallback when an error occurred and no output was produced —
-        # charging rate-limit tokens for completely failed requests is unfair.
-        if (
-            turn_prompt_tokens == 0
-            and turn_completion_tokens == 0
-            and not (_stream_error and not assistant_text)
-        ):
-            from backend.util.prompt import (
-                estimate_token_count,
-                estimate_token_count_str,
-            )
-
+        if turn_prompt_tokens == 0 and turn_completion_tokens == 0:
             turn_prompt_tokens = max(
-                estimate_token_count(openai_messages, model=config.model), 1
+                estimate_token_count(openai_messages, model=config.model), 0
             )
-            turn_completion_tokens = estimate_token_count_str(
-                assistant_text, model=config.model
+            turn_completion_tokens = max(
+                estimate_token_count_str(assistant_text, model=config.model), 0
             )
             logger.info(
                 "[Baseline] No streaming usage reported; estimated tokens: "
@@ -464,17 +451,34 @@ async def stream_chat_completion_baseline(
                 turn_completion_tokens,
             )
 
-        # Persist token usage to session and record for rate limiting.
-        # NOTE: OpenRouter folds cached tokens into prompt_tokens, so we
-        # cannot break out cache_read/cache_creation weights. Users on the
-        # baseline path may be slightly over-counted vs the SDK path.
-        await persist_and_record_usage(
-            session=session,
-            user_id=user_id,
-            prompt_tokens=turn_prompt_tokens,
-            completion_tokens=turn_completion_tokens,
-            log_prefix="[Baseline]",
-        )
+        # Emit token usage and update session for persistence
+        if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
+            total_tokens = turn_prompt_tokens + turn_completion_tokens
+            session.usage.append(
+                Usage(
+                    prompt_tokens=turn_prompt_tokens,
+                    completion_tokens=turn_completion_tokens,
+                    total_tokens=total_tokens,
+                )
+            )
+            logger.info(
+                "[Baseline] Turn usage: prompt=%d, completion=%d, total=%d",
+                turn_prompt_tokens,
+                turn_completion_tokens,
+                total_tokens,
+            )
+            # Record for rate limiting counters
+            if user_id:
+                try:
+                    await record_token_usage(
+                        user_id=user_id,
+                        prompt_tokens=turn_prompt_tokens,
+                        completion_tokens=turn_completion_tokens,
+                    )
+                except Exception as usage_err:
+                    logger.warning(
+                        "[Baseline] Failed to record token usage: %s", usage_err
+                    )
 
         # Persist assistant response
         if assistant_text:
@@ -493,9 +497,9 @@ async def stream_chat_completion_baseline(
     # are harmless; on normal completion they reach the SSE stream.
     if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
         yield StreamUsage(
-            prompt_tokens=turn_prompt_tokens,
-            completion_tokens=turn_completion_tokens,
-            total_tokens=turn_prompt_tokens + turn_completion_tokens,
+            promptTokens=turn_prompt_tokens,
+            completionTokens=turn_completion_tokens,
+            totalTokens=turn_prompt_tokens + turn_completion_tokens,
         )
 
     yield StreamFinish()

autogpt_platform/backend/backend/copilot/config.py

@@ -71,17 +71,10 @@ class ChatConfig(BaseSettings):
     )
 
     # Rate limiting — token-based limits per day and per week.
-    # Per-turn token cost varies with context size: ~10-15K for early turns,
-    # ~30-50K mid-session, up to ~100K pre-compaction. Average across a
-    # session with compaction cycles is ~25-35K tokens/turn, so 2.5M daily
-    # allows ~70-100 turns/day.
-    # Checked at the HTTP layer (routes.py) before each turn.
-    #
-    # TODO: These are deploy-time constants applied identically to every user.
-    #  If per-user or per-plan limits are needed (e.g., free tier vs paid), these
-    #  must move to the database (e.g., a UserPlan table) and get_usage_status /
-    #  check_rate_limit would look up each user's specific limits instead of
-    #  reading config.daily_token_limit / config.weekly_token_limit.
+    # Each CoPilot turn consumes ~10-15K tokens (system prompt + tool schemas + response),
+    # so 2.5M daily allows ~170-250 turns/day which is reasonable for normal use.
+    # TODO: These are global deploy-time constants. For per-user or per-plan limits,
+    #  move to the database (e.g. UserPlan table) and look up in get_usage_status.
     daily_token_limit: int = Field(
         default=2_500_000,
         description="Max tokens per day, resets at midnight UTC (0 = unlimited)",

autogpt_platform/backend/backend/copilot/context.py

@@ -11,8 +11,6 @@ from contextvars import ContextVar
 from typing import TYPE_CHECKING
 
 from backend.copilot.model import ChatSession
-from backend.data.db_accessors import workspace_db
-from backend.util.workspace import WorkspaceManager
 
 if TYPE_CHECKING:
     from e2b import AsyncSandbox
@@ -84,17 +82,6 @@ def resolve_sandbox_path(path: str) -> str:
     return normalized
 
 
-async def get_workspace_manager(user_id: str, session_id: str) -> WorkspaceManager:
-    """Create a session-scoped :class:`WorkspaceManager`.
-
-    Placed here (rather than in ``tools/workspace_files``) so that modules
-    like ``sdk/file_ref`` can import it without triggering the heavy
-    ``tools/__init__`` import chain.
-    """
-    workspace = await workspace_db().get_or_create_workspace(user_id)
-    return WorkspaceManager(user_id, workspace.id, session_id)
-
-
 def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
     """Return True if *path* is within an allowed host-filesystem location.
 

autogpt_platform/backend/backend/copilot/model.py

@@ -101,10 +101,7 @@ class ChatSessionInfo(BaseModel):
             prisma_session.successfulAgentSchedules, default={}
         )
 
-        # 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
-        # completion totals. This is a known limitation.
+        # Calculate usage from token counts
         usage = []
         if prisma_session.totalPromptTokens or prisma_session.totalCompletionTokens:
             usage.append(

autogpt_platform/backend/backend/copilot/prompting.py

@@ -52,43 +52,11 @@ Examples:
 You can embed a reference inside any string argument, or use it as the entire
 value.  Multiple references in one argument are all expanded.
 
-**Structured data**: When the **entire** argument value is a single file
-reference (no surrounding text), the platform automatically parses the file
-content based on its extension or MIME type.  Supported formats: JSON, JSONL,
-CSV, TSV, YAML, TOML, Parquet, and Excel (.xlsx — first sheet only).
-For example, pass `@@agptfile:workspace://<id>` where the file is a `.csv` and
-the rows will be parsed into `list[list[str]]` automatically.  If the format is
-unrecognised or parsing fails, the content is returned as a plain string.
-Legacy `.xls` files are **not** supported — only the modern `.xlsx` format.
+**Type coercion**: The platform automatically coerces expanded string values
+to match the block's expected input types.  For example, if a block expects
+`list[list[str]]` and you pass a string containing a JSON array (e.g. from
+an @@agptfile: expansion), the string will be parsed into the correct type.
 
-**Type coercion**: The platform also coerces expanded values to match the
-block's expected input types.  For example, if a block expects `list[list[str]]`
-and the expanded value is a JSON string, it will be parsed into the correct type.
-
-### Media file inputs (format: "file")
-Some block inputs accept media files — their schema shows `"format": "file"`.
-These fields accept:
-- **`workspace://<file_id>`** or **`workspace://<file_id>#<mime>`** — preferred
-  for large files (images, videos, PDFs). The platform passes the reference
-  directly to the block without reading the content into memory.
-- **`data:<mime>;base64,<payload>`** — inline base64 data URI, suitable for
-  small files only.
-
-When a block input has `format: "file"`, **pass the `workspace://` URI
-directly as the value** (do NOT wrap it in `@@agptfile:`). This avoids large
-payloads in tool arguments and preserves binary content (images, videos)
-that would be corrupted by text encoding.
-
-Example — committing an image file to GitHub:
-```json
-{
-  "files": [{
-    "path": "docs/hero.png",
-    "content": "workspace://abc123#image/png",
-    "operation": "upsert"
-  }]
-}
-```
 
 ### Sub-agent tasks
 - When using the Task tool, NEVER set `run_in_background` to true.

autogpt_platform/backend/backend/copilot/rate_limit.py

@@ -11,14 +11,13 @@ import logging
 from datetime import UTC, datetime, timedelta
 
 from pydantic import BaseModel, Field
-from redis.exceptions import RedisError
 
 from backend.data.redis_client import get_redis_async
 
 logger = logging.getLogger(__name__)
 
 # Redis key prefixes
-_USAGE_KEY_PREFIX = "copilot:usage"
+_PREFIX = "copilot:usage"
 
 
 class UsageWindow(BaseModel):
@@ -57,6 +56,53 @@ class RateLimitExceeded(Exception):
         )
 
 
+def _daily_key(user_id: str, now: datetime | None = None) -> str:
+    if now is None:
+        now = datetime.now(UTC)
+    return f"{_PREFIX}:daily:{user_id}:{now.strftime('%Y-%m-%d')}"
+
+
+def _weekly_key(user_id: str, now: datetime | None = None) -> str:
+    if now is None:
+        now = datetime.now(UTC)
+    year, week, _ = now.isocalendar()
+    return f"{_PREFIX}:weekly:{user_id}:{year}-W{week:02d}"
+
+
+def _daily_reset_time(now: datetime | None = None) -> datetime:
+    """Calculate when the current daily window resets (next midnight UTC)."""
+    if now is None:
+        now = datetime.now(UTC)
+    return now.replace(hour=0, minute=0, second=0, microsecond=0) + timedelta(days=1)
+
+
+def _weekly_reset_time(now: datetime | None = None) -> datetime:
+    """Calculate when the current weekly window resets (next Monday 00:00 UTC).
+
+    On Monday itself, ``(7 - weekday) % 7`` is 0; the ``or 7`` fallback
+    pushes to *next* Monday so the current week's window stays open.
+    """
+    if now is None:
+        now = datetime.now(UTC)
+    days_until_monday = (7 - now.weekday()) % 7 or 7
+    return now.replace(hour=0, minute=0, second=0, microsecond=0) + timedelta(
+        days=days_until_monday
+    )
+
+
+async def _fetch_counters(user_id: str, now: datetime) -> tuple[int, int]:
+    """Fetch daily and weekly token counters from Redis.
+
+    Returns (daily_used, weekly_used). Returns (0, 0) if Redis is unavailable.
+    """
+    redis = await get_redis_async()
+    daily_raw, weekly_raw = await asyncio.gather(
+        redis.get(_daily_key(user_id, now=now)),
+        redis.get(_weekly_key(user_id, now=now)),
+    )
+    return int(daily_raw or 0), int(weekly_raw or 0)
+
+
 async def get_usage_status(
     user_id: str,
     daily_token_limit: int,
@@ -73,18 +119,13 @@ async def get_usage_status(
         CoPilotUsageStatus with current usage and limits.
     """
     now = datetime.now(UTC)
-    daily_used = 0
-    weekly_used = 0
     try:
-        redis = await get_redis_async()
-        daily_raw, weekly_raw = await asyncio.gather(
-            redis.get(_daily_key(user_id, now=now)),
-            redis.get(_weekly_key(user_id, now=now)),
+        daily_used, weekly_used = await _fetch_counters(user_id, now)
+    except Exception:
+        logger.warning(
+            "Redis unavailable for usage status, returning zeros", exc_info=True
         )
-        daily_used = int(daily_raw or 0)
-        weekly_used = int(weekly_raw or 0)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for usage status, returning zeros")
+        daily_used, weekly_used = 0, 0
 
     return CoPilotUsageStatus(
         daily=UsageWindow(
@@ -115,25 +156,15 @@ async def check_rate_limit(
 
     Fails open: if Redis is unavailable, allows the request.
     """
-    # Short-circuit: when both limits are 0 (unlimited) skip the Redis
-    # round-trip entirely.
-    if daily_token_limit <= 0 and weekly_token_limit <= 0:
-        return
-
     now = datetime.now(UTC)
     try:
-        redis = await get_redis_async()
-        daily_raw, weekly_raw = await asyncio.gather(
-            redis.get(_daily_key(user_id, now=now)),
-            redis.get(_weekly_key(user_id, now=now)),
+        daily_used, weekly_used = await _fetch_counters(user_id, now)
+    except Exception:
+        logger.warning(
+            "Redis unavailable for rate limit check, allowing request", exc_info=True
         )
-        daily_used = int(daily_raw or 0)
-        weekly_used = int(weekly_raw or 0)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for rate limit check, allowing request")
         return
 
-    # Worst-case overshoot: N concurrent requests × ~15K tokens each.
     if daily_token_limit > 0 and daily_used >= daily_token_limit:
         raise RateLimitExceeded("daily", _daily_reset_time(now=now))
 
@@ -168,11 +199,6 @@ async def record_token_usage(
         cache_read_tokens: Tokens served from prompt cache (10% cost).
         cache_creation_tokens: Tokens written to prompt cache (25% cost).
     """
-    prompt_tokens = max(0, prompt_tokens)
-    completion_tokens = max(0, completion_tokens)
-    cache_read_tokens = max(0, cache_read_tokens)
-    cache_creation_tokens = max(0, cache_creation_tokens)
-
     weighted_input = (
         prompt_tokens
         + round(cache_creation_tokens * 0.25)
@@ -200,11 +226,6 @@ async def record_token_usage(
     now = datetime.now(UTC)
     try:
         redis = await get_redis_async()
-        # transaction=False: these are independent INCRBY+EXPIRE pairs on
-        # separate keys — no cross-key atomicity needed.  Skipping
-        # MULTI/EXEC avoids the overhead.  If the connection drops between
-        # INCRBY and EXPIRE the key survives until the next date-based key
-        # rotation (daily/weekly), so the memory-leak risk is negligible.
         pipe = redis.pipeline(transaction=False)
 
         # Daily counter (expires at next midnight UTC)
@@ -224,43 +245,9 @@ async def record_token_usage(
         pipe.expire(w_key, max(seconds_until_weekly_reset, 1))
 
         await pipe.execute()
-    except (RedisError, ConnectionError, OSError):
+    except Exception:
         logger.warning(
             "Redis unavailable for recording token usage (tokens=%d)",
             total,
+            exc_info=True,
         )
-
-
-# ---------------------------------------------------------------------------
-# Private helpers
-# ---------------------------------------------------------------------------
-
-
-def _daily_key(user_id: str, now: datetime | None = None) -> str:
-    if now is None:
-        now = datetime.now(UTC)
-    return f"{_USAGE_KEY_PREFIX}:daily:{user_id}:{now.strftime('%Y-%m-%d')}"
-
-
-def _weekly_key(user_id: str, now: datetime | None = None) -> str:
-    if now is None:
-        now = datetime.now(UTC)
-    year, week, _ = now.isocalendar()
-    return f"{_USAGE_KEY_PREFIX}:weekly:{user_id}:{year}-W{week:02d}"
-
-
-def _daily_reset_time(now: datetime | None = None) -> datetime:
-    """Calculate when the current daily window resets (next midnight UTC)."""
-    if now is None:
-        now = datetime.now(UTC)
-    return now.replace(hour=0, minute=0, second=0, microsecond=0) + timedelta(days=1)
-
-
-def _weekly_reset_time(now: datetime | None = None) -> datetime:
-    """Calculate when the current weekly window resets (next Monday 00:00 UTC)."""
-    if now is None:
-        now = datetime.now(UTC)
-    days_until_monday = (7 - now.weekday()) % 7 or 7
-    return now.replace(hour=0, minute=0, second=0, microsecond=0) + timedelta(
-        days=days_until_monday
-    )

autogpt_platform/backend/backend/copilot/response_model.py

@@ -194,35 +194,21 @@ class StreamUsage(StreamBaseResponse):
     """
 
     type: ResponseType = ResponseType.USAGE
-    prompt_tokens: int = Field(
-        ...,
-        serialization_alias="promptTokens",
-        description="Number of uncached prompt tokens",
+    promptTokens: int = Field(..., description="Number of uncached prompt tokens")
+    completionTokens: int = Field(..., description="Number of completion tokens")
+    totalTokens: int = Field(
+        ..., description="Total number of tokens (raw, not weighted)"
     )
-    completion_tokens: int = Field(
-        ...,
-        serialization_alias="completionTokens",
-        description="Number of completion tokens",
+    cacheReadTokens: int = Field(
+        default=0, description="Prompt tokens served from cache (10% cost)"
     )
-    total_tokens: int = Field(
-        ...,
-        serialization_alias="totalTokens",
-        description="Total number of tokens (raw, not weighted)",
-    )
-    cache_read_tokens: int = Field(
-        default=0,
-        serialization_alias="cacheReadTokens",
-        description="Prompt tokens served from cache (10% cost)",
-    )
-    cache_creation_tokens: int = Field(
-        default=0,
-        serialization_alias="cacheCreationTokens",
-        description="Prompt tokens written to cache (25% cost)",
+    cacheCreationTokens: int = Field(
+        default=0, description="Prompt tokens written to cache (25% cost)"
     )
 
     def to_sse(self) -> str:
         """Emit as SSE comment so the AI SDK parser ignores it."""
-        return f": usage {self.model_dump_json(exclude_none=True, by_alias=True)}\n\n"
+        return f": usage {self.model_dump_json(exclude_none=True)}\n\n"
 
 
 class StreamError(StreamBaseResponse):

autogpt_platform/backend/backend/copilot/sdk/__init__.py

@@ -3,45 +3,12 @@
 This module provides the integration layer between the Claude Agent SDK
 and the existing CoPilot tool system, enabling drop-in replacement of
 the current LLM orchestration with the battle-tested Claude Agent SDK.
-
-Submodule imports are deferred via PEP 562 ``__getattr__`` to break a
-circular import cycle::
-
-    sdk/__init__ → tool_adapter → copilot.tools (TOOL_REGISTRY)
-    copilot.tools → run_block → sdk.file_ref  (no cycle here, but…)
-    sdk/__init__ → service → copilot.prompting → copilot.tools  (cycle!)
-
-``tool_adapter`` uses ``TOOL_REGISTRY`` at **module level** to build the
-static ``COPILOT_TOOL_NAMES`` list, so the import cannot be deferred to
-function scope without a larger refactor (moving tool-name registration
-to a separate lightweight module).  The lazy-import pattern here is the
-least invasive way to break the cycle while keeping module-level constants
-intact.
 """
 
-from typing import Any
+from .service import stream_chat_completion_sdk
+from .tool_adapter import create_copilot_mcp_server
 
 __all__ = [
     "stream_chat_completion_sdk",
     "create_copilot_mcp_server",
 ]
-
-# Dispatch table for PEP 562 lazy imports.  Each entry is a (module, attr)
-# pair so new exports can be added without touching __getattr__ itself.
-_LAZY_IMPORTS: dict[str, tuple[str, str]] = {
-    "stream_chat_completion_sdk": (".service", "stream_chat_completion_sdk"),
-    "create_copilot_mcp_server": (".tool_adapter", "create_copilot_mcp_server"),
-}
-
-
-def __getattr__(name: str) -> Any:
-    entry = _LAZY_IMPORTS.get(name)
-    if entry is not None:
-        module_path, attr = entry
-        import importlib
-
-        module = importlib.import_module(module_path, package=__name__)
-        value = getattr(module, attr)
-        globals()[name] = value
-        return value
-    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

autogpt_platform/backend/backend/copilot/sdk/compaction.py

@@ -11,7 +11,7 @@ persistence, and the ``CompactionTracker`` state machine.
 import asyncio
 import logging
 import uuid
-from dataclasses import dataclass, field
+from collections.abc import Callable
 
 from ..constants import COMPACTION_DONE_MSG, COMPACTION_TOOL_NAME
 from ..model import ChatMessage, ChatSession
@@ -27,19 +27,6 @@ from ..response_model import (
 logger = logging.getLogger(__name__)
 
 
-@dataclass
-class CompactionResult:
-    """Result of emit_end_if_ready — bundles events with compaction metadata.
-
-    Eliminates the need for separate ``compaction_just_ended`` checks,
-    preventing TOCTOU races between the emit call and the flag read.
-    """
-
-    events: list[StreamBaseResponse] = field(default_factory=list)
-    just_ended: bool = False
-    transcript_path: str = ""
-
-
 # ---------------------------------------------------------------------------
 # Event builders (private — use CompactionTracker or compaction_events)
 # ---------------------------------------------------------------------------
@@ -190,22 +177,11 @@ class CompactionTracker:
         self._start_emitted = False
         self._done = False
         self._tool_call_id = ""
-        self._transcript_path: str = ""
 
-    def on_compact(self, transcript_path: str = "") -> None:
-        """Callback for the PreCompact hook. Stores transcript_path."""
-        if (
-            self._transcript_path
-            and transcript_path
-            and self._transcript_path != transcript_path
-        ):
-            logger.warning(
-                "[Compaction] Overwriting transcript_path %s -> %s",
-                self._transcript_path,
-                transcript_path,
-            )
-        self._transcript_path = transcript_path
-        self._compact_start.set()
+    @property
+    def on_compact(self) -> Callable[[], None]:
+        """Callback for the PreCompact hook."""
+        return self._compact_start.set
 
     # ------------------------------------------------------------------
     # Pre-query compaction
@@ -222,10 +198,10 @@ class CompactionTracker:
 
     def reset_for_query(self) -> None:
         """Reset per-query state before a new SDK query."""
+        self._compact_start.clear()
         self._done = False
         self._start_emitted = False
         self._tool_call_id = ""
-        self._transcript_path = ""
 
     def emit_start_if_ready(self) -> list[StreamBaseResponse]:
         """If the PreCompact hook fired, emit start events (spinning tool)."""
@@ -236,20 +212,15 @@ class CompactionTracker:
             return _start_events(self._tool_call_id)
         return []
 
-    async def emit_end_if_ready(self, session: ChatSession) -> CompactionResult:
-        """If compaction is in progress, emit end events and persist.
-
-        Returns a ``CompactionResult`` with ``just_ended=True`` and the
-        captured ``transcript_path`` when a compaction cycle completes.
-        This avoids a separate flag check (TOCTOU-safe).
-        """
+    async def emit_end_if_ready(self, session: ChatSession) -> list[StreamBaseResponse]:
+        """If compaction is in progress, emit end events and persist."""
         # Yield so pending hook tasks can set compact_start
         await asyncio.sleep(0)
 
         if self._done:
-            return CompactionResult()
+            return []
         if not self._start_emitted and not self._compact_start.is_set():
-            return CompactionResult()
+            return []
 
         if self._start_emitted:
             # Close the open spinner
@@ -262,12 +233,8 @@ class CompactionTracker:
                 COMPACTION_DONE_MSG, tool_call_id=persist_id
             )
 
-        transcript_path = self._transcript_path
         self._compact_start.clear()
         self._start_emitted = False
         self._done = True
-        self._transcript_path = ""
         _persist(session, persist_id, COMPACTION_DONE_MSG)
-        return CompactionResult(
-            events=done_events, just_ended=True, transcript_path=transcript_path
-        )
+        return done_events

autogpt_platform/backend/backend/copilot/sdk/compaction_test.py

@@ -195,11 +195,10 @@ class TestCompactionTracker:
         session = _make_session()
         tracker.on_compact()
         tracker.emit_start_if_ready()
-        result = await tracker.emit_end_if_ready(session)
-        assert result.just_ended is True
-        assert len(result.events) == 2
-        assert isinstance(result.events[0], StreamToolOutputAvailable)
-        assert isinstance(result.events[1], StreamFinishStep)
+        evts = await tracker.emit_end_if_ready(session)
+        assert len(evts) == 2
+        assert isinstance(evts[0], StreamToolOutputAvailable)
+        assert isinstance(evts[1], StreamFinishStep)
         # Should persist
         assert len(session.messages) == 2
 
@@ -211,32 +210,28 @@ class TestCompactionTracker:
         session = _make_session()
         tracker.on_compact()
         # Don't call emit_start_if_ready
-        result = await tracker.emit_end_if_ready(session)
-        assert result.just_ended is True
-        assert len(result.events) == 5  # Full self-contained event
-        assert isinstance(result.events[0], StreamStartStep)
+        evts = await tracker.emit_end_if_ready(session)
+        assert len(evts) == 5  # Full self-contained event
+        assert isinstance(evts[0], StreamStartStep)
         assert len(session.messages) == 2
 
     @pytest.mark.asyncio
-    async def test_emit_end_no_op_when_no_new_compaction(self):
+    async def test_emit_end_no_op_when_done(self):
         tracker = CompactionTracker()
         session = _make_session()
         tracker.on_compact()
         tracker.emit_start_if_ready()
-        result1 = await tracker.emit_end_if_ready(session)
-        assert result1.just_ended is True
-        # Second call should be no-op (no new on_compact)
-        result2 = await tracker.emit_end_if_ready(session)
-        assert result2.just_ended is False
-        assert result2.events == []
+        await tracker.emit_end_if_ready(session)
+        # Second call should be no-op
+        evts = await tracker.emit_end_if_ready(session)
+        assert evts == []
 
     @pytest.mark.asyncio
     async def test_emit_end_no_op_when_nothing_happened(self):
         tracker = CompactionTracker()
         session = _make_session()
-        result = await tracker.emit_end_if_ready(session)
-        assert result.just_ended is False
-        assert result.events == []
+        evts = await tracker.emit_end_if_ready(session)
+        assert evts == []
 
     def test_emit_pre_query(self):
         tracker = CompactionTracker()
@@ -251,29 +246,20 @@ class TestCompactionTracker:
         tracker._done = True
         tracker._start_emitted = True
         tracker._tool_call_id = "old"
-        tracker._transcript_path = "/some/path"
         tracker.reset_for_query()
         assert tracker._done is False
         assert tracker._start_emitted is False
         assert tracker._tool_call_id == ""
-        assert tracker._transcript_path == ""
 
     @pytest.mark.asyncio
-    async def test_pre_query_blocks_sdk_compaction_until_reset(self):
-        """After pre-query compaction, SDK compaction is blocked until
-        reset_for_query is called."""
+    async def test_pre_query_blocks_sdk_compaction(self):
+        """After pre-query compaction, SDK compaction events are suppressed."""
         tracker = CompactionTracker()
         session = _make_session()
         tracker.emit_pre_query(session)
         tracker.on_compact()
-        # _done is True so emit_start_if_ready is blocked
         evts = tracker.emit_start_if_ready()
-        assert evts == []
-        # Reset clears _done, allowing subsequent compaction
-        tracker.reset_for_query()
-        tracker.on_compact()
-        evts = tracker.emit_start_if_ready()
-        assert len(evts) == 3
+        assert evts == []  # _done blocks it
 
     @pytest.mark.asyncio
     async def test_reset_allows_new_compaction(self):
@@ -293,9 +279,9 @@ class TestCompactionTracker:
         session = _make_session()
         tracker.on_compact()
         start_evts = tracker.emit_start_if_ready()
-        result = await tracker.emit_end_if_ready(session)
+        end_evts = await tracker.emit_end_if_ready(session)
         start_evt = start_evts[1]
-        end_evt = result.events[0]
+        end_evt = end_evts[0]
         assert isinstance(start_evt, StreamToolInputStart)
         assert isinstance(end_evt, StreamToolOutputAvailable)
         assert start_evt.toolCallId == end_evt.toolCallId
@@ -303,105 +289,3 @@ class TestCompactionTracker:
         tool_calls = session.messages[0].tool_calls
         assert tool_calls is not None
         assert tool_calls[0]["id"] == start_evt.toolCallId
-
-    @pytest.mark.asyncio
-    async def test_multiple_compactions_within_query(self):
-        """Two mid-stream compactions within a single query both trigger."""
-        tracker = CompactionTracker()
-        session = _make_session()
-
-        # First compaction cycle
-        tracker.on_compact("/path/1")
-        tracker.emit_start_if_ready()
-        result1 = await tracker.emit_end_if_ready(session)
-        assert result1.just_ended is True
-        assert len(result1.events) == 2
-        assert result1.transcript_path == "/path/1"
-
-        # Second compaction cycle (should NOT be blocked — _done resets
-        # because emit_end_if_ready sets it True, but the next on_compact
-        # + emit_start_if_ready checks !_done which IS True now.
-        # So we need reset_for_query between queries, but within a single
-        # query multiple compactions work because _done blocks emit_start
-        # until the next message arrives, at which point emit_end detects it)
-        #
-        # Actually: _done=True blocks emit_start_if_ready, so we need
-        # the stream loop to reset. In practice service.py doesn't call
-        # reset between compactions within the same query — let's verify
-        # the actual behavior.
-        tracker.on_compact("/path/2")
-        # _done is True from first compaction, so start is blocked
-        start_evts = tracker.emit_start_if_ready()
-        assert start_evts == []
-        # But emit_end returns no-op because _done is True
-        result2 = await tracker.emit_end_if_ready(session)
-        assert result2.just_ended is False
-
-    @pytest.mark.asyncio
-    async def test_multiple_compactions_with_intervening_message(self):
-        """Multiple compactions work when the stream loop processes messages between them.
-
-        In the real service.py flow:
-        1. PreCompact fires → on_compact()
-        2. emit_start shows spinner
-        3. Next message arrives → emit_end completes compaction (_done=True)
-        4. Stream continues processing messages...
-        5. If a second PreCompact fires, _done=True blocks emit_start
-        6. But the next message triggers emit_end, which sees _done=True → no-op
-        7. The stream loop needs to detect this and handle accordingly
-
-        The actual flow for multiple compactions within a query requires
-        _done to be cleared between them. The service.py code uses
-        CompactionResult.just_ended to trigger replace_entries, and _done
-        stays True until reset_for_query.
-        """
-        tracker = CompactionTracker()
-        session = _make_session()
-
-        # First compaction
-        tracker.on_compact("/path/1")
-        tracker.emit_start_if_ready()
-        result1 = await tracker.emit_end_if_ready(session)
-        assert result1.just_ended is True
-        assert result1.transcript_path == "/path/1"
-
-        # Simulate reset between queries
-        tracker.reset_for_query()
-
-        # Second compaction in new query
-        tracker.on_compact("/path/2")
-        start_evts = tracker.emit_start_if_ready()
-        assert len(start_evts) == 3
-        result2 = await tracker.emit_end_if_ready(session)
-        assert result2.just_ended is True
-        assert result2.transcript_path == "/path/2"
-
-    def test_on_compact_stores_transcript_path(self):
-        tracker = CompactionTracker()
-        tracker.on_compact("/some/path.jsonl")
-        assert tracker._transcript_path == "/some/path.jsonl"
-
-    @pytest.mark.asyncio
-    async def test_emit_end_returns_transcript_path(self):
-        """CompactionResult includes the transcript_path from on_compact."""
-        tracker = CompactionTracker()
-        session = _make_session()
-        tracker.on_compact("/my/session.jsonl")
-        tracker.emit_start_if_ready()
-        result = await tracker.emit_end_if_ready(session)
-        assert result.just_ended is True
-        assert result.transcript_path == "/my/session.jsonl"
-        # transcript_path is cleared after emit_end
-        assert tracker._transcript_path == ""
-
-    @pytest.mark.asyncio
-    async def test_emit_end_clears_transcript_path(self):
-        """After emit_end, _transcript_path is reset so it doesn't leak to
-        subsequent non-compaction emit_end calls."""
-        tracker = CompactionTracker()
-        session = _make_session()
-        tracker.on_compact("/first/path.jsonl")
-        tracker.emit_start_if_ready()
-        await tracker.emit_end_if_ready(session)
-        # After compaction, _transcript_path is cleared
-        assert tracker._transcript_path == ""

autogpt_platform/backend/backend/copilot/sdk/e2e_compaction_test.py

@@ -7,8 +7,8 @@ JSONL session files — no SDK subprocess needed. Exercises:
   2. User query appended, assistant response streamed
   3. PreCompact hook fires → CompactionTracker.on_compact()
   4. Next message → emit_start_if_ready() yields spinner events
-  5. Message after that → emit_end_if_ready() returns CompactionResult
-  6. read_compacted_entries() reads the CLI session file
+  5. Message after that → emit_end_if_ready() returns end events
+  6. _read_compacted_entries() reads the CLI session file
   7. TranscriptBuilder.replace_entries() syncs state
   8. More messages appended post-compaction
   9. to_jsonl() exports full state for upload
@@ -16,6 +16,7 @@ JSONL session files — no SDK subprocess needed. Exercises:
 """
 
 import asyncio
+from pathlib import Path
 
 from backend.copilot.model import ChatSession
 from backend.copilot.response_model import (
@@ -26,10 +27,7 @@ from backend.copilot.response_model import (
     StreamToolOutputAvailable,
 )
 from backend.copilot.sdk.compaction import CompactionTracker
-from backend.copilot.sdk.transcript import (
-    read_compacted_entries,
-    strip_progress_entries,
-)
+from backend.copilot.sdk.transcript import strip_progress_entries
 from backend.copilot.sdk.transcript_builder import TranscriptBuilder
 from backend.util import json
 
@@ -43,6 +41,32 @@ def _run(coro):
     return asyncio.run(coro)
 
 
+def _read_compacted_entries(path: str) -> tuple[list[dict], str] | None:
+    """Test-only: read compacted entries from a session JSONL file.
+
+    Returns (parsed_dicts, jsonl_string) from the first ``isCompactSummary``
+    entry onward, or ``None`` if no summary is found.
+    """
+    content = Path(path).read_text()
+    lines = content.strip().split("\n")
+    compact_idx: int | None = None
+    parsed: list[dict] = []
+    raw_lines: list[str] = []
+    for line in lines:
+        if not line.strip():
+            continue
+        entry = json.loads(line, fallback=None)
+        if not isinstance(entry, dict):
+            continue
+        parsed.append(entry)
+        raw_lines.append(line.strip())
+        if compact_idx is None and entry.get("isCompactSummary"):
+            compact_idx = len(parsed) - 1
+    if compact_idx is None:
+        return None
+    return parsed[compact_idx:], "\n".join(raw_lines[compact_idx:]) + "\n"
+
+
 # ---------------------------------------------------------------------------
 # Fixtures: realistic CLI session file content
 # ---------------------------------------------------------------------------
@@ -205,7 +229,7 @@ class TestCompactionE2E:
         path.write_text(_make_jsonl(*entries))
         return path
 
-    def test_full_compaction_lifecycle(self, tmp_path, monkeypatch):
+    def test_full_compaction_lifecycle(self, tmp_path):
         """Simulate the complete service.py compaction flow.
 
         Timeline:
@@ -216,18 +240,14 @@ class TestCompactionE2E:
         5. Mid-stream: PreCompact hook fires (context too large)
         6. CLI writes compaction summary to session file
         7. Next SDK message → emit_start (spinner)
-        8. Following message → emit_end (CompactionResult)
-        9. read_compacted_entries reads the session file
+        8. Following message → emit_end (end events)
+        9. _read_compacted_entries reads the session file
         10. replace_entries syncs TranscriptBuilder
         11. More assistant messages appended
         12. Export → upload → next turn downloads it
         """
-        # --- Setup CLI projects directory ---
-        config_dir = tmp_path / "config"
-        projects_dir = config_dir / "projects"
-        session_dir = projects_dir / "proj"
+        session_dir = tmp_path / "session"
         session_dir.mkdir(parents=True)
-        monkeypatch.setenv("CLAUDE_CONFIG_DIR", str(config_dir))
 
         # --- Step 1-2: Load "downloaded" transcript from previous turn ---
         previous_transcript = _make_jsonl(
@@ -276,7 +296,8 @@ class TestCompactionE2E:
         # --- Step 7: CompactionTracker receives PreCompact hook ---
         tracker = CompactionTracker()
         session = ChatSession.new(user_id="test-user")
-        tracker.on_compact(str(session_file))
+        # on_compact is a property returning Event.set callable
+        tracker.on_compact()
 
         # --- Step 8: Next SDK message arrives → emit_start ---
         start_events = tracker.emit_start_if_ready()
@@ -290,31 +311,30 @@ class TestCompactionE2E:
         assert tool_call_id.startswith("compaction-")
 
         # --- Step 9: Following message → emit_end ---
-        result = _run(tracker.emit_end_if_ready(session))
-        assert result.just_ended is True
-        assert result.transcript_path == str(session_file)
-        assert len(result.events) == 2
-        assert isinstance(result.events[0], StreamToolOutputAvailable)
-        assert isinstance(result.events[1], StreamFinishStep)
+        end_events = _run(tracker.emit_end_if_ready(session))
+        assert len(end_events) == 2
+        assert isinstance(end_events[0], StreamToolOutputAvailable)
+        assert isinstance(end_events[1], StreamFinishStep)
         # Verify same tool_call_id
-        assert result.events[0].toolCallId == tool_call_id
+        assert end_events[0].toolCallId == tool_call_id
 
         # Session should have compaction messages persisted
         assert len(session.messages) == 2
         assert session.messages[0].role == "assistant"
         assert session.messages[1].role == "tool"
 
-        # --- Step 10: read_compacted_entries + replace_entries ---
-        compacted = read_compacted_entries(str(session_file))
-        assert compacted is not None
+        # --- Step 10: _read_compacted_entries + replace_entries ---
+        result = _read_compacted_entries(str(session_file))
+        assert result is not None
+        compacted_dicts, compacted_jsonl = result
         # Should have: COMPACT_SUMMARY + POST_COMPACT_ASST + USER_3 + ASST_3
-        assert len(compacted) == 4
-        assert compacted[0]["uuid"] == "cs1"
-        assert compacted[0]["isCompactSummary"] is True
+        assert len(compacted_dicts) == 4
+        assert compacted_dicts[0]["uuid"] == "cs1"
+        assert compacted_dicts[0]["isCompactSummary"] is True
 
-        # Replace builder state with compacted entries
+        # Replace builder state with compacted JSONL
         old_count = builder.entry_count
-        builder.replace_entries(compacted)
+        builder.replace_entries(compacted_jsonl)
         assert builder.entry_count == 4  # Only compacted entries
         assert builder.entry_count < old_count  # Compaction reduced entries
 
@@ -367,13 +387,10 @@ class TestCompactionE2E:
         # Parented to the last entry from previous turn
         assert last_entry["parentUuid"] == output_entries[-1]["uuid"]
 
-    def test_double_compaction_within_session(self, tmp_path, monkeypatch):
+    def test_double_compaction_within_session(self, tmp_path):
         """Two compactions in the same session (across reset_for_query)."""
-        config_dir = tmp_path / "config"
-        projects_dir = config_dir / "projects"
-        session_dir = projects_dir / "proj"
+        session_dir = tmp_path / "session"
         session_dir.mkdir(parents=True)
-        monkeypatch.setenv("CLAUDE_CONFIG_DIR", str(config_dir))
 
         tracker = CompactionTracker()
         session = ChatSession.new(user_id="test")
@@ -399,14 +416,15 @@ class TestCompactionE2E:
         file1 = session_dir / "session1.jsonl"
         file1.write_text(_make_jsonl(first_summary, first_post))
 
-        tracker.on_compact(str(file1))
+        tracker.on_compact()
         tracker.emit_start_if_ready()
-        result1 = _run(tracker.emit_end_if_ready(session))
-        assert result1.just_ended is True
+        end_events1 = _run(tracker.emit_end_if_ready(session))
+        assert len(end_events1) == 2  # output + finish
 
-        compacted1 = read_compacted_entries(str(file1))
-        assert compacted1 is not None
-        builder.replace_entries(compacted1)
+        result1_entries = _read_compacted_entries(str(file1))
+        assert result1_entries is not None
+        _, compacted1_jsonl = result1_entries
+        builder.replace_entries(compacted1_jsonl)
         assert builder.entry_count == 2
 
         # --- Reset for second query ---
@@ -431,14 +449,15 @@ class TestCompactionE2E:
         file2 = session_dir / "session2.jsonl"
         file2.write_text(_make_jsonl(second_summary, second_post))
 
-        tracker.on_compact(str(file2))
+        tracker.on_compact()
         tracker.emit_start_if_ready()
-        result2 = _run(tracker.emit_end_if_ready(session))
-        assert result2.just_ended is True
+        end_events2 = _run(tracker.emit_end_if_ready(session))
+        assert len(end_events2) == 2  # output + finish
 
-        compacted2 = read_compacted_entries(str(file2))
-        assert compacted2 is not None
-        builder.replace_entries(compacted2)
+        result2_entries = _read_compacted_entries(str(file2))
+        assert result2_entries is not None
+        _, compacted2_jsonl = result2_entries
+        builder.replace_entries(compacted2_jsonl)
         assert builder.entry_count == 2  # Only second compaction entries
 
         # Export and verify
@@ -447,9 +466,7 @@ class TestCompactionE2E:
         assert entries[0]["uuid"] == "cs-second"
         assert entries[0].get("isCompactSummary") is True
 
-    def test_strip_progress_then_load_then_compact_roundtrip(
-        self, tmp_path, monkeypatch
-    ):
+    def test_strip_progress_then_load_then_compact_roundtrip(self, tmp_path):
         """Full pipeline: strip → load → compact → replace → export → reload.
 
         This tests the exact sequence that happens across two turns:
@@ -458,11 +475,8 @@ class TestCompactionE2E:
         Turn 2: Download → load_previous → compaction fires → replace → export
         Turn 3: Download the Turn 2 export → load_previous (roundtrip)
         """
-        config_dir = tmp_path / "config"
-        projects_dir = config_dir / "projects"
-        session_dir = projects_dir / "proj"
+        session_dir = tmp_path / "session"
         session_dir.mkdir(parents=True)
-        monkeypatch.setenv("CLAUDE_CONFIG_DIR", str(config_dir))
 
         # --- Turn 1: SDK produces raw transcript ---
         raw_content = _make_jsonl(
@@ -511,9 +525,10 @@ class TestCompactionE2E:
             ],
         )
 
-        compacted = read_compacted_entries(str(session_file))
-        assert compacted is not None
-        builder.replace_entries(compacted)
+        result = _read_compacted_entries(str(session_file))
+        assert result is not None
+        _, compacted_jsonl = result
+        builder.replace_entries(compacted_jsonl)
 
         # Append post-compaction message
         builder.append_user("Thanks!")

autogpt_platform/backend/backend/copilot/sdk/file_ref.py

@@ -41,20 +41,12 @@ from typing import Any
 from backend.copilot.context import (
     get_current_sandbox,
     get_sdk_cwd,
-    get_workspace_manager,
     is_allowed_local_path,
     resolve_sandbox_path,
 )
 from backend.copilot.model import ChatSession
+from backend.copilot.tools.workspace_files import get_manager
 from backend.util.file import parse_workspace_uri
-from backend.util.file_content_parser import (
-    BINARY_FORMATS,
-    MIME_TO_FORMAT,
-    PARSE_EXCEPTIONS,
-    infer_format_from_uri,
-    parse_file_content,
-)
-from backend.util.type import MediaFileType
 
 
 class FileRefExpansionError(Exception):
@@ -82,8 +74,6 @@ _FILE_REF_RE = re.compile(
 _MAX_EXPAND_CHARS = 200_000
 # Maximum total characters across all @@agptfile: expansions in one string.
 _MAX_TOTAL_EXPAND_CHARS = 1_000_000
-# Maximum raw byte size for bare ref structured parsing (10 MB).
-_MAX_BARE_REF_BYTES = 10_000_000
 
 
 @dataclass
@@ -93,11 +83,6 @@ class FileRef:
     end_line: int | None  # 1-indexed, inclusive
 
 
-# ---------------------------------------------------------------------------
-# Public API  (top-down: main functions first, helpers below)
-# ---------------------------------------------------------------------------
-
-
 def parse_file_ref(text: str) -> FileRef | None:
     """Return a :class:`FileRef` if *text* is a bare file reference token.
 
@@ -119,6 +104,17 @@ def parse_file_ref(text: str) -> FileRef | None:
     return FileRef(uri=m.group(1), start_line=start, end_line=end)
 
 
+def _apply_line_range(text: str, start: int | None, end: int | None) -> str:
+    """Slice *text* to the requested 1-indexed line range (inclusive)."""
+    if start is None and end is None:
+        return text
+    lines = text.splitlines(keepends=True)
+    s = (start - 1) if start is not None else 0
+    e = end if end is not None else len(lines)
+    selected = list(itertools.islice(lines, s, e))
+    return "".join(selected)
+
+
 async def read_file_bytes(
     uri: str,
     user_id: str | None,
@@ -134,47 +130,27 @@ async def read_file_bytes(
     if plain.startswith("workspace://"):
         if not user_id:
             raise ValueError("workspace:// file references require authentication")
-        manager = await get_workspace_manager(user_id, session.session_id)
+        manager = await get_manager(user_id, session.session_id)
         ws = parse_workspace_uri(plain)
         try:
-            data = await (
+            return await (
                 manager.read_file(ws.file_ref)
                 if ws.is_path
                 else manager.read_file_by_id(ws.file_ref)
             )
         except FileNotFoundError:
             raise ValueError(f"File not found: {plain}")
-        except (PermissionError, OSError) as exc:
+        except Exception as exc:
             raise ValueError(f"Failed to read {plain}: {exc}") from exc
-        except (AttributeError, TypeError, RuntimeError) as exc:
-            # AttributeError/TypeError: workspace manager returned an
-            # unexpected type or interface; RuntimeError: async runtime issues.
-            logger.warning("Unexpected error reading %s: %s", plain, exc)
-            raise ValueError(f"Failed to read {plain}: {exc}") from exc
-        # NOTE: Workspace API does not support pre-read size checks;
-        # the full file is loaded before the size guard below.
-        if len(data) > _MAX_BARE_REF_BYTES:
-            raise ValueError(
-                f"File too large ({len(data)} bytes, limit {_MAX_BARE_REF_BYTES})"
-            )
-        return data
 
     if is_allowed_local_path(plain, get_sdk_cwd()):
         resolved = os.path.realpath(os.path.expanduser(plain))
         try:
-            # Read with a one-byte overshoot to detect files that exceed the limit
-            # without a separate os.path.getsize call (avoids TOCTOU race).
             with open(resolved, "rb") as fh:
-                data = fh.read(_MAX_BARE_REF_BYTES + 1)
-            if len(data) > _MAX_BARE_REF_BYTES:
-                raise ValueError(
-                    f"File too large (>{_MAX_BARE_REF_BYTES} bytes, "
-                    f"limit {_MAX_BARE_REF_BYTES})"
-                )
-            return data
+                return fh.read()
         except FileNotFoundError:
             raise ValueError(f"File not found: {plain}")
-        except OSError as exc:
+        except Exception as exc:
             raise ValueError(f"Failed to read {plain}: {exc}") from exc
 
     sandbox = get_current_sandbox()
@@ -186,33 +162,9 @@ async def read_file_bytes(
                 f"Path is not allowed (not in workspace, sdk_cwd, or sandbox): {plain}"
             ) from exc
         try:
-            data = bytes(await sandbox.files.read(remote, format="bytes"))
-        except (FileNotFoundError, OSError, UnicodeDecodeError) as exc:
-            raise ValueError(f"Failed to read from sandbox: {plain}: {exc}") from exc
+            return bytes(await sandbox.files.read(remote, format="bytes"))
         except Exception as exc:
-            # E2B SDK raises SandboxException subclasses (NotFoundException,
-            # TimeoutException, NotEnoughSpaceException, etc.) which don't
-            # inherit from standard exceptions.  Import lazily to avoid a
-            # hard dependency on e2b at module level.
-            try:
-                from e2b.exceptions import SandboxException  # noqa: PLC0415
-
-                if isinstance(exc, SandboxException):
-                    raise ValueError(
-                        f"Failed to read from sandbox: {plain}: {exc}"
-                    ) from exc
-            except ImportError:
-                pass
-            # Re-raise unexpected exceptions (TypeError, AttributeError, etc.)
-            # so they surface as real bugs rather than being silently masked.
-            raise
-        # NOTE: E2B sandbox API does not support pre-read size checks;
-        # the full file is loaded before the size guard below.
-        if len(data) > _MAX_BARE_REF_BYTES:
-            raise ValueError(
-                f"File too large ({len(data)} bytes, limit {_MAX_BARE_REF_BYTES})"
-            )
-        return data
+            raise ValueError(f"Failed to read from sandbox: {plain}: {exc}") from exc
 
     raise ValueError(
         f"Path is not allowed (not in workspace, sdk_cwd, or sandbox): {plain}"
@@ -226,13 +178,15 @@ async def resolve_file_ref(
 ) -> str:
     """Resolve a :class:`FileRef` to its text content."""
     raw = await read_file_bytes(ref.uri, user_id, session)
-    return _apply_line_range(_to_str(raw), ref.start_line, ref.end_line)
+    return _apply_line_range(
+        raw.decode("utf-8", errors="replace"), ref.start_line, ref.end_line
+    )
 
 
 async def expand_file_refs_in_string(
     text: str,
     user_id: str | None,
-    session: ChatSession,
+    session: "ChatSession",
     *,
     raise_on_error: bool = False,
 ) -> str:
@@ -278,9 +232,6 @@ async def expand_file_refs_in_string(
             if len(content) > _MAX_EXPAND_CHARS:
                 content = content[:_MAX_EXPAND_CHARS] + "\n... [truncated]"
             remaining = _MAX_TOTAL_EXPAND_CHARS - total_chars
-            # remaining == 0 means the budget was exactly exhausted by the
-            # previous ref.  The elif below (len > remaining) won't catch
-            # this since 0 > 0 is false, so we need the <= 0 check.
             if remaining <= 0:
                 content = "[file-ref budget exhausted: total expansion limit reached]"
             elif len(content) > remaining:
@@ -301,31 +252,13 @@ async def expand_file_refs_in_string(
 async def expand_file_refs_in_args(
     args: dict[str, Any],
     user_id: str | None,
-    session: ChatSession,
-    *,
-    input_schema: dict[str, Any] | None = None,
+    session: "ChatSession",
 ) -> dict[str, Any]:
     """Recursively expand ``@@agptfile:...`` references in tool call arguments.
 
     String values are expanded in-place.  Nested dicts and lists are
     traversed.  Non-string scalars are returned unchanged.
 
-    **Bare references** (the entire argument value is a single
-    ``@@agptfile:...`` token with no surrounding text) are resolved and then
-    parsed according to the file's extension or MIME type.  See
-    :mod:`backend.util.file_content_parser` for the full list of supported
-    formats (JSON, JSONL, CSV, TSV, YAML, TOML, Parquet, Excel).
-
-    When *input_schema* is provided and the target property has
-    ``"type": "string"``, structured parsing is skipped — the raw file content
-    is returned as a plain string so blocks receive the original text.
-
-    If the format is unrecognised or parsing fails, the content is returned as
-    a plain string (the fallback).
-
-    **Embedded references** (``@@agptfile:`` mixed with other text) always
-    produce a plain string — structured parsing only applies to bare refs.
-
     Raises :class:`FileRefExpansionError` if any reference fails to resolve,
     so the tool is *not* executed with an error string as its input.  The
     caller (the MCP tool wrapper) should convert this into an MCP error
@@ -334,382 +267,15 @@ async def expand_file_refs_in_args(
     if not args:
         return args
 
-    properties = (input_schema or {}).get("properties", {})
-
-    async def _expand(
-        value: Any,
-        *,
-        prop_schema: dict[str, Any] | None = None,
-    ) -> Any:
-        """Recursively expand a single argument value.
-
-        Strings are checked for ``@@agptfile:`` references and expanded
-        (bare refs get structured parsing; embedded refs get inline
-        substitution).  Dicts and lists are traversed recursively,
-        threading the corresponding sub-schema from *prop_schema* so
-        that nested fields also receive correct type-aware expansion.
-        Non-string scalars pass through unchanged.
-        """
+    async def _expand(value: Any) -> Any:
         if isinstance(value, str):
-            ref = parse_file_ref(value)
-            if ref is not None:
-                # MediaFileType fields: return the raw URI immediately —
-                # no file reading, no format inference, no content parsing.
-                if _is_media_file_field(prop_schema):
-                    return ref.uri
-
-                fmt = infer_format_from_uri(ref.uri)
-                # Workspace URIs by ID (workspace://abc123) have no extension.
-                # When the MIME fragment is also missing, fall back to the
-                # workspace file manager's metadata for format detection.
-                if fmt is None and ref.uri.startswith("workspace://"):
-                    fmt = await _infer_format_from_workspace(ref.uri, user_id, session)
-                return await _expand_bare_ref(ref, fmt, user_id, session, prop_schema)
-
-            # Not a bare ref — do normal inline expansion.
             return await expand_file_refs_in_string(
                 value, user_id, session, raise_on_error=True
             )
         if isinstance(value, dict):
-            # When the schema says this is an object but doesn't define
-            # inner properties, skip expansion — the caller (e.g.
-            # RunBlockTool) will expand with the actual nested schema.
-            if (
-                prop_schema is not None
-                and prop_schema.get("type") == "object"
-                and "properties" not in prop_schema
-            ):
-                return value
-            nested_props = (prop_schema or {}).get("properties", {})
-            return {
-                k: await _expand(v, prop_schema=nested_props.get(k))
-                for k, v in value.items()
-            }
+            return {k: await _expand(v) for k, v in value.items()}
         if isinstance(value, list):
-            items_schema = (prop_schema or {}).get("items")
-            return [await _expand(item, prop_schema=items_schema) for item in value]
+            return [await _expand(item) for item in value]
         return value
 
-    return {k: await _expand(v, prop_schema=properties.get(k)) for k, v in args.items()}
-
-
-# ---------------------------------------------------------------------------
-# Private helpers  (used by the public functions above)
-# ---------------------------------------------------------------------------
-
-
-def _apply_line_range(text: str, start: int | None, end: int | None) -> str:
-    """Slice *text* to the requested 1-indexed line range (inclusive).
-
-    When the requested range extends beyond the file, a note is appended
-    so the LLM knows it received the entire remaining content.
-    """
-    if start is None and end is None:
-        return text
-    lines = text.splitlines(keepends=True)
-    total = len(lines)
-    s = (start - 1) if start is not None else 0
-    e = end if end is not None else total
-    selected = list(itertools.islice(lines, s, e))
-    result = "".join(selected)
-    if end is not None and end > total:
-        result += f"\n[Note: file has only {total} lines]\n"
-    return result
-
-
-def _to_str(content: str | bytes) -> str:
-    """Decode *content* to a string if it is bytes, otherwise return as-is."""
-    if isinstance(content, str):
-        return content
-    return content.decode("utf-8", errors="replace")
-
-
-def _check_content_size(content: str | bytes) -> None:
-    """Raise :class:`ValueError` if *content* exceeds the byte limit.
-
-    Raises ``ValueError`` (not ``FileRefExpansionError``) so that the caller
-    (``_expand_bare_ref``) can unify all resolution errors into a single
-    ``except ValueError`` → ``FileRefExpansionError`` handler, keeping the
-    error-flow consistent with ``read_file_bytes`` and ``resolve_file_ref``.
-
-    For ``bytes``, the length is the byte count directly.  For ``str``,
-    we encode to UTF-8 first because multi-byte characters (e.g. emoji)
-    mean the byte size can be up to 4x the character count.
-    """
-    if isinstance(content, bytes):
-        size = len(content)
-    else:
-        char_len = len(content)
-        # Fast lower bound: UTF-8 byte count >= char count.
-        # If char count already exceeds the limit, reject immediately
-        # without allocating an encoded copy.
-        if char_len > _MAX_BARE_REF_BYTES:
-            size = char_len  # real byte size is even larger
-        # Fast upper bound: each char is at most 4 UTF-8 bytes.
-        # If worst-case is still under the limit, skip encoding entirely.
-        elif char_len * 4 <= _MAX_BARE_REF_BYTES:
-            return
-        else:
-            # Edge case: char count is under limit but multibyte chars
-            # might push byte count over. Encode to get exact size.
-            size = len(content.encode("utf-8"))
-    if size > _MAX_BARE_REF_BYTES:
-        raise ValueError(
-            f"File too large for structured parsing "
-            f"({size} bytes, limit {_MAX_BARE_REF_BYTES})"
-        )
-
-
-async def _infer_format_from_workspace(
-    uri: str,
-    user_id: str | None,
-    session: ChatSession,
-) -> str | None:
-    """Look up workspace file metadata to infer the format.
-
-    Workspace URIs by ID (``workspace://abc123``) have no file extension.
-    When the MIME fragment is also absent, we query the workspace file
-    manager for the file's stored MIME type and original filename.
-    """
-    if not user_id:
-        return None
-    try:
-        ws = parse_workspace_uri(uri)
-        manager = await get_workspace_manager(user_id, session.session_id)
-        info = await (
-            manager.get_file_info(ws.file_ref)
-            if not ws.is_path
-            else manager.get_file_info_by_path(ws.file_ref)
-        )
-        if info is None:
-            return None
-        # Try MIME type first, then filename extension.
-        mime = (info.mime_type or "").split(";", 1)[0].strip().lower()
-        return MIME_TO_FORMAT.get(mime) or infer_format_from_uri(info.name)
-    except (
-        ValueError,
-        FileNotFoundError,
-        OSError,
-        PermissionError,
-        AttributeError,
-        TypeError,
-    ):
-        # Expected failures: bad URI, missing file, permission denied, or
-        # workspace manager returning unexpected types.  Propagate anything
-        # else (e.g. programming errors) so they don't get silently swallowed.
-        logger.debug("workspace metadata lookup failed for %s", uri, exc_info=True)
-        return None
-
-
-def _is_media_file_field(prop_schema: dict[str, Any] | None) -> bool:
-    """Return True if *prop_schema* describes a MediaFileType field (format: file)."""
-    if prop_schema is None:
-        return False
-    return (
-        prop_schema.get("type") == "string"
-        and prop_schema.get("format") == MediaFileType.string_format
-    )
-
-
-async def _expand_bare_ref(
-    ref: FileRef,
-    fmt: str | None,
-    user_id: str | None,
-    session: ChatSession,
-    prop_schema: dict[str, Any] | None,
-) -> Any:
-    """Resolve and parse a bare ``@@agptfile:`` reference.
-
-    This is the structured-parsing path: the file is read, optionally parsed
-    according to *fmt*, and adapted to the target *prop_schema*.
-
-    Raises :class:`FileRefExpansionError` on resolution or parsing failure.
-
-    Note: MediaFileType fields (format: "file") are handled earlier in
-    ``_expand`` to avoid unnecessary format inference and file I/O.
-    """
-    try:
-        if fmt is not None and fmt in BINARY_FORMATS:
-            # Binary formats need raw bytes, not UTF-8 text.
-            # Line ranges are meaningless for binary formats (parquet/xlsx)
-            # — ignore them and parse full bytes.  Warn so the caller/model
-            # knows the range was silently dropped.
-            if ref.start_line is not None or ref.end_line is not None:
-                logger.warning(
-                    "Line range [%s-%s] ignored for binary format %s (%s); "
-                    "binary formats are always parsed in full.",
-                    ref.start_line,
-                    ref.end_line,
-                    fmt,
-                    ref.uri,
-                )
-            content: str | bytes = await read_file_bytes(ref.uri, user_id, session)
-        else:
-            content = await resolve_file_ref(ref, user_id, session)
-    except ValueError as exc:
-        raise FileRefExpansionError(str(exc)) from exc
-
-    # For known formats this rejects files >10 MB before parsing.
-    # For unknown formats _MAX_EXPAND_CHARS (200K chars) below is stricter,
-    # but this check still guards the parsing path which has no char limit.
-    # _check_content_size raises ValueError, which we unify here just like
-    # resolution errors above.
-    try:
-        _check_content_size(content)
-    except ValueError as exc:
-        raise FileRefExpansionError(str(exc)) from exc
-
-    # When the schema declares this parameter as "string",
-    # return raw file content — don't parse into a structured
-    # type that would need json.dumps() serialisation.
-    expect_string = (prop_schema or {}).get("type") == "string"
-    if expect_string:
-        if isinstance(content, bytes):
-            raise FileRefExpansionError(
-                f"Cannot use {fmt} file as text input: "
-                f"binary formats (parquet, xlsx) must be passed "
-                f"to a block that accepts structured data (list/object), "
-                f"not a string-typed parameter."
-            )
-        return content
-
-    if fmt is not None:
-        # Use strict mode for binary formats so we surface the
-        # actual error (e.g. missing pyarrow/openpyxl, corrupt
-        # file) instead of silently returning garbled bytes.
-        strict = fmt in BINARY_FORMATS
-        try:
-            parsed = parse_file_content(content, fmt, strict=strict)
-        except PARSE_EXCEPTIONS as exc:
-            raise FileRefExpansionError(f"Failed to parse {fmt} file: {exc}") from exc
-        # Normalize bytes fallback to str so tools never
-        # receive raw bytes when parsing fails.
-        if isinstance(parsed, bytes):
-            parsed = _to_str(parsed)
-        return _adapt_to_schema(parsed, prop_schema)
-
-    # Unknown format — return as plain string, but apply
-    # the same per-ref character limit used by inline refs
-    # to prevent injecting unexpectedly large content.
-    text = _to_str(content)
-    if len(text) > _MAX_EXPAND_CHARS:
-        text = text[:_MAX_EXPAND_CHARS] + "\n... [truncated]"
-    return text
-
-
-def _adapt_to_schema(parsed: Any, prop_schema: dict[str, Any] | None) -> Any:
-    """Adapt a parsed file value to better fit the target schema type.
-
-    When the parser returns a natural type (e.g. dict from YAML, list from CSV)
-    that doesn't match the block's expected type, this function converts it to
-    a more useful representation instead of relying on pydantic's generic
-    coercion (which can produce awkward results like flattened dicts → lists).
-
-    Returns *parsed* unchanged when no adaptation is needed.
-    """
-    if prop_schema is None:
-        return parsed
-
-    target_type = prop_schema.get("type")
-
-    # Dict → array: delegate to helper.
-    if isinstance(parsed, dict) and target_type == "array":
-        return _adapt_dict_to_array(parsed, prop_schema)
-
-    # List → object: delegate to helper (raises for non-tabular lists).
-    if isinstance(parsed, list) and target_type == "object":
-        return _adapt_list_to_object(parsed)
-
-    # Tabular list → Any (no type): convert to list of dicts.
-    # Blocks like FindInDictionaryBlock have `input: Any` which produces
-    # a schema with no "type" key.  Tabular [[header],[rows]] is unusable
-    # for key lookup, but [{col: val}, ...] works with FindInDict's
-    # list-of-dicts branch (line 195-199 in data_manipulation.py).
-    if isinstance(parsed, list) and target_type is None and _is_tabular(parsed):
-        return _tabular_to_list_of_dicts(parsed)
-
-    return parsed
-
-
-def _adapt_dict_to_array(parsed: dict, prop_schema: dict[str, Any]) -> Any:
-    """Adapt a parsed dict to an array-typed field.
-
-    Extracts list-valued entries when the target item type is ``array``,
-    passes through unchanged when item type is ``string`` (lets pydantic error),
-    or wraps in ``[parsed]`` as a fallback.
-    """
-    items_type = (prop_schema.get("items") or {}).get("type")
-    if items_type == "array":
-        # Target is List[List[Any]] — extract list-typed values from the
-        # dict as inner lists.  E.g. YAML {"fruits": [{...},...]}} with
-        # ConcatenateLists (List[List[Any]]) → [[{...},...]].
-        list_values = [v for v in parsed.values() if isinstance(v, list)]
-        if list_values:
-            return list_values
-    if items_type == "string":
-        # Target is List[str] — wrapping a dict would give [dict]
-        # which can't coerce to strings.  Return unchanged and let
-        # pydantic surface a clear validation error.
-        return parsed
-    # Fallback: wrap in a single-element list so the block gets [dict]
-    # instead of pydantic flattening keys/values into a flat list.
-    return [parsed]
-
-
-def _adapt_list_to_object(parsed: list) -> Any:
-    """Adapt a parsed list to an object-typed field.
-
-    Converts tabular lists to column-dicts; raises for non-tabular lists.
-    """
-    if _is_tabular(parsed):
-        return _tabular_to_column_dict(parsed)
-    # Non-tabular list (e.g. a plain Python list from a YAML file) cannot
-    # be meaningfully coerced to an object.  Raise explicitly so callers
-    # get a clear error rather than pydantic silently wrapping the list.
-    raise FileRefExpansionError(
-        "Cannot adapt a non-tabular list to an object-typed field. "
-        "Expected a tabular structure ([[header], [row1], ...]) or a dict."
-    )
-
-
-def _is_tabular(parsed: Any) -> bool:
-    """Check if parsed data is in tabular format: [[header], [row1], ...].
-
-    Uses isinstance checks because this is a structural type guard on
-    opaque parser output (Any), not duck typing.  A Protocol wouldn't
-    help here — we need to verify exact list-of-lists shape.
-    """
-    if not isinstance(parsed, list) or len(parsed) < 2:
-        return False
-    header = parsed[0]
-    if not isinstance(header, list) or not header:
-        return False
-    if not all(isinstance(h, str) for h in header):
-        return False
-    return all(isinstance(row, list) for row in parsed[1:])
-
-
-def _tabular_to_list_of_dicts(parsed: list) -> list[dict[str, Any]]:
-    """Convert [[header], [row1], ...] → [{header[0]: row[0], ...}, ...].
-
-    Ragged rows (fewer columns than the header) get None for missing values.
-    Extra values beyond the header length are silently dropped.
-    """
-    header = parsed[0]
-    return [
-        dict(itertools.zip_longest(header, row[: len(header)], fillvalue=None))
-        for row in parsed[1:]
-    ]
-
-
-def _tabular_to_column_dict(parsed: list) -> dict[str, list]:
-    """Convert [[header], [row1], ...] → {"col1": [val1, ...], ...}.
-
-    Ragged rows (fewer columns than the header) get None for missing values,
-    ensuring all columns have equal length.
-    """
-    header = parsed[0]
-    return {
-        col: [row[i] if i < len(row) else None for row in parsed[1:]]
-        for i, col in enumerate(header)
-    }
+    return {k: await _expand(v) for k, v in args.items()}

autogpt_platform/backend/backend/copilot/sdk/file_ref_integration_test.py

@@ -175,199 +175,6 @@ async def test_expand_args_replaces_file_ref_in_nested_dict():
         assert result["count"] == 42
 
 
-# ---------------------------------------------------------------------------
-# expand_file_refs_in_args — bare ref structured parsing
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.asyncio
-async def test_bare_ref_json_returns_parsed_dict():
-    """Bare ref to a .json file returns parsed dict, not raw string."""
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        json_file = os.path.join(sdk_cwd, "data.json")
-        with open(json_file, "w") as f:
-            f.write('{"key": "value", "count": 42}')
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            result = await expand_file_refs_in_args(
-                {"data": f"@@agptfile:{json_file}"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        assert result["data"] == {"key": "value", "count": 42}
-
-
-@pytest.mark.asyncio
-async def test_bare_ref_csv_returns_parsed_table():
-    """Bare ref to a .csv file returns list[list[str]] table."""
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        csv_file = os.path.join(sdk_cwd, "data.csv")
-        with open(csv_file, "w") as f:
-            f.write("Name,Score\nAlice,90\nBob,85")
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            result = await expand_file_refs_in_args(
-                {"input": f"@@agptfile:{csv_file}"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        assert result["input"] == [
-            ["Name", "Score"],
-            ["Alice", "90"],
-            ["Bob", "85"],
-        ]
-
-
-@pytest.mark.asyncio
-async def test_bare_ref_unknown_extension_returns_string():
-    """Bare ref to a file with unknown extension returns plain string."""
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        txt_file = os.path.join(sdk_cwd, "readme.txt")
-        with open(txt_file, "w") as f:
-            f.write("plain text content")
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            result = await expand_file_refs_in_args(
-                {"data": f"@@agptfile:{txt_file}"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        assert result["data"] == "plain text content"
-        assert isinstance(result["data"], str)
-
-
-@pytest.mark.asyncio
-async def test_bare_ref_invalid_json_falls_back_to_string():
-    """Bare ref to a .json file with invalid JSON falls back to string."""
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        json_file = os.path.join(sdk_cwd, "bad.json")
-        with open(json_file, "w") as f:
-            f.write("not valid json {{{")
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            result = await expand_file_refs_in_args(
-                {"data": f"@@agptfile:{json_file}"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        assert result["data"] == "not valid json {{{"
-        assert isinstance(result["data"], str)
-
-
-@pytest.mark.asyncio
-async def test_embedded_ref_always_returns_string_even_for_json():
-    """Embedded ref (text around it) returns plain string, not parsed JSON."""
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        json_file = os.path.join(sdk_cwd, "data.json")
-        with open(json_file, "w") as f:
-            f.write('{"key": "value"}')
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            result = await expand_file_refs_in_args(
-                {"data": f"prefix @@agptfile:{json_file} suffix"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        assert isinstance(result["data"], str)
-        assert result["data"].startswith("prefix ")
-        assert result["data"].endswith(" suffix")
-
-
-@pytest.mark.asyncio
-async def test_bare_ref_yaml_returns_parsed_dict():
-    """Bare ref to a .yaml file returns parsed dict."""
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        yaml_file = os.path.join(sdk_cwd, "config.yaml")
-        with open(yaml_file, "w") as f:
-            f.write("name: test\ncount: 42\n")
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            result = await expand_file_refs_in_args(
-                {"config": f"@@agptfile:{yaml_file}"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        assert result["config"] == {"name": "test", "count": 42}
-
-
-@pytest.mark.asyncio
-async def test_bare_ref_binary_with_line_range_ignores_range():
-    """Bare ref to a binary file (.parquet) with line range parses the full file.
-
-    Binary formats (parquet, xlsx) ignore line ranges — the full content is
-    parsed and the range is silently dropped with a log warning.
-    """
-    try:
-        import pandas as pd
-    except ImportError:
-        pytest.skip("pandas not installed")
-    try:
-        import pyarrow  # noqa: F401  # pyright: ignore[reportMissingImports]
-    except ImportError:
-        pytest.skip("pyarrow not installed")
-
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        parquet_file = os.path.join(sdk_cwd, "data.parquet")
-        import io as _io
-
-        df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
-        buf = _io.BytesIO()
-        df.to_parquet(buf, index=False)
-        with open(parquet_file, "wb") as f:
-            f.write(buf.getvalue())
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            # Line range [1-2] should be silently ignored for binary formats.
-            result = await expand_file_refs_in_args(
-                {"data": f"@@agptfile:{parquet_file}[1-2]"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        # Full file is returned despite the line range.
-        assert result["data"] == [["A", "B"], [1, 4], [2, 5], [3, 6]]
-
-
-@pytest.mark.asyncio
-async def test_bare_ref_toml_returns_parsed_dict():
-    """Bare ref to a .toml file returns parsed dict."""
-    with tempfile.TemporaryDirectory() as sdk_cwd:
-        toml_file = os.path.join(sdk_cwd, "config.toml")
-        with open(toml_file, "w") as f:
-            f.write('name = "test"\ncount = 42\n')
-
-        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
-            mock_cwd_var.get.return_value = sdk_cwd
-
-            result = await expand_file_refs_in_args(
-                {"config": f"@@agptfile:{toml_file}"},
-                user_id="u1",
-                session=_make_session(),
-            )
-
-        assert result["config"] == {"name": "test", "count": 42}
-
-
 # ---------------------------------------------------------------------------
 # _read_file_handler — extended to accept workspace:// and local paths
 # ---------------------------------------------------------------------------
@@ -412,7 +219,7 @@ async def test_read_file_handler_workspace_uri():
         "backend.copilot.sdk.tool_adapter.get_execution_context",
         return_value=("user-1", mock_session),
     ), patch(
-        "backend.copilot.sdk.file_ref.get_workspace_manager",
+        "backend.copilot.sdk.file_ref.get_manager",
         new=AsyncMock(return_value=mock_manager),
     ):
         result = await _read_file_handler(
@@ -469,7 +276,7 @@ async def test_read_file_bytes_workspace_virtual_path():
     mock_manager.read_file.return_value = b"virtual path content"
 
     with patch(
-        "backend.copilot.sdk.file_ref.get_workspace_manager",
+        "backend.copilot.sdk.file_ref.get_manager",
         new=AsyncMock(return_value=mock_manager),
     ):
         result = await read_file_bytes("workspace:///reports/q1.md", "user-1", session)

autogpt_platform/backend/backend/copilot/sdk/mcp_tool_guide.md

@@ -20,24 +20,7 @@ Use these URLs directly without asking the user:
 | Cloudflare | `https://mcp.cloudflare.com/mcp` |
 | Atlassian / Jira | `https://mcp.atlassian.com/mcp` |
 
-For other services, search the MCP registry API:
-```http
-GET https://registry.modelcontextprotocol.io/v0/servers?q=<search_term>
-```
-Each result includes a `remotes` array with the exact server URL to use.
-
-### Important: Check blocks first
-
-Before using `run_mcp_tool`, always check if the platform already has blocks for the service
-using `find_block`. The platform has hundreds of built-in blocks (Google Sheets, Google Docs,
-Google Calendar, Gmail, etc.) that work without MCP setup.
-
-Only use `run_mcp_tool` when:
-- The service is in the known hosted MCP servers list above, OR
-- You searched `find_block` first and found no matching blocks
-
-**Never guess or construct MCP server URLs.** Only use URLs from the known servers list above
-or from the `remotes[].url` field in MCP registry search results.
+For other services, search the MCP registry at https://registry.modelcontextprotocol.io/.
 
 ### Authentication
 

autogpt_platform/backend/backend/copilot/sdk/response_adapter.py

@@ -221,12 +221,12 @@ class SDKResponseAdapter:
                 responses.append(StreamFinish())
             else:
                 logger.warning(
-                    f"Unexpected ResultMessage subtype: {sdk_message.subtype}"
+                    "Unexpected ResultMessage subtype: %s", sdk_message.subtype
                 )
                 responses.append(StreamFinish())
 
         else:
-            logger.debug(f"Unhandled SDK message type: {type(sdk_message).__name__}")
+            logger.debug("Unhandled SDK message type: %s", type(sdk_message).__name__)
 
         return responses
 

autogpt_platform/backend/backend/copilot/sdk/security_hooks.py

@@ -52,7 +52,7 @@ def _validate_workspace_path(
     if is_allowed_local_path(path, sdk_cwd):
         return {}
 
-    logger.warning(f"Blocked {tool_name} outside workspace: {path}")
+    logger.warning("Blocked %s outside workspace: %s", tool_name, path)
     workspace_hint = f" Allowed workspace: {sdk_cwd}" if sdk_cwd else ""
     return _deny(
         f"[SECURITY] Tool '{tool_name}' can only access files within the workspace "
@@ -71,7 +71,7 @@ def _validate_tool_access(
     """
     # Block forbidden tools
     if tool_name in BLOCKED_TOOLS:
-        logger.warning(f"Blocked tool access attempt: {tool_name}")
+        logger.warning("Blocked tool access attempt: %s", tool_name)
         return _deny(
             f"[SECURITY] Tool '{tool_name}' is blocked for security. "
             "This is enforced by the platform and cannot be bypassed. "
@@ -111,7 +111,9 @@ def _validate_user_isolation(
         # the tool itself via _validate_ephemeral_path.
         path = tool_input.get("path", "") or tool_input.get("file_path", "")
         if path and ".." in path:
-            logger.warning(f"Blocked path traversal attempt: {path} by user {user_id}")
+            logger.warning(
+                "Blocked path traversal attempt: %s by user %s", path, user_id
+            )
             return {
                 "hookSpecificOutput": {
                     "hookEventName": "PreToolUse",
@@ -127,7 +129,7 @@ def create_security_hooks(
     user_id: str | None,
     sdk_cwd: str | None = None,
     max_subtasks: int = 3,
-    on_compact: Callable[[str], None] | None = None,
+    on_compact: Callable[[], None] | None = None,
 ) -> dict[str, Any]:
     """Create the security hooks configuration for Claude Agent SDK.
 
@@ -142,7 +144,6 @@ def create_security_hooks(
         sdk_cwd: SDK working directory for workspace-scoped tool validation
         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.
 
     Returns:
         Hooks configuration dict for ClaudeAgentOptions
@@ -170,7 +171,7 @@ def create_security_hooks(
                 # 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}")
+                    logger.info("[SDK] Blocked background Task, user=%s", user_id)
                     return cast(
                         SyncHookJSONOutput,
                         _deny(
@@ -212,7 +213,7 @@ def create_security_hooks(
             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}")
+            logger.debug("[SDK] Tool start: %s, user=%s", tool_name, user_id)
             return cast(SyncHookJSONOutput, {})
 
         def _release_task_slot(tool_name: str, tool_use_id: str | None) -> None:
@@ -302,21 +303,11 @@ def create_security_hooks(
             """
             _ = context, tool_use_id
             trigger = input_data.get("trigger", "auto")
-            # Sanitize untrusted input before logging to prevent log injection
-            transcript_path = (
-                str(input_data.get("transcript_path", ""))
-                .replace("\n", "")
-                .replace("\r", "")
-            )
             logger.info(
-                "[SDK] Context compaction triggered: %s, user=%s, "
-                "transcript_path=%s",
-                trigger,
-                user_id,
-                transcript_path,
+                f"[SDK] Context compaction triggered: {trigger}, user={user_id}"
             )
             if on_compact is not None:
-                on_compact(transcript_path)
+                on_compact()
             return cast(SyncHookJSONOutput, {})
 
         hooks: dict[str, Any] = {

autogpt_platform/backend/backend/copilot/sdk/service.py

@@ -29,7 +29,6 @@ from langfuse import propagate_attributes
 from langsmith.integrations.claude_agent_sdk import configure_claude_agent_sdk
 from pydantic import BaseModel
 
-from backend.copilot.context import get_workspace_manager
 from backend.data.redis_client import get_redis_async
 from backend.executor.cluster_lock import AsyncClusterLock
 from backend.util.exceptions import NotFoundError
@@ -41,11 +40,13 @@ from ..constants import COPILOT_ERROR_PREFIX, COPILOT_SYSTEM_PREFIX
 from ..model import (
     ChatMessage,
     ChatSession,
+    Usage,
     get_chat_session,
     update_session_title,
     upsert_chat_session,
 )
 from ..prompting import get_sdk_supplement
+from ..rate_limit import record_token_usage
 from ..response_model import (
     StreamBaseResponse,
     StreamError,
@@ -62,9 +63,9 @@ from ..service import (
     _generate_session_title,
     _is_langfuse_configured,
 )
-from ..token_tracking import persist_and_record_usage
 from ..tools.e2b_sandbox import get_or_create_sandbox, pause_sandbox_direct
 from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
+from ..tools.workspace_files import get_manager
 from ..tracking import track_user_message
 from .compaction import CompactionTracker, filter_compaction_messages
 from .response_adapter import SDKResponseAdapter
@@ -77,9 +78,12 @@ from .tool_adapter import (
     wait_for_stash,
 )
 from .transcript import (
+    COMPACT_THRESHOLD_BYTES,
+    TranscriptDownload,
     cleanup_cli_project_dir,
+    compact_transcript,
     download_transcript,
-    read_compacted_entries,
+    read_cli_session_file,
     upload_transcript,
     validate_transcript,
     write_transcript_to_tempfile,
@@ -297,7 +301,7 @@ def _cleanup_sdk_tool_results(cwd: str) -> None:
     """
     normalized = os.path.normpath(cwd)
     if not normalized.startswith(_SDK_CWD_PREFIX):
-        logger.warning(f"[SDK] Rejecting cleanup for path outside workspace: {cwd}")
+        logger.warning("[SDK] Rejecting cleanup for path outside workspace: %s", cwd)
         return
 
     # Clean the CLI's project directory (transcripts + tool-results).
@@ -391,7 +395,7 @@ async def _compress_messages(
                 client=client,
             )
     except Exception as e:
-        logger.warning(f"[SDK] Context compression with LLM failed: {e}")
+        logger.warning("[SDK] Context compression with LLM failed: %s", e)
         # Fall back to truncation-only (no LLM summarization)
         result = await compress_context(
             messages=messages_dict,
@@ -567,7 +571,7 @@ async def _prepare_file_attachments(
         return empty
 
     try:
-        manager = await get_workspace_manager(user_id, session_id)
+        manager = await get_manager(user_id, session_id)
     except Exception:
         logger.warning(
             "Failed to create workspace manager for file attachments",
@@ -627,6 +631,56 @@ async def _prepare_file_attachments(
     return PreparedAttachments(hint=hint, image_blocks=image_blocks)
 
 
+async def _maybe_compact_and_upload(
+    dl: TranscriptDownload,
+    user_id: str,
+    session_id: str,
+    log_prefix: str = "[Transcript]",
+) -> str:
+    """Compact an oversized transcript and upload the compacted version.
+
+    Returns the (possibly compacted) transcript content, or an empty string
+    if compaction was needed but failed.
+    """
+    content = dl.content
+    if len(content) <= COMPACT_THRESHOLD_BYTES:
+        return content
+
+    logger.warning(
+        "%s Transcript oversized (%dB > %dB), compacting",
+        log_prefix,
+        len(content),
+        COMPACT_THRESHOLD_BYTES,
+    )
+    compacted = await compact_transcript(content, log_prefix=log_prefix)
+    if not compacted:
+        logger.warning(
+            "%s Compaction failed, skipping resume for this turn", log_prefix
+        )
+        return ""
+
+    # Keep the original message_count: it reflects the number of
+    # session.messages covered by this transcript, which the gap-fill
+    # logic uses as a slice index.  Counting JSONL lines would give a
+    # smaller number (compacted messages != session message count) and
+    # cause already-covered messages to be re-injected.
+    try:
+        await upload_transcript(
+            user_id=user_id,
+            session_id=session_id,
+            content=compacted,
+            message_count=dl.message_count,
+            log_prefix=log_prefix,
+        )
+    except Exception:
+        logger.warning(
+            "%s Failed to upload compacted transcript",
+            log_prefix,
+            exc_info=True,
+        )
+    return compacted
+
+
 async def stream_chat_completion_sdk(
     session_id: str,
     message: str | None = None,
@@ -743,6 +797,7 @@ async def stream_chat_completion_sdk(
     turn_completion_tokens = 0
     turn_cache_read_tokens = 0
     turn_cache_creation_tokens = 0
+    total_tokens = 0  # computed once before StreamUsage, reused in finally
     turn_cost_usd: float | None = None
 
     try:
@@ -837,20 +892,33 @@ async def stream_chat_completion_sdk(
                 is_valid,
             )
             if is_valid:
-                # Load previous FULL context into builder
-                transcript_builder.load_previous(dl.content, log_prefix=log_prefix)
-                resume_file = write_transcript_to_tempfile(
-                    dl.content, session_id, sdk_cwd
+                transcript_content = await _maybe_compact_and_upload(
+                    dl,
+                    user_id=user_id or "",
+                    session_id=session_id,
+                    log_prefix=log_prefix,
+                )
+                # Load previous context into builder (empty string is a no-op)
+                if transcript_content:
+                    transcript_builder.load_previous(
+                        transcript_content, log_prefix=log_prefix
+                    )
+                resume_file = (
+                    write_transcript_to_tempfile(
+                        transcript_content, session_id, sdk_cwd
+                    )
+                    if transcript_content
+                    else None
                 )
                 if resume_file:
                     use_resume = True
                     transcript_msg_count = dl.message_count
                     logger.debug(
-                        f"{log_prefix} Using --resume ({len(dl.content)}B, "
+                        f"{log_prefix} Using --resume ({len(transcript_content)}B, "
                         f"msg_count={transcript_msg_count})"
                     )
             else:
-                logger.warning(f"{log_prefix} Transcript downloaded but invalid")
+                logger.warning("%s Transcript downloaded but invalid", log_prefix)
         elif config.claude_agent_use_resume and user_id and len(session.messages) > 1:
             logger.warning(
                 f"{log_prefix} No transcript available "
@@ -1055,7 +1123,6 @@ async def stream_chat_completion_sdk(
                             exc_info=True,
                         )
                         ended_with_stream_error = True
-
                         yield StreamError(
                             errorText=f"SDK stream error: {stream_err}",
                             code="sdk_stream_error",
@@ -1168,25 +1235,18 @@ async def stream_chat_completion_sdk(
                             turn_cost_usd = sdk_msg.total_cost_usd
 
                     # Emit compaction end if SDK finished compacting.
-                    # When compaction ends, sync TranscriptBuilder with the
-                    # CLI's active context so they stay identical.
-                    compact_result = await compaction.emit_end_if_ready(session)
-                    for ev in compact_result.events:
+                    # When compaction ends, sync TranscriptBuilder with
+                    # the CLI's compacted session file so the uploaded
+                    # transcript reflects compaction.
+                    compaction_events = await compaction.emit_end_if_ready(session)
+                    for ev in compaction_events:
                         yield ev
-                    # After replace_entries, skip append_assistant for this
-                    # sdk_msg — the CLI session file already contains it,
-                    # so appending again would create a duplicate.
-                    entries_replaced = False
-                    if compact_result.just_ended:
-                        compacted = await asyncio.to_thread(
-                            read_compacted_entries,
-                            compact_result.transcript_path,
-                        )
-                        if compacted is not None:
+                    if compaction_events and sdk_cwd:
+                        cli_content = await read_cli_session_file(sdk_cwd)
+                        if cli_content:
                             transcript_builder.replace_entries(
-                                compacted, log_prefix=log_prefix
+                                cli_content, log_prefix=log_prefix
                             )
-                            entries_replaced = True
 
                     for response in adapter.convert_message(sdk_msg):
                         if isinstance(response, StreamStart):
@@ -1273,11 +1333,10 @@ async def stream_chat_completion_sdk(
                                     tool_call_id=response.toolCallId,
                                 )
                             )
-                            if not entries_replaced:
-                                transcript_builder.append_tool_result(
-                                    tool_use_id=response.toolCallId,
-                                    content=content,
-                                )
+                            transcript_builder.append_tool_result(
+                                tool_use_id=response.toolCallId,
+                                content=content,
+                            )
                             has_tool_results = True
 
                         elif isinstance(response, StreamFinish):
@@ -1287,9 +1346,7 @@ async def stream_chat_completion_sdk(
                     # any stashed tool results from the previous turn are
                     # recorded first, preserving the required API order:
                     # assistant(tool_use) → tool_result → assistant(text).
-                    # Skip if replace_entries just ran — the CLI session
-                    # file already contains this message.
-                    if isinstance(sdk_msg, AssistantMessage) and not entries_replaced:
+                    if isinstance(sdk_msg, AssistantMessage):
                         transcript_builder.append_assistant(
                             content_blocks=_format_sdk_content_blocks(sdk_msg.content),
                             model=sdk_msg.model,
@@ -1387,20 +1444,21 @@ async def stream_chat_completion_sdk(
         # Session persistence of usage is in finally to stay consistent with
         # rate-limit recording even if an exception interrupts between here
         # and the finally block.
-        if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
-            # total_tokens = prompt (uncached input) + completion (output).
-            # Cache tokens are tracked separately and excluded from total
-            # so that the semantics match the baseline path (OpenRouter)
-            # which folds cache into prompt_tokens. Keeping total_tokens
-            # = prompt + completion everywhere makes cross-path comparisons
-            # and session-level aggregation consistent.
-            total_tokens = turn_prompt_tokens + turn_completion_tokens
+        # Compute total_tokens once; reused in the finally block for
+        # session persistence and rate-limit recording.
+        total_tokens = (
+            turn_prompt_tokens
+            + turn_cache_read_tokens
+            + turn_cache_creation_tokens
+            + turn_completion_tokens
+        )
+        if total_tokens > 0:
             yield StreamUsage(
-                prompt_tokens=turn_prompt_tokens,
-                completion_tokens=turn_completion_tokens,
-                total_tokens=total_tokens,
-                cache_read_tokens=turn_cache_read_tokens,
-                cache_creation_tokens=turn_cache_creation_tokens,
+                promptTokens=turn_prompt_tokens,
+                completionTokens=turn_completion_tokens,
+                totalTokens=total_tokens,
+                cacheReadTokens=turn_cache_read_tokens,
+                cacheCreationTokens=turn_cache_creation_tokens,
             )
 
         # Transcript upload is handled exclusively in the finally block
@@ -1470,16 +1528,44 @@ async def stream_chat_completion_sdk(
         # --- Persist token usage to session + rate-limit counters ---
         # Both must live in finally so they stay consistent even when an
         # exception interrupts the try block after StreamUsage was yielded.
-        await persist_and_record_usage(
-            session=session,
-            user_id=user_id,
-            prompt_tokens=turn_prompt_tokens,
-            completion_tokens=turn_completion_tokens,
-            cache_read_tokens=turn_cache_read_tokens,
-            cache_creation_tokens=turn_cache_creation_tokens,
-            log_prefix=log_prefix,
-            cost_usd=turn_cost_usd,
-        )
+        # total_tokens is computed once before StreamUsage yield above.
+        if total_tokens > 0:
+            if session is not None:
+                session.usage.append(
+                    Usage(
+                        prompt_tokens=turn_prompt_tokens,
+                        completion_tokens=turn_completion_tokens,
+                        total_tokens=total_tokens,
+                        cache_read_tokens=turn_cache_read_tokens,
+                        cache_creation_tokens=turn_cache_creation_tokens,
+                    )
+                )
+            logger.info(
+                "%s Turn usage: uncached=%d, cache_read=%d, cache_create=%d, "
+                "output=%d, total=%d, cost_usd=%s",
+                log_prefix,
+                turn_prompt_tokens,
+                turn_cache_read_tokens,
+                turn_cache_creation_tokens,
+                turn_completion_tokens,
+                total_tokens,
+                turn_cost_usd,
+            )
+        if user_id and total_tokens > 0:
+            try:
+                await record_token_usage(
+                    user_id=user_id,
+                    prompt_tokens=turn_prompt_tokens,
+                    completion_tokens=turn_completion_tokens,
+                    cache_read_tokens=turn_cache_read_tokens,
+                    cache_creation_tokens=turn_cache_creation_tokens,
+                )
+            except Exception as usage_err:
+                logger.warning(
+                    "%s Failed to record token usage: %s",
+                    log_prefix,
+                    usage_err,
+                )
 
         # --- Persist session messages ---
         # This MUST run in finally to persist messages even when the generator
@@ -1514,13 +1600,13 @@ async def stream_chat_completion_sdk(
             task.add_done_callback(_background_tasks.discard)
 
         # --- Upload transcript for next-turn --resume ---
-        # TranscriptBuilder is the single source of truth.  It mirrors the
-        # CLI's active context: on compaction, replace_entries() syncs it
-        # with the compacted session file.  No CLI file read needed here.
+        # This MUST run in finally so the transcript is uploaded even when
+        # the streaming loop raises an exception.
+        # The transcript represents the COMPLETE active context (atomic).
         if config.claude_agent_use_resume and user_id and session is not None:
             try:
+                # Build complete transcript from captured SDK messages
                 transcript_content = transcript_builder.to_jsonl()
-                entry_count = transcript_builder.entry_count
 
                 if not transcript_content:
                     logger.warning(
@@ -1530,15 +1616,18 @@ async def stream_chat_completion_sdk(
                     logger.warning(
                         "%s Transcript invalid, skipping upload (entries=%d)",
                         log_prefix,
-                        entry_count,
+                        transcript_builder.entry_count,
                     )
                 else:
                     logger.info(
-                        "%s Uploading transcript (entries=%d, bytes=%d)",
+                        "%s Uploading complete transcript (entries=%d, bytes=%d)",
                         log_prefix,
-                        entry_count,
+                        transcript_builder.entry_count,
                         len(transcript_content),
                     )
+                    # Shield upload from cancellation - let it complete even if
+                    # the finally block is interrupted. No timeout to avoid race
+                    # conditions where backgrounded uploads overwrite newer transcripts.
                     await asyncio.shield(
                         upload_transcript(
                             user_id=user_id,
@@ -1573,6 +1662,6 @@ async def _update_title_async(
         )
         if title and user_id:
             await update_session_title(session_id, user_id, title, only_if_empty=True)
-            logger.debug(f"[SDK] Generated title for {session_id}: {title}")
+            logger.debug("[SDK] Generated title for %s: %s", session_id, title)
     except Exception as e:
-        logger.warning(f"[SDK] Failed to update session title: {e}")
+        logger.warning("[SDK] Failed to update session title: %s", e)

autogpt_platform/backend/backend/copilot/sdk/service_test.py

@@ -20,7 +20,7 @@ class _FakeFileInfo:
     size_bytes: int
 
 
-_PATCH_TARGET = "backend.copilot.sdk.service.get_workspace_manager"
+_PATCH_TARGET = "backend.copilot.sdk.service.get_manager"
 
 
 class TestPrepareFileAttachments:

autogpt_platform/backend/backend/copilot/sdk/tool_adapter.py

@@ -234,7 +234,9 @@ def create_tool_handler(base_tool: BaseTool):
         try:
             return await _execute_tool_sync(base_tool, user_id, session, args)
         except Exception as e:
-            logger.error(f"Error executing tool {base_tool.name}: {e}", exc_info=True)
+            logger.error(
+                "Error executing tool %s: %s", base_tool.name, e, exc_info=True
+            )
             return _mcp_error(f"Failed to execute {base_tool.name}: {e}")
 
     return tool_handler
@@ -347,7 +349,7 @@ def create_copilot_mcp_server(*, use_e2b: bool = False):
     :func:`get_sdk_disallowed_tools`.
     """
 
-    def _truncating(fn, tool_name: str, input_schema: dict[str, Any] | None = None):
+    def _truncating(fn, tool_name: str):
         """Wrap a tool handler so its response is truncated to stay under the
         SDK's 10 MB JSON buffer, and stash the (truncated) output for the
         response adapter before the SDK can apply its own head-truncation.
@@ -361,9 +363,7 @@ def create_copilot_mcp_server(*, use_e2b: bool = False):
             user_id, session = get_execution_context()
             if session is not None:
                 try:
-                    args = await expand_file_refs_in_args(
-                        args, user_id, session, input_schema=input_schema
-                    )
+                    args = await expand_file_refs_in_args(args, user_id, session)
                 except FileRefExpansionError as exc:
                     return _mcp_error(
                         f"@@agptfile: reference could not be resolved: {exc}. "
@@ -391,12 +391,11 @@ 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)
         decorated = tool(
             tool_name,
             base_tool.description,
-            schema,
-        )(_truncating(handler, tool_name, input_schema=schema))
+            _build_input_schema(base_tool),
+        )(_truncating(handler, tool_name))
         sdk_tools.append(decorated)
 
     # E2B file tools replace SDK built-in Read/Write/Edit/Glob/Grep.

autogpt_platform/backend/backend/copilot/sdk/transcript.py

@@ -17,8 +17,13 @@ import shutil
 import time
 from dataclasses import dataclass
 from pathlib import Path
+from uuid import uuid4
 
+import openai
+
+from backend.copilot.config import ChatConfig
 from backend.util import json
+from backend.util.prompt import CompressResult, compress_context
 
 logger = logging.getLogger(__name__)
 
@@ -36,6 +41,11 @@ STRIPPABLE_TYPES = frozenset(
     {"progress", "file-history-snapshot", "queue-operation", "summary", "pr-link"}
 )
 
+# JSONL protocol values used in transcript serialization.
+STOP_REASON_END_TURN = "end_turn"
+COMPACT_MSG_ID_PREFIX = "msg_compact_"
+ENTRY_TYPE_MESSAGE = "message"
+
 
 @dataclass
 class TranscriptDownload:
@@ -99,7 +109,9 @@ def strip_progress_entries(content: str) -> str:
             continue
         parent = entry.get("parentUuid", "")
         original_parent = parent
-        while parent in stripped_uuids:
+        seen_parents: set[str] = set()
+        while parent in stripped_uuids and parent not in seen_parents:
+            seen_parents.add(parent)
             parent = uuid_to_parent.get(parent, "")
         if parent != original_parent:
             entry["parentUuid"] = parent
@@ -145,147 +157,60 @@ def _sanitize_id(raw_id: str, max_len: int = 36) -> str:
 _SAFE_CWD_PREFIX = os.path.realpath("/tmp/copilot-")
 
 
-def _projects_base() -> str:
-    """Return the resolved path to the CLI's projects directory."""
-    config_dir = os.environ.get("CLAUDE_CONFIG_DIR") or os.path.expanduser("~/.claude")
-    return os.path.realpath(os.path.join(config_dir, "projects"))
-
-
 def _cli_project_dir(sdk_cwd: str) -> str | None:
     """Return the CLI's project directory for a given working directory.
 
     Returns ``None`` if the path would escape the projects base.
     """
     cwd_encoded = re.sub(r"[^a-zA-Z0-9]", "-", os.path.realpath(sdk_cwd))
-    projects_base = _projects_base()
+    config_dir = os.environ.get("CLAUDE_CONFIG_DIR") or os.path.expanduser("~/.claude")
+    projects_base = os.path.realpath(os.path.join(config_dir, "projects"))
     project_dir = os.path.realpath(os.path.join(projects_base, cwd_encoded))
-
     if not project_dir.startswith(projects_base + os.sep):
-        logger.warning(
-            "[Transcript] Project dir escaped projects base: %s", project_dir
-        )
+        logger.warning("[Transcript] Project dir escaped base: %s", project_dir)
         return None
     return project_dir
 
 
-def _safe_glob_jsonl(project_dir: str) -> list[Path]:
-    """Glob ``*.jsonl`` files, filtering out symlinks that escape the directory."""
-    try:
-        resolved_base = Path(project_dir).resolve()
-    except OSError as e:
-        logger.warning("[Transcript] Failed to resolve project dir: %s", e)
-        return []
+async def read_cli_session_file(sdk_cwd: str) -> str | None:
+    """Read the CLI's own session file, which reflects any mid-stream compaction.
 
-    result: list[Path] = []
-    for candidate in Path(project_dir).glob("*.jsonl"):
-        try:
-            resolved = candidate.resolve()
-            if resolved.is_relative_to(resolved_base):
-                result.append(resolved)
-        except (OSError, RuntimeError) as e:
-            logger.debug(
-                "[Transcript] Skipping invalid CLI session candidate %s: %s",
-                candidate,
-                e,
-            )
-    return result
-
-
-def read_compacted_entries(transcript_path: str) -> list[dict] | None:
-    """Read compacted entries from the CLI session file after compaction.
-
-    Parses the JSONL file line-by-line, finds the ``isCompactSummary: true``
-    entry, and returns it plus all entries after it.
-
-    The CLI writes the compaction summary BEFORE sending the next message,
-    so the file is guaranteed to be flushed by the time we read it.
-
-    Returns a list of parsed dicts, or ``None`` if the file cannot be read
-    or no compaction summary is found.
+    After the CLI compacts context, its session file contains the compacted
+    conversation.  Reading this file lets ``TranscriptBuilder`` replace its
+    uncompacted entries with the CLI's compacted version.
     """
-    if not transcript_path:
-        return None
+    import aiofiles
 
-    projects_base = _projects_base()
-    real_path = os.path.realpath(transcript_path)
-    if not real_path.startswith(projects_base + os.sep):
-        logger.warning(
-            "[Transcript] transcript_path outside projects base: %s", transcript_path
-        )
-        return None
-
-    try:
-        content = Path(real_path).read_text()
-    except OSError as e:
-        logger.warning(
-            "[Transcript] Failed to read session file %s: %s", transcript_path, e
-        )
-        return None
-
-    lines = content.strip().split("\n")
-    compact_idx: int | None = None
-
-    for idx, line in enumerate(lines):
-        if not line.strip():
-            continue
-        entry = json.loads(line, fallback=None)
-        if not isinstance(entry, dict):
-            continue
-        if entry.get("isCompactSummary"):
-            compact_idx = idx  # don't break — find the LAST summary
-
-    if compact_idx is None:
-        logger.debug("[Transcript] No compaction summary found in %s", transcript_path)
-        return None
-
-    entries: list[dict] = []
-    for line in lines[compact_idx:]:
-        if not line.strip():
-            continue
-        entry = json.loads(line, fallback=None)
-        if isinstance(entry, dict):
-            entries.append(entry)
-
-    logger.info(
-        "[Transcript] Read %d compacted entries from %s (summary at line %d)",
-        len(entries),
-        transcript_path,
-        compact_idx + 1,
-    )
-    return entries
-
-
-def read_cli_session_file(sdk_cwd: str) -> str | None:
-    """Read the CLI's own session file, which reflects any compaction.
-
-    The CLI writes its session transcript to
-    ``~/.claude/projects/<encoded_cwd>/<session_id>.jsonl``.
-    Since each SDK turn uses a unique ``sdk_cwd``, there should be
-    exactly one ``.jsonl`` file in that directory.
-
-    Returns the file content, or ``None`` if not found.
-    """
     project_dir = _cli_project_dir(sdk_cwd)
     if not project_dir or not os.path.isdir(project_dir):
         return None
-
-    jsonl_files = _safe_glob_jsonl(project_dir)
+    jsonl_files = list(Path(project_dir).glob("*.jsonl"))
     if not jsonl_files:
-        logger.debug("[Transcript] No CLI session file found in %s", project_dir)
+        logger.debug("[Transcript] No CLI session file in %s", project_dir)
         return None
-
-    # Pick the most recently modified file (should be only one per turn).
-    try:
-        session_file = max(jsonl_files, key=lambda p: p.stat().st_mtime)
-    except OSError as e:
-        logger.warning("[Transcript] Failed to inspect CLI session files: %s", e)
+    # Pick the most recently modified file (there should only be one per turn).
+    # Guard against races where a file is deleted between glob and stat.
+    candidates: list[tuple[float, Path]] = []
+    for p in jsonl_files:
+        try:
+            candidates.append((p.stat().st_mtime, p))
+        except OSError:
+            continue
+    if not candidates:
+        logger.debug("[Transcript] No readable CLI session file in %s", project_dir)
+        return None
+    # Resolve + prefix check to prevent symlink escapes.
+    session_file = max(candidates, key=lambda item: item[0])[1]
+    real_path = str(session_file.resolve())
+    if not real_path.startswith(project_dir + os.sep):
+        logger.warning("[Transcript] Session file escaped project dir: %s", real_path)
         return None
-
     try:
-        content = session_file.read_text()
+        async with aiofiles.open(real_path) as f:
+            content = await f.read()
         logger.info(
             "[Transcript] Read CLI session file: %s (%d bytes)",
-            session_file,
+            real_path,
             len(content),
         )
         return content
@@ -295,16 +220,10 @@ def read_cli_session_file(sdk_cwd: str) -> str | None:
 
 
 def cleanup_cli_project_dir(sdk_cwd: str) -> None:
-    """Remove the CLI's project directory for a specific working directory.
-
-    The CLI stores session data under ``~/.claude/projects/<encoded_cwd>/``.
-    Each SDK turn uses a unique ``sdk_cwd``, so the project directory is
-    safe to remove entirely after the transcript has been uploaded.
-    """
+    """Remove the CLI's project directory for a specific working directory."""
     project_dir = _cli_project_dir(sdk_cwd)
     if not project_dir:
         return
-
     if os.path.isdir(project_dir):
         shutil.rmtree(project_dir, ignore_errors=True)
         logger.debug("[Transcript] Cleaned up CLI project dir: %s", project_dir)
@@ -327,7 +246,7 @@ def write_transcript_to_tempfile(
     # Validate cwd is under the expected sandbox prefix (CodeQL sanitizer).
     real_cwd = os.path.realpath(cwd)
     if not real_cwd.startswith(_SAFE_CWD_PREFIX):
-        logger.warning(f"[Transcript] cwd outside sandbox: {cwd}")
+        logger.warning("[Transcript] cwd outside sandbox: %s", cwd)
         return None
 
     try:
@@ -337,17 +256,17 @@ def write_transcript_to_tempfile(
             os.path.join(real_cwd, f"transcript-{safe_id}.jsonl")
         )
         if not jsonl_path.startswith(real_cwd):
-            logger.warning(f"[Transcript] Path escaped cwd: {jsonl_path}")
+            logger.warning("[Transcript] Path escaped cwd: %s", jsonl_path)
             return None
 
         with open(jsonl_path, "w") as f:
             f.write(transcript_content)
 
-        logger.info(f"[Transcript] Wrote resume file: {jsonl_path}")
+        logger.info("[Transcript] Wrote resume file: %s", jsonl_path)
         return jsonl_path
 
     except OSError as e:
-        logger.warning(f"[Transcript] Failed to write resume file: {e}")
+        logger.warning("[Transcript] Failed to write resume file: %s", e)
         return None
 
 
@@ -406,27 +325,24 @@ def _meta_storage_path_parts(user_id: str, session_id: str) -> tuple[str, str, s
     )
 
 
-def _build_path_from_parts(parts: tuple[str, str, str], backend: object) -> str:
-    """Build a full storage path from (workspace_id, file_id, filename) parts."""
+def _build_storage_path(user_id: str, session_id: str, backend: object) -> str:
+    """Build the full storage path string that ``retrieve()`` expects.
+
+    ``store()`` returns a path like ``gcs://bucket/workspaces/...`` or
+    ``local://workspace_id/file_id/filename``.  Since we use deterministic
+    arguments we can reconstruct the same path for download/delete without
+    having stored the return value.
+    """
     from backend.util.workspace_storage import GCSWorkspaceStorage
 
-    wid, fid, fname = parts
+    wid, fid, fname = _storage_path_parts(user_id, session_id)
+
     if isinstance(backend, GCSWorkspaceStorage):
         blob = f"workspaces/{wid}/{fid}/{fname}"
         return f"gcs://{backend.bucket_name}/{blob}"
-    return f"local://{wid}/{fid}/{fname}"
-
-
-def _build_storage_path(user_id: str, session_id: str, backend: object) -> str:
-    """Build the full storage path string that ``retrieve()`` expects."""
-    return _build_path_from_parts(_storage_path_parts(user_id, session_id), backend)
-
-
-def _build_meta_storage_path(user_id: str, session_id: str, backend: object) -> str:
-    """Build the full storage path for the companion .meta.json file."""
-    return _build_path_from_parts(
-        _meta_storage_path_parts(user_id, session_id), backend
-    )
+    else:
+        # LocalWorkspaceStorage returns local://{relative_path}
+        return f"local://{wid}/{fid}/{fname}"
 
 
 async def upload_transcript(
@@ -494,11 +410,14 @@ async def upload_transcript(
             content=json.dumps(meta).encode("utf-8"),
         )
     except Exception as e:
-        logger.warning(f"{log_prefix} Failed to write metadata: {e}")
+        logger.warning("%s Failed to write metadata: %s", log_prefix, e)
 
     logger.info(
-        f"{log_prefix} Uploaded {len(encoded)}B "
-        f"(stripped from {len(content)}B, msg_count={message_count})"
+        "%s Uploaded %dB (stripped from %dB, msg_count=%d)",
+        log_prefix,
+        len(encoded),
+        len(content),
+        message_count,
     )
 
 
@@ -521,25 +440,37 @@ async def download_transcript(
         data = await storage.retrieve(path)
         content = data.decode("utf-8")
     except FileNotFoundError:
-        logger.debug(f"{log_prefix} No transcript in storage")
+        logger.debug("%s No transcript in storage", log_prefix)
         return None
     except Exception as e:
-        logger.warning(f"{log_prefix} Failed to download transcript: {e}")
+        logger.warning("%s Failed to download transcript: %s", log_prefix, e)
         return None
 
     # Try to load metadata (best-effort — old transcripts won't have it)
     message_count = 0
     uploaded_at = 0.0
     try:
-        meta_path = _build_meta_storage_path(user_id, session_id, storage)
+        from backend.util.workspace_storage import GCSWorkspaceStorage
+
+        mwid, mfid, mfname = _meta_storage_path_parts(user_id, session_id)
+        if isinstance(storage, GCSWorkspaceStorage):
+            blob = f"workspaces/{mwid}/{mfid}/{mfname}"
+            meta_path = f"gcs://{storage.bucket_name}/{blob}"
+        else:
+            meta_path = f"local://{mwid}/{mfid}/{mfname}"
+
         meta_data = await storage.retrieve(meta_path)
         meta = json.loads(meta_data.decode("utf-8"), fallback={})
         message_count = meta.get("message_count", 0)
         uploaded_at = meta.get("uploaded_at", 0.0)
-    except (FileNotFoundError, Exception):
+    except FileNotFoundError:
         pass  # No metadata — treat as unknown (msg_count=0 → always fill gap)
+    except Exception as e:
+        logger.debug("%s Failed to load transcript metadata: %s", log_prefix, e)
 
-    logger.info(f"{log_prefix} Downloaded {len(content)}B (msg_count={message_count})")
+    logger.info(
+        "%s Downloaded %dB (msg_count=%d)", log_prefix, len(content), message_count
+    )
     return TranscriptDownload(
         content=content,
         message_count=message_count,
@@ -547,27 +478,171 @@ async def download_transcript(
     )
 
 
-async def delete_transcript(user_id: str, session_id: str) -> None:
-    """Delete transcript and its metadata from bucket storage.
+# ---------------------------------------------------------------------------
+# Transcript compaction
+# ---------------------------------------------------------------------------
 
-    Removes both the ``.jsonl`` transcript and the companion ``.meta.json``
-    so stale ``message_count`` watermarks cannot corrupt gap-fill logic.
+# Transcripts above this byte threshold are compacted at download time.
+COMPACT_THRESHOLD_BYTES = 400_000
+
+
+def _flatten_assistant_content(blocks: list) -> str:
+    """Flatten assistant content blocks into a single plain-text string."""
+    parts: list[str] = []
+    for block in blocks:
+        if isinstance(block, dict):
+            if block.get("type") == "text":
+                parts.append(block.get("text", ""))
+            elif block.get("type") == "tool_use":
+                parts.append(f"[tool_use: {block.get('name', '?')}]")
+        elif isinstance(block, str):
+            parts.append(block)
+    return "\n".join(parts) if parts else ""
+
+
+def _flatten_tool_result_content(blocks: list) -> str:
+    """Flatten tool_result and other content blocks into plain text.
+
+    Handles nested tool_result structures, text blocks, and raw strings.
+    Uses ``json.dumps`` as fallback for dict blocks without a ``text`` key
+    or where ``text`` is ``None``.
     """
-    from backend.util.workspace_storage import get_workspace_storage
+    str_parts: list[str] = []
+    for block in blocks:
+        if isinstance(block, dict) and block.get("type") == "tool_result":
+            inner = block.get("content", "")
+            if isinstance(inner, list):
+                for sub in inner:
+                    if isinstance(sub, dict):
+                        text = sub.get("text")
+                        str_parts.append(
+                            str(text) if text is not None else json.dumps(sub)
+                        )
+                    else:
+                        str_parts.append(str(sub))
+            else:
+                str_parts.append(str(inner))
+        elif isinstance(block, dict) and block.get("type") == "text":
+            str_parts.append(str(block.get("text", "")))
+        elif isinstance(block, str):
+            str_parts.append(block)
+    return "\n".join(str_parts) if str_parts else ""
 
-    storage = await get_workspace_storage()
-    path = _build_storage_path(user_id, session_id, storage)
 
+def _transcript_to_messages(content: str) -> list[dict]:
+    """Convert JSONL transcript entries to message dicts for compress_context."""
+    messages: list[dict] = []
+    for line in content.strip().split("\n"):
+        if not line.strip():
+            continue
+        entry = json.loads(line, fallback=None)
+        if not isinstance(entry, dict):
+            continue
+        if entry.get("type", "") in STRIPPABLE_TYPES and not entry.get(
+            "isCompactSummary"
+        ):
+            continue
+        msg = entry.get("message", {})
+        role = msg.get("role", "")
+        if not role:
+            continue
+        msg_dict: dict = {"role": role}
+        raw_content = msg.get("content")
+        if role == "assistant" and isinstance(raw_content, list):
+            msg_dict["content"] = _flatten_assistant_content(raw_content)
+        elif isinstance(raw_content, list):
+            msg_dict["content"] = _flatten_tool_result_content(raw_content)
+        else:
+            msg_dict["content"] = raw_content or ""
+        messages.append(msg_dict)
+    return messages
+
+
+def _messages_to_transcript(messages: list[dict]) -> str:
+    """Convert compressed message dicts back to JSONL transcript format."""
+    lines: list[str] = []
+    last_uuid: str | None = None
+    for msg in messages:
+        role = msg.get("role", "user")
+        entry_type = "assistant" if role == "assistant" else "user"
+        uid = str(uuid4())
+        content = msg.get("content", "")
+        if role == "assistant":
+            message: dict = {
+                "role": "assistant",
+                "model": "",
+                "id": f"{COMPACT_MSG_ID_PREFIX}{uuid4().hex[:24]}",
+                "type": ENTRY_TYPE_MESSAGE,
+                "content": [{"type": "text", "text": content}] if content else [],
+                "stop_reason": STOP_REASON_END_TURN,
+                "stop_sequence": None,
+            }
+        else:
+            message = {"role": role, "content": content}
+        entry = {
+            "type": entry_type,
+            "uuid": uid,
+            "parentUuid": last_uuid,
+            "message": message,
+        }
+        lines.append(json.dumps(entry, separators=(",", ":")))
+        last_uuid = uid
+    return "\n".join(lines) + "\n" if lines else ""
+
+
+async def _run_compression(
+    messages: list[dict],
+    model: str,
+    cfg: ChatConfig,
+    log_prefix: str,
+) -> CompressResult:
+    """Run LLM-based compression with truncation fallback."""
     try:
-        await storage.delete(path)
-        logger.info("[Transcript] Deleted transcript for session %s", session_id)
+        async with openai.AsyncOpenAI(
+            api_key=cfg.api_key, base_url=cfg.base_url, timeout=30.0
+        ) as client:
+            return await compress_context(messages=messages, model=model, client=client)
     except Exception as e:
-        logger.warning("[Transcript] Failed to delete transcript: %s", e)
+        logger.warning("%s LLM compaction failed, using truncation: %s", log_prefix, e)
+        return await compress_context(messages=messages, model=model, client=None)
 
-    # Also delete the companion .meta.json to avoid orphaned metadata.
+
+async def compact_transcript(
+    content: str,
+    log_prefix: str = "[Transcript]",
+) -> str | None:
+    """Compact an oversized JSONL transcript using LLM summarization.
+
+    Converts transcript entries to plain messages, runs ``compress_context``
+    (the same compressor used for pre-query history), and rebuilds JSONL.
+
+    Returns the compacted JSONL string, or ``None`` on failure.
+    """
+    cfg = ChatConfig()
+    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:
-        meta_path = _build_meta_storage_path(user_id, session_id, storage)
-        await storage.delete(meta_path)
-        logger.info("[Transcript] Deleted metadata for session %s", session_id)
+        result = await _run_compression(messages, cfg.model, cfg, log_prefix)
+        if not result.was_compacted:
+            logger.info("%s Transcript already within token budget", log_prefix)
+            return content
+        logger.info(
+            "%s Compacted transcript: %d->%d tokens (%d summarized, %d dropped)",
+            log_prefix,
+            result.original_token_count,
+            result.token_count,
+            result.messages_summarized,
+            result.messages_dropped,
+        )
+        compacted = _messages_to_transcript(result.messages)
+        if not validate_transcript(compacted):
+            logger.warning("%s Compacted transcript failed validation", log_prefix)
+            return None
+        return compacted
     except Exception as e:
-        logger.warning("[Transcript] Failed to delete metadata: %s", e)
+        logger.error(
+            "%s Transcript compaction failed: %s", log_prefix, e, exc_info=True
+        )
+        return None

autogpt_platform/backend/backend/copilot/sdk/transcript_builder.py

@@ -30,8 +30,8 @@ class TranscriptEntry(BaseModel):
     type: str
     uuid: str
     parentUuid: str | None
-    isCompactSummary: bool | None = None
     message: dict[str, Any]
+    isCompactSummary: bool | None = None
 
 
 class TranscriptBuilder:
@@ -54,24 +54,6 @@ class TranscriptBuilder:
             return self._entries[-1].message.get("id", "")
         return ""
 
-    @staticmethod
-    def _parse_entry(data: dict) -> TranscriptEntry | None:
-        """Parse a single transcript entry, filtering strippable types.
-
-        Returns ``None`` for entries that should be skipped (strippable types
-        that are not compaction summaries).
-        """
-        entry_type = data.get("type", "")
-        if entry_type in STRIPPABLE_TYPES and not data.get("isCompactSummary"):
-            return None
-        return TranscriptEntry(
-            type=entry_type,
-            uuid=data.get("uuid") or str(uuid4()),
-            parentUuid=data.get("parentUuid"),
-            isCompactSummary=data.get("isCompactSummary") or None,
-            message=data.get("message", {}),
-        )
-
     def load_previous(self, content: str, log_prefix: str = "[Transcript]") -> None:
         """Load complete previous transcript.
 
@@ -97,9 +79,21 @@ class TranscriptBuilder:
                 )
                 continue
 
-            entry = self._parse_entry(data)
-            if entry is None:
+            # Skip STRIPPABLE_TYPES unless the entry is a compaction summary.
+            # Compaction summaries may have type "summary" but must be preserved
+            # so --resume can reconstruct the compacted conversation.
+            entry_type = data.get("type", "")
+            is_compact = data.get("isCompactSummary", False)
+            if entry_type in STRIPPABLE_TYPES and not is_compact:
                 continue
+
+            entry = TranscriptEntry(
+                type=data["type"],
+                uuid=data.get("uuid") or str(uuid4()),
+                parentUuid=data.get("parentUuid"),
+                message=data.get("message", {}),
+                isCompactSummary=True if is_compact else None,
+            )
             self._entries.append(entry)
             self._last_uuid = entry.uuid
 
@@ -172,43 +166,6 @@ class TranscriptBuilder:
         )
         self._last_uuid = msg_uuid
 
-    def replace_entries(
-        self, compacted_entries: list[dict], log_prefix: str = "[Transcript]"
-    ) -> None:
-        """Replace all entries with compacted entries from the CLI session file.
-
-        Called after mid-stream compaction so TranscriptBuilder mirrors the
-        CLI's active context (compaction summary + post-compaction entries).
-
-        Builds the new list first and validates it's non-empty before swapping,
-        so corrupt input cannot wipe the conversation history.
-        """
-        new_entries: list[TranscriptEntry] = []
-        for data in compacted_entries:
-            entry = self._parse_entry(data)
-            if entry is not None:
-                new_entries.append(entry)
-
-        if not new_entries:
-            logger.warning(
-                "%s replace_entries produced 0 entries from %d inputs, keeping old (%d entries)",
-                log_prefix,
-                len(compacted_entries),
-                len(self._entries),
-            )
-            return
-
-        old_count = len(self._entries)
-        self._entries = new_entries
-        self._last_uuid = new_entries[-1].uuid
-
-        logger.info(
-            "%s TranscriptBuilder compacted: %d entries -> %d entries",
-            log_prefix,
-            old_count,
-            len(self._entries),
-        )
-
     def to_jsonl(self) -> str:
         """Export complete context as JSONL.
 
@@ -224,6 +181,33 @@ class TranscriptBuilder:
         lines = [entry.model_dump_json(exclude_none=True) for entry in self._entries]
         return "\n".join(lines) + "\n"
 
+    def replace_entries(self, content: str, log_prefix: str = "[Transcript]") -> None:
+        """Replace all entries with compacted JSONL content.
+
+        Called after the CLI performs mid-stream compaction so the builder's
+        state reflects the compacted conversation instead of the full
+        pre-compaction history.
+        """
+        prev_count = len(self._entries)
+        temp = TranscriptBuilder()
+        try:
+            temp.load_previous(content, log_prefix=log_prefix)
+        except Exception:
+            logger.exception(
+                "%s Failed to parse compacted transcript; keeping %d existing entries",
+                log_prefix,
+                prev_count,
+            )
+            return
+        self._entries = temp._entries
+        self._last_uuid = temp._last_uuid
+        logger.info(
+            "%s Replaced %d entries with %d compacted entries",
+            log_prefix,
+            prev_count,
+            len(self._entries),
+        )
+
     @property
     def entry_count(self) -> int:
         """Total number of entries in the complete context."""

autogpt_platform/backend/backend/copilot/service.py

@@ -28,24 +28,10 @@ logger = logging.getLogger(__name__)
 
 config = ChatConfig()
 settings = Settings()
-
-_client: LangfuseAsyncOpenAI | None = None
-_langfuse = None
+client = LangfuseAsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
 
 
-def _get_openai_client() -> LangfuseAsyncOpenAI:
-    global _client
-    if _client is None:
-        _client = LangfuseAsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
-    return _client
-
-
-def _get_langfuse():
-    global _langfuse
-    if _langfuse is None:
-        _langfuse = get_client()
-    return _langfuse
-
+langfuse = get_client()
 
 # Default system prompt used when Langfuse is not configured
 # Provides minimal baseline tone and personality - all workflow, tools, and
@@ -98,7 +84,7 @@ async def _get_system_prompt_template(context: str) -> str:
                 else "latest"
             )
             prompt = await asyncio.to_thread(
-                _get_langfuse().get_prompt,
+                langfuse.get_prompt,
                 config.langfuse_prompt_name,
                 label=label,
                 cache_ttl_seconds=config.langfuse_prompt_cache_ttl,
@@ -172,7 +158,7 @@ async def _generate_session_title(
             "environment": settings.config.app_env.value,
         }
 
-        response = await _get_openai_client().chat.completions.create(
+        response = await client.chat.completions.create(
             model=config.title_model,
             messages=[
                 {

autogpt_platform/backend/backend/copilot/token_tracking.py

@@ -1,93 +0,0 @@
-"""Shared token-usage persistence and rate-limit recording.
-
-Both the baseline (OpenRouter) and SDK (Anthropic) service layers need to:
-  1. Append a ``Usage`` record to the session.
-  2. Log the turn's token counts.
-  3. Record weighted usage in Redis for rate-limiting.
-
-This module extracts that common logic so both paths stay in sync.
-"""
-
-import logging
-
-from .model import ChatSession, Usage
-from .rate_limit import record_token_usage
-
-logger = logging.getLogger(__name__)
-
-
-async def persist_and_record_usage(
-    *,
-    session: ChatSession | None,
-    user_id: str | None,
-    prompt_tokens: int,
-    completion_tokens: int,
-    cache_read_tokens: int = 0,
-    cache_creation_tokens: int = 0,
-    log_prefix: str = "",
-    cost_usd: float | str | None = None,
-) -> int:
-    """Persist token usage to session and record for rate limiting.
-
-    Args:
-        session: The chat session to append usage to (may be None on error).
-        user_id: User ID for rate-limit counters (skipped if None).
-        prompt_tokens: Uncached input tokens.
-        completion_tokens: Output tokens.
-        cache_read_tokens: Tokens served from prompt cache (Anthropic only).
-        cache_creation_tokens: Tokens written to prompt cache (Anthropic only).
-        log_prefix: Prefix for log messages (e.g. "[SDK]", "[Baseline]").
-        cost_usd: Optional cost for logging (float from SDK, str otherwise).
-
-    Returns:
-        The computed total_tokens (prompt + completion; cache excluded).
-    """
-    prompt_tokens = max(0, prompt_tokens)
-    completion_tokens = max(0, completion_tokens)
-    cache_read_tokens = max(0, cache_read_tokens)
-    cache_creation_tokens = max(0, cache_creation_tokens)
-
-    if prompt_tokens <= 0 and completion_tokens <= 0:
-        return 0
-
-    # total_tokens = prompt + completion. Cache tokens are tracked
-    # separately and excluded from total so both baseline and SDK
-    # paths share the same semantics.
-    total_tokens = prompt_tokens + completion_tokens
-
-    if session is not None:
-        session.usage.append(
-            Usage(
-                prompt_tokens=prompt_tokens,
-                completion_tokens=completion_tokens,
-                total_tokens=total_tokens,
-                cache_read_tokens=cache_read_tokens,
-                cache_creation_tokens=cache_creation_tokens,
-            )
-        )
-
-    if cache_read_tokens or cache_creation_tokens:
-        logger.info(
-            f"{log_prefix} Turn usage: uncached={prompt_tokens}, "
-            f"cache_read={cache_read_tokens}, cache_create={cache_creation_tokens}, "
-            f"output={completion_tokens}, total={total_tokens}, cost_usd={cost_usd}"
-        )
-    else:
-        logger.info(
-            f"{log_prefix} Turn usage: prompt={prompt_tokens}, "
-            f"completion={completion_tokens}, total={total_tokens}"
-        )
-
-    if user_id:
-        try:
-            await record_token_usage(
-                user_id=user_id,
-                prompt_tokens=prompt_tokens,
-                completion_tokens=completion_tokens,
-                cache_read_tokens=cache_read_tokens,
-                cache_creation_tokens=cache_creation_tokens,
-            )
-        except Exception as usage_err:
-            logger.warning(f"{log_prefix} Failed to record token usage: {usage_err}")
-
-    return total_tokens

autogpt_platform/backend/backend/copilot/token_tracking_test.py

@@ -1,281 +0,0 @@
-"""Unit tests for token_tracking.persist_and_record_usage.
-
-Covers both the baseline (prompt+completion only) and SDK (with cache breakdown)
-calling conventions, session persistence, and rate-limit recording.
-"""
-
-from datetime import UTC, datetime
-from unittest.mock import AsyncMock, patch
-
-import pytest
-
-from .model import ChatSession, Usage
-from .token_tracking import persist_and_record_usage
-
-
-def _make_session() -> ChatSession:
-    """Return a minimal in-memory ChatSession for testing."""
-    return ChatSession(
-        session_id="sess-test",
-        user_id="user-test",
-        title=None,
-        messages=[],
-        usage=[],
-        started_at=datetime.now(UTC),
-        updated_at=datetime.now(UTC),
-    )
-
-
-# ---------------------------------------------------------------------------
-# Return value / total_tokens semantics
-# ---------------------------------------------------------------------------
-
-
-class TestTotalTokens:
-    @pytest.mark.asyncio
-    async def test_returns_prompt_plus_completion(self):
-        """total_tokens = prompt + completion (cache excluded from total)."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=300,
-                completion_tokens=200,
-            )
-        assert total == 500
-
-    @pytest.mark.asyncio
-    async def test_returns_zero_when_no_tokens(self):
-        """Returns 0 early when both prompt and completion are zero."""
-        total = await persist_and_record_usage(
-            session=None,
-            user_id=None,
-            prompt_tokens=0,
-            completion_tokens=0,
-        )
-        assert total == 0
-
-    @pytest.mark.asyncio
-    async def test_cache_tokens_excluded_from_total(self):
-        """Cache tokens are stored separately and not added to total_tokens."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-                cache_read_tokens=5000,
-                cache_creation_tokens=200,
-            )
-        # total = prompt + completion only (5000 + 200 cache excluded)
-        assert total == 150
-
-    @pytest.mark.asyncio
-    async def test_baseline_path_no_cache(self):
-        """Baseline (OpenRouter) path passes no cache tokens; total = prompt + completion."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id="u1",
-                prompt_tokens=1000,
-                completion_tokens=400,
-                log_prefix="[Baseline]",
-            )
-        assert total == 1400
-
-    @pytest.mark.asyncio
-    async def test_sdk_path_with_cache(self):
-        """SDK (Anthropic) path passes cache tokens; total still = prompt + completion."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id="u2",
-                prompt_tokens=200,
-                completion_tokens=100,
-                cache_read_tokens=8000,
-                cache_creation_tokens=400,
-                log_prefix="[SDK]",
-                cost_usd=0.0015,
-            )
-        assert total == 300
-
-
-# ---------------------------------------------------------------------------
-# Session persistence
-# ---------------------------------------------------------------------------
-
-
-class TestSessionPersistence:
-    @pytest.mark.asyncio
-    async def test_appends_usage_to_session(self):
-        session = _make_session()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            await persist_and_record_usage(
-                session=session,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        assert len(session.usage) == 1
-        usage: Usage = session.usage[0]
-        assert usage.prompt_tokens == 100
-        assert usage.completion_tokens == 50
-        assert usage.total_tokens == 150
-        assert usage.cache_read_tokens == 0
-        assert usage.cache_creation_tokens == 0
-
-    @pytest.mark.asyncio
-    async def test_appends_cache_breakdown_to_session(self):
-        session = _make_session()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            await persist_and_record_usage(
-                session=session,
-                user_id=None,
-                prompt_tokens=200,
-                completion_tokens=80,
-                cache_read_tokens=3000,
-                cache_creation_tokens=500,
-            )
-        usage: Usage = session.usage[0]
-        assert usage.cache_read_tokens == 3000
-        assert usage.cache_creation_tokens == 500
-
-    @pytest.mark.asyncio
-    async def test_multiple_turns_append_multiple_records(self):
-        session = _make_session()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            await persist_and_record_usage(
-                session=session, user_id=None, prompt_tokens=100, completion_tokens=50
-            )
-            await persist_and_record_usage(
-                session=session, user_id=None, prompt_tokens=200, completion_tokens=70
-            )
-        assert len(session.usage) == 2
-
-    @pytest.mark.asyncio
-    async def test_none_session_does_not_raise(self):
-        """When session is None (e.g. error path), no exception should be raised."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        assert total == 150
-
-    @pytest.mark.asyncio
-    async def test_no_append_when_zero_tokens(self):
-        """When tokens are zero, function returns early — session unchanged."""
-        session = _make_session()
-        total = await persist_and_record_usage(
-            session=session,
-            user_id=None,
-            prompt_tokens=0,
-            completion_tokens=0,
-        )
-        assert total == 0
-        assert len(session.usage) == 0
-
-
-# ---------------------------------------------------------------------------
-# Rate-limit recording
-# ---------------------------------------------------------------------------
-
-
-class TestRateLimitRecording:
-    @pytest.mark.asyncio
-    async def test_calls_record_token_usage_when_user_id_present(self):
-        mock_record = AsyncMock()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            await persist_and_record_usage(
-                session=None,
-                user_id="user-abc",
-                prompt_tokens=100,
-                completion_tokens=50,
-                cache_read_tokens=1000,
-                cache_creation_tokens=200,
-            )
-        mock_record.assert_awaited_once_with(
-            user_id="user-abc",
-            prompt_tokens=100,
-            completion_tokens=50,
-            cache_read_tokens=1000,
-            cache_creation_tokens=200,
-        )
-
-    @pytest.mark.asyncio
-    async def test_skips_record_when_user_id_is_none(self):
-        """Anonymous sessions should not create Redis keys."""
-        mock_record = AsyncMock()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        mock_record.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_record_failure_does_not_raise(self):
-        """A Redis error in record_token_usage should be swallowed (fail-open)."""
-        mock_record = AsyncMock(side_effect=ConnectionError("Redis down"))
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            # Should not raise
-            total = await persist_and_record_usage(
-                session=None,
-                user_id="user-xyz",
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        assert total == 150
-
-    @pytest.mark.asyncio
-    async def test_skips_record_when_zero_tokens(self):
-        """Returns 0 before calling record_token_usage when tokens are zero."""
-        mock_record = AsyncMock()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            await persist_and_record_usage(
-                session=None,
-                user_id="user-abc",
-                prompt_tokens=0,
-                completion_tokens=0,
-            )
-        mock_record.assert_not_awaited()

autogpt_platform/backend/backend/copilot/tools/agent_browser.py

@@ -32,7 +32,6 @@ import shutil
 import tempfile
 from typing import Any
 
-from backend.copilot.context import get_workspace_manager
 from backend.copilot.model import ChatSession
 from backend.util.request import validate_url_host
 
@@ -44,6 +43,7 @@ from .models import (
     ErrorResponse,
     ToolResponseBase,
 )
+from .workspace_files import get_manager
 
 logger = logging.getLogger(__name__)
 
@@ -194,7 +194,7 @@ async def _save_browser_state(
             ),
         }
 
-        manager = await get_workspace_manager(user_id, session.session_id)
+        manager = await get_manager(user_id, session.session_id)
         await manager.write_file(
             content=json.dumps(state).encode("utf-8"),
             filename=_STATE_FILENAME,
@@ -218,7 +218,7 @@ async def _restore_browser_state(
     Returns True on success (or no state to restore), False on failure.
     """
     try:
-        manager = await get_workspace_manager(user_id, session.session_id)
+        manager = await get_manager(user_id, session.session_id)
 
         file_info = await manager.get_file_info_by_path(_STATE_FILENAME)
         if file_info is None:
@@ -360,7 +360,7 @@ async def close_browser_session(session_name: str, user_id: str | None = None) -
     # Delete persisted browser state (cookies, localStorage) from workspace.
     if user_id:
         try:
-            manager = await get_workspace_manager(user_id, session_name)
+            manager = await get_manager(user_id, session_name)
             file_info = await manager.get_file_info_by_path(_STATE_FILENAME)
             if file_info is not None:
                 await manager.delete_file(file_info.id)

autogpt_platform/backend/backend/copilot/tools/agent_browser_test.py

@@ -897,7 +897,7 @@ class TestHasLocalSession:
 # _save_browser_state
 # ---------------------------------------------------------------------------
 
-_GET_MANAGER = "backend.copilot.tools.agent_browser.get_workspace_manager"
+_GET_MANAGER = "backend.copilot.tools.agent_browser.get_manager"
 
 
 def _make_mock_manager():

autogpt_platform/backend/backend/copilot/tools/agent_generator/validator.py

@@ -935,5 +935,5 @@ class AgentValidator:
             for i, error in enumerate(self.errors, 1):
                 error_message += f"{i}. {error}\n"
 
-            logger.warning(f"Agent validation failed: {error_message}")
+            logger.error(f"Agent validation failed: {error_message}")
             return False, error_message

autogpt_platform/backend/backend/copilot/tools/helpers.py

@@ -8,12 +8,14 @@ from pydantic_core import PydanticUndefined
 
 from backend.blocks._base import AnyBlockSchema
 from backend.copilot.constants import COPILOT_NODE_PREFIX, COPILOT_SESSION_PREFIX
-from backend.data.credit import UsageTransactionMetadata
-from backend.data.db_accessors import credit_db, workspace_db
+from backend.data import db
+from backend.data.credit import UsageTransactionMetadata, get_user_credit_model
+from backend.data.db_accessors import workspace_db
 from backend.data.execution import ExecutionContext
 from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
 from backend.executor.utils import block_usage_cost
 from backend.integrations.creds_manager import IntegrationCredentialsManager
+from backend.util.clients import get_database_manager_async_client
 from backend.util.exceptions import BlockError, InsufficientBalanceError
 from backend.util.type import coerce_inputs_to_schema
 
@@ -23,6 +25,26 @@ from .utils import match_credentials_to_requirements
 logger = logging.getLogger(__name__)
 
 
+async def _get_credits(user_id: str) -> int:
+    """Get user credits using the adapter pattern (RPC when Prisma unavailable)."""
+    if not db.is_connected():
+        return await get_database_manager_async_client().get_credits(user_id)
+    credit_model = await get_user_credit_model(user_id)
+    return await credit_model.get_credits(user_id)
+
+
+async def _spend_credits(
+    user_id: str, cost: int, metadata: UsageTransactionMetadata
+) -> int:
+    """Spend user credits using the adapter pattern (RPC when Prisma unavailable)."""
+    if not db.is_connected():
+        return await get_database_manager_async_client().spend_credits(
+            user_id, cost, metadata
+        )
+    credit_model = await get_user_credit_model(user_id)
+    return await credit_model.spend_credits(user_id, cost, metadata)
+
+
 def get_inputs_from_schema(
     input_schema: dict[str, Any],
     exclude_fields: set[str] | None = None,
@@ -117,12 +139,11 @@ async def execute_block(
         # Coerce non-matching data types to the expected input schema.
         coerce_inputs_to_schema(input_data, block.input_schema)
 
-        # Pre-execution credit check (courtesy; spend_credits is atomic)
+        # Pre-execution credit check
         cost, cost_filter = block_usage_cost(block, input_data)
         has_cost = cost > 0
-        _credit_db = credit_db()
         if has_cost:
-            balance = await _credit_db.get_credits(user_id)
+            balance = await _get_credits(user_id)
             if balance < cost:
                 return ErrorResponse(
                     message=(
@@ -143,7 +164,7 @@ async def execute_block(
         # Charge credits for block execution
         if has_cost:
             try:
-                await _credit_db.spend_credits(
+                await _spend_credits(
                     user_id=user_id,
                     cost=cost,
                     metadata=UsageTransactionMetadata(
@@ -157,32 +178,18 @@ async def execute_block(
                         reason="copilot_block_execution",
                     ),
                 )
-            except Exception as e:
-                # Block already executed (with possible side effects). Never
-                # return ErrorResponse here — the user received output and
-                # deserves it. Log the billing failure for reconciliation.
-                leak_type = (
-                    "INSUFFICIENT_BALANCE"
-                    if isinstance(e, InsufficientBalanceError)
-                    else "UNEXPECTED_ERROR"
-                )
-                logger.error(
-                    "BILLING_LEAK[%s]: block executed but credit charge failed — "
-                    "user_id=%s, block_id=%s, node_exec_id=%s, cost=%s: %s",
-                    leak_type,
-                    user_id,
-                    block_id,
-                    node_exec_id,
+            except InsufficientBalanceError:
+                logger.warning(
+                    "Post-exec credit charge failed for block %s (cost=%d)",
+                    block.name,
                     cost,
-                    e,
-                    extra={
-                        "json_fields": {
-                            "billing_leak": True,
-                            "leak_type": leak_type,
-                            "user_id": user_id,
-                            "cost": str(cost),
-                        }
-                    },
+                )
+                return ErrorResponse(
+                    message=(
+                        f"Insufficient credits to complete '{block.name}'. "
+                        "Please top up your credits to continue."
+                    ),
+                    session_id=session_id,
                 )
 
         return BlockOutputResponse(
@@ -204,7 +211,7 @@ async def execute_block(
     except Exception as e:
         logger.error("Unexpected error executing block: %s", e, exc_info=True)
         return ErrorResponse(
-            message=f"Failed to execute block: {str(e)}",
+            message="An unexpected error occurred while executing the block",
             error=str(e),
             session_id=session_id,
         )

autogpt_platform/backend/backend/copilot/tools/helpers_test.py

@@ -42,37 +42,17 @@ def _patch_workspace():
     return patch("backend.copilot.tools.helpers.workspace_db", return_value=mock_ws_db)
 
 
-def _patch_credit_db(
-    get_credits_return: int = 100,
-    spend_credits_side_effect: Any = None,
-):
-    """Patch credit_db accessor to return a mock credit adapter."""
-    mock_credit = MagicMock()
-    mock_credit.get_credits = AsyncMock(return_value=get_credits_return)
-    if spend_credits_side_effect is not None:
-        mock_credit.spend_credits = AsyncMock(side_effect=spend_credits_side_effect)
-    else:
-        mock_credit.spend_credits = AsyncMock()
-    return (
-        patch(
-            "backend.copilot.tools.helpers.credit_db",
-            return_value=mock_credit,
-        ),
-        mock_credit,
-    )
-
-
 # ---------------------------------------------------------------------------
 # Credit charging tests
 # ---------------------------------------------------------------------------
 
 
-@pytest.mark.asyncio(loop_scope="session")
+@pytest.mark.asyncio
 class TestExecuteBlockCreditCharging:
     async def test_charges_credits_when_cost_is_positive(self):
         """Block with cost > 0 should call spend_credits after execution."""
         block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db(get_credits_return=100)
+        mock_spend = AsyncMock()
 
         with (
             _patch_workspace(),
@@ -80,7 +60,16 @@ class TestExecuteBlockCreditCharging:
                 "backend.copilot.tools.helpers.block_usage_cost",
                 return_value=(10, {"key": "val"}),
             ),
-            credit_patch,
+            patch(
+                "backend.copilot.tools.helpers._get_credits",
+                new_callable=AsyncMock,
+                return_value=100,
+            ),
+            patch(
+                "backend.copilot.tools.helpers._spend_credits",
+                new_callable=AsyncMock,
+                side_effect=mock_spend,
+            ),
         ):
             result = await execute_block(
                 block=block,
@@ -94,15 +83,14 @@ class TestExecuteBlockCreditCharging:
 
         assert isinstance(result, BlockOutputResponse)
         assert result.success is True
-        mock_credit.spend_credits.assert_awaited_once()
-        call_kwargs = mock_credit.spend_credits.call_args.kwargs
+        mock_spend.assert_awaited_once()
+        call_kwargs = mock_spend.call_args.kwargs
         assert call_kwargs["cost"] == 10
         assert call_kwargs["metadata"].reason == "copilot_block_execution"
 
     async def test_returns_error_when_insufficient_credits_before_exec(self):
         """Pre-execution check should return ErrorResponse when balance < cost."""
         block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db(get_credits_return=5)
 
         with (
             _patch_workspace(),
@@ -110,7 +98,11 @@ class TestExecuteBlockCreditCharging:
                 "backend.copilot.tools.helpers.block_usage_cost",
                 return_value=(10, {}),
             ),
-            credit_patch,
+            patch(
+                "backend.copilot.tools.helpers._get_credits",
+                new_callable=AsyncMock,
+                return_value=5,  # balance < cost (10)
+            ),
         ):
             result = await execute_block(
                 block=block,
@@ -128,7 +120,6 @@ class TestExecuteBlockCreditCharging:
     async def test_no_charge_when_cost_is_zero(self):
         """Block with cost 0 should not call spend_credits."""
         block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db()
 
         with (
             _patch_workspace(),
@@ -136,7 +127,12 @@ class TestExecuteBlockCreditCharging:
                 "backend.copilot.tools.helpers.block_usage_cost",
                 return_value=(0, {}),
             ),
-            credit_patch,
+            patch(
+                "backend.copilot.tools.helpers._get_credits",
+            ) as mock_get_credits,
+            patch(
+                "backend.copilot.tools.helpers._spend_credits",
+            ) as mock_spend_credits,
         ):
             result = await execute_block(
                 block=block,
@@ -151,20 +147,14 @@ class TestExecuteBlockCreditCharging:
         assert isinstance(result, BlockOutputResponse)
         assert result.success is True
         # Credit functions should not be called at all for zero-cost blocks
-        mock_credit.get_credits.assert_not_awaited()
-        mock_credit.spend_credits.assert_not_awaited()
+        mock_get_credits.assert_not_awaited()
+        mock_spend_credits.assert_not_awaited()
 
-    async def test_returns_output_on_post_exec_insufficient_balance(self):
-        """If charging fails after execution, output is still returned (block already ran)."""
+    async def test_returns_error_on_post_exec_insufficient_balance(self):
+        """If charging fails after execution, return ErrorResponse."""
         from backend.util.exceptions import InsufficientBalanceError
 
         block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db(
-            get_credits_return=15,
-            spend_credits_side_effect=InsufficientBalanceError(
-                "Low balance", _USER, 5, 10
-            ),
-        )
 
         with (
             _patch_workspace(),
@@ -172,7 +162,18 @@ class TestExecuteBlockCreditCharging:
                 "backend.copilot.tools.helpers.block_usage_cost",
                 return_value=(10, {}),
             ),
-            credit_patch,
+            patch(
+                "backend.copilot.tools.helpers._get_credits",
+                new_callable=AsyncMock,
+                return_value=15,  # passes pre-check
+            ),
+            patch(
+                "backend.copilot.tools.helpers._spend_credits",
+                new_callable=AsyncMock,
+                side_effect=InsufficientBalanceError(
+                    "Low balance", _USER, 5, 10
+                ),  # fails during actual charge (race with concurrent spend)
+            ),
         ):
             result = await execute_block(
                 block=block,
@@ -184,9 +185,8 @@ class TestExecuteBlockCreditCharging:
                 matched_credentials={},
             )
 
-        # Block already executed (with side effects), so output is returned
-        assert isinstance(result, BlockOutputResponse)
-        assert result.success is True
+        assert isinstance(result, ErrorResponse)
+        assert "Insufficient credits" in result.message
 
 
 # ---------------------------------------------------------------------------
@@ -197,7 +197,6 @@ class TestExecuteBlockCreditCharging:
 def _make_block_schema(annotations: dict[str, Any]) -> MagicMock:
     """Create a mock input_schema with model_fields matching the given annotations."""
     schema = MagicMock()
-    # coerce_inputs_to_schema uses model_fields (Pydantic v2 API)
     model_fields = {}
     for name, ann in annotations.items():
         field = MagicMock()
@@ -269,7 +268,6 @@ async def test_coerce_json_string_to_nested_list():
 
     assert isinstance(response, BlockOutputResponse)
     assert response.success is True
-    # Verify the input was coerced from string to list[list[str]]
     assert block._captured_inputs["values"] == [
         ["Name", "Score"],
         ["Alice", "90"],
@@ -439,7 +437,6 @@ async def test_coerce_skips_none_values():
         )
 
     assert isinstance(response, BlockOutputResponse)
-    # 'data' was not provided, so it should not appear in captured inputs
     assert "data" not in block._captured_inputs
 
 
@@ -472,7 +469,6 @@ async def test_coerce_union_type_preserves_valid_member():
         )
 
     assert isinstance(response, BlockOutputResponse)
-    # list[str] should NOT be stringified to '["a", "b"]'
     assert block._captured_inputs["content"] == ["a", "b"]
     assert isinstance(block._captured_inputs["content"], list)
 
@@ -498,7 +494,6 @@ async def test_coerce_inner_elements_of_generic():
         response = await execute_block(
             block=block,
             block_id="inner-coerce",
-            # Inner elements are ints, but target is list[str]
             input_data={"values": [1, 2, 3]},
             user_id=_TEST_USER_ID,
             session_id=_TEST_SESSION_ID,
@@ -507,6 +502,5 @@ async def test_coerce_inner_elements_of_generic():
         )
 
     assert isinstance(response, BlockOutputResponse)
-    # Inner elements should be coerced from int to str
     assert block._captured_inputs["values"] == ["1", "2", "3"]
     assert all(isinstance(v, str) for v in block._captured_inputs["values"])

autogpt_platform/backend/backend/copilot/tools/run_block.py

@@ -12,7 +12,6 @@ from backend.copilot.constants import (
     COPILOT_SESSION_PREFIX,
 )
 from backend.copilot.model import ChatSession
-from backend.copilot.sdk.file_ref import FileRefExpansionError, expand_file_refs_in_args
 from backend.data.db_accessors import review_db
 from backend.data.execution import ExecutionContext
 
@@ -198,29 +197,6 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Expand @@agptfile: refs in input_data with the block's input
-        # schema.  The generic _truncating wrapper skips opaque object
-        # properties (input_data has no declared inner properties in the
-        # tool schema), so file ref tokens are still intact here.
-        # Using the block's schema lets us return raw text for string-typed
-        # fields and parsed structures for list/dict-typed fields.
-        if input_data:
-            try:
-                input_data = await expand_file_refs_in_args(
-                    input_data,
-                    user_id,
-                    session,
-                    input_schema=input_schema,
-                )
-            except FileRefExpansionError as exc:
-                return ErrorResponse(
-                    message=(
-                        f"Failed to resolve file reference: {exc}. "
-                        "Ensure the file exists before referencing it."
-                    ),
-                    session_id=session_id,
-                )
-
         if missing_credentials:
             # Return setup requirements response with missing credentials
             credentials_fields_info = block.input_schema.get_credentials_fields_info()

autogpt_platform/backend/backend/copilot/tools/run_mcp_tool.py

@@ -184,12 +184,10 @@ class RunMCPToolTool(BaseTool):
             if e.status_code in _AUTH_STATUS_CODES and not creds:
                 # Server requires auth and user has no stored credentials
                 return self._build_setup_requirements(server_url, session_id)
-            host = server_host(server_url)
-            logger.warning("MCP HTTP error for %s: status=%s", host, e.status_code)
+            logger.warning("MCP HTTP error for %s: %s", server_host(server_url), e)
             return ErrorResponse(
-                message=(f"MCP request to {host} failed with HTTP {e.status_code}."),
+                message=f"MCP server returned HTTP {e.status_code}: {e}",
                 session_id=session_id,
-                error=f"HTTP {e.status_code}: {str(e)[:300]}",
             )
 
         except MCPClientError as e:

autogpt_platform/backend/backend/copilot/tools/test_run_mcp_tool.py

@@ -580,49 +580,6 @@ async def test_auth_error_with_existing_creds_returns_error():
     assert "403" in response.message
 
 
-@pytest.mark.asyncio(loop_scope="session")
-async def test_http_error_returns_clean_message_with_collapsible_detail():
-    """Non-auth HTTP errors return a clean message with raw detail in the `error` field."""
-    from backend.util.request import HTTPClientError
-
-    tool = RunMCPToolTool()
-    session = make_session(_USER_ID)
-
-    with patch(
-        "backend.copilot.tools.run_mcp_tool.validate_url_host", new_callable=AsyncMock
-    ):
-        with patch(
-            "backend.copilot.tools.run_mcp_tool.auto_lookup_mcp_credential",
-            new_callable=AsyncMock,
-            return_value=None,
-        ):
-            mock_client = AsyncMock()
-            mock_client.initialize = AsyncMock(
-                side_effect=HTTPClientError(
-                    "<!doctype html><html><body>Not Found</body></html>",
-                    status_code=404,
-                )
-            )
-            with patch(
-                "backend.copilot.tools.run_mcp_tool.MCPClient",
-                return_value=mock_client,
-            ):
-                response = await tool._execute(
-                    user_id=_USER_ID,
-                    session=session,
-                    server_url=_SERVER_URL,
-                )
-
-    assert isinstance(response, ErrorResponse)
-    assert "404" in response.message
-    # Raw HTML body must NOT leak into the user-facing message
-    assert "<!doctype" not in response.message
-    # Raw detail (including original body) goes in the collapsible `error` field
-    assert response.error is not None
-    assert "404" in response.error
-    assert "<!doctype" in response.error.lower()
-
-
 @pytest.mark.asyncio(loop_scope="session")
 async def test_mcp_client_error_returns_error_response():
     """MCPClientError (protocol-level) maps to a clean ErrorResponse."""

autogpt_platform/backend/backend/copilot/tools/workspace_files.py

@@ -10,11 +10,11 @@ from pydantic import BaseModel
 from backend.copilot.context import (
     E2B_WORKDIR,
     get_current_sandbox,
-    get_workspace_manager,
     resolve_sandbox_path,
 )
 from backend.copilot.model import ChatSession
 from backend.copilot.tools.sandbox import make_session_path
+from backend.data.db_accessors import workspace_db
 from backend.util.settings import Config
 from backend.util.virus_scanner import scan_content_safe
 from backend.util.workspace import WorkspaceManager
@@ -218,6 +218,12 @@ def _is_text_mime(mime_type: str) -> bool:
     return any(mime_type.startswith(t) for t in _TEXT_MIME_PREFIXES)
 
 
+async def get_manager(user_id: str, session_id: str) -> WorkspaceManager:
+    """Create a session-scoped WorkspaceManager."""
+    workspace = await workspace_db().get_or_create_workspace(user_id)
+    return WorkspaceManager(user_id, workspace.id, session_id)
+
+
 async def _resolve_file(
     manager: WorkspaceManager,
     file_id: str | None,
@@ -380,7 +386,7 @@ class ListWorkspaceFilesTool(BaseTool):
         include_all_sessions: bool = kwargs.get("include_all_sessions", False)
 
         try:
-            manager = await get_workspace_manager(user_id, session_id)
+            manager = await get_manager(user_id, session_id)
             files = await manager.list_files(
                 path=path_prefix, limit=limit, include_all_sessions=include_all_sessions
             )
@@ -530,7 +536,7 @@ class ReadWorkspaceFileTool(BaseTool):
             )
 
         try:
-            manager = await get_workspace_manager(user_id, session_id)
+            manager = await get_manager(user_id, session_id)
             resolved = await _resolve_file(manager, file_id, path, session_id)
             if isinstance(resolved, ErrorResponse):
                 return resolved
@@ -766,7 +772,7 @@ class WriteWorkspaceFileTool(BaseTool):
 
         try:
             await scan_content_safe(content, filename=filename)
-            manager = await get_workspace_manager(user_id, session_id)
+            manager = await get_manager(user_id, session_id)
             rec = await manager.write_file(
                 content=content,
                 filename=filename,
@@ -893,7 +899,7 @@ class DeleteWorkspaceFileTool(BaseTool):
             )
 
         try:
-            manager = await get_workspace_manager(user_id, session_id)
+            manager = await get_manager(user_id, session_id)
             resolved = await _resolve_file(manager, file_id, path, session_id)
             if isinstance(resolved, ErrorResponse):
                 return resolved

autogpt_platform/backend/backend/data/db_accessors.py

@@ -129,16 +129,3 @@ def review_db():
         review_db = get_database_manager_async_client()
 
     return review_db
-
-
-def credit_db():
-    if db.is_connected():
-        from backend.data import db_manager as _credit_db
-
-        credit_db = _credit_db
-    else:
-        from backend.util.clients import get_database_manager_async_client
-
-        credit_db = get_database_manager_async_client()
-
-    return credit_db

autogpt_platform/backend/backend/data/db_manager.py

@@ -148,11 +148,6 @@ async def _get_credits(user_id: str) -> int:
     return await user_credit_model.get_credits(user_id)
 
 
-# Public aliases used by db_accessors.credit_db() when Prisma is connected
-get_credits = _get_credits
-spend_credits = _spend_credits
-
-
 class DatabaseManager(AppService):
     """Database connection pooling service.
 

autogpt_platform/backend/backend/executor/manager.py

@@ -61,12 +61,7 @@ from backend.util.decorator import (
     error_logged,
     time_measured,
 )
-from backend.util.exceptions import (
-    GraphNotFoundError,
-    InsufficientBalanceError,
-    ModerationError,
-    NotFoundError,
-)
+from backend.util.exceptions import InsufficientBalanceError, ModerationError
 from backend.util.file import clean_exec_files
 from backend.util.logging import TruncatedLogger, configure_logging
 from backend.util.metrics import DiscordChannel
@@ -380,16 +375,9 @@ async def execute_node(
             log_metadata.debug("Node produced output", **{output_name: output_data})
             yield output_name, output_data
     except Exception as ex:
-        # Only capture unexpected errors to Sentry, not user-caused ones.
-        # Most ValueError subclasses here are expected (BlockExecutionError,
-        # InsufficientBalanceError, plain ValueError for auth/disabled blocks, etc.)
-        # but NotFoundError/GraphNotFoundError could indicate real platform issues.
-        is_expected = isinstance(ex, ValueError) and not isinstance(
-            ex, (NotFoundError, GraphNotFoundError)
-        )
-        if not is_expected:
-            sentry_sdk.capture_exception(error=ex, scope=scope)
-            sentry_sdk.flush()
+        # Capture exception WITH context still set before restoring scope
+        sentry_sdk.capture_exception(error=ex, scope=scope)
+        sentry_sdk.flush()  # Ensure it's sent before we restore scope
         # Re-raise to maintain normal error flow
         raise
     finally:
@@ -1490,7 +1478,7 @@ class ExecutionProcessor:
                     alert_message, DiscordChannel.PRODUCT
                 )
             except Exception as e:
-                logger.warning(f"Failed to send low balance Discord alert: {e}")
+                logger.error(f"Failed to send low balance Discord alert: {e}")
 
 
 class ExecutionManager(AppProcess):
@@ -1912,16 +1900,17 @@ class ExecutionManager(AppProcess):
             channel = client.get_channel()
             channel.connection.add_callback_threadsafe(lambda: channel.stop_consuming())
 
-            thread.join(timeout=300)
-            if thread.is_alive():
-                logger.warning(
+            try:
+                thread.join(timeout=300)
+            except TimeoutError:
+                logger.error(
                     f"{prefix} ⚠️ Run thread did not finish in time, forcing disconnect"
                 )
 
             client.disconnect()
             logger.info(f"{prefix} ✅ Run client disconnected")
         except Exception as e:
-            logger.warning(f"{prefix} ⚠️ Error disconnecting run client: {type(e)} {e}")
+            logger.error(f"{prefix} ⚠️ Error disconnecting run client: {type(e)} {e}")
 
     def cleanup(self):
         """Override cleanup to implement graceful shutdown with active execution waiting."""
@@ -1937,9 +1926,7 @@ class ExecutionManager(AppProcess):
             )
             logger.info(f"{prefix} ✅ Exec consumer has been signaled to stop")
         except Exception as e:
-            logger.warning(
-                f"{prefix} ⚠️ Error signaling consumer to stop: {type(e)} {e}"
-            )
+            logger.error(f"{prefix} ⚠️ Error signaling consumer to stop: {type(e)} {e}")
 
         # Wait for active executions to complete
         if self.active_graph_runs:
@@ -1970,7 +1957,7 @@ class ExecutionManager(AppProcess):
                 waited += wait_interval
 
             if self.active_graph_runs:
-                logger.warning(
+                logger.error(
                     f"{prefix} ⚠️ {len(self.active_graph_runs)} executions still running after {max_wait}s"
                 )
             else:
@@ -1981,7 +1968,7 @@ class ExecutionManager(AppProcess):
             self.executor.shutdown(cancel_futures=True, wait=False)
             logger.info(f"{prefix} ✅ Executor shutdown completed")
         except Exception as e:
-            logger.warning(f"{prefix} ⚠️ Error during executor shutdown: {type(e)} {e}")
+            logger.error(f"{prefix} ⚠️ Error during executor shutdown: {type(e)} {e}")
 
         # Release remaining execution locks
         try:

autogpt_platform/backend/backend/executor/scheduler.py

@@ -94,7 +94,7 @@ SCHEDULER_OPERATION_TIMEOUT_SECONDS = 300  # 5 minutes for scheduler operations
 def job_listener(event):
     """Logs job execution outcomes for better monitoring."""
     if event.exception:
-        logger.warning(
+        logger.error(
             f"Job {event.job_id} failed: {type(event.exception).__name__}: {event.exception}"
         )
     else:
@@ -137,7 +137,7 @@ def run_async(coro, timeout: float = SCHEDULER_OPERATION_TIMEOUT_SECONDS):
     try:
         return future.result(timeout=timeout)
     except Exception as e:
-        logger.warning(f"Async operation failed: {type(e).__name__}: {e}")
+        logger.error(f"Async operation failed: {type(e).__name__}: {e}")
         raise
 
 
@@ -186,7 +186,7 @@ async def _execute_graph(**kwargs):
 
 
 async def _handle_graph_validation_error(args: "GraphExecutionJobArgs") -> None:
-    logger.warning(
+    logger.error(
         f"Scheduled Graph {args.graph_id} failed validation. Unscheduling graph"
     )
     if args.schedule_id:
@@ -196,9 +196,8 @@ async def _handle_graph_validation_error(args: "GraphExecutionJobArgs") -> None:
             user_id=args.user_id,
         )
     else:
-        logger.warning(
-            f"Unable to unschedule graph: {args.graph_id} as this is an old job "
-            f"with no associated schedule_id please remove manually"
+        logger.error(
+            f"Unable to unschedule graph: {args.graph_id} as this is an old job with no associated schedule_id please remove manually"
         )
 
 

autogpt_platform/backend/backend/notifications/notifications.py

@@ -303,9 +303,9 @@ class NotificationManager(AppService):
                     )
 
                     if not oldest_message:
-                        logger.warning(
-                            f"Batch for user {batch.user_id} and type {notification_type} "
-                            f"has no oldest message — batch may have been cleared concurrently"
+                        # this should never happen
+                        logger.error(
+                            f"Batch for user {batch.user_id} and type {notification_type} has no oldest message whichshould never happen!!!!!!!!!!!!!!!!"
                         )
                         continue
 
@@ -318,7 +318,7 @@ class NotificationManager(AppService):
                         ).get_user_email_by_id(batch.user_id)
 
                         if not recipient_email:
-                            logger.warning(
+                            logger.error(
                                 f"User email not found for user {batch.user_id}"
                             )
                             continue
@@ -344,7 +344,7 @@ class NotificationManager(AppService):
                         ).get_user_notification_batch(batch.user_id, notification_type)
 
                         if not batch_data or not batch_data.notifications:
-                            logger.warning(
+                            logger.error(
                                 f"Batch data not found for user {batch.user_id}"
                             )
                             # Clear the batch
@@ -372,7 +372,7 @@ class NotificationManager(AppService):
                                     )
                                 )
                             except Exception as e:
-                                logger.warning(
+                                logger.error(
                                     f"Error parsing notification event: {e=}, {db_event=}"
                                 )
                                 continue
@@ -415,10 +415,7 @@ class NotificationManager(AppService):
     async def discord_system_alert(
         self, content: str, channel: DiscordChannel = DiscordChannel.PLATFORM
     ):
-        try:
-            await discord_send_alert(content, channel)
-        except Exception as e:
-            logger.warning(f"Failed to send Discord system alert: {e}")
+        await discord_send_alert(content, channel)
 
     async def _queue_scheduled_notification(self, event: SummaryParamsEventModel):
         """Queue a scheduled notification - exposed method for other services to call"""
@@ -519,7 +516,7 @@ class NotificationManager(AppService):
                 raise ValueError("Invalid event type or params")
 
         except Exception as e:
-            logger.warning(f"Failed to gather summary data: {e}")
+            logger.error(f"Failed to gather summary data: {e}")
             # Return sensible defaults in case of error
             if event_type == NotificationType.DAILY_SUMMARY and isinstance(
                 params, DailySummaryParams
@@ -565,9 +562,8 @@ class NotificationManager(AppService):
             should_retry=False
         ).get_user_notification_oldest_message_in_batch(user_id, event_type)
         if not oldest_message:
-            logger.warning(
-                f"Batch for user {user_id} and type {event_type} "
-                f"has no oldest message — batch may have been cleared concurrently"
+            logger.error(
+                f"Batch for user {user_id} and type {event_type} has no oldest message whichshould never happen!!!!!!!!!!!!!!!!"
             )
             return False
         oldest_age = oldest_message.created_at
@@ -589,7 +585,7 @@ class NotificationManager(AppService):
                 get_notif_data_type(event.type)
             ].model_validate_json(message)
         except Exception as e:
-            logger.warning(f"Error parsing message due to non matching schema {e}")
+            logger.error(f"Error parsing message due to non matching schema {e}")
             return None
 
     async def _process_admin_message(self, message: str) -> bool:
@@ -618,7 +614,7 @@ class NotificationManager(AppService):
                 should_retry=False
             ).get_user_email_by_id(event.user_id)
             if not recipient_email:
-                logger.warning(f"User email not found for user {event.user_id}")
+                logger.error(f"User email not found for user {event.user_id}")
                 return False
 
             should_send = await self._should_email_user_based_on_preference(
@@ -655,7 +651,7 @@ class NotificationManager(AppService):
                 should_retry=False
             ).get_user_email_by_id(event.user_id)
             if not recipient_email:
-                logger.warning(f"User email not found for user {event.user_id}")
+                logger.error(f"User email not found for user {event.user_id}")
                 return False
 
             should_send = await self._should_email_user_based_on_preference(
@@ -676,7 +672,7 @@ class NotificationManager(AppService):
                 should_retry=False
             ).get_user_notification_batch(event.user_id, event.type)
             if not batch or not batch.notifications:
-                logger.warning(f"Batch not found for user {event.user_id}")
+                logger.error(f"Batch not found for user {event.user_id}")
                 return False
             unsub_link = generate_unsubscribe_link(event.user_id)
 
@@ -749,7 +745,7 @@ class NotificationManager(AppService):
                                         f"Removed {len(chunk_ids)} sent notifications from batch"
                                     )
                                 except Exception as e:
-                                    logger.warning(
+                                    logger.error(
                                         f"Failed to remove sent notifications: {e}"
                                     )
                                     # Continue anyway - better to risk duplicates than lose emails
@@ -774,7 +770,7 @@ class NotificationManager(AppService):
                         else:
                             # Message is too large even after size reduction
                             if attempt_size == 1:
-                                logger.warning(
+                                logger.error(
                                     f"Failed to send notification at index {i}: "
                                     f"Single notification exceeds email size limit "
                                     f"({len(test_message):,} chars > {MAX_EMAIL_SIZE:,} chars). "
@@ -793,7 +789,7 @@ class NotificationManager(AppService):
                                             f"Removed oversized notification {chunk_ids[0]} from batch permanently"
                                         )
                                     except Exception as e:
-                                        logger.warning(
+                                        logger.error(
                                             f"Failed to remove oversized notification: {e}"
                                         )
 
@@ -827,7 +823,7 @@ class NotificationManager(AppService):
                                         f"Set email verification to false for user {event.user_id}"
                                     )
                                 except Exception as deactivation_error:
-                                    logger.warning(
+                                    logger.error(
                                         f"Failed to deactivate email for user {event.user_id}: "
                                         f"{deactivation_error}"
                                     )
@@ -839,7 +835,7 @@ class NotificationManager(AppService):
                                         f"Disabled all notification preferences for user {event.user_id}"
                                     )
                                 except Exception as disable_error:
-                                    logger.warning(
+                                    logger.error(
                                         f"Failed to disable notification preferences: {disable_error}"
                                     )
 
@@ -852,7 +848,7 @@ class NotificationManager(AppService):
                                         f"Cleared ALL notification batches for user {event.user_id}"
                                     )
                                 except Exception as remove_error:
-                                    logger.warning(
+                                    logger.error(
                                         f"Failed to clear batches for inactive recipient: {remove_error}"
                                     )
 
@@ -863,7 +859,7 @@ class NotificationManager(AppService):
                                 "422" in error_message
                                 or "unprocessable" in error_message
                             ):
-                                logger.warning(
+                                logger.error(
                                     f"Failed to send notification at index {i}: "
                                     f"Malformed notification data rejected by Postmark. "
                                     f"Error: {e}. Removing from batch permanently."
@@ -881,7 +877,7 @@ class NotificationManager(AppService):
                                             "Removed malformed notification from batch permanently"
                                         )
                                     except Exception as remove_error:
-                                        logger.warning(
+                                        logger.error(
                                             f"Failed to remove malformed notification: {remove_error}"
                                         )
                             # Check if it's a ValueError for size limit
@@ -889,14 +885,14 @@ class NotificationManager(AppService):
                                 isinstance(e, ValueError)
                                 and "too large" in error_message
                             ):
-                                logger.warning(
+                                logger.error(
                                     f"Failed to send notification at index {i}: "
                                     f"Notification size exceeds email limit. "
                                     f"Error: {e}. Skipping this notification."
                                 )
                             # Other API errors
                             else:
-                                logger.warning(
+                                logger.error(
                                     f"Failed to send notification at index {i}: "
                                     f"Email API error ({error_type}): {e}. "
                                     f"Skipping this notification."
@@ -911,9 +907,7 @@ class NotificationManager(AppService):
 
                 if not chunk_sent:
                     # Should not reach here due to single notification handling
-                    logger.warning(
-                        f"Failed to send notifications starting at index {i}"
-                    )
+                    logger.error(f"Failed to send notifications starting at index {i}")
                     failed_indices.append(i)
                     i += 1
 
@@ -952,7 +946,7 @@ class NotificationManager(AppService):
                 should_retry=False
             ).get_user_email_by_id(event.user_id)
             if not recipient_email:
-                logger.warning(f"User email not found for user {event.user_id}")
+                logger.error(f"User email not found for user {event.user_id}")
                 return False
             should_send = await self._should_email_user_based_on_preference(
                 event.user_id, event.type
@@ -1013,10 +1007,7 @@ class NotificationManager(AppService):
                         # Let message.process() handle the rejection
                         pass
                     except Exception as e:
-                        logger.warning(
-                            f"Error processing message in {queue_name}: {e}",
-                            exc_info=True,
-                        )
+                        logger.error(f"Error processing message in {queue_name}: {e}")
                         # Let message.process() handle the rejection
                         raise
         except asyncio.CancelledError:

autogpt_platform/backend/backend/notifications/test_notifications.py

@@ -256,9 +256,9 @@ class TestNotificationErrorHandling:
             assert 2 not in successful_indices  # Index 2 failed
 
             # Verify 422 error was logged
-            warning_calls = [call[0][0] for call in mock_logger.warning.call_args_list]
+            error_calls = [call[0][0] for call in mock_logger.error.call_args_list]
             assert any(
-                "422" in call or "malformed" in call.lower() for call in warning_calls
+                "422" in call or "malformed" in call.lower() for call in error_calls
             )
 
             # Verify all notifications were removed (4 successful + 1 malformed)
@@ -371,10 +371,10 @@ class TestNotificationErrorHandling:
             assert 3 not in successful_indices  # Index 3 was not sent
 
             # Verify oversized error was logged
-            warning_calls = [call[0][0] for call in mock_logger.warning.call_args_list]
+            error_calls = [call[0][0] for call in mock_logger.error.call_args_list]
             assert any(
                 "exceeds email size limit" in call or "oversized" in call.lower()
-                for call in warning_calls
+                for call in error_calls
             )
 
     @pytest.mark.asyncio
@@ -478,10 +478,10 @@ class TestNotificationErrorHandling:
             assert 1 in failed_indices  # Index 1 failed
 
             # Verify generic error was logged
-            warning_calls = [call[0][0] for call in mock_logger.warning.call_args_list]
+            error_calls = [call[0][0] for call in mock_logger.error.call_args_list]
             assert any(
                 "api error" in call.lower() or "skipping" in call.lower()
-                for call in warning_calls
+                for call in error_calls
             )
 
             # Only successful ones should be removed from batch (failed one stays for retry)

autogpt_platform/backend/backend/util/cloud_storage.py

@@ -613,5 +613,5 @@ async def cleanup_expired_files_async() -> int:
             )
             return deleted_count
         except Exception as e:
-            logger.warning(f"[CloudStorage] Error during cloud storage cleanup: {e}")
+            logger.error(f"[CloudStorage] Error during cloud storage cleanup: {e}")
             return 0

autogpt_platform/backend/backend/util/file.py

@@ -275,12 +275,13 @@ async def store_media_file(
     # Process file
     elif file.startswith("data:"):
         # Data URI
-        parsed_uri = parse_data_uri(file)
-        if parsed_uri is None:
+        match = re.match(r"^data:([^;]+);base64,(.*)$", file, re.DOTALL)
+        if not match:
             raise ValueError(
                 "Invalid data URI format. Expected data:<mime>;base64,<data>"
             )
-        mime_type, b64_content = parsed_uri
+        mime_type = match.group(1).strip().lower()
+        b64_content = match.group(2).strip()
 
         # Generate filename and decode
         extension = _extension_from_mime(mime_type)
@@ -414,70 +415,13 @@ def get_dir_size(path: Path) -> int:
     return total
 
 
-async def resolve_media_content(
-    content: MediaFileType,
-    execution_context: "ExecutionContext",
-    *,
-    return_format: MediaReturnFormat,
-) -> MediaFileType:
-    """Resolve a ``MediaFileType`` value if it is a media reference, pass through otherwise.
-
-    Convenience wrapper around :func:`is_media_file_ref` + :func:`store_media_file`.
-    Plain text content (source code, filenames) is returned unchanged.  Media
-    references (``data:``, ``workspace://``, ``http(s)://``) are resolved via
-    :func:`store_media_file` using *return_format*.
-
-    Use this when a block field is typed as ``MediaFileType`` but may contain
-    either literal text or a media reference.
-    """
-    if not content or not is_media_file_ref(content):
-        return content
-    return await store_media_file(
-        content, execution_context, return_format=return_format
-    )
-
-
-def is_media_file_ref(value: str) -> bool:
-    """Return True if *value* looks like a ``MediaFileType`` reference.
-
-    Detects data URIs, workspace:// references, and HTTP(S) URLs — the
-    formats accepted by :func:`store_media_file`.  Plain text content
-    (e.g. source code, filenames) returns False.
-
-    Known limitation: HTTP(S) URL detection is heuristic.  Any string that
-    starts with ``http://`` or ``https://`` is treated as a media URL, even
-    if it appears as a URL inside source-code comments or documentation.
-    Blocks that produce source code or Markdown as output may therefore
-    trigger false positives.  Callers that need higher precision should
-    inspect the string further (e.g. verify the URL is reachable or has a
-    media-friendly extension).
-
-    Note: this does *not* match local file paths, which are ambiguous
-    (could be filenames or actual paths).  Blocks that need to resolve
-    local paths should check for them separately.
-    """
-    return value.startswith(("data:", "workspace://", "http://", "https://"))
-
-
-def parse_data_uri(value: str) -> tuple[str, str] | None:
-    """Parse a ``data:<mime>;base64,<payload>`` URI.
-
-    Returns ``(mime_type, base64_payload)`` if *value* is a valid data URI,
-    or ``None`` if it is not.
-    """
-    match = re.match(r"^data:([^;]+);base64,(.*)$", value, re.DOTALL)
-    if not match:
-        return None
-    return match.group(1).strip().lower(), match.group(2).strip()
-
-
 def get_mime_type(file: str) -> str:
     """
     Get the MIME type of a file, whether it's a data URI, URL, or local path.
     """
     if file.startswith("data:"):
-        parsed_uri = parse_data_uri(file)
-        return parsed_uri[0] if parsed_uri else "application/octet-stream"
+        match = re.match(r"^data:([^;]+);base64,", file)
+        return match.group(1) if match else "application/octet-stream"
 
     elif file.startswith(("http://", "https://")):
         parsed_url = urlparse(file)

autogpt_platform/backend/backend/util/file_content_parser.py

@@ -1,375 +0,0 @@
-"""Parse file content into structured Python objects based on file format.
-
-Used by the ``@@agptfile:`` expansion system to eagerly parse well-known file
-formats into native Python types *before* schema-driven coercion runs.  This
-lets blocks with ``Any``-typed inputs receive structured data rather than raw
-strings, while blocks expecting strings get the value coerced back via
-``convert()``.
-
-Supported formats:
-
-- **JSON** (``.json``) — arrays and objects are promoted; scalars stay as strings
-- **JSON Lines** (``.jsonl``, ``.ndjson``) — each non-empty line parsed as JSON;
-  when all lines are dicts with the same keys (tabular data), output is
-  ``list[list[Any]]`` with a header row, consistent with CSV/Parquet/Excel;
-  otherwise returns a plain ``list`` of parsed values
-- **CSV** (``.csv``) — ``csv.reader`` → ``list[list[str]]``
-- **TSV** (``.tsv``) — tab-delimited → ``list[list[str]]``
-- **YAML** (``.yaml``, ``.yml``) — parsed via PyYAML; containers only
-- **TOML** (``.toml``) — parsed via stdlib ``tomllib``
-- **Parquet** (``.parquet``) — via pandas/pyarrow → ``list[list[Any]]`` with header row
-- **Excel** (``.xlsx``) — via pandas/openpyxl → ``list[list[Any]]`` with header row
-  (legacy ``.xls`` is **not** supported — only the modern OOXML format)
-
-The **fallback contract** is enforced by :func:`parse_file_content`, not by
-individual parser functions.  If any parser raises, ``parse_file_content``
-catches the exception and returns the original content unchanged (string for
-text formats, bytes for binary formats).  Callers should never see an
-exception from the public API when ``strict=False``.
-"""
-
-import csv
-import io
-import json
-import logging
-import tomllib
-import zipfile
-from collections.abc import Callable
-
-# posixpath.splitext handles forward-slash URI paths correctly on all platforms,
-# unlike os.path.splitext which uses platform-native separators.
-from posixpath import splitext
-from typing import Any
-
-import yaml
-
-logger = logging.getLogger(__name__)
-
-# ---------------------------------------------------------------------------
-# Extension / MIME → format label mapping
-# ---------------------------------------------------------------------------
-
-_EXT_TO_FORMAT: dict[str, str] = {
-    ".json": "json",
-    ".jsonl": "jsonl",
-    ".ndjson": "jsonl",
-    ".csv": "csv",
-    ".tsv": "tsv",
-    ".yaml": "yaml",
-    ".yml": "yaml",
-    ".toml": "toml",
-    ".parquet": "parquet",
-    ".xlsx": "xlsx",
-}
-
-MIME_TO_FORMAT: dict[str, str] = {
-    "application/json": "json",
-    "application/x-ndjson": "jsonl",
-    "application/jsonl": "jsonl",
-    "text/csv": "csv",
-    "text/tab-separated-values": "tsv",
-    "application/x-yaml": "yaml",
-    "application/yaml": "yaml",
-    "text/yaml": "yaml",
-    "application/toml": "toml",
-    "application/vnd.apache.parquet": "parquet",
-    "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet": "xlsx",
-}
-
-# Formats that require raw bytes rather than decoded text.
-BINARY_FORMATS: frozenset[str] = frozenset({"parquet", "xlsx"})
-
-
-# ---------------------------------------------------------------------------
-# Public API  (top-down: main functions first, helpers below)
-# ---------------------------------------------------------------------------
-
-
-def infer_format_from_uri(uri: str) -> str | None:
-    """Return a format label based on URI extension or MIME fragment.
-
-    Returns ``None`` when the format cannot be determined — the caller should
-    fall back to returning the content as a plain string.
-    """
-    # 1. Check MIME fragment  (workspace://abc123#application/json)
-    if "#" in uri:
-        _, fragment = uri.rsplit("#", 1)
-        fmt = MIME_TO_FORMAT.get(fragment.lower())
-        if fmt:
-            return fmt
-
-    # 2. Check file extension from the path portion.
-    #    Strip the fragment first so ".json#mime" doesn't confuse splitext.
-    path = uri.split("#")[0].split("?")[0]
-    _, ext = splitext(path)
-    fmt = _EXT_TO_FORMAT.get(ext.lower())
-    if fmt is not None:
-        return fmt
-
-    # Legacy .xls is not supported — map it so callers can produce a
-    # user-friendly error instead of returning garbled binary.
-    if ext.lower() == ".xls":
-        return "xls"
-
-    return None
-
-
-def parse_file_content(content: str | bytes, fmt: str, *, strict: bool = False) -> Any:
-    """Parse *content* according to *fmt* and return a native Python value.
-
-    When *strict* is ``False`` (default), returns the original *content*
-    unchanged if *fmt* is not recognised or parsing fails for any reason.
-    This mode **never raises**.
-
-    When *strict* is ``True``, parsing errors are propagated to the caller.
-    Unrecognised formats or type mismatches (e.g. text for a binary format)
-    still return *content* unchanged without raising.
-    """
-    if fmt == "xls":
-        return (
-            "[Unsupported format] Legacy .xls files are not supported. "
-            "Please re-save the file as .xlsx (Excel 2007+) and upload again."
-        )
-
-    try:
-        if fmt in BINARY_FORMATS:
-            parser = _BINARY_PARSERS.get(fmt)
-            if parser is None:
-                return content
-            if isinstance(content, str):
-                # Caller gave us text for a binary format — can't parse.
-                return content
-            return parser(content)
-
-        parser = _TEXT_PARSERS.get(fmt)
-        if parser is None:
-            return content
-        if isinstance(content, bytes):
-            content = content.decode("utf-8", errors="replace")
-        return parser(content)
-
-    except PARSE_EXCEPTIONS:
-        if strict:
-            raise
-        logger.debug("Structured parsing failed for format=%s, falling back", fmt)
-        return content
-
-
-# ---------------------------------------------------------------------------
-# Exception loading helpers
-# ---------------------------------------------------------------------------
-
-
-def _load_openpyxl_exception() -> type[Exception]:
-    """Return openpyxl's InvalidFileException, raising ImportError if absent."""
-    from openpyxl.utils.exceptions import InvalidFileException  # noqa: PLC0415
-
-    return InvalidFileException
-
-
-def _load_arrow_exception() -> type[Exception]:
-    """Return pyarrow's ArrowException, raising ImportError if absent."""
-    from pyarrow import ArrowException  # noqa: PLC0415
-
-    return ArrowException
-
-
-def _optional_exc(loader: "Callable[[], type[Exception]]") -> "type[Exception] | None":
-    """Return the exception class from *loader*, or ``None`` if the dep is absent."""
-    try:
-        return loader()
-    except ImportError:
-        return None
-
-
-# Exception types that can be raised during file content parsing.
-# Shared between ``parse_file_content`` (which catches them in non-strict mode)
-# and ``file_ref._expand_bare_ref`` (which re-raises them as FileRefExpansionError).
-#
-# Optional-dependency exception types are loaded via a helper that raises
-# ``ImportError`` at *parse time* rather than silently becoming ``None`` here.
-# This ensures mypy sees clean types and missing deps surface as real errors.
-PARSE_EXCEPTIONS: tuple[type[BaseException], ...] = tuple(
-    exc
-    for exc in (
-        json.JSONDecodeError,
-        csv.Error,
-        yaml.YAMLError,
-        tomllib.TOMLDecodeError,
-        ValueError,
-        UnicodeDecodeError,
-        ImportError,
-        OSError,
-        KeyError,
-        TypeError,
-        zipfile.BadZipFile,
-        _optional_exc(_load_openpyxl_exception),
-        # ArrowException covers ArrowIOError and ArrowCapacityError which
-        # do not inherit from standard exceptions; ArrowInvalid/ArrowTypeError
-        # already map to ValueError/TypeError but this catches the rest.
-        _optional_exc(_load_arrow_exception),
-    )
-    if exc is not None
-)
-
-
-# ---------------------------------------------------------------------------
-# Text-based parsers  (content: str → Any)
-# ---------------------------------------------------------------------------
-
-
-def _parse_container(parser: Callable[[str], Any], content: str) -> list | dict | str:
-    """Parse *content* and return the result only if it is a container (list/dict).
-
-    Scalar values (strings, numbers, booleans, None) are discarded and the
-    original *content* string is returned instead.  This prevents e.g. a JSON
-    file containing just ``"42"`` from silently becoming an int.
-    """
-    parsed = parser(content)
-    if isinstance(parsed, (list, dict)):
-        return parsed
-    return content
-
-
-def _parse_json(content: str) -> list | dict | str:
-    return _parse_container(json.loads, content)
-
-
-def _parse_jsonl(content: str) -> Any:
-    lines = [json.loads(line) for line in content.splitlines() if line.strip()]
-    if not lines:
-        return content
-
-    # When every line is a dict with the same keys, convert to table format
-    # (header row + data rows) — consistent with CSV/TSV/Parquet/Excel output.
-    # Require ≥2 dicts so a single-line JSONL stays as [dict] (not a table).
-    if len(lines) >= 2 and all(isinstance(obj, dict) for obj in lines):
-        keys = list(lines[0].keys())
-        # Cache as tuple to avoid O(n×k) list allocations in the all() call.
-        keys_tuple = tuple(keys)
-        if keys and all(tuple(obj.keys()) == keys_tuple for obj in lines[1:]):
-            return [keys] + [[obj[k] for k in keys] for obj in lines]
-
-    return lines
-
-
-def _parse_csv(content: str) -> Any:
-    return _parse_delimited(content, delimiter=",")
-
-
-def _parse_tsv(content: str) -> Any:
-    return _parse_delimited(content, delimiter="\t")
-
-
-def _parse_delimited(content: str, *, delimiter: str) -> Any:
-    reader = csv.reader(io.StringIO(content), delimiter=delimiter)
-    # csv.reader never yields [] — blank lines yield [""]. Filter out
-    # rows where every cell is empty (i.e. truly blank lines).
-    rows = [row for row in reader if _row_has_content(row)]
-    if not rows:
-        return content
-    # If the declared delimiter produces only single-column rows, try
-    # sniffing the actual delimiter — catches misidentified files (e.g.
-    # a tab-delimited file with a .csv extension).
-    if len(rows[0]) == 1:
-        try:
-            dialect = csv.Sniffer().sniff(content[:8192])
-            if dialect.delimiter != delimiter:
-                reader = csv.reader(io.StringIO(content), dialect)
-                rows = [row for row in reader if _row_has_content(row)]
-        except csv.Error:
-            pass
-    if rows and len(rows[0]) >= 2:
-        return rows
-    return content
-
-
-def _row_has_content(row: list[str]) -> bool:
-    """Return True when *row* contains at least one non-empty cell.
-
-    ``csv.reader`` never yields ``[]`` — truly blank lines yield ``[""]``.
-    This predicate filters those out consistently across the initial read
-    and the sniffer-fallback re-read.
-    """
-    return any(cell for cell in row)
-
-
-def _parse_yaml(content: str) -> list | dict | str:
-    # NOTE: YAML anchor/alias expansion can amplify input beyond the 10MB cap.
-    # safe_load prevents code execution; for production hardening consider
-    # a YAML parser with expansion limits (e.g. ruamel.yaml with max_alias_count).
-    if "\n---" in content or content.startswith("---\n"):
-        # Multi-document YAML: only the first document is parsed; the rest
-        # are silently ignored by yaml.safe_load.  Warn so callers are aware.
-        logger.warning(
-            "Multi-document YAML detected (--- separator); "
-            "only the first document will be parsed."
-        )
-    return _parse_container(yaml.safe_load, content)
-
-
-def _parse_toml(content: str) -> Any:
-    parsed = tomllib.loads(content)
-    # tomllib.loads always returns a dict — return it even if empty.
-    return parsed
-
-
-_TEXT_PARSERS: dict[str, Callable[[str], Any]] = {
-    "json": _parse_json,
-    "jsonl": _parse_jsonl,
-    "csv": _parse_csv,
-    "tsv": _parse_tsv,
-    "yaml": _parse_yaml,
-    "toml": _parse_toml,
-}
-
-# ---------------------------------------------------------------------------
-# Binary-based parsers  (content: bytes → Any)
-# ---------------------------------------------------------------------------
-
-
-def _parse_parquet(content: bytes) -> list[list[Any]]:
-    import pandas as pd
-
-    df = pd.read_parquet(io.BytesIO(content))
-    return _df_to_rows(df)
-
-
-def _parse_xlsx(content: bytes) -> list[list[Any]]:
-    import pandas as pd
-
-    # Explicitly specify openpyxl engine; the default engine varies by pandas
-    # version and does not support legacy .xls (which is excluded by our format map).
-    df = pd.read_excel(io.BytesIO(content), engine="openpyxl")
-    return _df_to_rows(df)
-
-
-def _df_to_rows(df: Any) -> list[list[Any]]:
-    """Convert a DataFrame to ``list[list[Any]]`` with a header row.
-
-    NaN values are replaced with ``None`` so the result is JSON-serializable.
-    Uses explicit cell-level checking because ``df.where(df.notna(), None)``
-    silently converts ``None`` back to ``NaN`` in float64 columns.
-    """
-    header = df.columns.tolist()
-    rows = [
-        [None if _is_nan(cell) else cell for cell in row] for row in df.values.tolist()
-    ]
-    return [header] + rows
-
-
-def _is_nan(cell: Any) -> bool:
-    """Check if a cell value is NaN, handling non-scalar types (lists, dicts).
-
-    ``pd.isna()`` on a list/dict returns a boolean array which raises
-    ``ValueError`` in a boolean context.  Guard with a scalar check first.
-    """
-    import pandas as pd
-
-    return bool(pd.api.types.is_scalar(cell) and pd.isna(cell))
-
-
-_BINARY_PARSERS: dict[str, Callable[[bytes], Any]] = {
-    "parquet": _parse_parquet,
-    "xlsx": _parse_xlsx,
-}

autogpt_platform/backend/backend/util/file_content_parser_test.py

@@ -1,624 +0,0 @@
-"""Tests for file_content_parser — format inference and structured parsing."""
-
-import io
-import json
-
-import pytest
-
-from backend.util.file_content_parser import (
-    BINARY_FORMATS,
-    infer_format_from_uri,
-    parse_file_content,
-)
-
-# ---------------------------------------------------------------------------
-# infer_format_from_uri
-# ---------------------------------------------------------------------------
-
-
-class TestInferFormat:
-    # --- extension-based ---
-
-    def test_json_extension(self):
-        assert infer_format_from_uri("/home/user/data.json") == "json"
-
-    def test_jsonl_extension(self):
-        assert infer_format_from_uri("/tmp/events.jsonl") == "jsonl"
-
-    def test_ndjson_extension(self):
-        assert infer_format_from_uri("/tmp/events.ndjson") == "jsonl"
-
-    def test_csv_extension(self):
-        assert infer_format_from_uri("workspace:///reports/sales.csv") == "csv"
-
-    def test_tsv_extension(self):
-        assert infer_format_from_uri("/home/user/data.tsv") == "tsv"
-
-    def test_yaml_extension(self):
-        assert infer_format_from_uri("/home/user/config.yaml") == "yaml"
-
-    def test_yml_extension(self):
-        assert infer_format_from_uri("/home/user/config.yml") == "yaml"
-
-    def test_toml_extension(self):
-        assert infer_format_from_uri("/home/user/config.toml") == "toml"
-
-    def test_parquet_extension(self):
-        assert infer_format_from_uri("/data/table.parquet") == "parquet"
-
-    def test_xlsx_extension(self):
-        assert infer_format_from_uri("/data/spreadsheet.xlsx") == "xlsx"
-
-    def test_xls_extension_returns_xls_label(self):
-        # Legacy .xls is mapped so callers can produce a helpful error.
-        assert infer_format_from_uri("/data/old_spreadsheet.xls") == "xls"
-
-    def test_case_insensitive(self):
-        assert infer_format_from_uri("/data/FILE.JSON") == "json"
-        assert infer_format_from_uri("/data/FILE.CSV") == "csv"
-
-    def test_unicode_filename(self):
-        assert infer_format_from_uri("/home/user/\u30c7\u30fc\u30bf.json") == "json"
-        assert infer_format_from_uri("/home/user/\u00e9t\u00e9.csv") == "csv"
-
-    def test_unknown_extension(self):
-        assert infer_format_from_uri("/home/user/readme.txt") is None
-
-    def test_no_extension(self):
-        assert infer_format_from_uri("workspace://abc123") is None
-
-    # --- MIME-based ---
-
-    def test_mime_json(self):
-        assert infer_format_from_uri("workspace://abc123#application/json") == "json"
-
-    def test_mime_csv(self):
-        assert infer_format_from_uri("workspace://abc123#text/csv") == "csv"
-
-    def test_mime_tsv(self):
-        assert (
-            infer_format_from_uri("workspace://abc123#text/tab-separated-values")
-            == "tsv"
-        )
-
-    def test_mime_ndjson(self):
-        assert (
-            infer_format_from_uri("workspace://abc123#application/x-ndjson") == "jsonl"
-        )
-
-    def test_mime_yaml(self):
-        assert infer_format_from_uri("workspace://abc123#application/x-yaml") == "yaml"
-
-    def test_mime_xlsx(self):
-        uri = "workspace://abc123#application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
-        assert infer_format_from_uri(uri) == "xlsx"
-
-    def test_mime_parquet(self):
-        assert (
-            infer_format_from_uri("workspace://abc123#application/vnd.apache.parquet")
-            == "parquet"
-        )
-
-    def test_unknown_mime(self):
-        assert infer_format_from_uri("workspace://abc123#text/plain") is None
-
-    def test_unknown_mime_falls_through_to_extension(self):
-        # Unknown MIME (text/plain) should fall through to extension-based detection.
-        assert infer_format_from_uri("workspace:///data.csv#text/plain") == "csv"
-
-    # --- MIME takes precedence over extension ---
-
-    def test_mime_overrides_extension(self):
-        # .txt extension but JSON MIME → json
-        assert infer_format_from_uri("workspace:///file.txt#application/json") == "json"
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — JSON
-# ---------------------------------------------------------------------------
-
-
-class TestParseJson:
-    def test_array(self):
-        result = parse_file_content("[1, 2, 3]", "json")
-        assert result == [1, 2, 3]
-
-    def test_object(self):
-        result = parse_file_content('{"key": "value"}', "json")
-        assert result == {"key": "value"}
-
-    def test_nested(self):
-        content = json.dumps({"rows": [[1, 2], [3, 4]]})
-        result = parse_file_content(content, "json")
-        assert result == {"rows": [[1, 2], [3, 4]]}
-
-    def test_scalar_string_stays_as_string(self):
-        result = parse_file_content('"hello"', "json")
-        assert result == '"hello"'  # original content, not parsed
-
-    def test_scalar_number_stays_as_string(self):
-        result = parse_file_content("42", "json")
-        assert result == "42"
-
-    def test_scalar_boolean_stays_as_string(self):
-        result = parse_file_content("true", "json")
-        assert result == "true"
-
-    def test_null_stays_as_string(self):
-        result = parse_file_content("null", "json")
-        assert result == "null"
-
-    def test_invalid_json_fallback(self):
-        content = "not json at all"
-        result = parse_file_content(content, "json")
-        assert result == content
-
-    def test_empty_string_fallback(self):
-        result = parse_file_content("", "json")
-        assert result == ""
-
-    def test_bytes_input_decoded(self):
-        result = parse_file_content(b"[1, 2, 3]", "json")
-        assert result == [1, 2, 3]
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — JSONL
-# ---------------------------------------------------------------------------
-
-
-class TestParseJsonl:
-    def test_tabular_uniform_dicts_to_table_format(self):
-        """JSONL with uniform dict keys → table format (header + rows),
-        consistent with CSV/TSV/Parquet/Excel output."""
-        content = '{"name":"apple","color":"red"}\n{"name":"banana","color":"yellow"}\n{"name":"cherry","color":"red"}'
-        result = parse_file_content(content, "jsonl")
-        assert result == [
-            ["name", "color"],
-            ["apple", "red"],
-            ["banana", "yellow"],
-            ["cherry", "red"],
-        ]
-
-    def test_tabular_single_key_dicts(self):
-        """JSONL with single-key uniform dicts → table format."""
-        content = '{"a": 1}\n{"a": 2}\n{"a": 3}'
-        result = parse_file_content(content, "jsonl")
-        assert result == [["a"], [1], [2], [3]]
-
-    def test_tabular_blank_lines_skipped(self):
-        content = '{"a": 1}\n\n{"a": 2}\n'
-        result = parse_file_content(content, "jsonl")
-        assert result == [["a"], [1], [2]]
-
-    def test_heterogeneous_dicts_stay_as_list(self):
-        """JSONL with different keys across objects → list of dicts (no table)."""
-        content = '{"name":"apple"}\n{"color":"red"}\n{"size":3}'
-        result = parse_file_content(content, "jsonl")
-        assert result == [{"name": "apple"}, {"color": "red"}, {"size": 3}]
-
-    def test_partially_overlapping_keys_stay_as_list(self):
-        """JSONL dicts with partially overlapping keys → list of dicts."""
-        content = '{"name":"apple","color":"red"}\n{"name":"banana","size":"medium"}'
-        result = parse_file_content(content, "jsonl")
-        assert result == [
-            {"name": "apple", "color": "red"},
-            {"name": "banana", "size": "medium"},
-        ]
-
-    def test_mixed_types_stay_as_list(self):
-        """JSONL with non-dict lines → list of parsed values (no table)."""
-        content = '1\n"hello"\n[1,2]\n'
-        result = parse_file_content(content, "jsonl")
-        assert result == [1, "hello", [1, 2]]
-
-    def test_mixed_dicts_and_non_dicts_stay_as_list(self):
-        """JSONL mixing dicts and non-dicts → list of parsed values."""
-        content = '{"a": 1}\n42\n{"b": 2}'
-        result = parse_file_content(content, "jsonl")
-        assert result == [{"a": 1}, 42, {"b": 2}]
-
-    def test_tabular_preserves_key_order(self):
-        """Table header should follow the key order of the first object."""
-        content = '{"z": 1, "a": 2}\n{"z": 3, "a": 4}'
-        result = parse_file_content(content, "jsonl")
-        assert result[0] == ["z", "a"]  # order from first object
-        assert result[1] == [1, 2]
-        assert result[2] == [3, 4]
-
-    def test_single_dict_stays_as_list(self):
-        """Single-line JSONL with one dict → [dict], NOT a table.
-        Tabular detection requires ≥2 dicts to avoid vacuously true all()."""
-        content = '{"a": 1, "b": 2}'
-        result = parse_file_content(content, "jsonl")
-        assert result == [{"a": 1, "b": 2}]
-
-    def test_tabular_with_none_values(self):
-        """Uniform keys but some null values → table with None cells."""
-        content = '{"name":"apple","color":"red"}\n{"name":"banana","color":null}'
-        result = parse_file_content(content, "jsonl")
-        assert result == [
-            ["name", "color"],
-            ["apple", "red"],
-            ["banana", None],
-        ]
-
-    def test_empty_file_fallback(self):
-        result = parse_file_content("", "jsonl")
-        assert result == ""
-
-    def test_all_blank_lines_fallback(self):
-        result = parse_file_content("\n\n\n", "jsonl")
-        assert result == "\n\n\n"
-
-    def test_invalid_line_fallback(self):
-        content = '{"a": 1}\nnot json\n'
-        result = parse_file_content(content, "jsonl")
-        assert result == content  # fallback
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — CSV
-# ---------------------------------------------------------------------------
-
-
-class TestParseCsv:
-    def test_basic(self):
-        content = "Name,Score\nAlice,90\nBob,85"
-        result = parse_file_content(content, "csv")
-        assert result == [["Name", "Score"], ["Alice", "90"], ["Bob", "85"]]
-
-    def test_quoted_fields(self):
-        content = 'Name,Bio\nAlice,"Loves, commas"\nBob,Simple'
-        result = parse_file_content(content, "csv")
-        assert result[1] == ["Alice", "Loves, commas"]
-
-    def test_single_column_fallback(self):
-        # Only 1 column — not tabular enough.
-        content = "Name\nAlice\nBob"
-        result = parse_file_content(content, "csv")
-        assert result == content
-
-    def test_empty_rows_skipped(self):
-        content = "A,B\n\n1,2\n\n3,4"
-        result = parse_file_content(content, "csv")
-        assert result == [["A", "B"], ["1", "2"], ["3", "4"]]
-
-    def test_empty_file_fallback(self):
-        result = parse_file_content("", "csv")
-        assert result == ""
-
-    def test_utf8_bom(self):
-        """CSV with a UTF-8 BOM should parse correctly (BOM stripped by decode)."""
-        bom = "\ufeff"
-        content = bom + "Name,Score\nAlice,90\nBob,85"
-        result = parse_file_content(content, "csv")
-        # The BOM may be part of the first header cell; ensure rows are still parsed.
-        assert len(result) == 3
-        assert result[1] == ["Alice", "90"]
-        assert result[2] == ["Bob", "85"]
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — TSV
-# ---------------------------------------------------------------------------
-
-
-class TestParseTsv:
-    def test_basic(self):
-        content = "Name\tScore\nAlice\t90\nBob\t85"
-        result = parse_file_content(content, "tsv")
-        assert result == [["Name", "Score"], ["Alice", "90"], ["Bob", "85"]]
-
-    def test_single_column_fallback(self):
-        content = "Name\nAlice\nBob"
-        result = parse_file_content(content, "tsv")
-        assert result == content
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — YAML
-# ---------------------------------------------------------------------------
-
-
-class TestParseYaml:
-    def test_list(self):
-        content = "- apple\n- banana\n- cherry"
-        result = parse_file_content(content, "yaml")
-        assert result == ["apple", "banana", "cherry"]
-
-    def test_dict(self):
-        content = "name: Alice\nage: 30"
-        result = parse_file_content(content, "yaml")
-        assert result == {"name": "Alice", "age": 30}
-
-    def test_nested(self):
-        content = "users:\n  - name: Alice\n  - name: Bob"
-        result = parse_file_content(content, "yaml")
-        assert result == {"users": [{"name": "Alice"}, {"name": "Bob"}]}
-
-    def test_scalar_stays_as_string(self):
-        result = parse_file_content("hello world", "yaml")
-        assert result == "hello world"
-
-    def test_invalid_yaml_fallback(self):
-        content = ":\n  :\n    invalid: - -"
-        result = parse_file_content(content, "yaml")
-        # Malformed YAML should fall back to the original string, not raise.
-        assert result == content
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — TOML
-# ---------------------------------------------------------------------------
-
-
-class TestParseToml:
-    def test_basic(self):
-        content = '[server]\nhost = "localhost"\nport = 8080'
-        result = parse_file_content(content, "toml")
-        assert result == {"server": {"host": "localhost", "port": 8080}}
-
-    def test_flat(self):
-        content = 'name = "test"\ncount = 42'
-        result = parse_file_content(content, "toml")
-        assert result == {"name": "test", "count": 42}
-
-    def test_empty_string_returns_empty_dict(self):
-        result = parse_file_content("", "toml")
-        assert result == {}
-
-    def test_invalid_toml_fallback(self):
-        result = parse_file_content("not = [valid toml", "toml")
-        assert result == "not = [valid toml"
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — Parquet (binary)
-# ---------------------------------------------------------------------------
-
-
-try:
-    import pyarrow as _pa  # noqa: F401  # pyright: ignore[reportMissingImports]
-
-    _has_pyarrow = True
-except ImportError:
-    _has_pyarrow = False
-
-
-@pytest.mark.skipif(not _has_pyarrow, reason="pyarrow not installed")
-class TestParseParquet:
-    @pytest.fixture
-    def parquet_bytes(self) -> bytes:
-        import pandas as pd
-
-        df = pd.DataFrame({"Name": ["Alice", "Bob"], "Score": [90, 85]})
-        buf = io.BytesIO()
-        df.to_parquet(buf, index=False)
-        return buf.getvalue()
-
-    def test_basic(self, parquet_bytes: bytes):
-        result = parse_file_content(parquet_bytes, "parquet")
-        assert result == [["Name", "Score"], ["Alice", 90], ["Bob", 85]]
-
-    def test_string_input_fallback(self):
-        # Parquet is binary — string input can't be parsed.
-        result = parse_file_content("not parquet", "parquet")
-        assert result == "not parquet"
-
-    def test_invalid_bytes_fallback(self):
-        result = parse_file_content(b"not parquet bytes", "parquet")
-        assert result == b"not parquet bytes"
-
-    def test_empty_bytes_fallback(self):
-        """Empty binary input should return the empty bytes, not crash."""
-        result = parse_file_content(b"", "parquet")
-        assert result == b""
-
-    def test_nan_replaced_with_none(self):
-        """NaN values in Parquet must become None for JSON serializability."""
-        import math
-
-        import pandas as pd
-
-        df = pd.DataFrame({"A": [1.0, float("nan"), 3.0], "B": ["x", None, "z"]})
-        buf = io.BytesIO()
-        df.to_parquet(buf, index=False)
-        result = parse_file_content(buf.getvalue(), "parquet")
-        # Row with NaN in float col → None
-        assert result[2][0] is None  # float NaN → None
-        assert result[2][1] is None  # str None → None
-        # Ensure no NaN leaks
-        for row in result[1:]:
-            for cell in row:
-                if isinstance(cell, float):
-                    assert not math.isnan(cell), f"NaN leaked: {row}"
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — Excel (binary)
-# ---------------------------------------------------------------------------
-
-
-class TestParseExcel:
-    @pytest.fixture
-    def xlsx_bytes(self) -> bytes:
-        import pandas as pd
-
-        df = pd.DataFrame({"Name": ["Alice", "Bob"], "Score": [90, 85]})
-        buf = io.BytesIO()
-        df.to_excel(buf, index=False)  # type: ignore[arg-type]  # BytesIO is a valid target
-        return buf.getvalue()
-
-    def test_basic(self, xlsx_bytes: bytes):
-        result = parse_file_content(xlsx_bytes, "xlsx")
-        assert result == [["Name", "Score"], ["Alice", 90], ["Bob", 85]]
-
-    def test_string_input_fallback(self):
-        result = parse_file_content("not xlsx", "xlsx")
-        assert result == "not xlsx"
-
-    def test_invalid_bytes_fallback(self):
-        result = parse_file_content(b"not xlsx bytes", "xlsx")
-        assert result == b"not xlsx bytes"
-
-    def test_empty_bytes_fallback(self):
-        """Empty binary input should return the empty bytes, not crash."""
-        result = parse_file_content(b"", "xlsx")
-        assert result == b""
-
-    def test_nan_replaced_with_none(self):
-        """NaN values in float columns must become None for JSON serializability."""
-        import math
-
-        import pandas as pd
-
-        df = pd.DataFrame({"A": [1.0, float("nan"), 3.0], "B": ["x", "y", None]})
-        buf = io.BytesIO()
-        df.to_excel(buf, index=False)  # type: ignore[arg-type]
-        result = parse_file_content(buf.getvalue(), "xlsx")
-        # Row with NaN in float col → None, not float('nan')
-        assert result[2][0] is None  # float NaN → None
-        assert result[3][1] is None  # str None → None
-        # Ensure no NaN leaks
-        for row in result[1:]:  # skip header
-            for cell in row:
-                if isinstance(cell, float):
-                    assert not math.isnan(cell), f"NaN leaked: {row}"
-
-
-# ---------------------------------------------------------------------------
-# parse_file_content — unknown format / fallback
-# ---------------------------------------------------------------------------
-
-
-class TestFallback:
-    def test_unknown_format_returns_content(self):
-        result = parse_file_content("hello world", "xml")
-        assert result == "hello world"
-
-    def test_none_format_returns_content(self):
-        # Shouldn't normally be called with unrecognised format, but must not crash.
-        result = parse_file_content("hello", "unknown_format")
-        assert result == "hello"
-
-
-# ---------------------------------------------------------------------------
-# BINARY_FORMATS
-# ---------------------------------------------------------------------------
-
-
-class TestBinaryFormats:
-    def test_parquet_is_binary(self):
-        assert "parquet" in BINARY_FORMATS
-
-    def test_xlsx_is_binary(self):
-        assert "xlsx" in BINARY_FORMATS
-
-    def test_text_formats_not_binary(self):
-        for fmt in ("json", "jsonl", "csv", "tsv", "yaml", "toml"):
-            assert fmt not in BINARY_FORMATS
-
-
-# ---------------------------------------------------------------------------
-# MIME mapping
-# ---------------------------------------------------------------------------
-
-
-class TestMimeMapping:
-    def test_application_yaml(self):
-        assert infer_format_from_uri("workspace://abc123#application/yaml") == "yaml"
-
-
-# ---------------------------------------------------------------------------
-# CSV sniffer fallback
-# ---------------------------------------------------------------------------
-
-
-class TestCsvSnifferFallback:
-    def test_tab_delimited_with_csv_format(self):
-        """Tab-delimited content parsed as csv should use sniffer fallback."""
-        content = "Name\tScore\nAlice\t90\nBob\t85"
-        result = parse_file_content(content, "csv")
-        assert result == [["Name", "Score"], ["Alice", "90"], ["Bob", "85"]]
-
-    def test_sniffer_failure_returns_content(self):
-        """When sniffer fails, single-column falls back to raw content."""
-        content = "Name\nAlice\nBob"
-        result = parse_file_content(content, "csv")
-        assert result == content
-
-
-# ---------------------------------------------------------------------------
-# OpenpyxlInvalidFile fallback
-# ---------------------------------------------------------------------------
-
-
-class TestOpenpyxlFallback:
-    def test_invalid_xlsx_non_strict(self):
-        """Invalid xlsx bytes should fall back gracefully in non-strict mode."""
-        result = parse_file_content(b"not xlsx bytes", "xlsx")
-        assert result == b"not xlsx bytes"
-
-
-# ---------------------------------------------------------------------------
-# Header-only CSV
-# ---------------------------------------------------------------------------
-
-
-class TestHeaderOnlyCsv:
-    def test_header_only_csv_returns_header_row(self):
-        """CSV with only a header row (no data rows) should return [[header]]."""
-        content = "Name,Score"
-        result = parse_file_content(content, "csv")
-        assert result == [["Name", "Score"]]
-
-    def test_header_only_csv_with_trailing_newline(self):
-        content = "Name,Score\n"
-        result = parse_file_content(content, "csv")
-        assert result == [["Name", "Score"]]
-
-
-# ---------------------------------------------------------------------------
-# Binary format + line range (line range ignored for binary formats)
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.skipif(not _has_pyarrow, reason="pyarrow not installed")
-class TestBinaryFormatLineRange:
-    def test_parquet_ignores_line_range(self):
-        """Binary formats should parse the full file regardless of line range.
-
-        Line ranges are meaningless for binary formats (parquet/xlsx) — the
-        caller (file_ref._expand_bare_ref) passes raw bytes and the parser
-        should return the complete structured data.
-        """
-        import pandas as pd
-
-        df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
-        buf = io.BytesIO()
-        df.to_parquet(buf, index=False)
-        # parse_file_content itself doesn't take a line range — this tests
-        # that the full content is parsed even though the bytes could have
-        # been truncated upstream (it's not, by design).
-        result = parse_file_content(buf.getvalue(), "parquet")
-        assert result == [["A", "B"], [1, 4], [2, 5], [3, 6]]
-
-
-# ---------------------------------------------------------------------------
-# Legacy .xls UX
-# ---------------------------------------------------------------------------
-
-
-class TestXlsFallback:
-    def test_xls_returns_helpful_error_string(self):
-        """Uploading a .xls file should produce a helpful error, not garbled binary."""
-        result = parse_file_content(b"\xd0\xcf\x11\xe0garbled", "xls")
-        assert isinstance(result, str)
-        assert ".xlsx" in result
-        assert "not supported" in result.lower()
-
-    def test_xls_with_string_content(self):
-        result = parse_file_content("some text", "xls")
-        assert isinstance(result, str)
-        assert ".xlsx" in result

autogpt_platform/backend/backend/util/file_test.py

@@ -8,12 +8,7 @@ from unittest.mock import AsyncMock, MagicMock, patch
 import pytest
 
 from backend.data.execution import ExecutionContext
-from backend.util.file import (
-    is_media_file_ref,
-    parse_data_uri,
-    resolve_media_content,
-    store_media_file,
-)
+from backend.util.file import store_media_file
 from backend.util.type import MediaFileType
 
 
@@ -349,162 +344,3 @@ class TestFileCloudIntegration:
                     execution_context=make_test_context(graph_exec_id=graph_exec_id),
                     return_format="for_local_processing",
                 )
-
-
-# ---------------------------------------------------------------------------
-# is_media_file_ref
-# ---------------------------------------------------------------------------
-
-
-class TestIsMediaFileRef:
-    def test_data_uri(self):
-        assert is_media_file_ref("data:image/png;base64,iVBORw0KGg==") is True
-
-    def test_workspace_uri(self):
-        assert is_media_file_ref("workspace://abc123") is True
-
-    def test_workspace_uri_with_mime(self):
-        assert is_media_file_ref("workspace://abc123#image/png") is True
-
-    def test_http_url(self):
-        assert is_media_file_ref("http://example.com/image.png") is True
-
-    def test_https_url(self):
-        assert is_media_file_ref("https://example.com/image.png") is True
-
-    def test_plain_text(self):
-        assert is_media_file_ref("print('hello')") is False
-
-    def test_local_path(self):
-        assert is_media_file_ref("/tmp/file.txt") is False
-
-    def test_empty_string(self):
-        assert is_media_file_ref("") is False
-
-    def test_filename(self):
-        assert is_media_file_ref("image.png") is False
-
-
-# ---------------------------------------------------------------------------
-# parse_data_uri
-# ---------------------------------------------------------------------------
-
-
-class TestParseDataUri:
-    def test_valid_png(self):
-        result = parse_data_uri("data:image/png;base64,iVBORw0KGg==")
-        assert result is not None
-        mime, payload = result
-        assert mime == "image/png"
-        assert payload == "iVBORw0KGg=="
-
-    def test_valid_text(self):
-        result = parse_data_uri("data:text/plain;base64,SGVsbG8=")
-        assert result is not None
-        assert result[0] == "text/plain"
-        assert result[1] == "SGVsbG8="
-
-    def test_mime_case_normalized(self):
-        result = parse_data_uri("data:IMAGE/PNG;base64,abc")
-        assert result is not None
-        assert result[0] == "image/png"
-
-    def test_not_data_uri(self):
-        assert parse_data_uri("workspace://abc123") is None
-
-    def test_plain_text(self):
-        assert parse_data_uri("hello world") is None
-
-    def test_missing_base64(self):
-        assert parse_data_uri("data:image/png;utf-8,abc") is None
-
-    def test_empty_payload(self):
-        result = parse_data_uri("data:image/png;base64,")
-        assert result is not None
-        assert result[1] == ""
-
-
-# ---------------------------------------------------------------------------
-# resolve_media_content
-# ---------------------------------------------------------------------------
-
-
-class TestResolveMediaContent:
-    @pytest.mark.asyncio
-    async def test_plain_text_passthrough(self):
-        """Plain text content (not a media ref) passes through unchanged."""
-        ctx = make_test_context()
-        result = await resolve_media_content(
-            MediaFileType("print('hello')"),
-            ctx,
-            return_format="for_external_api",
-        )
-        assert result == "print('hello')"
-
-    @pytest.mark.asyncio
-    async def test_empty_string_passthrough(self):
-        """Empty string passes through unchanged."""
-        ctx = make_test_context()
-        result = await resolve_media_content(
-            MediaFileType(""),
-            ctx,
-            return_format="for_external_api",
-        )
-        assert result == ""
-
-    @pytest.mark.asyncio
-    async def test_media_ref_delegates_to_store(self):
-        """Media references are resolved via store_media_file."""
-        ctx = make_test_context()
-        with patch(
-            "backend.util.file.store_media_file",
-            new=AsyncMock(return_value=MediaFileType("data:image/png;base64,abc")),
-        ) as mock_store:
-            result = await resolve_media_content(
-                MediaFileType("workspace://img123"),
-                ctx,
-                return_format="for_external_api",
-            )
-        assert result == "data:image/png;base64,abc"
-        mock_store.assert_called_once_with(
-            MediaFileType("workspace://img123"),
-            ctx,
-            return_format="for_external_api",
-        )
-
-    @pytest.mark.asyncio
-    async def test_data_uri_delegates_to_store(self):
-        """Data URIs are also resolved via store_media_file."""
-        ctx = make_test_context()
-        data_uri = "data:image/png;base64,iVBORw0KGg=="
-        with patch(
-            "backend.util.file.store_media_file",
-            new=AsyncMock(return_value=MediaFileType(data_uri)),
-        ) as mock_store:
-            result = await resolve_media_content(
-                MediaFileType(data_uri),
-                ctx,
-                return_format="for_external_api",
-            )
-        assert result == data_uri
-        mock_store.assert_called_once()
-
-    @pytest.mark.asyncio
-    async def test_https_url_delegates_to_store(self):
-        """HTTPS URLs are resolved via store_media_file."""
-        ctx = make_test_context()
-        with patch(
-            "backend.util.file.store_media_file",
-            new=AsyncMock(return_value=MediaFileType("data:image/png;base64,abc")),
-        ) as mock_store:
-            result = await resolve_media_content(
-                MediaFileType("https://example.com/image.png"),
-                ctx,
-                return_format="for_local_processing",
-            )
-        assert result == "data:image/png;base64,abc"
-        mock_store.assert_called_once_with(
-            MediaFileType("https://example.com/image.png"),
-            ctx,
-            return_format="for_local_processing",
-        )

autogpt_platform/backend/backend/util/metrics.py

@@ -10,7 +10,7 @@ from sentry_sdk.integrations.launchdarkly import LaunchDarklyIntegration
 from sentry_sdk.integrations.logging import LoggingIntegration
 
 from backend.util import feature_flag
-from backend.util.settings import BehaveAs, Settings
+from backend.util.settings import Settings
 
 settings = Settings()
 logger = logging.getLogger(__name__)
@@ -21,95 +21,6 @@ class DiscordChannel(str, Enum):
     PRODUCT = "product"  # For product alerts (low balance, zero balance, etc.)
 
 
-def _before_send(event, hint):
-    """Filter out expected/transient errors from Sentry to reduce noise."""
-    if "exc_info" in hint:
-        exc_type, exc_value, _ = hint["exc_info"]
-        exc_msg = str(exc_value).lower() if exc_value else ""
-
-        # AMQP/RabbitMQ transient connection errors — expected during deploys
-        amqp_keywords = [
-            "amqpconnection",
-            "amqpconnector",
-            "connection_forced",
-            "channelinvalidstateerror",
-            "no active transport",
-        ]
-        if any(kw in exc_msg for kw in amqp_keywords):
-            return None
-
-        # "connection refused" only for AMQP-related exceptions (not other services)
-        if "connection refused" in exc_msg:
-            exc_module = getattr(exc_type, "__module__", "") or ""
-            exc_name = getattr(exc_type, "__name__", "") or ""
-            amqp_indicators = ["aio_pika", "aiormq", "amqp", "pika", "rabbitmq"]
-            if any(
-                ind in exc_module.lower() or ind in exc_name.lower()
-                for ind in amqp_indicators
-            ) or any(kw in exc_msg for kw in ["amqp", "pika", "rabbitmq"]):
-                return None
-
-        # User-caused credential/auth errors — not platform bugs
-        user_auth_keywords = [
-            "incorrect api key",
-            "invalid x-api-key",
-            "missing authentication header",
-            "invalid api token",
-            "authentication_error",
-        ]
-        if any(kw in exc_msg for kw in user_auth_keywords):
-            return None
-
-        # Expected business logic — insufficient balance
-        if "insufficient balance" in exc_msg or "no credits left" in exc_msg:
-            return None
-
-        # Expected security check — blocked IP access
-        if "access to blocked or private ip" in exc_msg:
-            return None
-
-        # Discord bot token misconfiguration — not a platform error
-        if "improper token has been passed" in exc_msg or (
-            exc_type and exc_type.__name__ == "Forbidden" and "50001" in exc_msg
-        ):
-            return None
-
-        # Google metadata DNS errors — expected in non-GCP environments
-        if (
-            "metadata.google.internal" in exc_msg
-            and settings.config.behave_as != BehaveAs.CLOUD
-        ):
-            return None
-
-        # Inactive email recipients — expected for bounced addresses
-        if "marked as inactive" in exc_msg or "inactive addresses" in exc_msg:
-            return None
-
-    # Also filter log-based events for known noisy messages.
-    # Sentry's LoggingIntegration stores log messages under "logentry", not "message".
-    logentry = event.get("logentry") or {}
-    log_msg = (
-        logentry.get("formatted") or logentry.get("message") or event.get("message")
-    )
-    if event.get("logger") and log_msg:
-        msg = log_msg.lower()
-        noisy_patterns = [
-            "amqpconnection",
-            "connection_forced",
-            "unclosed client session",
-            "unclosed connector",
-        ]
-        if any(p in msg for p in noisy_patterns):
-            return None
-        # "connection refused" in logs only when AMQP-related context is present
-        if "connection refused" in msg and any(
-            ind in msg for ind in ("amqp", "pika", "rabbitmq", "aio_pika", "aiormq")
-        ):
-            return None
-
-    return event
-
-
 def sentry_init():
     sentry_dsn = settings.secrets.sentry_dsn
     integrations = []
@@ -124,7 +35,6 @@ def sentry_init():
         profiles_sample_rate=1.0,
         environment=f"app:{settings.config.app_env.value}-behave:{settings.config.behave_as.value}",
         _experiments={"enable_logs": True},
-        before_send=_before_send,
         integrations=[
             AsyncioIntegration(),
             LoggingIntegration(sentry_logs_level=logging.INFO),

autogpt_platform/backend/backend/util/prompt.py

@@ -70,6 +70,9 @@ def _msg_tokens(msg: dict, enc) -> int:
                 # Count tool result tokens
                 tool_call_tokens += _tok_len(item.get("tool_use_id", ""), enc)
                 tool_call_tokens += _tok_len(item.get("content", ""), enc)
+            elif isinstance(item, dict) and item.get("type") == "text":
+                # Count text block tokens
+                tool_call_tokens += _tok_len(item.get("text", ""), enc)
             elif isinstance(item, dict) and "content" in item:
                 # Other content types with content field
                 tool_call_tokens += _tok_len(item.get("content", ""), enc)
@@ -145,10 +148,14 @@ def _truncate_middle_tokens(text: str, enc, max_tok: int) -> str:
     if len(ids) <= max_tok:
         return text  # nothing to do
 
+    # Need at least 3 tokens (head + ellipsis + tail) for meaningful truncation
+    mid = enc.encode(" … ")
+    if max_tok < 3:
+        return enc.decode(mid)
+
     # Split the allowance between the two ends:
     head = max_tok // 2 - 1  # -1 for the ellipsis
     tail = max_tok - head - 1
-    mid = enc.encode(" … ")
     return enc.decode(ids[:head] + mid + ids[-tail:])
 
 
@@ -396,7 +403,7 @@ def validate_and_remove_orphan_tool_responses(
 
     if log_warning:
         logger.warning(
-            f"Removing {len(orphan_ids)} orphan tool response(s): {orphan_ids}"
+            "Removing %d orphan tool response(s): %s", len(orphan_ids), orphan_ids
         )
 
     return _remove_orphan_tool_responses(messages, orphan_ids)
@@ -488,8 +495,9 @@ def _ensure_tool_pairs_intact(
         # Some tool_call_ids couldn't be resolved - remove those tool responses
         # This shouldn't happen in normal operation but handles edge cases
         logger.warning(
-            f"Could not find assistant messages for tool_call_ids: {orphan_tool_call_ids}. "
-            "Removing orphan tool responses."
+            "Could not find assistant messages for tool_call_ids: %s. "
+            "Removing orphan tool responses.",
+            orphan_tool_call_ids,
         )
         recent_messages = _remove_orphan_tool_responses(
             recent_messages, orphan_tool_call_ids
@@ -497,8 +505,8 @@ def _ensure_tool_pairs_intact(
 
     if messages_to_prepend:
         logger.info(
-            f"Extended recent messages by {len(messages_to_prepend)} to preserve "
-            f"tool_call/tool_response pairs"
+            "Extended recent messages by %d to preserve tool_call/tool_response pairs",
+            len(messages_to_prepend),
         )
         return messages_to_prepend + recent_messages
 
@@ -686,11 +694,15 @@ async def compress_context(
                     msgs = [summary_msg] + recent_msgs
 
                 logger.info(
-                    f"Context summarized: {original_count} -> {total_tokens()} tokens, "
-                    f"summarized {messages_summarized} messages"
+                    "Context summarized: %d -> %d tokens, summarized %d messages",
+                    original_count,
+                    total_tokens(),
+                    messages_summarized,
                 )
             except Exception as e:
-                logger.warning(f"Summarization failed, continuing with truncation: {e}")
+                logger.warning(
+                    "Summarization failed, continuing with truncation: %s", e
+                )
                 # Fall through to content truncation
 
     # ---- STEP 2: Normalize content ----------------------------------------
@@ -728,6 +740,12 @@ async def compress_context(
     # This is more granular than dropping all old messages at once.
     while total_tokens() + reserve > target_tokens and len(msgs) > 2:
         deletable: list[int] = []
+        # Count assistant messages to ensure we keep at least one
+        assistant_indices: set[int] = {
+            i
+            for i in range(len(msgs))
+            if msgs[i] is not None and msgs[i].get("role") == "assistant"
+        }
         for i in range(1, len(msgs) - 1):
             msg = msgs[i]
             if (
@@ -735,6 +753,9 @@ async def compress_context(
                 and not _is_tool_message(msg)
                 and not _is_objective_message(msg)
             ):
+                # Skip if this is the last remaining assistant message
+                if msg.get("role") == "assistant" and len(assistant_indices) <= 1:
+                    continue
                 deletable.append(i)
         if not deletable:
             break

autogpt_platform/backend/backend/util/retry.py

@@ -64,7 +64,7 @@ def send_rate_limited_discord_alert(
         return True
 
     except Exception as alert_error:
-        logger.warning(f"Failed to send Discord alert: {alert_error}")
+        logger.error(f"Failed to send Discord alert: {alert_error}")
         return False
 
 
@@ -182,8 +182,7 @@ def conn_retry(
         func_name = getattr(retry_state.fn, "__name__", "unknown")
 
         if retry_state.outcome.failed and retry_state.next_action is None:
-            # Final failure is logged by sync_wrapper/async_wrapper — skip here to avoid duplicates
-            pass
+            logger.error(f"{prefix} {action_name} failed after retries: {exception}")
         else:
             if attempt_number == EXCESSIVE_RETRY_THRESHOLD:
                 if send_rate_limited_discord_alert(
@@ -226,7 +225,7 @@ def conn_retry(
                 logger.info(f"{prefix} {action_name} completed successfully.")
                 return result
             except Exception as e:
-                logger.warning(f"{prefix} {action_name} failed after retries: {e}")
+                logger.error(f"{prefix} {action_name} failed after retries: {e}")
                 raise
 
         @wraps(func)
@@ -238,7 +237,7 @@ def conn_retry(
                 logger.info(f"{prefix} {action_name} completed successfully.")
                 return result
             except Exception as e:
-                logger.warning(f"{prefix} {action_name} failed after retries: {e}")
+                logger.error(f"{prefix} {action_name} failed after retries: {e}")
                 raise
 
         return async_wrapper if is_coroutine else sync_wrapper

autogpt_platform/backend/poetry.lock

@@ -1360,18 +1360,6 @@ files = [
 dnspython = ">=2.0.0"
 idna = ">=2.0.0"
 
-[[package]]
-name = "et-xmlfile"
-version = "2.0.0"
-description = "An implementation of lxml.xmlfile for the standard library"
-optional = false
-python-versions = ">=3.8"
-groups = ["main"]
-files = [
-    {file = "et_xmlfile-2.0.0-py3-none-any.whl", hash = "sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa"},
-    {file = "et_xmlfile-2.0.0.tar.gz", hash = "sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54"},
-]
-
 [[package]]
 name = "exa-py"
 version = "1.16.1"
@@ -4240,21 +4228,6 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 realtime = ["websockets (>=13,<16)"]
 voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"]
 
-[[package]]
-name = "openpyxl"
-version = "3.1.5"
-description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
-optional = false
-python-versions = ">=3.8"
-groups = ["main"]
-files = [
-    {file = "openpyxl-3.1.5-py2.py3-none-any.whl", hash = "sha256:5282c12b107bffeef825f4617dc029afaf41d0ea60823bbb665ef3079dc79de2"},
-    {file = "openpyxl-3.1.5.tar.gz", hash = "sha256:cf0e3cf56142039133628b5acffe8ef0c12bc902d2aadd3e0fe5878dc08d1050"},
-]
-
-[package.dependencies]
-et-xmlfile = "*"
-
 [[package]]
 name = "opentelemetry-api"
 version = "1.39.1"
@@ -5457,66 +5430,6 @@ files = [
     {file = "psycopg2_binary-2.9.11-cp39-cp39-win_amd64.whl", hash = "sha256:875039274f8a2361e5207857899706da840768e2a775bf8c65e82f60b197df02"},
 ]
 
-[[package]]
-name = "pyarrow"
-version = "23.0.1"
-description = "Python library for Apache Arrow"
-optional = false
-python-versions = ">=3.10"
-groups = ["main"]
-files = [
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-    {file = "pyarrow-23.0.1.tar.gz", hash = "sha256:b8c5873e33440b2bc2f4a79d2b47017a89c5a24116c055625e6f2ee50523f019"},
-]
-
 [[package]]
 name = "pyasn1"
 version = "0.6.2"
@@ -8969,4 +8882,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "86dab25684dd46e635a33bd33281a926e5626a874ecc048c34389fecf34a87d8"
+content-hash = "4e4365721cd3b68c58c237353b74adae1c64233fd4446904c335f23eb866fdca"

autogpt_platform/backend/pyproject.toml

@@ -92,8 +92,6 @@ gravitas-md2gdocs = "^0.1.0"
 posthog = "^7.6.0"
 fpdf2 = "^2.8.6"
 langsmith = "^0.7.7"
-openpyxl = "^3.1.5"
-pyarrow = "^23.0.0"
 
 [tool.poetry.group.dev.dependencies]
 aiohappyeyeballs = "^2.6.1"

autogpt_platform/frontend/CLAUDE.md

@@ -44,12 +44,6 @@ Do NOT skip these steps. If any command reports errors, fix them and re-run unti
 
 - Fully capitalize acronyms in symbols, e.g. `graphID`, `useBackendAPI`
 - Use function declarations (not arrow functions) for components/handlers
-- No `dark:` Tailwind classes — the design system handles dark mode
-- Use Next.js `<Link>` for internal navigation — never raw `<a>` tags
-- No `any` types unless the value genuinely can be anything
-- No linter suppressors (`// @ts-ignore`, `// eslint-disable`) — fix the actual issue
-- **File length** — keep files under ~200 lines; extract sub-components or hooks into their own files when a file grows beyond this
-- **Function/component length** — keep render functions and hooks under ~50 lines; extract named helpers or sub-components when they grow longer
 
 ## Architecture
 

autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx

@@ -83,7 +83,7 @@ export function CopilotPage() {
     handleDrawerOpenChange,
     handleSelectSession,
     handleNewChat,
-    // Delete functionality (available via ChatSidebar context menu on all viewports)
+    // Delete functionality
     sessionToDelete,
     isDeleting,
     handleConfirmDelete,

autogpt_platform/frontend/src/app/(platform)/copilot/components/JobStatsBar/useWorkDoneCounters.ts

@@ -5,7 +5,7 @@ const TOOL_TO_CATEGORY: Record<string, string> = {
   find_agent: "search",
   find_library_agent: "search",
   run_agent: "agent run",
-  run_block: "action",
+  run_block: "block run",
   create_agent: "agent created",
   edit_agent: "agent edited",
   schedule_agent: "agent scheduled",

autogpt_platform/frontend/src/app/(platform)/copilot/components/UsageLimits/UsageLimits.tsx

@@ -1,5 +1,4 @@
 import type { CoPilotUsageStatus } from "@/app/api/__generated__/models/coPilotUsageStatus";
-import { useGetV2GetCopilotUsage } from "@/app/api/__generated__/endpoints/chat/chat";
 import {
   Popover,
   PopoverContent,
@@ -7,18 +6,127 @@ import {
 } from "@/components/molecules/Popover/Popover";
 import { Button } from "@/components/ui/button";
 import { ChartBar } from "@phosphor-icons/react";
-import { UsagePanelContent } from "./UsagePanelContent";
+import { useUsageLimits } from "./useUsageLimits";
 
-export { UsagePanelContent, formatResetTime } from "./UsagePanelContent";
+const MS_PER_MINUTE = 60_000;
+const MS_PER_HOUR = 3_600_000;
+
+function formatResetTime(resetsAt: Date | string): string {
+  const resetDate =
+    typeof resetsAt === "string" ? new Date(resetsAt) : resetsAt;
+  const now = new Date();
+  const diffMs = resetDate.getTime() - now.getTime();
+  if (diffMs <= 0) return "now";
+
+  const hours = Math.floor(diffMs / MS_PER_HOUR);
+
+  // Under 24h: show relative time ("in 4h 23m")
+  if (hours < 24) {
+    const minutes = Math.floor((diffMs % MS_PER_HOUR) / MS_PER_MINUTE);
+    if (hours > 0) return `in ${hours}h ${minutes}m`;
+    return `in ${minutes}m`;
+  }
+
+  // Over 24h: show day and time in local timezone ("Mon 12:00 AM PST")
+  return resetDate.toLocaleString(undefined, {
+    weekday: "short",
+    hour: "numeric",
+    minute: "2-digit",
+    timeZoneName: "short",
+  });
+}
+
+function UsageBar({
+  label,
+  used,
+  limit,
+  resetsAt,
+}: {
+  label: string;
+  used: number;
+  limit: number;
+  resetsAt: Date | string;
+}) {
+  if (limit <= 0) return null;
+
+  const rawPercent = (used / limit) * 100;
+  const percent = Math.min(100, Math.round(rawPercent));
+  const isHigh = percent >= 80;
+  const percentLabel =
+    used > 0 && percent === 0 ? "<1% used" : `${percent}% used`;
+
+  return (
+    <div className="flex flex-col gap-1">
+      <div className="flex items-baseline justify-between">
+        <span className="text-xs font-medium text-neutral-700">{label}</span>
+        <span className="text-[11px] tabular-nums text-neutral-500">
+          {percentLabel}
+        </span>
+      </div>
+      <div className="text-[10px] text-neutral-400">
+        Resets {formatResetTime(resetsAt)}
+      </div>
+      <div className="h-2 w-full overflow-hidden rounded-full bg-neutral-200">
+        <div
+          className={`h-full rounded-full transition-[width] duration-300 ease-out ${
+            isHigh ? "bg-orange-500" : "bg-blue-500"
+          }`}
+          style={{ width: `${Math.max(used > 0 ? 1 : 0, percent)}%` }}
+        />
+      </div>
+    </div>
+  );
+}
+
+export function UsagePanelContent({
+  usage,
+  showBillingLink = true,
+}: {
+  usage: CoPilotUsageStatus;
+  showBillingLink?: boolean;
+}) {
+  const hasDailyLimit = usage.daily.limit > 0;
+  const hasWeeklyLimit = usage.weekly.limit > 0;
+
+  if (!hasDailyLimit && !hasWeeklyLimit) {
+    return (
+      <div className="text-xs text-neutral-500">No usage limits configured</div>
+    );
+  }
+
+  return (
+    <div className="flex flex-col gap-3">
+      <div className="text-xs font-semibold text-neutral-800">Usage limits</div>
+      {hasDailyLimit && (
+        <UsageBar
+          label="Today"
+          used={usage.daily.used}
+          limit={usage.daily.limit}
+          resetsAt={usage.daily.resets_at}
+        />
+      )}
+      {hasWeeklyLimit && (
+        <UsageBar
+          label="This week"
+          used={usage.weekly.used}
+          limit={usage.weekly.limit}
+          resetsAt={usage.weekly.resets_at}
+        />
+      )}
+      {showBillingLink && (
+        <a
+          href="/profile/credits"
+          className="text-[11px] text-blue-600 hover:underline"
+        >
+          Learn more about usage limits
+        </a>
+      )}
+    </div>
+  );
+}
 
 export function UsageLimits() {
-  const { data: usage, isLoading } = useGetV2GetCopilotUsage({
-    query: {
-      select: (res) => res.data as CoPilotUsageStatus,
-      refetchInterval: 30000,
-      staleTime: 10000,
-    },
-  });
+  const { data: usage, isLoading } = useUsageLimits();
 
   if (isLoading || !usage) return null;
   if (usage.daily.limit <= 0 && usage.weekly.limit <= 0) return null;

autogpt_platform/frontend/src/app/(platform)/copilot/components/UsageLimits/UsagePanelContent.tsx

@@ -1,118 +0,0 @@
-import type { CoPilotUsageStatus } from "@/app/api/__generated__/models/coPilotUsageStatus";
-import Link from "next/link";
-
-export function formatResetTime(
-  resetsAt: Date | string,
-  now: Date = new Date(),
-): string {
-  const resetDate =
-    typeof resetsAt === "string" ? new Date(resetsAt) : resetsAt;
-  const diffMs = resetDate.getTime() - now.getTime();
-  if (diffMs <= 0) return "now";
-
-  const hours = Math.floor(diffMs / (1000 * 60 * 60));
-
-  // Under 24h: show relative time ("in 4h 23m")
-  if (hours < 24) {
-    const minutes = Math.floor((diffMs % (1000 * 60 * 60)) / (1000 * 60));
-    if (hours > 0) return `in ${hours}h ${minutes}m`;
-    return `in ${minutes}m`;
-  }
-
-  // Over 24h: show day and time in local timezone ("Mon 12:00 AM PST")
-  return resetDate.toLocaleString(undefined, {
-    weekday: "short",
-    hour: "numeric",
-    minute: "2-digit",
-    timeZoneName: "short",
-  });
-}
-
-function UsageBar({
-  label,
-  used,
-  limit,
-  resetsAt,
-}: {
-  label: string;
-  used: number;
-  limit: number;
-  resetsAt: Date | string;
-}) {
-  if (limit <= 0) return null;
-
-  const rawPercent = (used / limit) * 100;
-  const percent = Math.min(100, Math.round(rawPercent));
-  const isHigh = percent >= 80;
-  const percentLabel =
-    used > 0 && percent === 0 ? "<1% used" : `${percent}% used`;
-
-  return (
-    <div className="flex flex-col gap-1">
-      <div className="flex items-baseline justify-between">
-        <span className="text-xs font-medium text-neutral-700">{label}</span>
-        <span className="text-[11px] tabular-nums text-neutral-500">
-          {percentLabel}
-        </span>
-      </div>
-      <div className="text-[10px] text-neutral-400">
-        Resets {formatResetTime(resetsAt)}
-      </div>
-      <div className="h-2 w-full overflow-hidden rounded-full bg-neutral-200">
-        <div
-          className={`h-full rounded-full transition-[width] duration-300 ease-out ${
-            isHigh ? "bg-orange-500" : "bg-blue-500"
-          }`}
-          style={{ width: `${Math.max(used > 0 ? 1 : 0, percent)}%` }}
-        />
-      </div>
-    </div>
-  );
-}
-
-export function UsagePanelContent({
-  usage,
-  showBillingLink = true,
-}: {
-  usage: CoPilotUsageStatus;
-  showBillingLink?: boolean;
-}) {
-  const hasDailyLimit = usage.daily.limit > 0;
-  const hasWeeklyLimit = usage.weekly.limit > 0;
-
-  if (!hasDailyLimit && !hasWeeklyLimit) {
-    return (
-      <div className="text-xs text-neutral-500">No usage limits configured</div>
-    );
-  }
-
-  return (
-    <div className="flex flex-col gap-3">
-      <div className="text-xs font-semibold text-neutral-800">Usage limits</div>
-      {hasDailyLimit && (
-        <UsageBar
-          label="Today"
-          used={usage.daily.used}
-          limit={usage.daily.limit}
-          resetsAt={usage.daily.resets_at}
-        />
-      )}
-      {hasWeeklyLimit && (
-        <UsageBar
-          label="This week"
-          used={usage.weekly.used}
-          limit={usage.weekly.limit}
-          resetsAt={usage.weekly.resets_at}
-        />
-      )}
-      {showBillingLink && (
-        <Link
-          href="/profile/credits"
-          className="text-[11px] text-blue-600 hover:underline"
-        >
-          Learn more about usage limits
-        </Link>
-      )}
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/UsageLimits/__tests__/UsageLimits.test.tsx

@@ -2,10 +2,10 @@ import { render, screen, cleanup } from "@/tests/integrations/test-utils";
 import { afterEach, describe, expect, it, vi } from "vitest";
 import { UsageLimits } from "../UsageLimits";
 
-// Mock the generated Orval hook
-const mockUseGetV2GetCopilotUsage = vi.fn();
-vi.mock("@/app/api/__generated__/endpoints/chat/chat", () => ({
-  useGetV2GetCopilotUsage: (opts: unknown) => mockUseGetV2GetCopilotUsage(opts),
+// Mock the useUsageLimits hook
+const mockUseUsageLimits = vi.fn();
+vi.mock("../useUsageLimits", () => ({
+  useUsageLimits: () => mockUseUsageLimits(),
 }));
 
 // Mock Popover to render children directly (Radix portals don't work in happy-dom)
@@ -23,7 +23,7 @@ vi.mock("@/components/molecules/Popover/Popover", () => ({
 
 afterEach(() => {
   cleanup();
-  mockUseGetV2GetCopilotUsage.mockReset();
+  mockUseUsageLimits.mockReset();
 });
 
 function makeUsage({
@@ -46,16 +46,13 @@ function makeUsage({
 
 describe("UsageLimits", () => {
   it("renders nothing while loading", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: undefined,
-      isLoading: true,
-    });
+    mockUseUsageLimits.mockReturnValue({ data: undefined, isLoading: true });
     const { container } = render(<UsageLimits />);
     expect(container.innerHTML).toBe("");
   });
 
   it("renders nothing when no limits are configured", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
+    mockUseUsageLimits.mockReturnValue({
       data: makeUsage({ dailyLimit: 0, weeklyLimit: 0 }),
       isLoading: false,
     });
@@ -64,7 +61,7 @@ describe("UsageLimits", () => {
   });
 
   it("renders the usage button when limits exist", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
+    mockUseUsageLimits.mockReturnValue({
       data: makeUsage(),
       isLoading: false,
     });
@@ -73,7 +70,7 @@ describe("UsageLimits", () => {
   });
 
   it("displays daily and weekly usage percentages", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
+    mockUseUsageLimits.mockReturnValue({
       data: makeUsage({ dailyUsed: 5000, dailyLimit: 10000 }),
       isLoading: false,
     });
@@ -86,7 +83,7 @@ describe("UsageLimits", () => {
   });
 
   it("shows only weekly bar when daily limit is 0", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
+    mockUseUsageLimits.mockReturnValue({
       data: makeUsage({
         dailyLimit: 0,
         weeklyUsed: 25000,
@@ -101,7 +98,7 @@ describe("UsageLimits", () => {
   });
 
   it("caps percentage at 100% when over limit", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
+    mockUseUsageLimits.mockReturnValue({
       data: makeUsage({ dailyUsed: 15000, dailyLimit: 10000 }),
       isLoading: false,
     });
@@ -111,7 +108,7 @@ describe("UsageLimits", () => {
   });
 
   it("shows learn more link to credits page", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
+    mockUseUsageLimits.mockReturnValue({
       data: makeUsage(),
       isLoading: false,
     });

autogpt_platform/frontend/src/app/(platform)/copilot/components/UsageLimits/useUsageLimits.ts

@@ -0,0 +1,12 @@
+import type { CoPilotUsageStatus } from "@/app/api/__generated__/models/coPilotUsageStatus";
+import { useGetV2GetCopilotUsage } from "@/app/api/__generated__/endpoints/chat/chat";
+
+export function useUsageLimits() {
+  return useGetV2GetCopilotUsage({
+    query: {
+      select: (res) => res.data as CoPilotUsageStatus,
+      refetchInterval: 30000,
+      staleTime: 10000,
+    },
+  });
+}

autogpt_platform/frontend/src/app/(platform)/copilot/styleguide/page.tsx

@@ -706,8 +706,8 @@ export default function StyleguidePage() {
                     input: { block_id: "weather-block-123" },
                     output: {
                       type: ResponseType.error,
-                      message: "Something went wrong while running this step.",
-                      error: "Execution timed out after 30 seconds.",
+                      message: "Failed to run the block.",
+                      error: "Block execution timed out after 30 seconds.",
                       details: {
                         block_id: "weather-block-123",
                         timeout_ms: 30000,

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/FindBlocks.tsx

@@ -61,7 +61,7 @@ export function FindBlocksTool({ part }: Props) {
 
   const query = (part.input as FindBlockInput | undefined)?.query?.trim();
   const accordionDescription = parsed
-    ? `Found ${parsed.count} action${parsed.count === 1 ? "" : "s"}${query ? ` for "${query}"` : ""}`
+    ? `Found ${parsed.count} block${parsed.count === 1 ? "" : "s"}${query ? ` for "${query}"` : ""}`
     : undefined;
 
   return (
@@ -77,7 +77,7 @@ export function FindBlocksTool({ part }: Props) {
       {hasBlocks && parsed && (
         <ToolAccordion
           icon={<AccordionIcon />}
-          title="Results"
+          title="Block results"
           description={accordionDescription}
         >
           <HorizontalScroll dependencyList={[parsed.blocks.length]}>

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/helpers.tsx

@@ -30,21 +30,21 @@ export function getAnimationText(part: FindBlockToolPart): string {
   switch (part.state) {
     case "input-streaming":
     case "input-available":
-      return `Searching for actions${queryText}`;
+      return `Searching for blocks${queryText}`;
 
     case "output-available": {
       const parsed = parseOutput(part.output);
       if (parsed) {
-        return `Found ${parsed.count} action${parsed.count === 1 ? "" : "s"}${queryText}`;
+        return `Found ${parsed.count} block${parsed.count === 1 ? "" : "s"}${queryText}`;
       }
-      return `Searching for actions${queryText}`;
+      return `Searching for blocks${queryText}`;
     }
 
     case "output-error":
-      return `Search failed${query ? ` for "${query}"` : ""}`;
+      return `Error finding blocks${queryText}`;
 
     default:
-      return "Searching for actions";
+      return "Searching for blocks";
   }
 }
 

autogpt_platform/frontend/src/app/(platform)/copilot/tools/GenericTool/helpers.ts

@@ -144,23 +144,6 @@ export function truncate(text: string, maxLen: number): string {
   return text.slice(0, maxLen).trimEnd() + "\u2026";
 }
 
-const STRIPPABLE_EXTENSIONS =
-  /\.(md|csv|json|txt|yaml|yml|xml|html|js|ts|py|sh|toml|cfg|ini|log|pdf|png|jpg|jpeg|gif|svg|mp4|mp3|wav|zip|tar|gz)$/i;
-
-export function humanizeFileName(filePath: string): string {
-  const fileName = filePath.split("/").pop() ?? filePath;
-  const stem = fileName.replace(STRIPPABLE_EXTENSIONS, "");
-  const words = stem
-    .replace(/[_-]/g, " ")
-    .split(/\s+/)
-    .filter(Boolean)
-    .map((w) => {
-      if (w === w.toUpperCase()) return w;
-      return w.charAt(0).toUpperCase() + w.slice(1).toLowerCase();
-    });
-  return `"${words.join(" ")}"`;
-}
-
 /* ------------------------------------------------------------------ */
 /*  Exit code helper                                                   */
 /* ------------------------------------------------------------------ */
@@ -208,16 +191,16 @@ export function getAnimationText(
             ? `Browsing ${shortSummary}`
             : "Interacting with browser\u2026";
         case "file-read":
-          return summary
-            ? `Reading ${humanizeFileName(summary)}`
+          return shortSummary
+            ? `Reading ${shortSummary}`
             : "Reading file\u2026";
         case "file-write":
-          return summary
-            ? `Writing ${humanizeFileName(summary)}`
+          return shortSummary
+            ? `Writing ${shortSummary}`
             : "Writing file\u2026";
         case "file-delete":
-          return summary
-            ? `Deleting ${humanizeFileName(summary)}`
+          return shortSummary
+            ? `Deleting ${shortSummary}`
             : "Deleting file\u2026";
         case "file-list":
           return shortSummary
@@ -228,8 +211,8 @@ export function getAnimationText(
             ? `Searching for "${shortSummary}"`
             : "Searching\u2026";
         case "edit":
-          return summary
-            ? `Editing ${humanizeFileName(summary)}`
+          return shortSummary
+            ? `Editing ${shortSummary}`
             : "Editing file\u2026";
         case "todo":
           return shortSummary ? `${shortSummary}` : "Updating task list\u2026";
@@ -263,17 +246,11 @@ export function getAnimationText(
             ? `Browsed ${shortSummary}`
             : "Browser action completed";
         case "file-read":
-          return summary
-            ? `Read ${humanizeFileName(summary)}`
-            : "File read completed";
+          return shortSummary ? `Read ${shortSummary}` : "File read completed";
         case "file-write":
-          return summary
-            ? `Wrote ${humanizeFileName(summary)}`
-            : "File written";
+          return shortSummary ? `Wrote ${shortSummary}` : "File written";
         case "file-delete":
-          return summary
-            ? `Deleted ${humanizeFileName(summary)}`
-            : "File deleted";
+          return shortSummary ? `Deleted ${shortSummary}` : "File deleted";
         case "file-list":
           return "Listed files";
         case "search":
@@ -281,9 +258,7 @@ export function getAnimationText(
             ? `Searched for "${shortSummary}"`
             : "Search completed";
         case "edit":
-          return summary
-            ? `Edited ${humanizeFileName(summary)}`
-            : "Edit completed";
+          return shortSummary ? `Edited ${shortSummary}` : "Edit completed";
         case "todo":
           return "Updated task list";
         case "compaction":

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/helpers.tsx

@@ -149,10 +149,10 @@ export function getAnimationText(part: {
       }
       if (isRunAgentNeedLoginOutput(output))
         return "Sign in required to run agent";
-      return "Something went wrong";
+      return "Error running agent";
     }
     case "output-error":
-      return "Something went wrong";
+      return "Error running agent";
     default:
       return actionPhrase;
   }

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/SetupRequirementsCard.tsx

@@ -18,10 +18,10 @@ import {
 interface Props {
   output: SetupRequirementsResponse;
   /** Override the message sent to the chat when the user clicks Proceed after connecting credentials.
-   * Defaults to "Please re-run this step now." */
+   * Defaults to "Please re-run the block now." */
   retryInstruction?: string;
   /** Override the label shown above the credentials section.
-   * Defaults to "Credentials". */
+   * Defaults to "Block credentials". */
   credentialsLabel?: string;
 }
 
@@ -87,9 +87,11 @@ export function SetupRequirementsCard({
           ([, v]) => v !== undefined && v !== null && v !== "",
         ),
       );
-      parts.push(`Run with these inputs: ${JSON.stringify(nonEmpty, null, 2)}`);
+      parts.push(
+        `Run the block with these inputs: ${JSON.stringify(nonEmpty, null, 2)}`,
+      );
     } else {
-      parts.push(retryInstruction ?? "Please re-run this step now.");
+      parts.push(retryInstruction ?? "Please re-run the block now.");
     }
 
     onSend(parts.join(" "));
@@ -103,7 +105,7 @@ export function SetupRequirementsCard({
       {needsCredentials && (
         <div className="rounded-2xl border bg-background p-3">
           <Text variant="small" className="w-fit border-b text-zinc-500">
-            {credentialsLabel ?? "Credentials"}
+            {credentialsLabel ?? "Block credentials"}
           </Text>
           <div className="mt-6">
             <CredentialsGroupedView
@@ -120,7 +122,7 @@ export function SetupRequirementsCard({
       {inputSchema && (
         <div className="rounded-2xl border bg-background p-3 pt-4">
           <Text variant="small" className="w-fit border-b text-zinc-500">
-            Inputs
+            Block inputs
           </Text>
           <FormRenderer
             jsonSchema={inputSchema}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/helpers.tsx

@@ -165,12 +165,12 @@ export function getAnimationText(part: {
       if (isRunBlockReviewRequiredOutput(output)) {
         return `Review needed for "${output.block_name}"`;
       }
-      return "Action failed";
+      return "Error running block";
     }
     case "output-error":
-      return "Action failed";
+      return "Error running block";
     default:
-      return "Running";
+      return "Running the block";
   }
 }
 

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotStream.ts

@@ -178,41 +178,12 @@ export function useCopilotStream({
     onError: (error) => {
       if (!sessionId) return;
 
-      // Detect rate limit (429) responses and show reset time to the user.
-      // The SDK throws a plain Error whose message is the raw response body
-      // (FastAPI returns {"detail": "...usage limit..."} for 429s).
-      let errorDetail: string = error.message;
-      try {
-        const parsed = JSON.parse(error.message) as unknown;
-        if (
-          typeof parsed === "object" &&
-          parsed !== null &&
-          "detail" in parsed &&
-          typeof (parsed as { detail: unknown }).detail === "string"
-        ) {
-          errorDetail = (parsed as { detail: string }).detail;
-        }
-      } catch {
-        // Not JSON — use message as-is
-      }
-      const isRateLimited = errorDetail.toLowerCase().includes("usage limit");
-      if (isRateLimited) {
-        toast({
-          title: "Usage limit reached",
-          description:
-            errorDetail ||
-            "You've reached your usage limit. Please try again later.",
-          variant: "destructive",
-        });
-        return;
-      }
-
       // Detect authentication failures (from getAuthHeaders or 401 responses)
       const isAuthError =
-        errorDetail.includes("Authentication failed") ||
-        errorDetail.includes("Unauthorized") ||
-        errorDetail.includes("Not authenticated") ||
-        errorDetail.toLowerCase().includes("401");
+        error.message.includes("Authentication failed") ||
+        error.message.includes("Unauthorized") ||
+        error.message.includes("Not authenticated") ||
+        error.message.toLowerCase().includes("401");
       if (isAuthError) {
         toast({
           title: "Authentication error",

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/NewAgentLibraryView.tsx

@@ -209,7 +209,6 @@ export function NewAgentLibraryView() {
               agent={agent}
               scheduleId={activeItem}
               onScheduleDeleted={handleScheduleDeleted}
-              onSelectRun={(id) => handleSelectRun(id, "runs")}
               banner={renderMarketplaceUpdateBanner()}
             />
           ) : activeTab === "templates" ? (

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/SelectedScheduleView.tsx

@@ -20,7 +20,6 @@ interface Props {
   agent: LibraryAgent;
   scheduleId: string;
   onScheduleDeleted?: (deletedScheduleId: string) => void;
-  onSelectRun?: (id: string) => void;
   banner?: React.ReactNode;
 }
 
@@ -28,7 +27,6 @@ export function SelectedScheduleView({
   agent,
   scheduleId,
   onScheduleDeleted,
-  onSelectRun,
   banner,
 }: Props) {
   const { schedule, isLoading, error } = useSelectedScheduleView(
@@ -91,9 +89,7 @@ export function SelectedScheduleView({
                   <SelectedScheduleActions
                     agent={agent}
                     scheduleId={schedule.id}
-                    schedule={schedule}
                     onDeleted={() => onScheduleDeleted?.(schedule.id)}
-                    onSelectRun={onSelectRun}
                   />
                 </div>
               ) : null}
@@ -172,9 +168,7 @@ export function SelectedScheduleView({
           <SelectedScheduleActions
             agent={agent}
             scheduleId={schedule.id}
-            schedule={schedule}
             onDeleted={() => onScheduleDeleted?.(schedule.id)}
-            onSelectRun={onSelectRun}
           />
         </div>
       ) : null}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions/SelectedScheduleActions.tsx

@@ -1,12 +1,11 @@
 "use client";
 
-import type { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo";
-import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
+import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { Button } from "@/components/atoms/Button/Button";
 import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { Text } from "@/components/atoms/Text/Text";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
-import { EyeIcon, Play, TrashIcon } from "@phosphor-icons/react";
+import { EyeIcon, TrashIcon } from "@phosphor-icons/react";
 import { AgentActionsDropdown } from "../../../AgentActionsDropdown";
 import { SelectedActionsWrap } from "../../../SelectedActionsWrap";
 import { useSelectedScheduleActions } from "./useSelectedScheduleActions";
@@ -14,17 +13,13 @@ import { useSelectedScheduleActions } from "./useSelectedScheduleActions";
 type Props = {
   agent: LibraryAgent;
   scheduleId: string;
-  schedule?: GraphExecutionJobInfo;
   onDeleted?: () => void;
-  onSelectRun?: (id: string) => void;
 };
 
 export function SelectedScheduleActions({
   agent,
   scheduleId,
-  schedule,
   onDeleted,
-  onSelectRun,
 }: Props) {
   const {
     openInBuilderHref,
@@ -32,32 +27,11 @@ export function SelectedScheduleActions({
     setShowDeleteDialog,
     handleDelete,
     isDeleting,
-    handleRunNow,
-    isRunning,
-  } = useSelectedScheduleActions({
-    agent,
-    scheduleId,
-    schedule,
-    onDeleted,
-    onSelectRun,
-  });
+  } = useSelectedScheduleActions({ agent, scheduleId, onDeleted });
 
   return (
     <>
       <SelectedActionsWrap>
-        <Button
-          variant="icon"
-          size="icon"
-          aria-label="Run now"
-          onClick={handleRunNow}
-          disabled={isRunning || !schedule}
-        >
-          {isRunning ? (
-            <LoadingSpinner size="small" />
-          ) : (
-            <Play weight="bold" size={18} className="text-zinc-700" />
-          )}
-        </Button>
         {openInBuilderHref && (
           <Button
             variant="icon"

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions/useSelectedScheduleActions.ts

@@ -1,16 +1,10 @@
 "use client";
 
-import {
-  getGetV1ListGraphExecutionsQueryKey,
-  usePostV1ExecuteGraphAgent,
-} from "@/app/api/__generated__/endpoints/graphs/graphs";
 import {
   getGetV1ListExecutionSchedulesForAGraphQueryOptions,
   useDeleteV1DeleteExecutionSchedule,
 } from "@/app/api/__generated__/endpoints/schedules/schedules";
-import type { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo";
-import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
-import { okData } from "@/app/api/helpers";
+import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { useQueryClient } from "@tanstack/react-query";
 import { useState } from "react";
@@ -18,17 +12,13 @@ import { useState } from "react";
 interface UseSelectedScheduleActionsProps {
   agent: LibraryAgent;
   scheduleId: string;
-  schedule?: GraphExecutionJobInfo;
   onDeleted?: () => void;
-  onSelectRun?: (id: string) => void;
 }
 
 export function useSelectedScheduleActions({
   agent,
   scheduleId,
-  schedule,
   onDeleted,
-  onSelectRun,
 }: UseSelectedScheduleActionsProps) {
   const { toast } = useToast();
   const queryClient = useQueryClient();
@@ -60,58 +50,11 @@ export function useSelectedScheduleActions({
     },
   });
 
-  const { mutateAsync: executeAgent, isPending: isRunning } =
-    usePostV1ExecuteGraphAgent();
-
   function handleDelete() {
     if (!scheduleId) return;
     deleteMutation.mutate({ scheduleId });
   }
 
-  async function handleRunNow() {
-    if (!schedule) {
-      toast({
-        title: "Schedule not loaded",
-        description: "Please wait for the schedule to load.",
-        variant: "destructive",
-      });
-      return;
-    }
-
-    try {
-      toast({ title: "Run started" });
-
-      const res = await executeAgent({
-        graphId: schedule.graph_id,
-        graphVersion: schedule.graph_version,
-        data: {
-          inputs: schedule.input_data || {},
-          credentials_inputs: schedule.input_credentials || {},
-          source: "library",
-        },
-      });
-
-      const newRunID = okData(res)?.id;
-
-      await queryClient.invalidateQueries({
-        queryKey: getGetV1ListGraphExecutionsQueryKey(agent.graph_id),
-      });
-
-      if (newRunID && onSelectRun) {
-        onSelectRun(newRunID);
-      }
-    } catch (error: unknown) {
-      toast({
-        title: "Failed to start run",
-        description:
-          error instanceof Error
-            ? error.message
-            : "An unexpected error occurred.",
-        variant: "destructive",
-      });
-    }
-  }
-
   const openInBuilderHref = `/build?flowID=${agent.graph_id}&flowVersion=${agent.graph_version}`;
 
   return {
@@ -120,7 +63,5 @@ export function useSelectedScheduleActions({
     setShowDeleteDialog,
     handleDelete,
     isDeleting: deleteMutation.isPending,
-    handleRunNow,
-    isRunning,
   };
 }

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/SidebarRunsList.tsx

@@ -186,7 +186,6 @@ export function SidebarRunsList({
                     selected={selectedRunId === s.id}
                     onClick={() => onSelectRun(s.id, "scheduled")}
                     onDeleted={() => onScheduleDeleted?.(s.id)}
-                    onRunCreated={(runID) => onSelectRun(runID, "runs")}
                   />
                 </div>
               ))

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleActionsDropdown.tsx

@@ -1,16 +1,11 @@
 "use client";
 
-import {
-  getGetV1ListGraphExecutionsQueryKey,
-  usePostV1ExecuteGraphAgent,
-} from "@/app/api/__generated__/endpoints/graphs/graphs";
 import {
   getGetV1ListExecutionSchedulesForAGraphQueryOptions,
   useDeleteV1DeleteExecutionSchedule,
 } from "@/app/api/__generated__/endpoints/schedules/schedules";
 import type { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo";
 import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
-import { okData } from "@/app/api/helpers";
 import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
@@ -18,7 +13,6 @@ import {
   DropdownMenu,
   DropdownMenuContent,
   DropdownMenuItem,
-  DropdownMenuSeparator,
   DropdownMenuTrigger,
 } from "@/components/molecules/DropdownMenu/DropdownMenu";
 import { useToast } from "@/components/molecules/Toast/use-toast";
@@ -30,15 +24,9 @@ interface Props {
   agent: LibraryAgent;
   schedule: GraphExecutionJobInfo;
   onDeleted?: () => void;
-  onRunCreated?: (runID: string) => void;
 }
 
-export function ScheduleActionsDropdown({
-  agent,
-  schedule,
-  onDeleted,
-  onRunCreated,
-}: Props) {
+export function ScheduleActionsDropdown({ agent, schedule, onDeleted }: Props) {
   const { toast } = useToast();
   const queryClient = useQueryClient();
   const [showDeleteDialog, setShowDeleteDialog] = useState(false);
@@ -46,9 +34,6 @@ export function ScheduleActionsDropdown({
   const { mutateAsync: deleteSchedule, isPending: isDeleting } =
     useDeleteV1DeleteExecutionSchedule();
 
-  const { mutateAsync: executeAgent, isPending: isRunning } =
-    usePostV1ExecuteGraphAgent();
-
   async function handleDelete() {
     try {
       await deleteSchedule({ scheduleId: schedule.id });
@@ -75,43 +60,6 @@ export function ScheduleActionsDropdown({
     }
   }
 
-  async function handleRunNow(e: React.MouseEvent) {
-    e.stopPropagation();
-
-    try {
-      toast({ title: "Run started" });
-
-      const res = await executeAgent({
-        graphId: schedule.graph_id,
-        graphVersion: schedule.graph_version,
-        data: {
-          inputs: schedule.input_data || {},
-          credentials_inputs: schedule.input_credentials || {},
-          source: "library",
-        },
-      });
-
-      const newRunID = okData(res)?.id;
-
-      await queryClient.invalidateQueries({
-        queryKey: getGetV1ListGraphExecutionsQueryKey(agent.graph_id),
-      });
-
-      if (newRunID) {
-        onRunCreated?.(newRunID);
-      }
-    } catch (error: unknown) {
-      toast({
-        title: "Failed to start run",
-        description:
-          error instanceof Error
-            ? error.message
-            : "An unexpected error occurred.",
-        variant: "destructive",
-      });
-    }
-  }
-
   return (
     <>
       <DropdownMenu>
@@ -125,14 +73,6 @@ export function ScheduleActionsDropdown({
           </button>
         </DropdownMenuTrigger>
         <DropdownMenuContent align="end">
-          <DropdownMenuItem
-            onClick={handleRunNow}
-            disabled={isRunning}
-            className="flex items-center gap-2"
-          >
-            {isRunning ? "Running..." : "Run now"}
-          </DropdownMenuItem>
-          <DropdownMenuSeparator />
           <DropdownMenuItem
             onClick={(e) => {
               e.stopPropagation();

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleListItem.tsx

@@ -14,7 +14,6 @@ interface Props {
   selected?: boolean;
   onClick?: () => void;
   onDeleted?: () => void;
-  onRunCreated?: (runID: string) => void;
 }
 
 export function ScheduleListItem({
@@ -23,7 +22,6 @@ export function ScheduleListItem({
   selected,
   onClick,
   onDeleted,
-  onRunCreated,
 }: Props) {
   return (
     <SidebarItemCard
@@ -48,7 +46,6 @@ export function ScheduleListItem({
           agent={agent}
           schedule={schedule}
           onDeleted={onDeleted}
-          onRunCreated={onRunCreated}
         />
       }
     />

autogpt_platform/frontend/src/app/(platform)/library/components/JumpBackIn/JumpBackIn.tsx

@@ -1,40 +0,0 @@
-"use client";
-
-import { ArrowRight, Lightning } from "@phosphor-icons/react";
-import NextLink from "next/link";
-
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { useJumpBackIn } from "./useJumpBackIn";
-
-export function JumpBackIn() {
-  const { agent, isLoading } = useJumpBackIn();
-
-  if (isLoading || !agent) {
-    return null;
-  }
-
-  return (
-    <div className="flex items-center justify-between rounded-large border border-zinc-200 bg-gradient-to-r from-zinc-50 to-white px-5 py-4">
-      <div className="flex items-center gap-3">
-        <div className="flex h-9 w-9 items-center justify-center rounded-full bg-zinc-900">
-          <Lightning size={18} weight="fill" className="text-white" />
-        </div>
-        <div className="flex flex-col">
-          <Text variant="small" className="text-zinc-500">
-            Continue where you left off
-          </Text>
-          <Text variant="body-medium" className="text-zinc-900">
-            {agent.name}
-          </Text>
-        </div>
-      </div>
-      <NextLink href={`/library/agents/${agent.id}`}>
-        <Button variant="primary" size="small" className="gap-1.5">
-          Jump Back In
-          <ArrowRight size={16} />
-        </Button>
-      </NextLink>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/components/JumpBackIn/useJumpBackIn.ts

@@ -1,28 +0,0 @@
-"use client";
-
-import { useGetV2ListLibraryAgents } from "@/app/api/__generated__/endpoints/library/library";
-import { okData } from "@/app/api/helpers";
-
-export function useJumpBackIn() {
-  const { data, isLoading } = useGetV2ListLibraryAgents(
-    {
-      page: 1,
-      page_size: 1,
-      sort_by: "updatedAt",
-    },
-    {
-      query: { select: okData },
-    },
-  );
-
-  // The API doesn't include execution data by default (include_executions is
-  // internal to the backend), so recent_executions is always empty here.
-  // We use the most recently updated agent as the "jump back in" candidate
-  // instead — updatedAt is the best available proxy for recent activity.
-  const agent = data?.agents[0] ?? null;
-
-  return {
-    agent,
-    isLoading,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/library/page.tsx

@@ -2,7 +2,6 @@
 
 import { useEffect, useState, useCallback } from "react";
 import { HeartIcon, ListIcon } from "@phosphor-icons/react";
-import { JumpBackIn } from "./components/JumpBackIn/JumpBackIn";
 import { LibraryActionHeader } from "./components/LibraryActionHeader/LibraryActionHeader";
 import { LibraryAgentList } from "./components/LibraryAgentList/LibraryAgentList";
 import { Tab } from "./components/LibraryTabs/LibraryTabs";
@@ -39,7 +38,6 @@ export default function LibraryPage() {
       onAnimationComplete={handleFavoriteAnimationComplete}
     >
       <main className="pt-160 container min-h-screen space-y-4 pb-20 pt-16 sm:px-8 md:px-12">
-        <JumpBackIn />
         <LibraryActionHeader setSearchTerm={setSearchTerm} />
         <LibraryAgentList
           searchTerm={searchTerm}

autogpt_platform/frontend/src/app/(platform)/profile/(user)/credits/page.tsx

@@ -12,8 +12,7 @@ import {
 import { RefundModal } from "./RefundModal";
 import { CreditTransaction } from "@/lib/autogpt-server-api";
 import { UsagePanelContent } from "@/app/(platform)/copilot/components/UsageLimits/UsageLimits";
-import type { CoPilotUsageStatus } from "@/app/api/__generated__/models/coPilotUsageStatus";
-import { useGetV2GetCopilotUsage } from "@/app/api/__generated__/endpoints/chat/chat";
+import { useUsageLimits } from "@/app/(platform)/copilot/components/UsageLimits/useUsageLimits";
 
 import {
   Table,
@@ -25,14 +24,8 @@ import {
 } from "@/components/__legacy__/ui/table";
 
 function CoPilotUsageSection() {
+  const { data: usage, isLoading } = useUsageLimits();
   const router = useRouter();
-  const { data: usage, isLoading } = useGetV2GetCopilotUsage({
-    query: {
-      select: (res) => res.data as CoPilotUsageStatus,
-      refetchInterval: 30000,
-      staleTime: 10000,
-    },
-  });
 
   if (isLoading || !usage) return null;
   if (usage.daily.limit <= 0 && usage.weekly.limit <= 0) return null;
@@ -40,7 +33,7 @@ function CoPilotUsageSection() {
   return (
     <div className="my-6 space-y-4">
       <h3 className="text-lg font-medium">CoPilot Usage Limits</h3>
-      <div className="rounded-lg border border-neutral-200 p-4">
+      <div className="rounded-lg border border-neutral-200 p-4 dark:border-neutral-700">
         <UsagePanelContent usage={usage} showBillingLink={false} />
       </div>
       <Button className="w-full" onClick={() => router.push("/copilot")}>

autogpt_platform/frontend/src/app/api/openapi.json

@@ -1267,7 +1267,7 @@
       "post": {
         "tags": ["v2", "chat", "chat"],
         "summary": "Stream Chat Post",
-        "description": "Stream chat responses for a session (POST with context support).\n\nStreams the AI/completion responses in real time over Server-Sent Events (SSE), including:\n  - Text fragments as they are generated\n  - Tool call UI elements (if invoked)\n  - Tool execution results\n\nThe AI generation runs in a background task that continues even if the client disconnects.\nAll chunks are written to a per-turn Redis stream for reconnection support. If the client\ndisconnects, they can reconnect using GET /sessions/{session_id}/stream to resume.\n\nArgs:\n    session_id: The chat session identifier to associate with the streamed messages.\n    request: Request body containing message, is_user_message, and optional context.\n    user_id: Authenticated user ID.\nReturns:\n    StreamingResponse: SSE-formatted response chunks.",
+        "description": "Stream chat responses for a session (POST with context support).\n\nStreams the AI/completion responses in real time over Server-Sent Events (SSE), including:\n  - Text fragments as they are generated\n  - Tool call UI elements (if invoked)\n  - Tool execution results\n\nThe AI generation runs in a background task that continues even if the client disconnects.\nAll chunks are written to a per-turn Redis stream for reconnection support. If the client\ndisconnects, they can reconnect using GET /sessions/{session_id}/stream to resume.\n\nArgs:\n    session_id: The chat session identifier to associate with the streamed messages.\n    request: Request body containing message, is_user_message, and optional context.\n    user_id: Optional authenticated user ID.\nReturns:\n    StreamingResponse: SSE-formatted response chunks.",
         "operationId": "postV2StreamChatPost",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [