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5 Commits

Author SHA1 Message Date
Otto
435738f2f9 refactor: address Pwuts review feedback
- Remove unused error_response() and format_inputs_as_markdown() from helpers.py
- Remove _get_inputs_list() wrapper from run_agent.py, use get_inputs_from_schema directly
- Fix type annotations: get_user_credentials, find_matching_credential, create_credential_meta_from_match
- Remove check_scopes parameter - always check scopes (original missing check was broken behavior)
- Reorder _credential_has_required_scopes to be defined before find_matching_credential
2026-02-08 16:43:21 +00:00
Otto
10ebaf5104 fix: enable scope checking for block credentials (consistency with graphs)
Previously run_block didn't check OAuth2 scopes while run_agent did.
Now both use the same scope-checking logic for credential matching.
2026-02-08 16:42:58 +00:00
Otto
59e58d5e9b fix: preserve original credential matching behavior
- Add check_scopes parameter to find_matching_credential and
  match_credentials_to_requirements (default True)
- run_block uses check_scopes=False to preserve original behavior
  (original run_block did not verify OAuth2 scopes)
- Add isinstance check to get_inputs_from_schema for safety
  (original returned [] if input_schema wasn't a dict)
2026-02-08 16:42:58 +00:00
Otto
f458adf2a5 chore: remove docstrings and use sorted() for deterministic UUID ordering 2026-02-08 16:42:53 +00:00
Otto
1613e41cab refactor(copilot): code cleanup - extract shared helpers and reduce duplication
- Create tools/helpers.py with shared utilities (get_inputs_from_schema)
- Add shared credential matching utilities to utils.py
- Refactor run_block to use shared matching with discriminator support
- Update run_agent.py to use shared helpers
- Add validation.py with UUID helpers

Note: routes.py streaming refactor dropped - dev has new stream registry implementation
2026-02-08 16:42:50 +00:00
208 changed files with 9537 additions and 13847 deletions

View File

@@ -49,7 +49,7 @@ jobs:
- name: Create PR ${{ env.BUILD_BRANCH }} -> ${{ github.ref_name }}
if: github.event_name == 'push'
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v7
with:
add-paths: classic/frontend/build/web
base: ${{ github.ref_name }}

View File

@@ -22,7 +22,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
ref: ${{ github.event.workflow_run.head_branch }}
fetch-depth: 0
@@ -42,7 +42,7 @@ jobs:
- name: Get CI failure details
id: failure_details
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
const run = await github.rest.actions.getWorkflowRun({

View File

@@ -30,7 +30,7 @@ jobs:
actions: read # Required for CI access
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1
@@ -41,7 +41,7 @@ jobs:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -78,7 +78,7 @@ jobs:
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22"
@@ -91,7 +91,7 @@ jobs:
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -124,7 +124,7 @@ jobs:
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes
@@ -309,7 +309,6 @@ jobs:
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
allowed_bots: "dependabot[bot]"
claude_args: |
--allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*)"
prompt: |

View File

@@ -40,7 +40,7 @@ jobs:
actions: read # Required for CI access
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1
@@ -57,7 +57,7 @@ jobs:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -94,7 +94,7 @@ jobs:
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22"
@@ -107,7 +107,7 @@ jobs:
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -140,7 +140,7 @@ jobs:
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes

View File

@@ -58,7 +58,7 @@ jobs:
# your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL

View File

@@ -27,7 +27,7 @@ jobs:
# If you do not check out your code, Copilot will do this for you.
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true
@@ -39,7 +39,7 @@ jobs:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -76,7 +76,7 @@ jobs:
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22"
@@ -89,7 +89,7 @@ jobs:
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -132,7 +132,7 @@ jobs:
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes

View File

@@ -23,7 +23,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1
@@ -33,7 +33,7 @@ jobs:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

View File

@@ -23,7 +23,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
@@ -33,7 +33,7 @@ jobs:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

View File

@@ -28,7 +28,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1
@@ -38,7 +38,7 @@ jobs:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

View File

@@ -25,7 +25,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
ref: ${{ github.event.inputs.git_ref || github.ref_name }}
@@ -52,7 +52,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Trigger deploy workflow
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

View File

@@ -17,7 +17,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
ref: ${{ github.ref_name || 'master' }}
@@ -45,7 +45,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Trigger deploy workflow
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

View File

@@ -68,7 +68,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true
@@ -88,7 +88,7 @@ jobs:
run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
- name: Set up Python dependency cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

View File

@@ -17,7 +17,7 @@ jobs:
- name: Check comment permissions and deployment status
id: check_status
if: github.event_name == 'issue_comment' && github.event.issue.pull_request
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
const commentBody = context.payload.comment.body.trim();
@@ -55,7 +55,7 @@ jobs:
- name: Post permission denied comment
if: steps.check_status.outputs.permission_denied == 'true'
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
await github.rest.issues.createComment({
@@ -68,7 +68,7 @@ jobs:
- name: Get PR details for deployment
id: pr_details
if: steps.check_status.outputs.should_deploy == 'true' || steps.check_status.outputs.should_undeploy == 'true'
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
const pr = await github.rest.pulls.get({
@@ -82,7 +82,7 @@ jobs:
- name: Dispatch Deploy Event
if: steps.check_status.outputs.should_deploy == 'true'
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -98,7 +98,7 @@ jobs:
- name: Post deploy success comment
if: steps.check_status.outputs.should_deploy == 'true'
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
await github.rest.issues.createComment({
@@ -110,7 +110,7 @@ jobs:
- name: Dispatch Undeploy Event (from comment)
if: steps.check_status.outputs.should_undeploy == 'true'
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -126,7 +126,7 @@ jobs:
- name: Post undeploy success comment
if: steps.check_status.outputs.should_undeploy == 'true'
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
await github.rest.issues.createComment({
@@ -139,7 +139,7 @@ jobs:
- name: Check deployment status on PR close
id: check_pr_close
if: github.event_name == 'pull_request' && github.event.action == 'closed'
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
const comments = await github.rest.issues.listComments({
@@ -168,7 +168,7 @@ jobs:
github.event_name == 'pull_request' &&
github.event.action == 'closed' &&
steps.check_pr_close.outputs.should_undeploy == 'true'
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -187,7 +187,7 @@ jobs:
github.event_name == 'pull_request' &&
github.event.action == 'closed' &&
steps.check_pr_close.outputs.should_undeploy == 'true'
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
await github.rest.issues.createComment({

View File

@@ -31,7 +31,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Check for component changes
uses: dorny/paths-filter@v3
@@ -42,7 +42,7 @@ jobs:
- 'autogpt_platform/frontend/src/components/**'
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
@@ -54,7 +54,7 @@ jobs:
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
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ steps.cache-key.outputs.key }}
@@ -71,10 +71,10 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
@@ -82,7 +82,7 @@ jobs:
run: corepack enable
- name: Restore dependencies cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
@@ -107,12 +107,12 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
@@ -120,7 +120,7 @@ jobs:
run: corepack enable
- name: Restore dependencies cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
@@ -148,12 +148,12 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: recursive
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
@@ -176,7 +176,7 @@ jobs:
uses: docker/setup-buildx-action@v3
- name: Cache Docker layers
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: /tmp/.buildx-cache
key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
@@ -231,7 +231,7 @@ jobs:
fi
- name: Restore dependencies cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
@@ -277,12 +277,12 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: recursive
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
@@ -290,7 +290,7 @@ jobs:
run: corepack enable
- name: Restore dependencies cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}

View File

@@ -29,10 +29,10 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
@@ -44,7 +44,7 @@ jobs:
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
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ steps.cache-key.outputs.key }}
@@ -56,19 +56,19 @@ jobs:
run: pnpm install --frozen-lockfile
types:
runs-on: big-boi
runs-on: ubuntu-latest
needs: setup
strategy:
fail-fast: false
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: recursive
- name: Set up Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
@@ -85,10 +85,10 @@ jobs:
- name: Run docker compose
run: |
docker compose -f ../docker-compose.yml --profile local up -d deps_backend
docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
- name: Restore dependencies cache
uses: actions/cache@v5
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}

View File

@@ -11,7 +11,7 @@ jobs:
steps:
# - name: Wait some time for all actions to start
# run: sleep 30
- uses: actions/checkout@v6
- uses: actions/checkout@v4
# with:
# fetch-depth: 0
- name: Set up Python

View File

@@ -99,101 +99,84 @@ files = [
[[package]]
name = "cffi"
version = "2.0.0"
version = "1.17.1"
description = "Foreign Function Interface for Python calling C code."
optional = false
python-versions = ">=3.9"
python-versions = ">=3.8"
groups = ["main"]
markers = "platform_python_implementation != \"PyPy\""
files = [
{file = "cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44"},
{file = "cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49"},
{file = "cffi-2.0.0-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:53f77cbe57044e88bbd5ed26ac1d0514d2acf0591dd6bb02a3ae37f76811b80c"},
{file = "cffi-2.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3e837e369566884707ddaf85fc1744b47575005c0a229de3327f8f9a20f4efeb"},
{file = "cffi-2.0.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5eda85d6d1879e692d546a078b44251cdd08dd1cfb98dfb77b670c97cee49ea0"},
{file = "cffi-2.0.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9332088d75dc3241c702d852d4671613136d90fa6881da7d770a483fd05248b4"},
{file = "cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fc7de24befaeae77ba923797c7c87834c73648a05a4bde34b3b7e5588973a453"},
{file = "cffi-2.0.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cf364028c016c03078a23b503f02058f1814320a56ad535686f90565636a9495"},
{file = "cffi-2.0.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e11e82b744887154b182fd3e7e8512418446501191994dbf9c9fc1f32cc8efd5"},
{file = "cffi-2.0.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8ea985900c5c95ce9db1745f7933eeef5d314f0565b27625d9a10ec9881e1bfb"},
{file = "cffi-2.0.0-cp310-cp310-win32.whl", hash = "sha256:1f72fb8906754ac8a2cc3f9f5aaa298070652a0ffae577e0ea9bd480dc3c931a"},
{file = "cffi-2.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:b18a3ed7d5b3bd8d9ef7a8cb226502c6bf8308df1525e1cc676c3680e7176739"},
{file = "cffi-2.0.0-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:b4c854ef3adc177950a8dfc81a86f5115d2abd545751a304c5bcf2c2c7283cfe"},
{file = "cffi-2.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2de9a304e27f7596cd03d16f1b7c72219bd944e99cc52b84d0145aefb07cbd3c"},
{file = "cffi-2.0.0-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:baf5215e0ab74c16e2dd324e8ec067ef59e41125d3eade2b863d294fd5035c92"},
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[[package]]
@@ -2911,4 +2863,4 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<4.0"
content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"
content-hash = "5f15a9c9381c9a374f3d18e087c23b1f1ba8cce192d6f67463a3e3a7a18fee44"

View File

@@ -9,7 +9,7 @@ packages = [{ include = "autogpt_libs" }]
[tool.poetry.dependencies]
python = ">=3.10,<4.0"
colorama = "^0.4.6"
cryptography = "^46.0"
cryptography = "^45.0"
expiringdict = "^1.2.2"
fastapi = "^0.128.0"
google-cloud-logging = "^3.13.0"
@@ -22,12 +22,12 @@ supabase = "^2.27.2"
uvicorn = "^0.40.0"
[tool.poetry.group.dev.dependencies]
pyright = "^1.1.408"
pyright = "^1.1.404"
pytest = "^8.4.1"
pytest-asyncio = "^1.3.0"
pytest-mock = "^3.15.1"
pytest-cov = "^7.0.0"
ruff = "^0.15.0"
pytest-asyncio = "^1.1.0"
pytest-mock = "^3.14.1"
pytest-cov = "^6.2.1"
ruff = "^0.12.11"
[build-system]
requires = ["poetry-core"]

View File

@@ -93,12 +93,6 @@ class ChatConfig(BaseSettings):
description="Name of the prompt in Langfuse to fetch",
)
# Extended thinking configuration for Claude models
thinking_enabled: bool = Field(
default=True,
description="Enable adaptive thinking for Claude models via OpenRouter",
)
@field_validator("api_key", mode="before")
@classmethod
def get_api_key(cls, v):

View File

@@ -45,7 +45,10 @@ async def create_chat_session(
successfulAgentRuns=SafeJson({}),
successfulAgentSchedules=SafeJson({}),
)
return await PrismaChatSession.prisma().create(data=data)
return await PrismaChatSession.prisma().create(
data=data,
include={"Messages": True},
)
async def update_chat_session(

View File

@@ -18,10 +18,6 @@ class ResponseType(str, Enum):
START = "start"
FINISH = "finish"
# Step lifecycle (one LLM API call within a message)
START_STEP = "start-step"
FINISH_STEP = "finish-step"
# Text streaming
TEXT_START = "text-start"
TEXT_DELTA = "text-delta"
@@ -61,16 +57,6 @@ class StreamStart(StreamBaseResponse):
description="Task ID for SSE reconnection. Clients can reconnect using GET /tasks/{taskId}/stream",
)
def to_sse(self) -> str:
"""Convert to SSE format, excluding non-protocol fields like taskId."""
import json
data: dict[str, Any] = {
"type": self.type.value,
"messageId": self.messageId,
}
return f"data: {json.dumps(data)}\n\n"
class StreamFinish(StreamBaseResponse):
"""End of message/stream."""
@@ -78,26 +64,6 @@ class StreamFinish(StreamBaseResponse):
type: ResponseType = ResponseType.FINISH
class StreamStartStep(StreamBaseResponse):
"""Start of a step (one LLM API call within a message).
The AI SDK uses this to add a step-start boundary to message.parts,
enabling visual separation between multiple LLM calls in a single message.
"""
type: ResponseType = ResponseType.START_STEP
class StreamFinishStep(StreamBaseResponse):
"""End of a step (one LLM API call within a message).
The AI SDK uses this to reset activeTextParts and activeReasoningParts,
so the next LLM call in a tool-call continuation starts with clean state.
"""
type: ResponseType = ResponseType.FINISH_STEP
# ========== Text Streaming ==========
@@ -151,7 +117,7 @@ class StreamToolOutputAvailable(StreamBaseResponse):
type: ResponseType = ResponseType.TOOL_OUTPUT_AVAILABLE
toolCallId: str = Field(..., description="Tool call ID this responds to")
output: str | dict[str, Any] = Field(..., description="Tool execution output")
# Keep these for internal backend use
# Additional fields for internal use (not part of AI SDK spec but useful)
toolName: str | None = Field(
default=None, description="Name of the tool that was executed"
)
@@ -159,17 +125,6 @@ class StreamToolOutputAvailable(StreamBaseResponse):
default=True, description="Whether the tool execution succeeded"
)
def to_sse(self) -> str:
"""Convert to SSE format, excluding non-spec fields."""
import json
data = {
"type": self.type.value,
"toolCallId": self.toolCallId,
"output": self.output,
}
return f"data: {json.dumps(data)}\n\n"
# ========== Other ==========

View File

@@ -1,48 +1,29 @@
"""Chat API routes for chat session management and streaming via SSE."""
import logging
import uuid as uuid_module
from collections.abc import AsyncGenerator
from typing import Annotated
from autogpt_libs import auth
from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
from fastapi import APIRouter, Depends, Query, Security
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
from backend.util.exceptions import NotFoundError
from . import service as chat_service
from . import stream_registry
from .completion_handler import process_operation_failure, process_operation_success
from .config import ChatConfig
from .model import ChatSession, create_chat_session, get_chat_session, get_user_sessions
from .response_model import StreamFinish, StreamHeartbeat
from .tools.models import (
AgentDetailsResponse,
AgentOutputResponse,
AgentPreviewResponse,
AgentSavedResponse,
AgentsFoundResponse,
BlockListResponse,
BlockOutputResponse,
ClarificationNeededResponse,
DocPageResponse,
DocSearchResultsResponse,
ErrorResponse,
ExecutionStartedResponse,
InputValidationErrorResponse,
NeedLoginResponse,
NoResultsResponse,
OperationInProgressResponse,
OperationPendingResponse,
OperationStartedResponse,
SetupRequirementsResponse,
UnderstandingUpdatedResponse,
)
config = ChatConfig()
SSE_RESPONSE_HEADERS = {
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"x-vercel-ai-ui-message-stream": "v1",
}
logger = logging.getLogger(__name__)
@@ -58,6 +39,48 @@ async def _validate_and_get_session(
return session
async def _create_stream_generator(
session_id: str,
message: str,
user_id: str | None,
session: ChatSession,
is_user_message: bool = True,
context: dict[str, str] | None = None,
) -> AsyncGenerator[str, None]:
"""Create SSE event generator for chat streaming."""
chunk_count = 0
first_chunk_type: str | None = None
async for chunk in chat_service.stream_chat_completion(
session_id,
message,
is_user_message=is_user_message,
user_id=user_id,
session=session,
context=context,
):
if chunk_count < 3:
logger.info(
"Chat stream chunk",
extra={
"session_id": session_id,
"chunk_type": str(chunk.type),
},
)
if not first_chunk_type:
first_chunk_type = str(chunk.type)
chunk_count += 1
yield chunk.to_sse()
logger.info(
"Chat stream completed",
extra={
"session_id": session_id,
"chunk_count": chunk_count,
"first_chunk_type": first_chunk_type,
},
)
yield "data: [DONE]\n\n"
router = APIRouter(
tags=["chat"],
)
@@ -81,15 +104,6 @@ class CreateSessionResponse(BaseModel):
user_id: str | None
class ActiveStreamInfo(BaseModel):
"""Information about an active stream for reconnection."""
task_id: str
last_message_id: str # Redis Stream message ID for resumption
operation_id: str # Operation ID for completion tracking
tool_name: str # Name of the tool being executed
class SessionDetailResponse(BaseModel):
"""Response model providing complete details for a chat session, including messages."""
@@ -98,7 +112,6 @@ class SessionDetailResponse(BaseModel):
updated_at: str
user_id: str | None
messages: list[dict]
active_stream: ActiveStreamInfo | None = None # Present if stream is still active
class SessionSummaryResponse(BaseModel):
@@ -117,14 +130,6 @@ class ListSessionsResponse(BaseModel):
total: int
class OperationCompleteRequest(BaseModel):
"""Request model for external completion webhook."""
success: bool
result: dict | str | None = None
error: str | None = None
# ========== Routes ==========
@@ -210,14 +215,13 @@ async def get_session(
Retrieve the details of a specific chat session.
Looks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.
If there's an active stream for this session, returns the task_id for reconnection.
Args:
session_id: The unique identifier for the desired chat session.
user_id: The optional authenticated user ID, or None for anonymous access.
Returns:
SessionDetailResponse: Details for the requested session, including active_stream info if applicable.
SessionDetailResponse: Details for the requested session, or None if not found.
"""
session = await get_chat_session(session_id, user_id)
@@ -225,28 +229,11 @@ async def get_session(
raise NotFoundError(f"Session {session_id} not found.")
messages = [message.model_dump() for message in session.messages]
# Check if there's an active stream for this session
active_stream_info = None
active_task, last_message_id = await stream_registry.get_active_task_for_session(
session_id, user_id
logger.info(
f"Returning session {session_id}: "
f"message_count={len(messages)}, "
f"roles={[m.get('role') for m in messages]}"
)
if active_task:
# Filter out the in-progress assistant message from the session response.
# The client will receive the complete assistant response through the SSE
# stream replay instead, preventing duplicate content.
if messages and messages[-1].get("role") == "assistant":
messages = messages[:-1]
# Use "0-0" as last_message_id to replay the stream from the beginning.
# Since we filtered out the cached assistant message, the client needs
# the full stream to reconstruct the response.
active_stream_info = ActiveStreamInfo(
task_id=active_task.task_id,
last_message_id="0-0",
operation_id=active_task.operation_id,
tool_name=active_task.tool_name,
)
return SessionDetailResponse(
id=session.session_id,
@@ -254,7 +241,6 @@ async def get_session(
updated_at=session.updated_at.isoformat(),
user_id=session.user_id or None,
messages=messages,
active_stream=active_stream_info,
)
@@ -274,374 +260,68 @@ async def stream_chat_post(
- Tool call UI elements (if invoked)
- Tool execution results
The AI generation runs in a background task that continues even if the client disconnects.
All chunks are written to Redis for reconnection support. If the client disconnects,
they can reconnect using GET /tasks/{task_id}/stream to resume from where they left off.
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: Optional authenticated user ID.
Returns:
StreamingResponse: SSE-formatted response chunks. First chunk is a "start" event
containing the task_id for reconnection.
StreamingResponse: SSE-formatted response chunks.
"""
import asyncio
import time
stream_start_time = time.perf_counter()
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}, "
f"user={user_id}, message_len={len(request.message)}",
extra={"json_fields": log_meta},
)
session = await _validate_and_get_session(session_id, user_id)
logger.info(
f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - stream_start_time) * 1000,
}
},
)
# Create a task in the stream registry for reconnection support
task_id = str(uuid_module.uuid4())
operation_id = str(uuid_module.uuid4())
log_meta["task_id"] = task_id
task_create_start = time.perf_counter()
await stream_registry.create_task(
task_id=task_id,
session_id=session_id,
user_id=user_id,
tool_call_id="chat_stream", # Not a tool call, but needed for the model
tool_name="chat",
operation_id=operation_id,
)
logger.info(
f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - task_create_start) * 1000,
}
},
)
# Background task that runs the AI generation independently of SSE connection
async def run_ai_generation():
import time as time_module
gen_start_time = time_module.perf_counter()
logger.info(
f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
extra={"json_fields": log_meta},
)
first_chunk_time, ttfc = None, None
chunk_count = 0
try:
async for chunk in chat_service.stream_chat_completion(
session_id,
request.message,
is_user_message=request.is_user_message,
user_id=user_id,
session=session, # Pass pre-fetched session to avoid double-fetch
context=request.context,
_task_id=task_id, # Pass task_id so service emits start with taskId for reconnection
):
chunk_count += 1
if first_chunk_time is None:
first_chunk_time = time_module.perf_counter()
ttfc = first_chunk_time - gen_start_time
logger.info(
f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"chunk_type": type(chunk).__name__,
"time_to_first_chunk_ms": ttfc * 1000,
}
},
)
# Write to Redis (subscribers will receive via XREAD)
await stream_registry.publish_chunk(task_id, chunk)
gen_end_time = time_module.perf_counter()
total_time = (gen_end_time - gen_start_time) * 1000
logger.info(
f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
f"task={task_id}, session={session_id}, "
f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"time_to_first_chunk_ms": (
ttfc * 1000 if ttfc is not None else None
),
"n_chunks": chunk_count,
}
},
)
await stream_registry.mark_task_completed(task_id, "completed")
except Exception as e:
elapsed = time_module.perf_counter() - gen_start_time
logger.error(
f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed * 1000,
"error": str(e),
}
},
)
await stream_registry.mark_task_completed(task_id, "failed")
# Start the AI generation in a background task
bg_task = asyncio.create_task(run_ai_generation())
await stream_registry.set_task_asyncio_task(task_id, bg_task)
setup_time = (time.perf_counter() - stream_start_time) * 1000
logger.info(
f"[TIMING] Background task started, setup={setup_time:.1f}ms",
extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
)
# SSE endpoint that subscribes to the task's stream
async def event_generator() -> AsyncGenerator[str, None]:
import time as time_module
event_gen_start = time_module.perf_counter()
logger.info(
f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
f"user={user_id}",
extra={"json_fields": log_meta},
)
subscriber_queue = None
first_chunk_yielded = False
chunks_yielded = 0
try:
# Subscribe to the task stream (this replays existing messages + live updates)
subscriber_queue = await stream_registry.subscribe_to_task(
task_id=task_id,
user_id=user_id,
last_message_id="0-0", # Get all messages from the beginning
)
if subscriber_queue is None:
yield StreamFinish().to_sse()
yield "data: [DONE]\n\n"
return
# Read from the subscriber queue and yield to SSE
logger.info(
"[TIMING] Starting to read from subscriber_queue",
extra={"json_fields": log_meta},
)
while True:
try:
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
chunks_yielded += 1
if not first_chunk_yielded:
first_chunk_yielded = True
elapsed = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
f"type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"chunk_type": type(chunk).__name__,
"elapsed_ms": elapsed * 1000,
}
},
)
yield chunk.to_sse()
# Check for finish signal
if isinstance(chunk, StreamFinish):
total_time = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] StreamFinish received in {total_time:.2f}s; "
f"n_chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"chunks_yielded": chunks_yielded,
"total_time_ms": total_time * 1000,
}
},
)
break
except asyncio.TimeoutError:
yield StreamHeartbeat().to_sse()
except GeneratorExit:
logger.info(
f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"chunks_yielded": chunks_yielded,
"reason": "client_disconnect",
}
},
)
pass # Client disconnected - background task continues
except Exception as e:
elapsed = (time_module.perf_counter() - event_gen_start) * 1000
logger.error(
f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
extra={
"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
},
)
finally:
# Unsubscribe when client disconnects or stream ends to prevent resource leak
if subscriber_queue is not None:
try:
await stream_registry.unsubscribe_from_task(
task_id, subscriber_queue
)
except Exception as unsub_err:
logger.error(
f"Error unsubscribing from task {task_id}: {unsub_err}",
exc_info=True,
)
# AI SDK protocol termination - always yield even if unsubscribe fails
total_time = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time * 1000,
"chunks_yielded": chunks_yielded,
}
},
)
yield "data: [DONE]\n\n"
return StreamingResponse(
event_generator(),
_create_stream_generator(
session_id=session_id,
message=request.message,
user_id=user_id,
session=session,
is_user_message=request.is_user_message,
context=request.context,
),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no", # Disable nginx buffering
"x-vercel-ai-ui-message-stream": "v1", # AI SDK protocol header
},
headers=SSE_RESPONSE_HEADERS,
)
@router.get(
"/sessions/{session_id}/stream",
)
async def resume_session_stream(
async def stream_chat_get(
session_id: str,
message: Annotated[str, Query(min_length=1, max_length=10000)],
user_id: str | None = Depends(auth.get_user_id),
is_user_message: bool = Query(default=True),
):
"""
Resume an active stream for a session.
Stream chat responses for a session (GET - legacy endpoint).
Called by the AI SDK's ``useChat(resume: true)`` on page load.
Checks for an active (in-progress) task on the session and either replays
the full SSE stream or returns 204 No Content if nothing is running.
Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
- Text fragments as they are generated
- Tool call UI elements (if invoked)
- Tool execution results
Args:
session_id: The chat session identifier.
session_id: The chat session identifier to associate with the streamed messages.
message: The user's new message to process.
user_id: Optional authenticated user ID.
is_user_message: Whether the message is a user message.
Returns:
StreamingResponse (SSE) when an active stream exists,
or 204 No Content when there is nothing to resume.
StreamingResponse: SSE-formatted response chunks.
"""
import asyncio
active_task, _last_id = await stream_registry.get_active_task_for_session(
session_id, user_id
)
if not active_task:
return Response(status_code=204)
subscriber_queue = await stream_registry.subscribe_to_task(
task_id=active_task.task_id,
user_id=user_id,
last_message_id="0-0", # Full replay so useChat rebuilds the message
)
if subscriber_queue is None:
return Response(status_code=204)
async def event_generator() -> AsyncGenerator[str, None]:
chunk_count = 0
first_chunk_type: str | None = None
try:
while True:
try:
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
if chunk_count < 3:
logger.info(
"Resume stream chunk",
extra={
"session_id": session_id,
"chunk_type": str(chunk.type),
},
)
if not first_chunk_type:
first_chunk_type = str(chunk.type)
chunk_count += 1
yield chunk.to_sse()
if isinstance(chunk, StreamFinish):
break
except asyncio.TimeoutError:
yield StreamHeartbeat().to_sse()
except GeneratorExit:
pass
except Exception as e:
logger.error(f"Error in resume stream for session {session_id}: {e}")
finally:
try:
await stream_registry.unsubscribe_from_task(
active_task.task_id, subscriber_queue
)
except Exception as unsub_err:
logger.error(
f"Error unsubscribing from task {active_task.task_id}: {unsub_err}",
exc_info=True,
)
logger.info(
"Resume stream completed",
extra={
"session_id": session_id,
"n_chunks": chunk_count,
"first_chunk_type": first_chunk_type,
},
)
yield "data: [DONE]\n\n"
session = await _validate_and_get_session(session_id, user_id)
return StreamingResponse(
event_generator(),
_create_stream_generator(
session_id=session_id,
message=message,
user_id=user_id,
session=session,
is_user_message=is_user_message,
),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"x-vercel-ai-ui-message-stream": "v1",
},
headers=SSE_RESPONSE_HEADERS,
)
@@ -671,251 +351,6 @@ async def session_assign_user(
return {"status": "ok"}
# ========== Task Streaming (SSE Reconnection) ==========
@router.get(
"/tasks/{task_id}/stream",
)
async def stream_task(
task_id: str,
user_id: str | None = Depends(auth.get_user_id),
last_message_id: str = Query(
default="0-0",
description="Last Redis Stream message ID received (e.g., '1706540123456-0'). Use '0-0' for full replay.",
),
):
"""
Reconnect to a long-running task's SSE stream.
When a long-running operation (like agent generation) starts, the client
receives a task_id. If the connection drops, the client can reconnect
using this endpoint to resume receiving updates.
Args:
task_id: The task ID from the operation_started response.
user_id: Authenticated user ID for ownership validation.
last_message_id: Last Redis Stream message ID received ("0-0" for full replay).
Returns:
StreamingResponse: SSE-formatted response chunks starting after last_message_id.
Raises:
HTTPException: 404 if task not found, 410 if task expired, 403 if access denied.
"""
# Check task existence and expiry before subscribing
task, error_code = await stream_registry.get_task_with_expiry_info(task_id)
if error_code == "TASK_EXPIRED":
raise HTTPException(
status_code=410,
detail={
"code": "TASK_EXPIRED",
"message": "This operation has expired. Please try again.",
},
)
if error_code == "TASK_NOT_FOUND":
raise HTTPException(
status_code=404,
detail={
"code": "TASK_NOT_FOUND",
"message": f"Task {task_id} not found.",
},
)
# Validate ownership if task has an owner
if task and task.user_id and user_id != task.user_id:
raise HTTPException(
status_code=403,
detail={
"code": "ACCESS_DENIED",
"message": "You do not have access to this task.",
},
)
# Get subscriber queue from stream registry
subscriber_queue = await stream_registry.subscribe_to_task(
task_id=task_id,
user_id=user_id,
last_message_id=last_message_id,
)
if subscriber_queue is None:
raise HTTPException(
status_code=404,
detail={
"code": "TASK_NOT_FOUND",
"message": f"Task {task_id} not found or access denied.",
},
)
async def event_generator() -> AsyncGenerator[str, None]:
import asyncio
heartbeat_interval = 15.0 # Send heartbeat every 15 seconds
try:
while True:
try:
# Wait for next chunk with timeout for heartbeats
chunk = await asyncio.wait_for(
subscriber_queue.get(), timeout=heartbeat_interval
)
yield chunk.to_sse()
# Check for finish signal
if isinstance(chunk, StreamFinish):
break
except asyncio.TimeoutError:
# Send heartbeat to keep connection alive
yield StreamHeartbeat().to_sse()
except Exception as e:
logger.error(f"Error in task stream {task_id}: {e}", exc_info=True)
finally:
# Unsubscribe when client disconnects or stream ends
try:
await stream_registry.unsubscribe_from_task(task_id, subscriber_queue)
except Exception as unsub_err:
logger.error(
f"Error unsubscribing from task {task_id}: {unsub_err}",
exc_info=True,
)
# AI SDK protocol termination - always yield even if unsubscribe fails
yield "data: [DONE]\n\n"
return StreamingResponse(
event_generator(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"x-vercel-ai-ui-message-stream": "v1",
},
)
@router.get(
"/tasks/{task_id}",
)
async def get_task_status(
task_id: str,
user_id: str | None = Depends(auth.get_user_id),
) -> dict:
"""
Get the status of a long-running task.
Args:
task_id: The task ID to check.
user_id: Authenticated user ID for ownership validation.
Returns:
dict: Task status including task_id, status, tool_name, and operation_id.
Raises:
NotFoundError: If task_id is not found or user doesn't have access.
"""
task = await stream_registry.get_task(task_id)
if task is None:
raise NotFoundError(f"Task {task_id} not found.")
# Validate ownership - if task has an owner, requester must match
if task.user_id and user_id != task.user_id:
raise NotFoundError(f"Task {task_id} not found.")
return {
"task_id": task.task_id,
"session_id": task.session_id,
"status": task.status,
"tool_name": task.tool_name,
"operation_id": task.operation_id,
"created_at": task.created_at.isoformat(),
}
# ========== External Completion Webhook ==========
@router.post(
"/operations/{operation_id}/complete",
status_code=200,
)
async def complete_operation(
operation_id: str,
request: OperationCompleteRequest,
x_api_key: str | None = Header(default=None),
) -> dict:
"""
External completion webhook for long-running operations.
Called by Agent Generator (or other services) when an operation completes.
This triggers the stream registry to publish completion and continue LLM generation.
Args:
operation_id: The operation ID to complete.
request: Completion payload with success status and result/error.
x_api_key: Internal API key for authentication.
Returns:
dict: Status of the completion.
Raises:
HTTPException: If API key is invalid or operation not found.
"""
# Validate internal API key - reject if not configured or invalid
if not config.internal_api_key:
logger.error(
"Operation complete webhook rejected: CHAT_INTERNAL_API_KEY not configured"
)
raise HTTPException(
status_code=503,
detail="Webhook not available: internal API key not configured",
)
if x_api_key != config.internal_api_key:
raise HTTPException(status_code=401, detail="Invalid API key")
# Find task by operation_id
task = await stream_registry.find_task_by_operation_id(operation_id)
if task is None:
raise HTTPException(
status_code=404,
detail=f"Operation {operation_id} not found",
)
logger.info(
f"Received completion webhook for operation {operation_id} "
f"(task_id={task.task_id}, success={request.success})"
)
if request.success:
await process_operation_success(task, request.result)
else:
await process_operation_failure(task, request.error)
return {"status": "ok", "task_id": task.task_id}
# ========== Configuration ==========
@router.get("/config/ttl", status_code=200)
async def get_ttl_config() -> dict:
"""
Get the stream TTL configuration.
Returns the Time-To-Live settings for chat streams, which determines
how long clients can reconnect to an active stream.
Returns:
dict: TTL configuration with seconds and milliseconds values.
"""
return {
"stream_ttl_seconds": config.stream_ttl,
"stream_ttl_ms": config.stream_ttl * 1000,
}
# ========== Health Check ==========
@@ -952,42 +387,3 @@ async def health_check() -> dict:
"service": "chat",
"version": "0.1.0",
}
# ========== Schema Export (for OpenAPI / Orval codegen) ==========
ToolResponseUnion = (
AgentsFoundResponse
| NoResultsResponse
| AgentDetailsResponse
| SetupRequirementsResponse
| ExecutionStartedResponse
| NeedLoginResponse
| ErrorResponse
| InputValidationErrorResponse
| AgentOutputResponse
| UnderstandingUpdatedResponse
| AgentPreviewResponse
| AgentSavedResponse
| ClarificationNeededResponse
| BlockListResponse
| BlockOutputResponse
| DocSearchResultsResponse
| DocPageResponse
| OperationStartedResponse
| OperationPendingResponse
| OperationInProgressResponse
)
@router.get(
"/schema/tool-responses",
response_model=ToolResponseUnion,
include_in_schema=True,
summary="[Dummy] Tool response type export for codegen",
description="This endpoint is not meant to be called. It exists solely to "
"expose tool response models in the OpenAPI schema for frontend codegen.",
)
async def _tool_response_schema() -> ToolResponseUnion: # type: ignore[return]
"""Never called at runtime. Exists only so Orval generates TS types."""
raise HTTPException(status_code=501, detail="Schema-only endpoint")

View File

@@ -52,10 +52,8 @@ from .response_model import (
StreamBaseResponse,
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
StreamTextDelta,
StreamTextEnd,
StreamTextStart,
@@ -353,10 +351,6 @@ async def stream_chat_completion(
retry_count: int = 0,
session: ChatSession | None = None,
context: dict[str, str] | None = None, # {url: str, content: str}
_continuation_message_id: (
str | None
) = None, # Internal: reuse message ID for tool call continuations
_task_id: str | None = None, # Internal: task ID for SSE reconnection support
) -> AsyncGenerator[StreamBaseResponse, None]:
"""Main entry point for streaming chat completions with database handling.
@@ -377,45 +371,21 @@ async def stream_chat_completion(
ValueError: If max_context_messages is exceeded
"""
completion_start = time.monotonic()
# Build log metadata for structured logging
log_meta = {"component": "ChatService", "session_id": session_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
f"message_len={len(message) if message else 0}, is_user={is_user_message}",
extra={
"json_fields": {
**log_meta,
"message_len": len(message) if message else 0,
"is_user_message": is_user_message,
}
},
f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
)
# Only fetch from Redis if session not provided (initial call)
if session is None:
fetch_start = time.monotonic()
session = await get_chat_session(session_id, user_id)
fetch_time = (time.monotonic() - fetch_start) * 1000
logger.info(
f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
f"n_messages={len(session.messages) if session else 0}",
extra={
"json_fields": {
**log_meta,
"duration_ms": fetch_time,
"n_messages": len(session.messages) if session else 0,
}
},
f"Fetched session from Redis: {session.session_id if session else 'None'}, "
f"message_count={len(session.messages) if session else 0}"
)
else:
logger.info(
f"[TIMING] Using provided session, messages={len(session.messages)}",
extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
f"Using provided session object: {session.session_id}, "
f"message_count={len(session.messages)}"
)
if not session:
@@ -436,25 +406,17 @@ async def stream_chat_completion(
# Track user message in PostHog
if is_user_message:
posthog_start = time.monotonic()
track_user_message(
user_id=user_id,
session_id=session_id,
message_length=len(message),
)
posthog_time = (time.monotonic() - posthog_start) * 1000
logger.info(
f"[TIMING] track_user_message took {posthog_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
)
upsert_start = time.monotonic()
session = await upsert_chat_session(session)
upsert_time = (time.monotonic() - upsert_start) * 1000
logger.info(
f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
f"Upserting session: {session.session_id} with user id {session.user_id}, "
f"message_count={len(session.messages)}"
)
session = await upsert_chat_session(session)
assert session, "Session not found"
# Generate title for new sessions on first user message (non-blocking)
@@ -492,13 +454,7 @@ async def stream_chat_completion(
asyncio.create_task(_update_title())
# Build system prompt with business understanding
prompt_start = time.monotonic()
system_prompt, understanding = await _build_system_prompt(user_id)
prompt_time = (time.monotonic() - prompt_start) * 1000
logger.info(
f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
)
# Initialize variables for streaming
assistant_response = ChatMessage(
@@ -523,27 +479,13 @@ async def stream_chat_completion(
# Generate unique IDs for AI SDK protocol
import uuid as uuid_module
is_continuation = _continuation_message_id is not None
message_id = _continuation_message_id or str(uuid_module.uuid4())
message_id = str(uuid_module.uuid4())
text_block_id = str(uuid_module.uuid4())
# Only yield message start for the initial call, not for continuations.
setup_time = (time.monotonic() - completion_start) * 1000
logger.info(
f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
)
if not is_continuation:
yield StreamStart(messageId=message_id, taskId=_task_id)
# Emit start-step before each LLM call (AI SDK uses this to add step boundaries)
yield StreamStartStep()
# Yield message start
yield StreamStart(messageId=message_id)
try:
logger.info(
"[TIMING] Calling _stream_chat_chunks",
extra={"json_fields": log_meta},
)
async for chunk in _stream_chat_chunks(
session=session,
tools=tools,
@@ -643,10 +585,6 @@ async def stream_chat_completion(
)
yield chunk
elif isinstance(chunk, StreamFinish):
if has_done_tool_call:
# Tool calls happened — close the step but don't send message-level finish.
# The continuation will open a new step, and finish will come at the end.
yield StreamFinishStep()
if not has_done_tool_call:
# Emit text-end before finish if we received text but haven't closed it
if has_received_text and not text_streaming_ended:
@@ -678,8 +616,6 @@ async def stream_chat_completion(
has_saved_assistant_message = True
has_yielded_end = True
# Emit finish-step before finish (resets AI SDK text/reasoning state)
yield StreamFinishStep()
yield chunk
elif isinstance(chunk, StreamError):
has_yielded_error = True
@@ -729,10 +665,6 @@ async def stream_chat_completion(
logger.info(
f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
)
# Close the current step before retrying so the recursive call's
# StreamStartStep doesn't produce unbalanced step events.
if not has_yielded_end:
yield StreamFinishStep()
should_retry = True
else:
# Non-retryable error or max retries exceeded
@@ -768,7 +700,6 @@ async def stream_chat_completion(
error_response = StreamError(errorText=error_message)
yield error_response
if not has_yielded_end:
yield StreamFinishStep()
yield StreamFinish()
return
@@ -783,8 +714,6 @@ async def stream_chat_completion(
retry_count=retry_count + 1,
session=session,
context=context,
_continuation_message_id=message_id, # Reuse message ID since start was already sent
_task_id=_task_id,
):
yield chunk
return # Exit after retry to avoid double-saving in finally block
@@ -854,8 +783,6 @@ async def stream_chat_completion(
session=session, # Pass session object to avoid Redis refetch
context=context,
tool_call_response=str(tool_response_messages),
_continuation_message_id=message_id, # Reuse message ID to avoid duplicates
_task_id=_task_id,
):
yield chunk
@@ -966,21 +893,9 @@ async def _stream_chat_chunks(
SSE formatted JSON response objects
"""
import time as time_module
stream_chunks_start = time_module.perf_counter()
model = config.model
# Build log metadata for structured logging
log_meta = {"component": "ChatService", "session_id": session.session_id}
if session.user_id:
log_meta["user_id"] = session.user_id
logger.info(
f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
f"user={session.user_id}, n_messages={len(session.messages)}",
extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
)
logger.info("Starting pure chat stream")
messages = session.to_openai_messages()
if system_prompt:
@@ -991,18 +906,12 @@ async def _stream_chat_chunks(
messages = [system_message] + messages
# Apply context window management
context_start = time_module.perf_counter()
context_result = await _manage_context_window(
messages=messages,
model=model,
api_key=config.api_key,
base_url=config.base_url,
)
context_time = (time_module.perf_counter() - context_start) * 1000
logger.info(
f"[TIMING] _manage_context_window took {context_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": context_time}},
)
if context_result.error:
if "System prompt dropped" in context_result.error:
@@ -1037,19 +946,9 @@ async def _stream_chat_chunks(
while retry_count <= MAX_RETRIES:
try:
elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
retry_info = (
f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
)
logger.info(
f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"retry_count": retry_count,
}
},
f"Creating OpenAI chat completion stream..."
f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
)
# Build extra_body for OpenRouter tracing and PostHog analytics
@@ -1066,11 +965,6 @@ async def _stream_chat_chunks(
:128
] # OpenRouter limit
# Enable adaptive thinking for Anthropic models via OpenRouter
if config.thinking_enabled and "anthropic" in model.lower():
extra_body["reasoning"] = {"enabled": True}
api_call_start = time_module.perf_counter()
stream = await client.chat.completions.create(
model=model,
messages=cast(list[ChatCompletionMessageParam], messages),
@@ -1080,11 +974,6 @@ async def _stream_chat_chunks(
stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
extra_body=extra_body,
)
api_init_time = (time_module.perf_counter() - api_call_start) * 1000
logger.info(
f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
)
# Variables to accumulate tool calls
tool_calls: list[dict[str, Any]] = []
@@ -1095,13 +984,10 @@ async def _stream_chat_chunks(
# Track if we've started the text block
text_started = False
first_content_chunk = True
chunk_count = 0
# Process the stream
chunk: ChatCompletionChunk
async for chunk in stream:
chunk_count += 1
if chunk.usage:
yield StreamUsage(
promptTokens=chunk.usage.prompt_tokens,
@@ -1124,23 +1010,6 @@ async def _stream_chat_chunks(
if not text_started and text_block_id:
yield StreamTextStart(id=text_block_id)
text_started = True
# Log timing for first content chunk
if first_content_chunk:
first_content_chunk = False
ttfc = (
time_module.perf_counter() - api_call_start
) * 1000
logger.info(
f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
f"(since API call), n_chunks={chunk_count}",
extra={
"json_fields": {
**log_meta,
"time_to_first_chunk_ms": ttfc,
"n_chunks": chunk_count,
}
},
)
# Stream the text delta
text_response = StreamTextDelta(
id=text_block_id or "",
@@ -1197,21 +1066,7 @@ async def _stream_chat_chunks(
toolName=tool_calls[idx]["function"]["name"],
)
emitted_start_for_idx.add(idx)
stream_duration = time_module.perf_counter() - api_call_start
logger.info(
f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
f"duration={stream_duration:.2f}s, "
f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
extra={
"json_fields": {
**log_meta,
"stream_duration_ms": stream_duration * 1000,
"finish_reason": finish_reason,
"n_chunks": chunk_count,
"n_tool_calls": len(tool_calls),
}
},
)
logger.info(f"Stream complete. Finish reason: {finish_reason}")
# Yield all accumulated tool calls after the stream is complete
# This ensures all tool call arguments have been fully received
@@ -1231,12 +1086,6 @@ async def _stream_chat_chunks(
# Re-raise to trigger retry logic in the parent function
raise
total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
logger.info(
f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
f"session={session.session_id}, user={session.user_id}",
extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
)
yield StreamFinish()
return
except Exception as e:
@@ -1716,7 +1565,6 @@ async def _execute_long_running_tool_with_streaming(
task_id,
StreamError(errorText=str(e)),
)
await stream_registry.publish_chunk(task_id, StreamFinishStep())
await stream_registry.publish_chunk(task_id, StreamFinish())
await _update_pending_operation(
@@ -1833,10 +1681,6 @@ async def _generate_llm_continuation(
if session_id:
extra_body["session_id"] = session_id[:128]
# Enable adaptive thinking for Anthropic models via OpenRouter
if config.thinking_enabled and "anthropic" in config.model.lower():
extra_body["reasoning"] = {"enabled": True}
retry_count = 0
last_error: Exception | None = None
response = None
@@ -1967,10 +1811,6 @@ async def _generate_llm_continuation_with_streaming(
if session_id:
extra_body["session_id"] = session_id[:128]
# Enable adaptive thinking for Anthropic models via OpenRouter
if config.thinking_enabled and "anthropic" in config.model.lower():
extra_body["reasoning"] = {"enabled": True}
# Make streaming LLM call (no tools - just text response)
from typing import cast
@@ -1982,7 +1822,6 @@ async def _generate_llm_continuation_with_streaming(
# Publish start event
await stream_registry.publish_chunk(task_id, StreamStart(messageId=message_id))
await stream_registry.publish_chunk(task_id, StreamStartStep())
await stream_registry.publish_chunk(task_id, StreamTextStart(id=text_block_id))
# Stream the response
@@ -2006,7 +1845,6 @@ async def _generate_llm_continuation_with_streaming(
# Publish end events
await stream_registry.publish_chunk(task_id, StreamTextEnd(id=text_block_id))
await stream_registry.publish_chunk(task_id, StreamFinishStep())
if assistant_content:
# Reload session from DB to avoid race condition with user messages
@@ -2048,5 +1886,4 @@ async def _generate_llm_continuation_with_streaming(
task_id,
StreamError(errorText=f"Failed to generate response: {e}"),
)
await stream_registry.publish_chunk(task_id, StreamFinishStep())
await stream_registry.publish_chunk(task_id, StreamFinish())

View File

@@ -104,24 +104,6 @@ async def create_task(
Returns:
The created ActiveTask instance (metadata only)
"""
import time
start_time = time.perf_counter()
# Build log metadata for structured logging
log_meta = {
"component": "StreamRegistry",
"task_id": task_id,
"session_id": session_id,
}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}",
extra={"json_fields": log_meta},
)
task = ActiveTask(
task_id=task_id,
session_id=session_id,
@@ -132,18 +114,10 @@ async def create_task(
)
# Store metadata in Redis
redis_start = time.perf_counter()
redis = await get_redis_async()
redis_time = (time.perf_counter() - redis_start) * 1000
logger.info(
f"[TIMING] get_redis_async took {redis_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": redis_time}},
)
meta_key = _get_task_meta_key(task_id)
op_key = _get_operation_mapping_key(operation_id)
hset_start = time.perf_counter()
await redis.hset( # type: ignore[misc]
meta_key,
mapping={
@@ -157,22 +131,12 @@ async def create_task(
"created_at": task.created_at.isoformat(),
},
)
hset_time = (time.perf_counter() - hset_start) * 1000
logger.info(
f"[TIMING] redis.hset took {hset_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": hset_time}},
)
await redis.expire(meta_key, config.stream_ttl)
# Create operation_id -> task_id mapping for webhook lookups
await redis.set(op_key, task_id, ex=config.stream_ttl)
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
)
logger.debug(f"Created task {task_id} for session {session_id}")
return task
@@ -192,60 +156,26 @@ async def publish_chunk(
Returns:
The Redis Stream message ID
"""
import time
start_time = time.perf_counter()
chunk_type = type(chunk).__name__
chunk_json = chunk.model_dump_json()
message_id = "0-0"
# Build log metadata
log_meta = {
"component": "StreamRegistry",
"task_id": task_id,
"chunk_type": chunk_type,
}
try:
redis = await get_redis_async()
stream_key = _get_task_stream_key(task_id)
# Write to Redis Stream for persistence and real-time delivery
xadd_start = time.perf_counter()
raw_id = await redis.xadd(
stream_key,
{"data": chunk_json},
maxlen=config.stream_max_length,
)
xadd_time = (time.perf_counter() - xadd_start) * 1000
message_id = raw_id if isinstance(raw_id, str) else raw_id.decode()
# Set TTL on stream to match task metadata TTL
await redis.expire(stream_key, config.stream_ttl)
total_time = (time.perf_counter() - start_time) * 1000
# Only log timing for significant chunks or slow operations
if (
chunk_type
in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd")
or total_time > 50
):
logger.info(
f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"xadd_time_ms": xadd_time,
"message_id": message_id,
}
},
)
except Exception as e:
elapsed = (time.perf_counter() - start_time) * 1000
logger.error(
f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}",
extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
f"Failed to publish chunk for task {task_id}: {e}",
exc_info=True,
)
@@ -270,61 +200,24 @@ async def subscribe_to_task(
An asyncio Queue that will receive stream chunks, or None if task not found
or user doesn't have access
"""
import time
start_time = time.perf_counter()
# Build log metadata
log_meta = {"component": "StreamRegistry", "task_id": task_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}",
extra={"json_fields": {**log_meta, "last_message_id": last_message_id}},
)
redis_start = time.perf_counter()
redis = await get_redis_async()
meta_key = _get_task_meta_key(task_id)
meta: dict[Any, Any] = await redis.hgetall(meta_key) # type: ignore[misc]
hgetall_time = (time.perf_counter() - redis_start) * 1000
logger.info(
f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}},
)
if not meta:
elapsed = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"reason": "task_not_found",
}
},
)
logger.debug(f"Task {task_id} not found in Redis")
return None
# Note: Redis client uses decode_responses=True, so keys are strings
task_status = meta.get("status", "")
task_user_id = meta.get("user_id", "") or None
log_meta["session_id"] = meta.get("session_id", "")
# Validate ownership - if task has an owner, requester must match
if task_user_id:
if user_id != task_user_id:
logger.warning(
f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}",
extra={
"json_fields": {
**log_meta,
"task_owner": task_user_id,
"reason": "access_denied",
}
},
f"User {user_id} denied access to task {task_id} "
f"owned by {task_user_id}"
)
return None
@@ -332,19 +225,7 @@ async def subscribe_to_task(
stream_key = _get_task_stream_key(task_id)
# Step 1: Replay messages from Redis Stream
xread_start = time.perf_counter()
messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
xread_time = (time.perf_counter() - xread_start) * 1000
logger.info(
f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}",
extra={
"json_fields": {
**log_meta,
"duration_ms": xread_time,
"task_status": task_status,
}
},
)
replayed_count = 0
replay_last_id = last_message_id
@@ -363,48 +244,19 @@ async def subscribe_to_task(
except Exception as e:
logger.warning(f"Failed to replay message: {e}")
logger.info(
f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
extra={
"json_fields": {
**log_meta,
"n_messages_replayed": replayed_count,
"replay_last_id": replay_last_id,
}
},
)
logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
# Step 2: If task is still running, start stream listener for live updates
if task_status == "running":
logger.info(
"[TIMING] Task still running, starting _stream_listener",
extra={"json_fields": {**log_meta, "task_status": task_status}},
)
listener_task = asyncio.create_task(
_stream_listener(task_id, subscriber_queue, replay_last_id, log_meta)
_stream_listener(task_id, subscriber_queue, replay_last_id)
)
# Track listener task for cleanup on unsubscribe
_listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
else:
# Task is completed/failed - add finish marker
logger.info(
f"[TIMING] Task already {task_status}, adding StreamFinish",
extra={"json_fields": {**log_meta, "task_status": task_status}},
)
await subscriber_queue.put(StreamFinish())
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
f"n_messages_replayed={replayed_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"n_messages_replayed": replayed_count,
}
},
)
return subscriber_queue
@@ -412,7 +264,6 @@ async def _stream_listener(
task_id: str,
subscriber_queue: asyncio.Queue[StreamBaseResponse],
last_replayed_id: str,
log_meta: dict | None = None,
) -> None:
"""Listen to Redis Stream for new messages using blocking XREAD.
@@ -423,27 +274,10 @@ async def _stream_listener(
task_id: Task ID to listen for
subscriber_queue: Queue to deliver messages to
last_replayed_id: Last message ID from replay (continue from here)
log_meta: Structured logging metadata
"""
import time
start_time = time.perf_counter()
# Use provided log_meta or build minimal one
if log_meta is None:
log_meta = {"component": "StreamRegistry", "task_id": task_id}
logger.info(
f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}",
extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}},
)
queue_id = id(subscriber_queue)
# Track the last successfully delivered message ID for recovery hints
last_delivered_id = last_replayed_id
messages_delivered = 0
first_message_time = None
xread_count = 0
try:
redis = await get_redis_async()
@@ -453,39 +287,9 @@ async def _stream_listener(
while True:
# Block for up to 30 seconds waiting for new messages
# This allows periodic checking if task is still running
xread_start = time.perf_counter()
xread_count += 1
messages = await redis.xread(
{stream_key: current_id}, block=30000, count=100
)
xread_time = (time.perf_counter() - xread_start) * 1000
if messages:
msg_count = sum(len(msgs) for _, msgs in messages)
logger.info(
f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms",
extra={
"json_fields": {
**log_meta,
"xread_count": xread_count,
"n_messages": msg_count,
"duration_ms": xread_time,
}
},
)
elif xread_time > 1000:
# Only log timeouts (30s blocking)
logger.info(
f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms",
extra={
"json_fields": {
**log_meta,
"xread_count": xread_count,
"duration_ms": xread_time,
"reason": "timeout",
}
},
)
if not messages:
# Timeout - check if task is still running
@@ -522,30 +326,10 @@ async def _stream_listener(
)
# Update last delivered ID on successful delivery
last_delivered_id = current_id
messages_delivered += 1
if first_message_time is None:
first_message_time = time.perf_counter()
elapsed = (first_message_time - start_time) * 1000
logger.info(
f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"chunk_type": type(chunk).__name__,
}
},
)
except asyncio.TimeoutError:
logger.warning(
f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
extra={
"json_fields": {
**log_meta,
"timeout_s": QUEUE_PUT_TIMEOUT,
"reason": "queue_full",
}
},
f"Subscriber queue full for task {task_id}, "
f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
)
# Send overflow error with recovery info
try:
@@ -567,44 +351,15 @@ async def _stream_listener(
# Stop listening on finish
if isinstance(chunk, StreamFinish):
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"messages_delivered": messages_delivered,
}
},
)
return
except Exception as e:
logger.warning(
f"Error processing stream message: {e}",
extra={"json_fields": {**log_meta, "error": str(e)}},
)
logger.warning(f"Error processing stream message: {e}")
except asyncio.CancelledError:
elapsed = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"messages_delivered": messages_delivered,
"reason": "cancelled",
}
},
)
logger.debug(f"Stream listener cancelled for task {task_id}")
raise # Re-raise to propagate cancellation
except Exception as e:
elapsed = (time.perf_counter() - start_time) * 1000
logger.error(
f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}",
extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
)
logger.error(f"Stream listener error for task {task_id}: {e}")
# On error, send finish to unblock subscriber
try:
await asyncio.wait_for(
@@ -613,24 +368,10 @@ async def _stream_listener(
)
except (asyncio.TimeoutError, asyncio.QueueFull):
logger.warning(
"Could not deliver finish event after error",
extra={"json_fields": log_meta},
f"Could not deliver finish event for task {task_id} after error"
)
finally:
# Clean up listener task mapping on exit
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
f"delivered={messages_delivered}, xread_count={xread_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"messages_delivered": messages_delivered,
"xread_count": xread_count,
}
},
)
_listener_tasks.pop(queue_id, None)
@@ -857,10 +598,8 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
ResponseType,
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
StreamTextDelta,
StreamTextEnd,
StreamTextStart,
@@ -874,8 +613,6 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
type_to_class: dict[str, type[StreamBaseResponse]] = {
ResponseType.START.value: StreamStart,
ResponseType.FINISH.value: StreamFinish,
ResponseType.START_STEP.value: StreamStartStep,
ResponseType.FINISH_STEP.value: StreamFinishStep,
ResponseType.TEXT_START.value: StreamTextStart,
ResponseType.TEXT_DELTA.value: StreamTextDelta,
ResponseType.TEXT_END.value: StreamTextEnd,

View File

@@ -13,32 +13,10 @@ from backend.api.features.chat.tools.models import (
NoResultsResponse,
)
from backend.api.features.store.hybrid_search import unified_hybrid_search
from backend.data.block import BlockType, get_block
from backend.data.block import get_block
logger = logging.getLogger(__name__)
_TARGET_RESULTS = 10
# Over-fetch to compensate for post-hoc filtering of graph-only blocks.
# 40 is 2x current removed; speed of query 10 vs 40 is minimial
_OVERFETCH_PAGE_SIZE = 40
# Block types that only work within graphs and cannot run standalone in CoPilot.
COPILOT_EXCLUDED_BLOCK_TYPES = {
BlockType.INPUT, # Graph interface definition - data enters via chat, not graph inputs
BlockType.OUTPUT, # Graph interface definition - data exits via chat, not graph outputs
BlockType.WEBHOOK, # Wait for external events - would hang forever in CoPilot
BlockType.WEBHOOK_MANUAL, # Same as WEBHOOK
BlockType.NOTE, # Visual annotation only - no runtime behavior
BlockType.HUMAN_IN_THE_LOOP, # Pauses for human approval - CoPilot IS human-in-the-loop
BlockType.AGENT, # AgentExecutorBlock requires execution_context - use run_agent tool
}
# Specific block IDs excluded from CoPilot (STANDARD type but still require graph context)
COPILOT_EXCLUDED_BLOCK_IDS = {
# SmartDecisionMakerBlock - dynamically discovers downstream blocks via graph topology
"3b191d9f-356f-482d-8238-ba04b6d18381",
}
class FindBlockTool(BaseTool):
"""Tool for searching available blocks."""
@@ -110,7 +88,7 @@ class FindBlockTool(BaseTool):
query=query,
content_types=[ContentType.BLOCK],
page=1,
page_size=_OVERFETCH_PAGE_SIZE,
page_size=10,
)
if not results:
@@ -130,90 +108,60 @@ class FindBlockTool(BaseTool):
block = get_block(block_id)
# Skip disabled blocks
if not block or block.disabled:
continue
if block and not block.disabled:
# Get input/output schemas
input_schema = {}
output_schema = {}
try:
input_schema = block.input_schema.jsonschema()
except Exception:
pass
try:
output_schema = block.output_schema.jsonschema()
except Exception:
pass
# Skip blocks excluded from CoPilot (graph-only blocks)
if (
block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
or block.id in COPILOT_EXCLUDED_BLOCK_IDS
):
continue
# Get categories from block instance
categories = []
if hasattr(block, "categories") and block.categories:
categories = [cat.value for cat in block.categories]
# Get input/output schemas
input_schema = {}
output_schema = {}
try:
input_schema = block.input_schema.jsonschema()
except Exception as e:
logger.debug(
"Failed to generate input schema for block %s: %s",
block_id,
e,
)
try:
output_schema = block.output_schema.jsonschema()
except Exception as e:
logger.debug(
"Failed to generate output schema for block %s: %s",
block_id,
e,
)
# Get categories from block instance
categories = []
if hasattr(block, "categories") and block.categories:
categories = [cat.value for cat in block.categories]
# Extract required inputs for easier use
required_inputs: list[BlockInputFieldInfo] = []
if input_schema:
properties = input_schema.get("properties", {})
required_fields = set(input_schema.get("required", []))
# Get credential field names to exclude from required inputs
credentials_fields = set(
block.input_schema.get_credentials_fields().keys()
)
for field_name, field_schema in properties.items():
# Skip credential fields - they're handled separately
if field_name in credentials_fields:
continue
required_inputs.append(
BlockInputFieldInfo(
name=field_name,
type=field_schema.get("type", "string"),
description=field_schema.get("description", ""),
required=field_name in required_fields,
default=field_schema.get("default"),
)
# Extract required inputs for easier use
required_inputs: list[BlockInputFieldInfo] = []
if input_schema:
properties = input_schema.get("properties", {})
required_fields = set(input_schema.get("required", []))
# Get credential field names to exclude from required inputs
credentials_fields = set(
block.input_schema.get_credentials_fields().keys()
)
blocks.append(
BlockInfoSummary(
id=block_id,
name=block.name,
description=block.description or "",
categories=categories,
input_schema=input_schema,
output_schema=output_schema,
required_inputs=required_inputs,
for field_name, field_schema in properties.items():
# Skip credential fields - they're handled separately
if field_name in credentials_fields:
continue
required_inputs.append(
BlockInputFieldInfo(
name=field_name,
type=field_schema.get("type", "string"),
description=field_schema.get("description", ""),
required=field_name in required_fields,
default=field_schema.get("default"),
)
)
blocks.append(
BlockInfoSummary(
id=block_id,
name=block.name,
description=block.description or "",
categories=categories,
input_schema=input_schema,
output_schema=output_schema,
required_inputs=required_inputs,
)
)
)
if len(blocks) >= _TARGET_RESULTS:
break
if blocks and len(blocks) < _TARGET_RESULTS:
logger.debug(
"find_block returned %d/%d results for query '%s' "
"(filtered %d excluded/disabled blocks)",
len(blocks),
_TARGET_RESULTS,
query,
len(results) - len(blocks),
)
if not blocks:
return NoResultsResponse(

View File

@@ -1,139 +0,0 @@
"""Tests for block filtering in FindBlockTool."""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from backend.api.features.chat.tools.find_block import (
COPILOT_EXCLUDED_BLOCK_IDS,
COPILOT_EXCLUDED_BLOCK_TYPES,
FindBlockTool,
)
from backend.api.features.chat.tools.models import BlockListResponse
from backend.data.block import BlockType
from ._test_data import make_session
_TEST_USER_ID = "test-user-find-block"
def make_mock_block(
block_id: str, name: str, block_type: BlockType, disabled: bool = False
):
"""Create a mock block for testing."""
mock = MagicMock()
mock.id = block_id
mock.name = name
mock.description = f"{name} description"
mock.block_type = block_type
mock.disabled = disabled
mock.input_schema = MagicMock()
mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
mock.input_schema.get_credentials_fields.return_value = {}
mock.output_schema = MagicMock()
mock.output_schema.jsonschema.return_value = {}
mock.categories = []
return mock
class TestFindBlockFiltering:
"""Tests for block filtering in FindBlockTool."""
def test_excluded_block_types_contains_expected_types(self):
"""Verify COPILOT_EXCLUDED_BLOCK_TYPES contains all graph-only types."""
assert BlockType.INPUT in COPILOT_EXCLUDED_BLOCK_TYPES
assert BlockType.OUTPUT in COPILOT_EXCLUDED_BLOCK_TYPES
assert BlockType.WEBHOOK in COPILOT_EXCLUDED_BLOCK_TYPES
assert BlockType.WEBHOOK_MANUAL in COPILOT_EXCLUDED_BLOCK_TYPES
assert BlockType.NOTE in COPILOT_EXCLUDED_BLOCK_TYPES
assert BlockType.HUMAN_IN_THE_LOOP in COPILOT_EXCLUDED_BLOCK_TYPES
assert BlockType.AGENT in COPILOT_EXCLUDED_BLOCK_TYPES
def test_excluded_block_ids_contains_smart_decision_maker(self):
"""Verify SmartDecisionMakerBlock is in COPILOT_EXCLUDED_BLOCK_IDS."""
assert "3b191d9f-356f-482d-8238-ba04b6d18381" in COPILOT_EXCLUDED_BLOCK_IDS
@pytest.mark.asyncio(loop_scope="session")
async def test_excluded_block_type_filtered_from_results(self):
"""Verify blocks with excluded BlockTypes are filtered from search results."""
session = make_session(user_id=_TEST_USER_ID)
# Mock search returns an INPUT block (excluded) and a STANDARD block (included)
search_results = [
{"content_id": "input-block-id", "score": 0.9},
{"content_id": "standard-block-id", "score": 0.8},
]
input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
standard_block = make_mock_block(
"standard-block-id", "HTTP Request", BlockType.STANDARD
)
def mock_get_block(block_id):
return {
"input-block-id": input_block,
"standard-block-id": standard_block,
}.get(block_id)
with patch(
"backend.api.features.chat.tools.find_block.unified_hybrid_search",
new_callable=AsyncMock,
return_value=(search_results, 2),
):
with patch(
"backend.api.features.chat.tools.find_block.get_block",
side_effect=mock_get_block,
):
tool = FindBlockTool()
response = await tool._execute(
user_id=_TEST_USER_ID, session=session, query="test"
)
# Should only return the standard block, not the INPUT block
assert isinstance(response, BlockListResponse)
assert len(response.blocks) == 1
assert response.blocks[0].id == "standard-block-id"
@pytest.mark.asyncio(loop_scope="session")
async def test_excluded_block_id_filtered_from_results(self):
"""Verify SmartDecisionMakerBlock is filtered from search results."""
session = make_session(user_id=_TEST_USER_ID)
smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
search_results = [
{"content_id": smart_decision_id, "score": 0.9},
{"content_id": "normal-block-id", "score": 0.8},
]
# SmartDecisionMakerBlock has STANDARD type but is excluded by ID
smart_block = make_mock_block(
smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
)
normal_block = make_mock_block(
"normal-block-id", "Normal Block", BlockType.STANDARD
)
def mock_get_block(block_id):
return {
smart_decision_id: smart_block,
"normal-block-id": normal_block,
}.get(block_id)
with patch(
"backend.api.features.chat.tools.find_block.unified_hybrid_search",
new_callable=AsyncMock,
return_value=(search_results, 2),
):
with patch(
"backend.api.features.chat.tools.find_block.get_block",
side_effect=mock_get_block,
):
tool = FindBlockTool()
response = await tool._execute(
user_id=_TEST_USER_ID, session=session, query="decision"
)
# Should only return normal block, not SmartDecisionMakerBlock
assert isinstance(response, BlockListResponse)
assert len(response.blocks) == 1
assert response.blocks[0].id == "normal-block-id"

View File

@@ -8,11 +8,7 @@ from typing import Any
from pydantic_core import PydanticUndefined
from backend.api.features.chat.model import ChatSession
from backend.api.features.chat.tools.find_block import (
COPILOT_EXCLUDED_BLOCK_IDS,
COPILOT_EXCLUDED_BLOCK_TYPES,
)
from backend.data.block import AnyBlockSchema, get_block
from backend.data.block import get_block
from backend.data.execution import ExecutionContext
from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
from backend.data.workspace import get_or_create_workspace
@@ -81,6 +77,69 @@ class RunBlockTool(BaseTool):
def requires_auth(self) -> bool:
return True
def _resolve_discriminated_credentials(
self,
block: Any,
input_data: dict[str, Any],
) -> dict[str, CredentialsFieldInfo]:
"""Resolve credential requirements, applying discriminator logic where needed."""
credentials_fields_info = block.input_schema.get_credentials_fields_info()
if not credentials_fields_info:
return {}
resolved: dict[str, CredentialsFieldInfo] = {}
for field_name, field_info in credentials_fields_info.items():
effective_field_info = field_info
if field_info.discriminator and field_info.discriminator_mapping:
discriminator_value = input_data.get(field_info.discriminator)
if discriminator_value is None:
field = block.input_schema.model_fields.get(
field_info.discriminator
)
if field and field.default is not PydanticUndefined:
discriminator_value = field.default
if (
discriminator_value
and discriminator_value in field_info.discriminator_mapping
):
effective_field_info = field_info.discriminate(discriminator_value)
logger.debug(
f"Discriminated provider for {field_name}: "
f"{discriminator_value} -> {effective_field_info.provider}"
)
resolved[field_name] = effective_field_info
return resolved
async def _check_block_credentials(
self,
user_id: str,
block: Any,
input_data: dict[str, Any] | None = None,
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Check if user has required credentials for a block.
Args:
user_id: User ID
block: Block to check credentials for
input_data: Input data for the block (used to determine provider via discriminator)
Returns:
tuple[matched_credentials, missing_credentials]
"""
input_data = input_data or {}
requirements = self._resolve_discriminated_credentials(block, input_data)
if not requirements:
return {}, []
return await match_credentials_to_requirements(user_id, requirements)
async def _execute(
self,
user_id: str | None,
@@ -135,24 +194,11 @@ class RunBlockTool(BaseTool):
session_id=session_id,
)
# Check if block is excluded from CoPilot (graph-only blocks)
if (
block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
or block.id in COPILOT_EXCLUDED_BLOCK_IDS
):
return ErrorResponse(
message=(
f"Block '{block.name}' cannot be run directly in CoPilot. "
"This block is designed for use within graphs only."
),
session_id=session_id,
)
logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
creds_manager = IntegrationCredentialsManager()
matched_credentials, missing_credentials = (
await self._resolve_block_credentials(user_id, block, input_data)
matched_credentials, missing_credentials = await self._check_block_credentials(
user_id, block, input_data
)
if missing_credentials:
@@ -281,75 +327,8 @@ class RunBlockTool(BaseTool):
session_id=session_id,
)
async def _resolve_block_credentials(
self,
user_id: str,
block: AnyBlockSchema,
input_data: dict[str, Any] | None = None,
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Resolve credentials for a block by matching user's available credentials.
Args:
user_id: User ID
block: Block to resolve credentials for
input_data: Input data for the block (used to determine provider via discriminator)
Returns:
tuple of (matched_credentials, missing_credentials) - matched credentials
are used for block execution, missing ones indicate setup requirements.
"""
input_data = input_data or {}
requirements = self._resolve_discriminated_credentials(block, input_data)
if not requirements:
return {}, []
return await match_credentials_to_requirements(user_id, requirements)
def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]:
def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
"""Extract non-credential inputs from block schema."""
schema = block.input_schema.jsonschema()
credentials_fields = set(block.input_schema.get_credentials_fields().keys())
return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
def _resolve_discriminated_credentials(
self,
block: AnyBlockSchema,
input_data: dict[str, Any],
) -> dict[str, CredentialsFieldInfo]:
"""Resolve credential requirements, applying discriminator logic where needed."""
credentials_fields_info = block.input_schema.get_credentials_fields_info()
if not credentials_fields_info:
return {}
resolved: dict[str, CredentialsFieldInfo] = {}
for field_name, field_info in credentials_fields_info.items():
effective_field_info = field_info
if field_info.discriminator and field_info.discriminator_mapping:
discriminator_value = input_data.get(field_info.discriminator)
if discriminator_value is None:
field = block.input_schema.model_fields.get(
field_info.discriminator
)
if field and field.default is not PydanticUndefined:
discriminator_value = field.default
if (
discriminator_value
and discriminator_value in field_info.discriminator_mapping
):
effective_field_info = field_info.discriminate(discriminator_value)
# For host-scoped credentials, add the discriminator value
# (e.g., URL) so _credential_is_for_host can match it
effective_field_info.discriminator_values.add(discriminator_value)
logger.debug(
f"Discriminated provider for {field_name}: "
f"{discriminator_value} -> {effective_field_info.provider}"
)
resolved[field_name] = effective_field_info
return resolved

View File

@@ -1,106 +0,0 @@
"""Tests for block execution guards in RunBlockTool."""
from unittest.mock import MagicMock, patch
import pytest
from backend.api.features.chat.tools.models import ErrorResponse
from backend.api.features.chat.tools.run_block import RunBlockTool
from backend.data.block import BlockType
from ._test_data import make_session
_TEST_USER_ID = "test-user-run-block"
def make_mock_block(
block_id: str, name: str, block_type: BlockType, disabled: bool = False
):
"""Create a mock block for testing."""
mock = MagicMock()
mock.id = block_id
mock.name = name
mock.block_type = block_type
mock.disabled = disabled
mock.input_schema = MagicMock()
mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
mock.input_schema.get_credentials_fields_info.return_value = []
return mock
class TestRunBlockFiltering:
"""Tests for block execution guards in RunBlockTool."""
@pytest.mark.asyncio(loop_scope="session")
async def test_excluded_block_type_returns_error(self):
"""Attempting to execute a block with excluded BlockType returns error."""
session = make_session(user_id=_TEST_USER_ID)
input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
with patch(
"backend.api.features.chat.tools.run_block.get_block",
return_value=input_block,
):
tool = RunBlockTool()
response = await tool._execute(
user_id=_TEST_USER_ID,
session=session,
block_id="input-block-id",
input_data={},
)
assert isinstance(response, ErrorResponse)
assert "cannot be run directly in CoPilot" in response.message
assert "designed for use within graphs only" in response.message
@pytest.mark.asyncio(loop_scope="session")
async def test_excluded_block_id_returns_error(self):
"""Attempting to execute SmartDecisionMakerBlock returns error."""
session = make_session(user_id=_TEST_USER_ID)
smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
smart_block = make_mock_block(
smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
)
with patch(
"backend.api.features.chat.tools.run_block.get_block",
return_value=smart_block,
):
tool = RunBlockTool()
response = await tool._execute(
user_id=_TEST_USER_ID,
session=session,
block_id=smart_decision_id,
input_data={},
)
assert isinstance(response, ErrorResponse)
assert "cannot be run directly in CoPilot" in response.message
@pytest.mark.asyncio(loop_scope="session")
async def test_non_excluded_block_passes_guard(self):
"""Non-excluded blocks pass the filtering guard (may fail later for other reasons)."""
session = make_session(user_id=_TEST_USER_ID)
standard_block = make_mock_block(
"standard-id", "HTTP Request", BlockType.STANDARD
)
with patch(
"backend.api.features.chat.tools.run_block.get_block",
return_value=standard_block,
):
tool = RunBlockTool()
response = await tool._execute(
user_id=_TEST_USER_ID,
session=session,
block_id="standard-id",
input_data={},
)
# Should NOT be an ErrorResponse about CoPilot exclusion
# (may be other errors like missing credentials, but not the exclusion guard)
if isinstance(response, ErrorResponse):
assert "cannot be run directly in CoPilot" not in response.message

View File

@@ -8,7 +8,6 @@ from backend.api.features.library import model as library_model
from backend.api.features.store import db as store_db
from backend.data.graph import GraphModel
from backend.data.model import (
Credentials,
CredentialsFieldInfo,
CredentialsMetaInput,
HostScopedCredentials,
@@ -224,14 +223,54 @@ async def get_or_create_library_agent(
return library_agents[0]
async def get_user_credentials(user_id: str) -> list:
"""Get all available credentials for a user."""
creds_manager = IntegrationCredentialsManager()
return await creds_manager.store.get_all_creds(user_id)
def find_matching_credential(
available_creds: list,
field_info: CredentialsFieldInfo,
check_scopes: bool = True,
):
"""Find a credential that matches the required provider, type, and optionally scopes."""
for cred in available_creds:
if cred.provider not in field_info.provider:
continue
if cred.type not in field_info.supported_types:
continue
if check_scopes and not _credential_has_required_scopes(cred, field_info):
continue
return cred
return None
def create_credential_meta_from_match(matching_cred) -> CredentialsMetaInput:
"""Create a CredentialsMetaInput from a matched credential."""
return CredentialsMetaInput(
id=matching_cred.id,
provider=matching_cred.provider, # type: ignore
type=matching_cred.type,
title=matching_cred.title,
)
async def match_credentials_to_requirements(
user_id: str,
requirements: dict[str, CredentialsFieldInfo],
check_scopes: bool = True,
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Match user's credentials against a dictionary of credential requirements.
This is the core matching logic shared by both graph and block credential matching.
Args:
user_id: User ID to fetch credentials for
requirements: Dict mapping field names to CredentialsFieldInfo
check_scopes: Whether to verify OAuth2 scopes match requirements (default True).
Set to False to preserve original run_block behavior which didn't check scopes.
"""
matched: dict[str, CredentialsMetaInput] = {}
missing: list[CredentialsMetaInput] = []
@@ -242,7 +281,9 @@ async def match_credentials_to_requirements(
available_creds = await get_user_credentials(user_id)
for field_name, field_info in requirements.items():
matching_cred = find_matching_credential(available_creds, field_info)
matching_cred = find_matching_credential(
available_creds, field_info, check_scopes=check_scopes
)
if matching_cred:
try:
@@ -279,44 +320,6 @@ async def match_credentials_to_requirements(
return matched, missing
async def get_user_credentials(user_id: str) -> list[Credentials]:
"""Get all available credentials for a user."""
creds_manager = IntegrationCredentialsManager()
return await creds_manager.store.get_all_creds(user_id)
def find_matching_credential(
available_creds: list[Credentials],
field_info: CredentialsFieldInfo,
) -> Credentials | None:
"""Find a credential that matches the required provider, type, scopes, and host."""
for cred in available_creds:
if cred.provider not in field_info.provider:
continue
if cred.type not in field_info.supported_types:
continue
if cred.type == "oauth2" and not _credential_has_required_scopes(
cred, field_info
):
continue
if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info):
continue
return cred
return None
def create_credential_meta_from_match(
matching_cred: Credentials,
) -> CredentialsMetaInput:
"""Create a CredentialsMetaInput from a matched credential."""
return CredentialsMetaInput(
id=matching_cred.id,
provider=matching_cred.provider, # type: ignore
type=matching_cred.type,
title=matching_cred.title,
)
async def match_user_credentials_to_graph(
user_id: str,
graph: GraphModel,
@@ -425,6 +428,8 @@ def _credential_has_required_scopes(
# If no scopes are required, any credential matches
if not requirements.required_scopes:
return True
# Check that credential scopes are a superset of required scopes
return set(credential.scopes).issuperset(requirements.required_scopes)

View File

@@ -8,7 +8,6 @@ Includes BM25 reranking for improved lexical relevance.
import logging
import re
import time
from dataclasses import dataclass
from typing import Any, Literal
@@ -363,11 +362,7 @@ async def unified_hybrid_search(
LIMIT {limit_param} OFFSET {offset_param}
"""
try:
results = await query_raw_with_schema(sql_query, *params)
except Exception as e:
await _log_vector_error_diagnostics(e)
raise
results = await query_raw_with_schema(sql_query, *params)
total = results[0]["total_count"] if results else 0
# Apply BM25 reranking
@@ -691,11 +686,7 @@ async def hybrid_search(
LIMIT {limit_param} OFFSET {offset_param}
"""
try:
results = await query_raw_with_schema(sql_query, *params)
except Exception as e:
await _log_vector_error_diagnostics(e)
raise
results = await query_raw_with_schema(sql_query, *params)
total = results[0]["total_count"] if results else 0
@@ -727,87 +718,6 @@ async def hybrid_search_simple(
return await hybrid_search(query=query, page=page, page_size=page_size)
# ============================================================================
# Diagnostics
# ============================================================================
# Rate limit: only log vector error diagnostics once per this interval
_VECTOR_DIAG_INTERVAL_SECONDS = 60
_last_vector_diag_time: float = 0
async def _log_vector_error_diagnostics(error: Exception) -> None:
"""Log diagnostic info when 'type vector does not exist' error occurs.
Note: Diagnostic queries use query_raw_with_schema which may run on a different
pooled connection than the one that failed. Session-level search_path can differ,
so these diagnostics show cluster-wide state, not necessarily the failed session.
Includes rate limiting to avoid log spam - only logs once per minute.
Caller should re-raise the error after calling this function.
"""
global _last_vector_diag_time
# Check if this is the vector type error
error_str = str(error).lower()
if not (
"type" in error_str and "vector" in error_str and "does not exist" in error_str
):
return
# Rate limit: only log once per interval
now = time.time()
if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS:
return
_last_vector_diag_time = now
try:
diagnostics: dict[str, object] = {}
try:
search_path_result = await query_raw_with_schema("SHOW search_path")
diagnostics["search_path"] = search_path_result
except Exception as e:
diagnostics["search_path"] = f"Error: {e}"
try:
schema_result = await query_raw_with_schema("SELECT current_schema()")
diagnostics["current_schema"] = schema_result
except Exception as e:
diagnostics["current_schema"] = f"Error: {e}"
try:
user_result = await query_raw_with_schema(
"SELECT current_user, session_user, current_database()"
)
diagnostics["user_info"] = user_result
except Exception as e:
diagnostics["user_info"] = f"Error: {e}"
try:
# Check pgvector extension installation (cluster-wide, stable info)
ext_result = await query_raw_with_schema(
"SELECT extname, extversion, nspname as schema "
"FROM pg_extension e "
"JOIN pg_namespace n ON e.extnamespace = n.oid "
"WHERE extname = 'vector'"
)
diagnostics["pgvector_extension"] = ext_result
except Exception as e:
diagnostics["pgvector_extension"] = f"Error: {e}"
logger.error(
f"Vector type error diagnostics:\n"
f" Error: {error}\n"
f" search_path: {diagnostics.get('search_path')}\n"
f" current_schema: {diagnostics.get('current_schema')}\n"
f" user_info: {diagnostics.get('user_info')}\n"
f" pgvector_extension: {diagnostics.get('pgvector_extension')}"
)
except Exception as diag_error:
logger.error(f"Failed to collect vector error diagnostics: {diag_error}")
# Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights
# for existing code that expects the popularity parameter
HybridSearchWeights = StoreAgentSearchWeights

View File

@@ -531,12 +531,12 @@ class LLMResponse(BaseModel):
def convert_openai_tool_fmt_to_anthropic(
openai_tools: list[dict] | None = None,
) -> Iterable[ToolParam] | anthropic.Omit:
) -> Iterable[ToolParam] | anthropic.NotGiven:
"""
Convert OpenAI tool format to Anthropic tool format.
"""
if not openai_tools or len(openai_tools) == 0:
return anthropic.omit
return anthropic.NOT_GIVEN
anthropic_tools = []
for tool in openai_tools:

View File

@@ -1,8 +1,9 @@
import logging
import queue
from collections import defaultdict
from datetime import datetime, timedelta, timezone
from enum import Enum
from multiprocessing import Manager
from queue import Empty
from typing import (
TYPE_CHECKING,
Annotated,
@@ -1199,16 +1200,12 @@ class NodeExecutionEntry(BaseModel):
class ExecutionQueue(Generic[T]):
"""
Thread-safe queue for managing node execution within a single graph execution.
Note: Uses queue.Queue (not multiprocessing.Queue) since all access is from
threads within the same process. If migrating back to ProcessPoolExecutor,
replace with multiprocessing.Manager().Queue() for cross-process safety.
Queue for managing the execution of agents.
This will be shared between different processes
"""
def __init__(self):
# Thread-safe queue (not multiprocessing) — see class docstring
self.queue: queue.Queue[T] = queue.Queue()
self.queue = Manager().Queue()
def add(self, execution: T) -> T:
self.queue.put(execution)
@@ -1223,7 +1220,7 @@ class ExecutionQueue(Generic[T]):
def get_or_none(self) -> T | None:
try:
return self.queue.get_nowait()
except queue.Empty:
except Empty:
return None

View File

@@ -1,58 +0,0 @@
"""Tests for ExecutionQueue thread-safety."""
import queue
import threading
from backend.data.execution import ExecutionQueue
def test_execution_queue_uses_stdlib_queue():
"""Verify ExecutionQueue uses queue.Queue (not multiprocessing)."""
q = ExecutionQueue()
assert isinstance(q.queue, queue.Queue)
def test_basic_operations():
"""Test add, get, empty, and get_or_none."""
q = ExecutionQueue()
assert q.empty() is True
assert q.get_or_none() is None
result = q.add("item1")
assert result == "item1"
assert q.empty() is False
item = q.get()
assert item == "item1"
assert q.empty() is True
def test_thread_safety():
"""Test concurrent access from multiple threads."""
q = ExecutionQueue()
results = []
num_items = 100
def producer():
for i in range(num_items):
q.add(f"item_{i}")
def consumer():
count = 0
while count < num_items:
item = q.get_or_none()
if item is not None:
results.append(item)
count += 1
producer_thread = threading.Thread(target=producer)
consumer_thread = threading.Thread(target=consumer)
producer_thread.start()
consumer_thread.start()
producer_thread.join(timeout=5)
consumer_thread.join(timeout=5)
assert len(results) == num_items

View File

@@ -743,11 +743,6 @@ class GraphModel(Graph, GraphMeta):
# For invalid blocks, we still raise immediately as this is a structural issue
raise ValueError(f"Invalid block {node.block_id} for node #{node.id}")
if block.disabled:
raise ValueError(
f"Block {node.block_id} is disabled and cannot be used in graphs"
)
node_input_mask = (
nodes_input_masks.get(node.id, {}) if nodes_input_masks else {}
)

View File

@@ -1,4 +1,3 @@
import asyncio
import logging
from abc import ABC, abstractmethod
from enum import Enum
@@ -226,10 +225,6 @@ class SyncRabbitMQ(RabbitMQBase):
class AsyncRabbitMQ(RabbitMQBase):
"""Asynchronous RabbitMQ client"""
def __init__(self, config: RabbitMQConfig):
super().__init__(config)
self._reconnect_lock: asyncio.Lock | None = None
@property
def is_connected(self) -> bool:
return bool(self._connection and not self._connection.is_closed)
@@ -240,17 +235,7 @@ class AsyncRabbitMQ(RabbitMQBase):
@conn_retry("AsyncRabbitMQ", "Acquiring async connection")
async def connect(self):
if self.is_connected and self._channel and not self._channel.is_closed:
return
if (
self.is_connected
and self._connection
and (self._channel is None or self._channel.is_closed)
):
self._channel = await self._connection.channel()
await self._channel.set_qos(prefetch_count=1)
await self.declare_infrastructure()
if self.is_connected:
return
self._connection = await aio_pika.connect_robust(
@@ -306,46 +291,24 @@ class AsyncRabbitMQ(RabbitMQBase):
exchange, routing_key=queue.routing_key or queue.name
)
@property
def _lock(self) -> asyncio.Lock:
if self._reconnect_lock is None:
self._reconnect_lock = asyncio.Lock()
return self._reconnect_lock
async def _ensure_channel(self) -> aio_pika.abc.AbstractChannel:
"""Get a valid channel, reconnecting if the current one is stale.
Uses a lock to prevent concurrent reconnection attempts from racing.
"""
if self.is_ready:
return self._channel # type: ignore # is_ready guarantees non-None
async with self._lock:
# Double-check after acquiring lock
if self.is_ready:
return self._channel # type: ignore
self._channel = None
await self.connect()
if self._channel is None:
raise RuntimeError("Channel should be established after connect")
return self._channel
async def _publish_once(
@func_retry
async def publish_message(
self,
routing_key: str,
message: str,
exchange: Optional[Exchange] = None,
persistent: bool = True,
) -> None:
channel = await self._ensure_channel()
if not self.is_ready:
await self.connect()
if self._channel is None:
raise RuntimeError("Channel should be established after connect")
if exchange:
exchange_obj = await channel.get_exchange(exchange.name)
exchange_obj = await self._channel.get_exchange(exchange.name)
else:
exchange_obj = channel.default_exchange
exchange_obj = self._channel.default_exchange
await exchange_obj.publish(
aio_pika.Message(
@@ -359,23 +322,9 @@ class AsyncRabbitMQ(RabbitMQBase):
routing_key=routing_key,
)
@func_retry
async def publish_message(
self,
routing_key: str,
message: str,
exchange: Optional[Exchange] = None,
persistent: bool = True,
) -> None:
try:
await self._publish_once(routing_key, message, exchange, persistent)
except aio_pika.exceptions.ChannelInvalidStateError:
logger.warning(
"RabbitMQ channel invalid, forcing reconnect and retrying publish"
)
async with self._lock:
self._channel = None
await self._publish_once(routing_key, message, exchange, persistent)
async def get_channel(self) -> aio_pika.abc.AbstractChannel:
return await self._ensure_channel()
if not self.is_ready:
await self.connect()
if self._channel is None:
raise RuntimeError("Channel should be established after connect")
return self._channel

View File

@@ -213,9 +213,6 @@ async def execute_node(
block_name=node_block.name,
)
if node_block.disabled:
raise ValueError(f"Block {node_block.id} is disabled and cannot be executed")
# Sanity check: validate the execution input.
input_data, error = validate_exec(node, data.inputs, resolve_input=False)
if input_data is None:

View File

@@ -342,14 +342,6 @@ async def store_media_file(
if not target_path.is_file():
raise ValueError(f"Local file does not exist: {target_path}")
# Virus scan the local file before any further processing
local_content = target_path.read_bytes()
if len(local_content) > MAX_FILE_SIZE_BYTES:
raise ValueError(
f"File too large: {len(local_content)} bytes > {MAX_FILE_SIZE_BYTES} bytes"
)
await scan_content_safe(local_content, filename=sanitized_file)
# Return based on requested format
if return_format == "for_local_processing":
# Use when processing files locally with tools like ffmpeg, MoviePy, PIL

View File

@@ -247,100 +247,3 @@ class TestFileCloudIntegration:
execution_context=make_test_context(graph_exec_id=graph_exec_id),
return_format="for_local_processing",
)
@pytest.mark.asyncio
async def test_store_media_file_local_path_scanned(self):
"""Test that local file paths are scanned for viruses."""
graph_exec_id = "test-exec-123"
local_file = "test_video.mp4"
file_content = b"fake video content"
with patch(
"backend.util.file.get_cloud_storage_handler"
) as mock_handler_getter, patch(
"backend.util.file.scan_content_safe"
) as mock_scan, patch(
"backend.util.file.Path"
) as mock_path_class:
# Mock cloud storage handler - not a cloud path
mock_handler = MagicMock()
mock_handler.is_cloud_path.return_value = False
mock_handler_getter.return_value = mock_handler
# Mock virus scanner
mock_scan.return_value = None
# Mock file system operations
mock_base_path = MagicMock()
mock_target_path = MagicMock()
mock_resolved_path = MagicMock()
mock_path_class.return_value = mock_base_path
mock_base_path.mkdir = MagicMock()
mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
mock_target_path.resolve.return_value = mock_resolved_path
mock_resolved_path.is_relative_to.return_value = True
mock_resolved_path.is_file.return_value = True
mock_resolved_path.read_bytes.return_value = file_content
mock_resolved_path.relative_to.return_value = Path(local_file)
mock_resolved_path.name = local_file
result = await store_media_file(
file=MediaFileType(local_file),
execution_context=make_test_context(graph_exec_id=graph_exec_id),
return_format="for_local_processing",
)
# Verify virus scan was called for local file
mock_scan.assert_called_once_with(file_content, filename=local_file)
# Result should be the relative path
assert str(result) == local_file
@pytest.mark.asyncio
async def test_store_media_file_local_path_virus_detected(self):
"""Test that infected local files raise VirusDetectedError."""
from backend.api.features.store.exceptions import VirusDetectedError
graph_exec_id = "test-exec-123"
local_file = "infected.exe"
file_content = b"malicious content"
with patch(
"backend.util.file.get_cloud_storage_handler"
) as mock_handler_getter, patch(
"backend.util.file.scan_content_safe"
) as mock_scan, patch(
"backend.util.file.Path"
) as mock_path_class:
# Mock cloud storage handler - not a cloud path
mock_handler = MagicMock()
mock_handler.is_cloud_path.return_value = False
mock_handler_getter.return_value = mock_handler
# Mock virus scanner to detect virus
mock_scan.side_effect = VirusDetectedError(
"EICAR-Test-File", "File rejected due to virus detection"
)
# Mock file system operations
mock_base_path = MagicMock()
mock_target_path = MagicMock()
mock_resolved_path = MagicMock()
mock_path_class.return_value = mock_base_path
mock_base_path.mkdir = MagicMock()
mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
mock_target_path.resolve.return_value = mock_resolved_path
mock_resolved_path.is_relative_to.return_value = True
mock_resolved_path.is_file.return_value = True
mock_resolved_path.read_bytes.return_value = file_content
with pytest.raises(VirusDetectedError):
await store_media_file(
file=MediaFileType(local_file),
execution_context=make_test_context(graph_exec_id=graph_exec_id),
return_format="for_local_processing",
)

View File

@@ -0,0 +1,16 @@
"""Validation utilities."""
import re
_UUID_V4_PATTERN = re.compile(
r"[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}",
re.IGNORECASE,
)
def is_uuid_v4(text: str) -> bool:
return bool(_UUID_V4_PATTERN.fullmatch(text.strip()))
def extract_uuids(text: str) -> list[str]:
return sorted({m.lower() for m in _UUID_V4_PATTERN.findall(text)})

View File

@@ -46,14 +46,14 @@ pycares = ">=4.9.0,<5"
[[package]]
name = "aiofiles"
version = "25.1.0"
version = "24.1.0"
description = "File support for asyncio."
optional = false
python-versions = ">=3.9"
python-versions = ">=3.8"
groups = ["main"]
files = [
{file = "aiofiles-25.1.0-py3-none-any.whl", hash = "sha256:abe311e527c862958650f9438e859c1fa7568a141b22abcd015e120e86a85695"},
{file = "aiofiles-25.1.0.tar.gz", hash = "sha256:a8d728f0a29de45dc521f18f07297428d56992a742f0cd2701ba86e44d23d5b2"},
{file = "aiofiles-24.1.0-py3-none-any.whl", hash = "sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5"},
{file = "aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c"},
]
[[package]]
@@ -269,20 +269,19 @@ files = [
[[package]]
name = "anthropic"
version = "0.79.0"
version = "0.59.0"
description = "The official Python library for the anthropic API"
optional = false
python-versions = ">=3.9"
python-versions = ">=3.8"
groups = ["main"]
files = [
{file = "anthropic-0.79.0-py3-none-any.whl", hash = "sha256:04cbd473b6bbda4ca2e41dd670fe2f829a911530f01697d0a1e37321eb75f3cf"},
{file = "anthropic-0.79.0.tar.gz", hash = "sha256:8707aafb3b1176ed6c13e2b1c9fb3efddce90d17aee5d8b83a86c70dcdcca871"},
{file = "anthropic-0.59.0-py3-none-any.whl", hash = "sha256:cbc8b3dccef66ad6435c4fa1d317e5ebb092399a4b88b33a09dc4bf3944c3183"},
{file = "anthropic-0.59.0.tar.gz", hash = "sha256:d710d1ef0547ebbb64b03f219e44ba078e83fc83752b96a9b22e9726b523fd8f"},
]
[package.dependencies]
anyio = ">=3.5.0,<5"
distro = ">=1.7.0,<2"
docstring-parser = ">=0.15,<1"
httpx = ">=0.25.0,<1"
jiter = ">=0.4.0,<1"
pydantic = ">=1.9.0,<3"
@@ -290,7 +289,7 @@ sniffio = "*"
typing-extensions = ">=4.10,<5"
[package.extras]
aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.9)"]
aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"]
bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
vertex = ["google-auth[requests] (>=2,<3)"]
@@ -439,7 +438,7 @@ develop = true
[package.dependencies]
colorama = "^0.4.6"
cryptography = "^46.0"
cryptography = "^45.0"
expiringdict = "^1.2.2"
fastapi = "^0.128.0"
google-cloud-logging = "^3.13.0"
@@ -971,75 +970,62 @@ pytz = ">2021.1"
[[package]]
name = "cryptography"
version = "46.0.4"
version = "45.0.7"
description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
optional = false
python-versions = "!=3.9.0,!=3.9.1,>=3.8"
python-versions = "!=3.9.0,!=3.9.1,>=3.7"
groups = ["main"]
files = [
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{file = "tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5edb8743b88d5be814b1a8a8854494719080c28faaa1ccbef02e87354fe71ef0"},
{file = "tiktoken-0.12.0-cp314-cp314t-win_amd64.whl", hash = "sha256:f61c0aea5565ac82e2ec50a05e02a6c44734e91b51c10510b084ea1b8e633a71"},
{file = "tiktoken-0.12.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:d51d75a5bffbf26f86554d28e78bfb921eae998edc2675650fd04c7e1f0cdc1e"},
{file = "tiktoken-0.12.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:09eb4eae62ae7e4c62364d9ec3a57c62eea707ac9a2b2c5d6bd05de6724ea179"},
{file = "tiktoken-0.12.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:df37684ace87d10895acb44b7f447d4700349b12197a526da0d4a4149fde074c"},
{file = "tiktoken-0.12.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:4c9614597ac94bb294544345ad8cf30dac2129c05e2db8dc53e082f355857af7"},
{file = "tiktoken-0.12.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:20cf97135c9a50de0b157879c3c4accbb29116bcf001283d26e073ff3b345946"},
{file = "tiktoken-0.12.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:15d875454bbaa3728be39880ddd11a5a2a9e548c29418b41e8fd8a767172b5ec"},
{file = "tiktoken-0.12.0-cp39-cp39-win_amd64.whl", hash = "sha256:2cff3688ba3c639ebe816f8d58ffbbb0aa7433e23e08ab1cade5d175fc973fb3"},
{file = "tiktoken-0.12.0.tar.gz", hash = "sha256:b18ba7ee2b093863978fcb14f74b3707cdc8d4d4d3836853ce7ec60772139931"},
{file = "tiktoken-0.9.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:586c16358138b96ea804c034b8acf3f5d3f0258bd2bc3b0227af4af5d622e382"},
{file = "tiktoken-0.9.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d9c59ccc528c6c5dd51820b3474402f69d9a9e1d656226848ad68a8d5b2e5108"},
{file = "tiktoken-0.9.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f0968d5beeafbca2a72c595e8385a1a1f8af58feaebb02b227229b69ca5357fd"},
{file = "tiktoken-0.9.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:92a5fb085a6a3b7350b8fc838baf493317ca0e17bd95e8642f95fc69ecfed1de"},
{file = "tiktoken-0.9.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:15a2752dea63d93b0332fb0ddb05dd909371ededa145fe6a3242f46724fa7990"},
{file = "tiktoken-0.9.0-cp310-cp310-win_amd64.whl", hash = "sha256:26113fec3bd7a352e4b33dbaf1bd8948de2507e30bd95a44e2b1156647bc01b4"},
{file = "tiktoken-0.9.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:f32cc56168eac4851109e9b5d327637f15fd662aa30dd79f964b7c39fbadd26e"},
{file = "tiktoken-0.9.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:45556bc41241e5294063508caf901bf92ba52d8ef9222023f83d2483a3055348"},
{file = "tiktoken-0.9.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:03935988a91d6d3216e2ec7c645afbb3d870b37bcb67ada1943ec48678e7ee33"},
{file = "tiktoken-0.9.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8b3d80aad8d2c6b9238fc1a5524542087c52b860b10cbf952429ffb714bc1136"},
{file = "tiktoken-0.9.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:b2a21133be05dc116b1d0372af051cd2c6aa1d2188250c9b553f9fa49301b336"},
{file = "tiktoken-0.9.0-cp311-cp311-win_amd64.whl", hash = "sha256:11a20e67fdf58b0e2dea7b8654a288e481bb4fc0289d3ad21291f8d0849915fb"},
{file = "tiktoken-0.9.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:e88f121c1c22b726649ce67c089b90ddda8b9662545a8aeb03cfef15967ddd03"},
{file = "tiktoken-0.9.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a6600660f2f72369acb13a57fb3e212434ed38b045fd8cc6cdd74947b4b5d210"},
{file = "tiktoken-0.9.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:95e811743b5dfa74f4b227927ed86cbc57cad4df859cb3b643be797914e41794"},
{file = "tiktoken-0.9.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:99376e1370d59bcf6935c933cb9ba64adc29033b7e73f5f7569f3aad86552b22"},
{file = "tiktoken-0.9.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:badb947c32739fb6ddde173e14885fb3de4d32ab9d8c591cbd013c22b4c31dd2"},
{file = "tiktoken-0.9.0-cp312-cp312-win_amd64.whl", hash = "sha256:5a62d7a25225bafed786a524c1b9f0910a1128f4232615bf3f8257a73aaa3b16"},
{file = "tiktoken-0.9.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:2b0e8e05a26eda1249e824156d537015480af7ae222ccb798e5234ae0285dbdb"},
{file = "tiktoken-0.9.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:27d457f096f87685195eea0165a1807fae87b97b2161fe8c9b1df5bd74ca6f63"},
{file = "tiktoken-0.9.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2cf8ded49cddf825390e36dd1ad35cd49589e8161fdcb52aa25f0583e90a3e01"},
{file = "tiktoken-0.9.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cc156cb314119a8bb9748257a2eaebd5cc0753b6cb491d26694ed42fc7cb3139"},
{file = "tiktoken-0.9.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:cd69372e8c9dd761f0ab873112aba55a0e3e506332dd9f7522ca466e817b1b7a"},
{file = "tiktoken-0.9.0-cp313-cp313-win_amd64.whl", hash = "sha256:5ea0edb6f83dc56d794723286215918c1cde03712cbbafa0348b33448faf5b95"},
{file = "tiktoken-0.9.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:c6386ca815e7d96ef5b4ac61e0048cd32ca5a92d5781255e13b31381d28667dc"},
{file = "tiktoken-0.9.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:75f6d5db5bc2c6274b674ceab1615c1778e6416b14705827d19b40e6355f03e0"},
{file = "tiktoken-0.9.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e15b16f61e6f4625a57a36496d28dd182a8a60ec20a534c5343ba3cafa156ac7"},
{file = "tiktoken-0.9.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ebcec91babf21297022882344c3f7d9eed855931466c3311b1ad6b64befb3df"},
{file = "tiktoken-0.9.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:e5fd49e7799579240f03913447c0cdfa1129625ebd5ac440787afc4345990427"},
{file = "tiktoken-0.9.0-cp39-cp39-win_amd64.whl", hash = "sha256:26242ca9dc8b58e875ff4ca078b9a94d2f0813e6a535dcd2205df5d49d927cc7"},
{file = "tiktoken-0.9.0.tar.gz", hash = "sha256:d02a5ca6a938e0490e1ff957bc48c8b078c88cb83977be1625b1fd8aac792c5d"},
]
[package.dependencies]
@@ -8440,4 +8382,4 @@ 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 = "c06e96ad49388ba7a46786e9ea55ea2c1a57408e15613237b4bee40a592a12af"
content-hash = "40b2c87c3c86bd10214bd30ad291cead75da5060ab894105025ee4c0a3b3828e"

View File

@@ -12,16 +12,16 @@ python = ">=3.10,<3.14"
aio-pika = "^9.5.5"
aiohttp = "^3.10.0"
aiodns = "^3.5.0"
anthropic = "^0.79.0"
anthropic = "^0.59.0"
apscheduler = "^3.11.1"
autogpt-libs = { path = "../autogpt_libs", develop = true }
bleach = { extras = ["css"], version = "^6.2.0" }
click = "^8.2.0"
cryptography = "^46.0"
cryptography = "^45.0"
discord-py = "^2.5.2"
e2b-code-interpreter = "^1.5.2"
elevenlabs = "^1.50.0"
fastapi = "^0.128.6"
fastapi = "^0.128.0"
feedparser = "^6.0.11"
flake8 = "^7.3.0"
google-api-python-client = "^2.177.0"
@@ -34,11 +34,11 @@ html2text = "^2024.2.26"
jinja2 = "^3.1.6"
jsonref = "^1.1.0"
jsonschema = "^4.25.0"
langfuse = "^3.14.1"
langfuse = "^3.11.0"
launchdarkly-server-sdk = "^9.14.1"
mem0ai = "^0.1.115"
moviepy = "^2.1.2"
ollama = "^0.6.1"
ollama = "^0.5.1"
openai = "^1.97.1"
orjson = "^3.10.0"
pika = "^1.3.2"
@@ -48,7 +48,7 @@ postmarker = "^1.0"
praw = "~7.8.1"
prisma = "^0.15.0"
rank-bm25 = "^0.2.2"
prometheus-client = "^0.24.1"
prometheus-client = "^0.22.1"
prometheus-fastapi-instrumentator = "^7.0.0"
psutil = "^7.0.0"
psycopg2-binary = "^2.9.10"
@@ -57,7 +57,7 @@ pydantic-settings = "^2.12.0"
pytest = "^8.4.1"
pytest-asyncio = "^1.1.0"
python-dotenv = "^1.1.1"
python-multipart = "^0.0.22"
python-multipart = "^0.0.20"
redis = "^6.2.0"
regex = "^2025.9.18"
replicate = "^1.0.6"
@@ -65,8 +65,8 @@ sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlal
sqlalchemy = "^2.0.40"
strenum = "^0.4.9"
stripe = "^11.5.0"
supabase = "2.27.3"
tenacity = "^9.1.4"
supabase = "2.27.2"
tenacity = "^9.1.2"
todoist-api-python = "^2.1.7"
tweepy = "^4.16.0"
uvicorn = { extras = ["standard"], version = "^0.40.0" }
@@ -76,8 +76,8 @@ yt-dlp = "2025.12.08"
zerobouncesdk = "^1.1.2"
# NOTE: please insert new dependencies in their alphabetical location
pytest-snapshot = "^0.9.0"
aiofiles = "^25.1.0"
tiktoken = "^0.12.0"
aiofiles = "^24.1.0"
tiktoken = "^0.9.0"
aioclamd = "^1.0.0"
setuptools = "^80.9.0"
gcloud-aio-storage = "^9.5.0"
@@ -95,13 +95,13 @@ black = "^24.10.0"
faker = "^38.2.0"
httpx = "^0.28.1"
isort = "^5.13.2"
poethepoet = "^0.41.0"
poethepoet = "^0.37.0"
pre-commit = "^4.4.0"
pyright = "^1.1.407"
pytest-mock = "^3.15.1"
pytest-watcher = "^0.6.3"
pytest-watcher = "^0.4.2"
requests = "^2.32.5"
ruff = "^0.15.0"
ruff = "^0.14.5"
# NOTE: please insert new dependencies in their alphabetical location
[build-system]

View File

@@ -25,12 +25,8 @@ RUN if [ -f .env.production ]; then \
cp .env.default .env; \
fi
RUN pnpm run generate:api
# Disable source-map generation in Docker builds to halve webpack memory usage.
# Source maps are only useful when SENTRY_AUTH_TOKEN is set (Vercel deploys);
# the Docker image never uploads them, so generating them just wastes RAM.
ENV NEXT_PUBLIC_SOURCEMAPS="false"
# In CI, we want NEXT_PUBLIC_PW_TEST=true during build so Next.js inlines it
RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=8192" pnpm build; else NODE_OPTIONS="--max-old-space-size=8192" pnpm build; fi
RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=4096" pnpm build; else NODE_OPTIONS="--max-old-space-size=4096" pnpm build; fi
# Prod stage - based on NextJS reference Dockerfile https://github.com/vercel/next.js/blob/64271354533ed16da51be5dce85f0dbd15f17517/examples/with-docker/Dockerfile
FROM node:21-alpine AS prod

View File

@@ -1,12 +1,8 @@
import { withSentryConfig } from "@sentry/nextjs";
// Allow Docker builds to skip source-map generation (halves memory usage).
// Defaults to true so Vercel/local builds are unaffected.
const enableSourceMaps = process.env.NEXT_PUBLIC_SOURCEMAPS !== "false";
/** @type {import('next').NextConfig} */
const nextConfig = {
productionBrowserSourceMaps: enableSourceMaps,
productionBrowserSourceMaps: true,
// Externalize OpenTelemetry packages to fix Turbopack HMR issues
serverExternalPackages: [
"@opentelemetry/instrumentation",
@@ -18,37 +14,9 @@ const nextConfig = {
serverActions: {
bodySizeLimit: "256mb",
},
// Increase body size limit for API routes (file uploads) - 256MB to match backend limit
proxyClientMaxBodySize: "256mb",
middlewareClientMaxBodySize: "256mb",
// Limit parallel webpack workers to reduce peak memory during builds.
cpus: 2,
},
// Work around cssnano "Invalid array length" bug in Next.js's bundled
// cssnano-simple comment parser when processing very large CSS chunks.
// CSS is still bundled correctly; gzip handles most of the size savings anyway.
webpack: (config, { dev }) => {
if (!dev) {
// Next.js adds CssMinimizerPlugin internally (after user config), so we
// can't filter it from config.plugins. Instead, intercept the webpack
// compilation hooks and replace the buggy plugin's tap with a no-op.
config.plugins.push({
apply(compiler) {
compiler.hooks.compilation.tap(
"DisableCssMinimizer",
(compilation) => {
compilation.hooks.processAssets.intercept({
register: (tap) => {
if (tap.name === "CssMinimizerPlugin") {
return { ...tap, fn: async () => {} };
}
return tap;
},
});
},
);
},
});
}
return config;
},
images: {
domains: [
@@ -86,16 +54,9 @@ const nextConfig = {
transpilePackages: ["geist"],
};
// Only run the Sentry webpack plugin when we can actually upload source maps
// (i.e. on Vercel with SENTRY_AUTH_TOKEN set). The Sentry *runtime* SDK
// (imported in app code) still captures errors without the plugin.
// Skipping the plugin saves ~1 GB of peak memory during `next build`.
const skipSentryPlugin =
process.env.NODE_ENV !== "production" ||
!enableSourceMaps ||
!process.env.SENTRY_AUTH_TOKEN;
const isDevelopmentBuild = process.env.NODE_ENV !== "production";
export default skipSentryPlugin
export default isDevelopmentBuild
? nextConfig
: withSentryConfig(nextConfig, {
// For all available options, see:
@@ -135,7 +96,7 @@ export default skipSentryPlugin
// This helps Sentry with sourcemaps... https://docs.sentry.io/platforms/javascript/guides/nextjs/sourcemaps/
sourcemaps: {
disable: !enableSourceMaps,
disable: false,
assets: [".next/**/*.js", ".next/**/*.js.map"],
ignore: ["**/node_modules/**"],
deleteSourcemapsAfterUpload: false, // Source is public anyway :)

View File

@@ -7,7 +7,7 @@
},
"scripts": {
"dev": "pnpm run generate:api:force && next dev --turbo",
"build": "cross-env NODE_OPTIONS=--max-old-space-size=16384 next build",
"build": "next build",
"start": "next start",
"start:standalone": "cd .next/standalone && node server.js",
"lint": "next lint && prettier --check .",
@@ -30,7 +30,6 @@
"defaults"
],
"dependencies": {
"@ai-sdk/react": "3.0.61",
"@faker-js/faker": "10.0.0",
"@hookform/resolvers": "5.2.2",
"@next/third-parties": "15.4.6",
@@ -61,10 +60,6 @@
"@rjsf/utils": "6.1.2",
"@rjsf/validator-ajv8": "6.1.2",
"@sentry/nextjs": "10.27.0",
"@streamdown/cjk": "1.0.1",
"@streamdown/code": "1.0.1",
"@streamdown/math": "1.0.1",
"@streamdown/mermaid": "1.0.1",
"@supabase/ssr": "0.7.0",
"@supabase/supabase-js": "2.78.0",
"@tanstack/react-query": "5.90.6",
@@ -73,7 +68,6 @@
"@vercel/analytics": "1.5.0",
"@vercel/speed-insights": "1.2.0",
"@xyflow/react": "12.9.2",
"ai": "6.0.59",
"boring-avatars": "1.11.2",
"class-variance-authority": "0.7.1",
"clsx": "2.1.1",
@@ -93,6 +87,7 @@
"launchdarkly-react-client-sdk": "3.9.0",
"lodash": "4.17.21",
"lucide-react": "0.552.0",
"moment": "2.30.1",
"next": "15.4.10",
"next-themes": "0.4.6",
"nuqs": "2.7.2",
@@ -107,7 +102,7 @@
"react-markdown": "9.0.3",
"react-modal": "3.16.3",
"react-shepherd": "6.1.9",
"react-window": "2.2.0",
"react-window": "1.8.11",
"recharts": "3.3.0",
"rehype-autolink-headings": "7.1.0",
"rehype-highlight": "7.0.2",
@@ -117,11 +112,9 @@
"remark-math": "6.0.0",
"shepherd.js": "14.5.1",
"sonner": "2.0.7",
"streamdown": "2.1.0",
"tailwind-merge": "2.6.0",
"tailwind-scrollbar": "3.1.0",
"tailwindcss-animate": "1.0.7",
"use-stick-to-bottom": "1.1.2",
"uuid": "11.1.0",
"vaul": "1.1.2",
"zod": "3.25.76",
@@ -147,7 +140,7 @@
"@types/react": "18.3.17",
"@types/react-dom": "18.3.5",
"@types/react-modal": "3.16.3",
"@types/react-window": "2.0.0",
"@types/react-window": "1.8.8",
"@vitejs/plugin-react": "5.1.2",
"axe-playwright": "2.2.2",
"chromatic": "13.3.3",
@@ -179,8 +172,7 @@
},
"pnpm": {
"overrides": {
"@opentelemetry/instrumentation": "0.209.0",
"lodash-es": "4.17.23"
"@opentelemetry/instrumentation": "0.209.0"
}
},
"packageManager": "pnpm@10.20.0+sha512.cf9998222162dd85864d0a8102e7892e7ba4ceadebbf5a31f9c2fce48dfce317a9c53b9f6464d1ef9042cba2e02ae02a9f7c143a2b438cd93c91840f0192b9dd"

File diff suppressed because it is too large Load Diff

View File

@@ -1,4 +1,4 @@
import debounce from "lodash/debounce";
import { debounce } from "lodash";
import { useCallback, useEffect, useRef, useState } from "react";
import { useBlockMenuStore } from "../../../../stores/blockMenuStore";
import { getQueryClient } from "@/lib/react-query/queryClient";

View File

@@ -70,10 +70,10 @@ export const HorizontalScroll: React.FC<HorizontalScrollAreaProps> = ({
{children}
</div>
{canScrollLeft && (
<div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-background via-background/80 to-background/0" />
<div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-white via-white/80 to-white/0" />
)}
{canScrollRight && (
<div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-background via-background/80 to-background/0" />
<div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-white via-white/80 to-white/0" />
)}
{canScrollLeft && (
<button

View File

@@ -1,80 +0,0 @@
"use client";
import { SidebarProvider } from "@/components/ui/sidebar";
import { ChatContainer } from "./components/ChatContainer/ChatContainer";
import { ChatSidebar } from "./components/ChatSidebar/ChatSidebar";
import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
import { MobileHeader } from "./components/MobileHeader/MobileHeader";
import { ScaleLoader } from "./components/ScaleLoader/ScaleLoader";
import { useCopilotPage } from "./useCopilotPage";
export function CopilotPage() {
const {
sessionId,
messages,
status,
error,
stop,
createSession,
onSend,
isLoadingSession,
isCreatingSession,
isUserLoading,
isLoggedIn,
// Mobile drawer
isMobile,
isDrawerOpen,
sessions,
isLoadingSessions,
handleOpenDrawer,
handleCloseDrawer,
handleDrawerOpenChange,
handleSelectSession,
handleNewChat,
} = useCopilotPage();
if (isUserLoading || !isLoggedIn) {
return (
<div className="fixed inset-0 z-50 flex items-center justify-center bg-[#f8f8f9]">
<ScaleLoader className="text-neutral-400" />
</div>
);
}
return (
<SidebarProvider
defaultOpen={true}
className="h-[calc(100vh-72px)] min-h-0"
>
{!isMobile && <ChatSidebar />}
<div className="relative flex h-full w-full flex-col overflow-hidden bg-[#f8f8f9] px-0">
{isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
<div className="flex-1 overflow-hidden">
<ChatContainer
messages={messages}
status={status}
error={error}
sessionId={sessionId}
isLoadingSession={isLoadingSession}
isCreatingSession={isCreatingSession}
onCreateSession={createSession}
onSend={onSend}
onStop={stop}
/>
</div>
</div>
{isMobile && (
<MobileDrawer
isOpen={isDrawerOpen}
sessions={sessions}
currentSessionId={sessionId}
isLoading={isLoadingSessions}
onSelectSession={handleSelectSession}
onNewChat={handleNewChat}
onClose={handleCloseDrawer}
onOpenChange={handleDrawerOpenChange}
/>
)}
</SidebarProvider>
);
}

View File

@@ -1,74 +0,0 @@
"use client";
import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
import { UIDataTypes, UIMessage, UITools } from "ai";
import { LayoutGroup, motion } from "framer-motion";
import { ChatMessagesContainer } from "../ChatMessagesContainer/ChatMessagesContainer";
import { CopilotChatActionsProvider } from "../CopilotChatActionsProvider/CopilotChatActionsProvider";
import { EmptySession } from "../EmptySession/EmptySession";
export interface ChatContainerProps {
messages: UIMessage<unknown, UIDataTypes, UITools>[];
status: string;
error: Error | undefined;
sessionId: string | null;
isLoadingSession: boolean;
isCreatingSession: boolean;
onCreateSession: () => void | Promise<string>;
onSend: (message: string) => void | Promise<void>;
onStop: () => void;
}
export const ChatContainer = ({
messages,
status,
error,
sessionId,
isLoadingSession,
isCreatingSession,
onCreateSession,
onSend,
onStop,
}: ChatContainerProps) => {
const inputLayoutId = "copilot-2-chat-input";
return (
<CopilotChatActionsProvider onSend={onSend}>
<LayoutGroup id="copilot-2-chat-layout">
<div className="flex h-full min-h-0 w-full flex-col bg-[#f8f8f9] px-2 lg:px-0">
{sessionId ? (
<div className="mx-auto flex h-full min-h-0 w-full max-w-3xl flex-col">
<ChatMessagesContainer
messages={messages}
status={status}
error={error}
isLoading={isLoadingSession}
/>
<motion.div
initial={{ opacity: 0 }}
animate={{ opacity: 1 }}
transition={{ duration: 0.3 }}
className="relative px-3 pb-2 pt-2"
>
<div className="pointer-events-none absolute left-0 right-0 top-[-18px] z-10 h-6 bg-gradient-to-b from-transparent to-[#f8f8f9]" />
<ChatInput
inputId="chat-input-session"
onSend={onSend}
disabled={status === "streaming"}
isStreaming={status === "streaming"}
onStop={onStop}
placeholder="What else can I help with?"
/>
</motion.div>
</div>
) : (
<EmptySession
inputLayoutId={inputLayoutId}
isCreatingSession={isCreatingSession}
onCreateSession={onCreateSession}
onSend={onSend}
/>
)}
</div>
</LayoutGroup>
</CopilotChatActionsProvider>
);
};

View File

@@ -1,274 +0,0 @@
import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
import {
Conversation,
ConversationContent,
ConversationScrollButton,
} from "@/components/ai-elements/conversation";
import {
Message,
MessageContent,
MessageResponse,
} from "@/components/ai-elements/message";
import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
import { useEffect, useState } from "react";
import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
import { FindAgentsTool } from "../../tools/FindAgents/FindAgents";
import { FindBlocksTool } from "../../tools/FindBlocks/FindBlocks";
import { RunAgentTool } from "../../tools/RunAgent/RunAgent";
import { RunBlockTool } from "../../tools/RunBlock/RunBlock";
import { SearchDocsTool } from "../../tools/SearchDocs/SearchDocs";
import { ViewAgentOutputTool } from "../../tools/ViewAgentOutput/ViewAgentOutput";
// ---------------------------------------------------------------------------
// Workspace media support
// ---------------------------------------------------------------------------
/**
* Resolve workspace:// URLs in markdown text to proxy download URLs.
* Detects MIME type from the hash fragment (e.g. workspace://id#video/mp4)
* and prefixes the alt text with "video:" so the custom img component can
* render a <video> element instead.
*/
function resolveWorkspaceUrls(text: string): string {
return text.replace(
/!\[([^\]]*)\]\(workspace:\/\/([^)#\s]+)(?:#([^)\s]*))?\)/g,
(_match, alt: string, fileId: string, mimeHint?: string) => {
const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
const url = `/api/proxy${apiPath}`;
if (mimeHint?.startsWith("video/")) {
return `![video:${alt || "Video"}](${url})`;
}
return `![${alt || "Image"}](${url})`;
},
);
}
/**
* Custom img component for Streamdown that renders <video> elements
* for workspace video files (detected via "video:" alt-text prefix).
* Falls back to <video> when an <img> fails to load for workspace files.
*/
function WorkspaceMediaImage(props: React.JSX.IntrinsicElements["img"]) {
const { src, alt, ...rest } = props;
const [imgFailed, setImgFailed] = useState(false);
const isWorkspace = src?.includes("/workspace/files/") ?? false;
if (!src) return null;
if (alt?.startsWith("video:") || (imgFailed && isWorkspace)) {
return (
<span className="my-2 inline-block">
<video
controls
className="h-auto max-w-full rounded-md border border-zinc-200"
preload="metadata"
>
<source src={src} />
Your browser does not support the video tag.
</video>
</span>
);
}
return (
// eslint-disable-next-line @next/next/no-img-element
<img
src={src}
alt={alt || "Image"}
className="h-auto max-w-full rounded-md border border-zinc-200"
loading="lazy"
onError={() => {
if (isWorkspace) setImgFailed(true);
}}
{...rest}
/>
);
}
/** Stable components override for Streamdown (avoids re-creating on every render). */
const STREAMDOWN_COMPONENTS = { img: WorkspaceMediaImage };
const THINKING_PHRASES = [
"Thinking...",
"Considering this...",
"Working through this...",
"Analyzing your request...",
"Reasoning...",
"Looking into it...",
"Processing your request...",
"Mulling this over...",
"Piecing it together...",
"On it...",
];
function getRandomPhrase() {
return THINKING_PHRASES[Math.floor(Math.random() * THINKING_PHRASES.length)];
}
interface ChatMessagesContainerProps {
messages: UIMessage<unknown, UIDataTypes, UITools>[];
status: string;
error: Error | undefined;
isLoading: boolean;
}
export const ChatMessagesContainer = ({
messages,
status,
error,
isLoading,
}: ChatMessagesContainerProps) => {
const [thinkingPhrase, setThinkingPhrase] = useState(getRandomPhrase);
useEffect(() => {
if (status === "submitted") {
setThinkingPhrase(getRandomPhrase());
}
}, [status]);
const lastMessage = messages[messages.length - 1];
const lastAssistantHasVisibleContent =
lastMessage?.role === "assistant" &&
lastMessage.parts.some(
(p) =>
(p.type === "text" && p.text.trim().length > 0) ||
p.type.startsWith("tool-"),
);
const showThinking =
status === "submitted" ||
(status === "streaming" && !lastAssistantHasVisibleContent);
return (
<Conversation className="min-h-0 flex-1">
<ConversationContent className="flex min-h-screen flex-1 flex-col gap-6 px-3 py-6">
{isLoading && messages.length === 0 && (
<div className="flex min-h-full flex-1 items-center justify-center">
<LoadingSpinner className="text-neutral-600" />
</div>
)}
{messages.map((message, messageIndex) => {
const isLastAssistant =
messageIndex === messages.length - 1 &&
message.role === "assistant";
const messageHasVisibleContent = message.parts.some(
(p) =>
(p.type === "text" && p.text.trim().length > 0) ||
p.type.startsWith("tool-"),
);
return (
<Message from={message.role} key={message.id}>
<MessageContent
className={
"text-[1rem] leading-relaxed " +
"group-[.is-user]:rounded-xl group-[.is-user]:bg-purple-100 group-[.is-user]:px-3 group-[.is-user]:py-2.5 group-[.is-user]:text-slate-900 group-[.is-user]:[border-bottom-right-radius:0] " +
"group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900"
}
>
{message.parts.map((part, i) => {
switch (part.type) {
case "text":
return (
<MessageResponse
key={`${message.id}-${i}`}
components={STREAMDOWN_COMPONENTS}
>
{resolveWorkspaceUrls(part.text)}
</MessageResponse>
);
case "tool-find_block":
return (
<FindBlocksTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
case "tool-find_agent":
case "tool-find_library_agent":
return (
<FindAgentsTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
case "tool-search_docs":
case "tool-get_doc_page":
return (
<SearchDocsTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
case "tool-run_block":
return (
<RunBlockTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
case "tool-run_agent":
case "tool-schedule_agent":
return (
<RunAgentTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
case "tool-create_agent":
return (
<CreateAgentTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
case "tool-edit_agent":
return (
<EditAgentTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
case "tool-view_agent_output":
return (
<ViewAgentOutputTool
key={`${message.id}-${i}`}
part={part as ToolUIPart}
/>
);
default:
return null;
}
})}
{isLastAssistant &&
!messageHasVisibleContent &&
showThinking && (
<span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
{thinkingPhrase}
</span>
)}
</MessageContent>
</Message>
);
})}
{showThinking && lastMessage?.role !== "assistant" && (
<Message from="assistant">
<MessageContent className="text-[1rem] leading-relaxed">
<span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
{thinkingPhrase}
</span>
</MessageContent>
</Message>
)}
{error && (
<div className="rounded-lg bg-red-50 p-3 text-red-600">
Error: {error.message}
</div>
)}
</ConversationContent>
<ConversationScrollButton />
</Conversation>
);
};

View File

@@ -1,188 +0,0 @@
"use client";
import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
import { Button } from "@/components/atoms/Button/Button";
import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
import { Text } from "@/components/atoms/Text/Text";
import {
Sidebar,
SidebarContent,
SidebarFooter,
SidebarHeader,
SidebarTrigger,
useSidebar,
} from "@/components/ui/sidebar";
import { cn } from "@/lib/utils";
import { PlusCircleIcon, PlusIcon } from "@phosphor-icons/react";
import { motion } from "framer-motion";
import { parseAsString, useQueryState } from "nuqs";
export function ChatSidebar() {
const { state } = useSidebar();
const isCollapsed = state === "collapsed";
const [sessionId, setSessionId] = useQueryState("sessionId", parseAsString);
const { data: sessionsResponse, isLoading: isLoadingSessions } =
useGetV2ListSessions({ limit: 50 });
const sessions =
sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
function handleNewChat() {
setSessionId(null);
}
function handleSelectSession(id: string) {
setSessionId(id);
}
function formatDate(dateString: string) {
const date = new Date(dateString);
const now = new Date();
const diffMs = now.getTime() - date.getTime();
const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
if (diffDays === 0) return "Today";
if (diffDays === 1) return "Yesterday";
if (diffDays < 7) return `${diffDays} days ago`;
const day = date.getDate();
const ordinal =
day % 10 === 1 && day !== 11
? "st"
: day % 10 === 2 && day !== 12
? "nd"
: day % 10 === 3 && day !== 13
? "rd"
: "th";
const month = date.toLocaleDateString("en-US", { month: "short" });
const year = date.getFullYear();
return `${day}${ordinal} ${month} ${year}`;
}
return (
<Sidebar
variant="inset"
collapsible="icon"
className="!top-[50px] !h-[calc(100vh-50px)] border-r border-zinc-100 px-0"
>
{isCollapsed && (
<SidebarHeader
className={cn(
"flex",
isCollapsed
? "flex-row items-center justify-between gap-y-4 md:flex-col md:items-start md:justify-start"
: "flex-row items-center justify-between",
)}
>
<motion.div
key={isCollapsed ? "header-collapsed" : "header-expanded"}
className="flex flex-col items-center gap-3 pt-4"
initial={{ opacity: 0, filter: "blur(3px)" }}
animate={{ opacity: 1, filter: "blur(0px)" }}
transition={{ type: "spring", bounce: 0.2 }}
>
<div className="flex flex-col items-center gap-2">
<SidebarTrigger />
<Button
variant="ghost"
onClick={handleNewChat}
style={{ minWidth: "auto", width: "auto" }}
>
<PlusCircleIcon className="!size-5" />
<span className="sr-only">New Chat</span>
</Button>
</div>
</motion.div>
</SidebarHeader>
)}
<SidebarContent className="gap-4 overflow-y-auto px-4 py-4 [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
{!isCollapsed && (
<motion.div
initial={{ opacity: 0 }}
animate={{ opacity: 1 }}
transition={{ duration: 0.2, delay: 0.1 }}
className="flex items-center justify-between px-3"
>
<Text variant="h3" size="body-medium">
Your chats
</Text>
<div className="relative left-6">
<SidebarTrigger />
</div>
</motion.div>
)}
{!isCollapsed && (
<motion.div
initial={{ opacity: 0 }}
animate={{ opacity: 1 }}
transition={{ duration: 0.2, delay: 0.15 }}
className="mt-4 flex flex-col gap-1"
>
{isLoadingSessions ? (
<div className="flex min-h-[30rem] items-center justify-center py-4">
<LoadingSpinner size="small" className="text-neutral-600" />
</div>
) : sessions.length === 0 ? (
<p className="py-4 text-center text-sm text-neutral-500">
No conversations yet
</p>
) : (
sessions.map((session) => (
<button
key={session.id}
onClick={() => handleSelectSession(session.id)}
className={cn(
"w-full rounded-lg px-3 py-2.5 text-left transition-colors",
session.id === sessionId
? "bg-zinc-100"
: "hover:bg-zinc-50",
)}
>
<div className="flex min-w-0 max-w-full flex-col overflow-hidden">
<div className="min-w-0 max-w-full">
<Text
variant="body"
className={cn(
"truncate font-normal",
session.id === sessionId
? "text-zinc-600"
: "text-zinc-800",
)}
>
{session.title || `Untitled chat`}
</Text>
</div>
<Text variant="small" className="text-neutral-400">
{formatDate(session.updated_at)}
</Text>
</div>
</button>
))
)}
</motion.div>
)}
</SidebarContent>
{!isCollapsed && sessionId && (
<SidebarFooter className="shrink-0 bg-zinc-50 p-3 pb-1 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
<motion.div
initial={{ opacity: 0 }}
animate={{ opacity: 1 }}
transition={{ duration: 0.2, delay: 0.2 }}
>
<Button
variant="primary"
size="small"
onClick={handleNewChat}
className="w-full"
leftIcon={<PlusIcon className="h-4 w-4" weight="bold" />}
>
New Chat
</Button>
</motion.div>
</SidebarFooter>
)}
</Sidebar>
);
}

View File

@@ -1,16 +0,0 @@
"use client";
import { CopilotChatActionsContext } from "./useCopilotChatActions";
interface Props {
onSend: (message: string) => void | Promise<void>;
children: React.ReactNode;
}
export function CopilotChatActionsProvider({ onSend, children }: Props) {
return (
<CopilotChatActionsContext.Provider value={{ onSend }}>
{children}
</CopilotChatActionsContext.Provider>
);
}

View File

@@ -1,23 +0,0 @@
"use client";
import { createContext, useContext } from "react";
interface CopilotChatActions {
onSend: (message: string) => void | Promise<void>;
}
const CopilotChatActionsContext = createContext<CopilotChatActions | null>(
null,
);
export function useCopilotChatActions(): CopilotChatActions {
const ctx = useContext(CopilotChatActionsContext);
if (!ctx) {
throw new Error(
"useCopilotChatActions must be used within CopilotChatActionsProvider",
);
}
return ctx;
}
export { CopilotChatActionsContext };

View File

@@ -0,0 +1,99 @@
"use client";
import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
import { Text } from "@/components/atoms/Text/Text";
import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
import type { ReactNode } from "react";
import { DesktopSidebar } from "./components/DesktopSidebar/DesktopSidebar";
import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
import { MobileHeader } from "./components/MobileHeader/MobileHeader";
import { useCopilotShell } from "./useCopilotShell";
interface Props {
children: ReactNode;
}
export function CopilotShell({ children }: Props) {
const {
isMobile,
isDrawerOpen,
isLoading,
isCreatingSession,
isLoggedIn,
hasActiveSession,
sessions,
currentSessionId,
handleOpenDrawer,
handleCloseDrawer,
handleDrawerOpenChange,
handleNewChatClick,
handleSessionClick,
hasNextPage,
isFetchingNextPage,
fetchNextPage,
} = useCopilotShell();
if (!isLoggedIn) {
return (
<div className="flex h-full items-center justify-center">
<ChatLoader />
</div>
);
}
return (
<div
className="flex overflow-hidden bg-[#EFEFF0]"
style={{ height: `calc(100vh - ${NAVBAR_HEIGHT_PX}px)` }}
>
{!isMobile && (
<DesktopSidebar
sessions={sessions}
currentSessionId={currentSessionId}
isLoading={isLoading}
hasNextPage={hasNextPage}
isFetchingNextPage={isFetchingNextPage}
onSelectSession={handleSessionClick}
onFetchNextPage={fetchNextPage}
onNewChat={handleNewChatClick}
hasActiveSession={Boolean(hasActiveSession)}
/>
)}
<div className="relative flex min-h-0 flex-1 flex-col">
{isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
<div className="flex min-h-0 flex-1 flex-col">
{isCreatingSession ? (
<div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9]">
<div className="flex flex-col items-center gap-4">
<ChatLoader />
<Text variant="body" className="text-zinc-500">
Creating your chat...
</Text>
</div>
</div>
) : (
children
)}
</div>
</div>
{isMobile && (
<MobileDrawer
isOpen={isDrawerOpen}
sessions={sessions}
currentSessionId={currentSessionId}
isLoading={isLoading}
hasNextPage={hasNextPage}
isFetchingNextPage={isFetchingNextPage}
onSelectSession={handleSessionClick}
onFetchNextPage={fetchNextPage}
onNewChat={handleNewChatClick}
onClose={handleCloseDrawer}
onOpenChange={handleDrawerOpenChange}
hasActiveSession={Boolean(hasActiveSession)}
/>
)}
</div>
);
}

View File

@@ -0,0 +1,70 @@
import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
import { Button } from "@/components/atoms/Button/Button";
import { Text } from "@/components/atoms/Text/Text";
import { scrollbarStyles } from "@/components/styles/scrollbars";
import { cn } from "@/lib/utils";
import { Plus } from "@phosphor-icons/react";
import { SessionsList } from "../SessionsList/SessionsList";
interface Props {
sessions: SessionSummaryResponse[];
currentSessionId: string | null;
isLoading: boolean;
hasNextPage: boolean;
isFetchingNextPage: boolean;
onSelectSession: (sessionId: string) => void;
onFetchNextPage: () => void;
onNewChat: () => void;
hasActiveSession: boolean;
}
export function DesktopSidebar({
sessions,
currentSessionId,
isLoading,
hasNextPage,
isFetchingNextPage,
onSelectSession,
onFetchNextPage,
onNewChat,
hasActiveSession,
}: Props) {
return (
<aside className="flex h-full w-80 flex-col border-r border-zinc-100 bg-zinc-50">
<div className="shrink-0 px-6 py-4">
<Text variant="h3" size="body-medium">
Your chats
</Text>
</div>
<div
className={cn(
"flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
scrollbarStyles,
)}
>
<SessionsList
sessions={sessions}
currentSessionId={currentSessionId}
isLoading={isLoading}
hasNextPage={hasNextPage}
isFetchingNextPage={isFetchingNextPage}
onSelectSession={onSelectSession}
onFetchNextPage={onFetchNextPage}
/>
</div>
{hasActiveSession && (
<div className="shrink-0 bg-zinc-50 p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
<Button
variant="primary"
size="small"
onClick={onNewChat}
className="w-full"
leftIcon={<Plus width="1rem" height="1rem" />}
>
New Chat
</Button>
</div>
)}
</aside>
);
}

View File

@@ -0,0 +1,91 @@
import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
import { Button } from "@/components/atoms/Button/Button";
import { scrollbarStyles } from "@/components/styles/scrollbars";
import { cn } from "@/lib/utils";
import { PlusIcon, X } from "@phosphor-icons/react";
import { Drawer } from "vaul";
import { SessionsList } from "../SessionsList/SessionsList";
interface Props {
isOpen: boolean;
sessions: SessionSummaryResponse[];
currentSessionId: string | null;
isLoading: boolean;
hasNextPage: boolean;
isFetchingNextPage: boolean;
onSelectSession: (sessionId: string) => void;
onFetchNextPage: () => void;
onNewChat: () => void;
onClose: () => void;
onOpenChange: (open: boolean) => void;
hasActiveSession: boolean;
}
export function MobileDrawer({
isOpen,
sessions,
currentSessionId,
isLoading,
hasNextPage,
isFetchingNextPage,
onSelectSession,
onFetchNextPage,
onNewChat,
onClose,
onOpenChange,
hasActiveSession,
}: Props) {
return (
<Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
<Drawer.Portal>
<Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
<Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
<div className="shrink-0 border-b border-zinc-200 p-4">
<div className="flex items-center justify-between">
<Drawer.Title className="text-lg font-semibold text-zinc-800">
Your chats
</Drawer.Title>
<Button
variant="icon"
size="icon"
aria-label="Close sessions"
onClick={onClose}
>
<X width="1.25rem" height="1.25rem" />
</Button>
</div>
</div>
<div
className={cn(
"flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
scrollbarStyles,
)}
>
<SessionsList
sessions={sessions}
currentSessionId={currentSessionId}
isLoading={isLoading}
hasNextPage={hasNextPage}
isFetchingNextPage={isFetchingNextPage}
onSelectSession={onSelectSession}
onFetchNextPage={onFetchNextPage}
/>
</div>
{hasActiveSession && (
<div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
<Button
variant="primary"
size="small"
onClick={onNewChat}
className="w-full"
leftIcon={<PlusIcon width="1rem" height="1rem" />}
>
New Chat
</Button>
</div>
)}
</Drawer.Content>
</Drawer.Portal>
</Drawer.Root>
);
}

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import { useState } from "react";
export function useMobileDrawer() {
const [isDrawerOpen, setIsDrawerOpen] = useState(false);
const handleOpenDrawer = () => {
setIsDrawerOpen(true);
};
const handleCloseDrawer = () => {
setIsDrawerOpen(false);
};
const handleDrawerOpenChange = (open: boolean) => {
setIsDrawerOpen(open);
};
return {
isDrawerOpen,
handleOpenDrawer,
handleCloseDrawer,
handleDrawerOpenChange,
};
}

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import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
import { Skeleton } from "@/components/__legacy__/ui/skeleton";
import { Text } from "@/components/atoms/Text/Text";
import { InfiniteList } from "@/components/molecules/InfiniteList/InfiniteList";
import { cn } from "@/lib/utils";
import { getSessionTitle } from "../../helpers";
interface Props {
sessions: SessionSummaryResponse[];
currentSessionId: string | null;
isLoading: boolean;
hasNextPage: boolean;
isFetchingNextPage: boolean;
onSelectSession: (sessionId: string) => void;
onFetchNextPage: () => void;
}
export function SessionsList({
sessions,
currentSessionId,
isLoading,
hasNextPage,
isFetchingNextPage,
onSelectSession,
onFetchNextPage,
}: Props) {
if (isLoading) {
return (
<div className="space-y-1">
{Array.from({ length: 5 }).map((_, i) => (
<div key={i} className="rounded-lg px-3 py-2.5">
<Skeleton className="h-5 w-full" />
</div>
))}
</div>
);
}
if (sessions.length === 0) {
return (
<div className="flex h-full items-center justify-center">
<Text variant="body" className="text-zinc-500">
You don&apos;t have previous chats
</Text>
</div>
);
}
return (
<InfiniteList
items={sessions}
hasMore={hasNextPage}
isFetchingMore={isFetchingNextPage}
onEndReached={onFetchNextPage}
className="space-y-1"
renderItem={(session) => {
const isActive = session.id === currentSessionId;
return (
<button
onClick={() => onSelectSession(session.id)}
className={cn(
"w-full rounded-lg px-3 py-2.5 text-left transition-colors",
isActive ? "bg-zinc-100" : "hover:bg-zinc-50",
)}
>
<Text
variant="body"
className={cn(
"font-normal",
isActive ? "text-zinc-600" : "text-zinc-800",
)}
>
{getSessionTitle(session)}
</Text>
</button>
);
}}
/>
);
}

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import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
import { okData } from "@/app/api/helpers";
import { useEffect, useState } from "react";
const PAGE_SIZE = 50;
export interface UseSessionsPaginationArgs {
enabled: boolean;
}
export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
const [offset, setOffset] = useState(0);
const [accumulatedSessions, setAccumulatedSessions] = useState<
SessionSummaryResponse[]
>([]);
const [totalCount, setTotalCount] = useState<number | null>(null);
const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
{ limit: PAGE_SIZE, offset },
{
query: {
enabled: enabled && offset >= 0,
},
},
);
useEffect(() => {
const responseData = okData(data);
if (responseData) {
const newSessions = responseData.sessions;
const total = responseData.total;
setTotalCount(total);
if (offset === 0) {
setAccumulatedSessions(newSessions);
} else {
setAccumulatedSessions((prev) => [...prev, ...newSessions]);
}
} else if (!enabled) {
setAccumulatedSessions([]);
setTotalCount(null);
}
}, [data, offset, enabled]);
const hasNextPage =
totalCount !== null && accumulatedSessions.length < totalCount;
const areAllSessionsLoaded =
totalCount !== null &&
accumulatedSessions.length >= totalCount &&
!isFetching &&
!isLoading;
useEffect(() => {
if (
hasNextPage &&
!isFetching &&
!isLoading &&
!isError &&
totalCount !== null
) {
setOffset((prev) => prev + PAGE_SIZE);
}
}, [hasNextPage, isFetching, isLoading, isError, totalCount]);
const fetchNextPage = () => {
if (hasNextPage && !isFetching) {
setOffset((prev) => prev + PAGE_SIZE);
}
};
const reset = () => {
// Only reset the offset - keep existing sessions visible during refetch
// The effect will replace sessions when new data arrives at offset 0
setOffset(0);
};
return {
sessions: accumulatedSessions,
isLoading,
isFetching,
hasNextPage,
areAllSessionsLoaded,
totalCount,
fetchNextPage,
reset,
};
}

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import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
import { format, formatDistanceToNow, isToday } from "date-fns";
export function convertSessionDetailToSummary(session: SessionDetailResponse) {
return {
id: session.id,
created_at: session.created_at,
updated_at: session.updated_at,
title: undefined,
};
}
export function filterVisibleSessions(sessions: SessionSummaryResponse[]) {
const fiveMinutesAgo = Date.now() - 5 * 60 * 1000;
return sessions.filter((session) => {
const hasBeenUpdated = session.updated_at !== session.created_at;
if (hasBeenUpdated) return true;
const isRecentlyCreated =
new Date(session.created_at).getTime() > fiveMinutesAgo;
return isRecentlyCreated;
});
}
export function getSessionTitle(session: SessionSummaryResponse) {
if (session.title) return session.title;
const isNewSession = session.updated_at === session.created_at;
if (isNewSession) {
const createdDate = new Date(session.created_at);
if (isToday(createdDate)) {
return "Today";
}
return format(createdDate, "MMM d, yyyy");
}
return "Untitled Chat";
}
export function getSessionUpdatedLabel(session: SessionSummaryResponse) {
if (!session.updated_at) return "";
return formatDistanceToNow(new Date(session.updated_at), { addSuffix: true });
}
export function mergeCurrentSessionIntoList(
accumulatedSessions: SessionSummaryResponse[],
currentSessionId: string | null,
currentSessionData: SessionDetailResponse | null | undefined,
recentlyCreatedSessions?: Map<string, SessionSummaryResponse>,
) {
const filteredSessions: SessionSummaryResponse[] = [];
const addedIds = new Set<string>();
if (accumulatedSessions.length > 0) {
const visibleSessions = filterVisibleSessions(accumulatedSessions);
if (currentSessionId) {
const currentInAll = accumulatedSessions.find(
(s) => s.id === currentSessionId,
);
if (currentInAll) {
const isInVisible = visibleSessions.some(
(s) => s.id === currentSessionId,
);
if (!isInVisible) {
filteredSessions.push(currentInAll);
addedIds.add(currentInAll.id);
}
}
}
for (const session of visibleSessions) {
if (!addedIds.has(session.id)) {
filteredSessions.push(session);
addedIds.add(session.id);
}
}
}
if (currentSessionId && currentSessionData) {
if (!addedIds.has(currentSessionId)) {
const summarySession = convertSessionDetailToSummary(currentSessionData);
filteredSessions.unshift(summarySession);
addedIds.add(currentSessionId);
}
}
if (recentlyCreatedSessions) {
for (const [sessionId, sessionData] of recentlyCreatedSessions) {
if (!addedIds.has(sessionId)) {
filteredSessions.unshift(sessionData);
addedIds.add(sessionId);
}
}
}
return filteredSessions;
}
export function getCurrentSessionId(searchParams: URLSearchParams) {
return searchParams.get("sessionId");
}

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"use client";
import {
getGetV2GetSessionQueryKey,
getGetV2ListSessionsQueryKey,
useGetV2GetSession,
} from "@/app/api/__generated__/endpoints/chat/chat";
import { okData } from "@/app/api/helpers";
import { useChatStore } from "@/components/contextual/Chat/chat-store";
import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
import { useQueryClient } from "@tanstack/react-query";
import { usePathname, useSearchParams } from "next/navigation";
import { useCopilotStore } from "../../copilot-page-store";
import { useCopilotSessionId } from "../../useCopilotSessionId";
import { useMobileDrawer } from "./components/MobileDrawer/useMobileDrawer";
import { getCurrentSessionId } from "./helpers";
import { useShellSessionList } from "./useShellSessionList";
export function useCopilotShell() {
const pathname = usePathname();
const searchParams = useSearchParams();
const queryClient = useQueryClient();
const breakpoint = useBreakpoint();
const { isLoggedIn } = useSupabase();
const isMobile =
breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
const isOnHomepage = pathname === "/copilot";
const paramSessionId = searchParams.get("sessionId");
const {
isDrawerOpen,
handleOpenDrawer,
handleCloseDrawer,
handleDrawerOpenChange,
} = useMobileDrawer();
const paginationEnabled = !isMobile || isDrawerOpen || !!paramSessionId;
const currentSessionId = getCurrentSessionId(searchParams);
const { data: currentSessionData } = useGetV2GetSession(
currentSessionId || "",
{
query: {
enabled: !!currentSessionId,
select: okData,
},
},
);
const {
sessions,
isLoading,
isSessionsFetching,
hasNextPage,
fetchNextPage,
resetPagination,
recentlyCreatedSessionsRef,
} = useShellSessionList({
paginationEnabled,
currentSessionId,
currentSessionData,
isOnHomepage,
paramSessionId,
});
const stopStream = useChatStore((s) => s.stopStream);
const isCreatingSession = useCopilotStore((s) => s.isCreatingSession);
function handleSessionClick(sessionId: string) {
if (sessionId === currentSessionId) return;
// Stop current stream - SSE reconnection allows resuming later
if (currentSessionId) {
stopStream(currentSessionId);
}
if (recentlyCreatedSessionsRef.current.has(sessionId)) {
queryClient.invalidateQueries({
queryKey: getGetV2GetSessionQueryKey(sessionId),
});
}
setUrlSessionId(sessionId, { shallow: false });
if (isMobile) handleCloseDrawer();
}
function handleNewChatClick() {
// Stop current stream - SSE reconnection allows resuming later
if (currentSessionId) {
stopStream(currentSessionId);
}
resetPagination();
queryClient.invalidateQueries({
queryKey: getGetV2ListSessionsQueryKey(),
});
setUrlSessionId(null, { shallow: false });
if (isMobile) handleCloseDrawer();
}
return {
isMobile,
isDrawerOpen,
isLoggedIn,
hasActiveSession:
Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
isLoading: isLoading || isCreatingSession,
isCreatingSession,
sessions,
currentSessionId: urlSessionId,
handleOpenDrawer,
handleCloseDrawer,
handleDrawerOpenChange,
handleNewChatClick,
handleSessionClick,
hasNextPage,
isFetchingNextPage: isSessionsFetching,
fetchNextPage,
};
}

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import { getGetV2ListSessionsQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
import { useChatStore } from "@/components/contextual/Chat/chat-store";
import { useQueryClient } from "@tanstack/react-query";
import { useEffect, useMemo, useRef } from "react";
import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
import {
convertSessionDetailToSummary,
filterVisibleSessions,
mergeCurrentSessionIntoList,
} from "./helpers";
interface UseShellSessionListArgs {
paginationEnabled: boolean;
currentSessionId: string | null;
currentSessionData: SessionDetailResponse | null | undefined;
isOnHomepage: boolean;
paramSessionId: string | null;
}
export function useShellSessionList({
paginationEnabled,
currentSessionId,
currentSessionData,
isOnHomepage,
paramSessionId,
}: UseShellSessionListArgs) {
const queryClient = useQueryClient();
const onStreamComplete = useChatStore((s) => s.onStreamComplete);
const {
sessions: accumulatedSessions,
isLoading: isSessionsLoading,
isFetching: isSessionsFetching,
hasNextPage,
fetchNextPage,
reset: resetPagination,
} = useSessionsPagination({
enabled: paginationEnabled,
});
const recentlyCreatedSessionsRef = useRef<
Map<string, SessionSummaryResponse>
>(new Map());
useEffect(() => {
if (isOnHomepage && !paramSessionId) {
queryClient.invalidateQueries({
queryKey: getGetV2ListSessionsQueryKey(),
});
}
}, [isOnHomepage, paramSessionId, queryClient]);
useEffect(() => {
if (currentSessionId && currentSessionData) {
const isNewSession =
currentSessionData.updated_at === currentSessionData.created_at;
const isNotInAccumulated = !accumulatedSessions.some(
(s) => s.id === currentSessionId,
);
if (isNewSession || isNotInAccumulated) {
const summary = convertSessionDetailToSummary(currentSessionData);
recentlyCreatedSessionsRef.current.set(currentSessionId, summary);
}
}
}, [currentSessionId, currentSessionData, accumulatedSessions]);
useEffect(() => {
for (const sessionId of recentlyCreatedSessionsRef.current.keys()) {
if (accumulatedSessions.some((s) => s.id === sessionId)) {
recentlyCreatedSessionsRef.current.delete(sessionId);
}
}
}, [accumulatedSessions]);
useEffect(() => {
const unsubscribe = onStreamComplete(() => {
queryClient.invalidateQueries({
queryKey: getGetV2ListSessionsQueryKey(),
});
});
return unsubscribe;
}, [onStreamComplete, queryClient]);
const sessions = useMemo(
() =>
mergeCurrentSessionIntoList(
accumulatedSessions,
currentSessionId,
currentSessionData,
recentlyCreatedSessionsRef.current,
),
[accumulatedSessions, currentSessionId, currentSessionData],
);
const visibleSessions = useMemo(
() => filterVisibleSessions(sessions),
[sessions],
);
const isLoading = isSessionsLoading && accumulatedSessions.length === 0;
return {
sessions: visibleSessions,
isLoading,
isSessionsFetching,
hasNextPage,
fetchNextPage,
resetPagination,
recentlyCreatedSessionsRef,
};
}

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@@ -1,111 +0,0 @@
"use client";
import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
import { Button } from "@/components/atoms/Button/Button";
import { Text } from "@/components/atoms/Text/Text";
import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
import { SpinnerGapIcon } from "@phosphor-icons/react";
import { motion } from "framer-motion";
import { useEffect, useState } from "react";
import {
getGreetingName,
getInputPlaceholder,
getQuickActions,
} from "./helpers";
interface Props {
inputLayoutId: string;
isCreatingSession: boolean;
onCreateSession: () => void | Promise<string>;
onSend: (message: string) => void | Promise<void>;
}
export function EmptySession({
inputLayoutId,
isCreatingSession,
onSend,
}: Props) {
const { user } = useSupabase();
const greetingName = getGreetingName(user);
const quickActions = getQuickActions();
const [loadingAction, setLoadingAction] = useState<string | null>(null);
const [inputPlaceholder, setInputPlaceholder] = useState(
getInputPlaceholder(),
);
useEffect(() => {
setInputPlaceholder(getInputPlaceholder(window.innerWidth));
}, [window.innerWidth]);
async function handleQuickActionClick(action: string) {
if (isCreatingSession || loadingAction) return;
setLoadingAction(action);
try {
await onSend(action);
} finally {
setLoadingAction(null);
}
}
return (
<div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-0 py-5 md:px-6 md:py-10">
<motion.div
className="w-full max-w-3xl text-center"
initial={{ opacity: 0 }}
animate={{ opacity: 1 }}
transition={{ duration: 0.3 }}
>
<div className="mx-auto max-w-3xl">
<Text variant="h3" className="mb-1 !text-[1.375rem] text-zinc-700">
Hey, <span className="text-violet-600">{greetingName}</span>
</Text>
<Text variant="h3" className="mb-8 !font-normal">
Tell me about your work I&apos;ll find what to automate.
</Text>
<div className="mb-6">
<motion.div
layoutId={inputLayoutId}
transition={{ type: "spring", bounce: 0.2, duration: 0.65 }}
className="w-full px-2"
>
<ChatInput
inputId="chat-input-empty"
onSend={onSend}
disabled={isCreatingSession}
placeholder={inputPlaceholder}
className="w-full"
/>
</motion.div>
</div>
</div>
<div className="flex flex-wrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
{quickActions.map((action) => (
<Button
key={action}
type="button"
variant="outline"
size="small"
onClick={() => void handleQuickActionClick(action)}
disabled={isCreatingSession || loadingAction !== null}
aria-busy={loadingAction === action}
leftIcon={
loadingAction === action ? (
<SpinnerGapIcon
className="h-4 w-4 animate-spin"
weight="bold"
/>
) : null
}
className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
>
{action}
</Button>
))}
</div>
</motion.div>
</div>
);
}

View File

@@ -1,140 +0,0 @@
import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
import { Button } from "@/components/atoms/Button/Button";
import { Text } from "@/components/atoms/Text/Text";
import { scrollbarStyles } from "@/components/styles/scrollbars";
import { cn } from "@/lib/utils";
import { PlusIcon, SpinnerGapIcon, X } from "@phosphor-icons/react";
import { Drawer } from "vaul";
interface Props {
isOpen: boolean;
sessions: SessionSummaryResponse[];
currentSessionId: string | null;
isLoading: boolean;
onSelectSession: (sessionId: string) => void;
onNewChat: () => void;
onClose: () => void;
onOpenChange: (open: boolean) => void;
}
function formatDate(dateString: string) {
const date = new Date(dateString);
const now = new Date();
const diffMs = now.getTime() - date.getTime();
const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
if (diffDays === 0) return "Today";
if (diffDays === 1) return "Yesterday";
if (diffDays < 7) return `${diffDays} days ago`;
const day = date.getDate();
const ordinal =
day % 10 === 1 && day !== 11
? "st"
: day % 10 === 2 && day !== 12
? "nd"
: day % 10 === 3 && day !== 13
? "rd"
: "th";
const month = date.toLocaleDateString("en-US", { month: "short" });
const year = date.getFullYear();
return `${day}${ordinal} ${month} ${year}`;
}
export function MobileDrawer({
isOpen,
sessions,
currentSessionId,
isLoading,
onSelectSession,
onNewChat,
onClose,
onOpenChange,
}: Props) {
return (
<Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
<Drawer.Portal>
<Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
<Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
<div className="shrink-0 border-b border-zinc-200 px-4 py-2">
<div className="flex items-center justify-between">
<Drawer.Title className="text-lg font-semibold text-zinc-800">
Your chats
</Drawer.Title>
<Button
variant="icon"
size="icon"
aria-label="Close sessions"
onClick={onClose}
>
<X width="1rem" height="1rem" />
</Button>
</div>
</div>
<div
className={cn(
"flex min-h-0 flex-1 flex-col gap-1 overflow-y-auto px-3 py-3",
scrollbarStyles,
)}
>
{isLoading ? (
<div className="flex items-center justify-center py-4">
<SpinnerGapIcon className="h-5 w-5 animate-spin text-neutral-400" />
</div>
) : sessions.length === 0 ? (
<p className="py-4 text-center text-sm text-neutral-500">
No conversations yet
</p>
) : (
sessions.map((session) => (
<button
key={session.id}
onClick={() => onSelectSession(session.id)}
className={cn(
"w-full rounded-lg px-3 py-2.5 text-left transition-colors",
session.id === currentSessionId
? "bg-zinc-100"
: "hover:bg-zinc-50",
)}
>
<div className="flex min-w-0 max-w-full flex-col overflow-hidden">
<div className="min-w-0 max-w-full">
<Text
variant="body"
className={cn(
"truncate font-normal",
session.id === currentSessionId
? "text-zinc-600"
: "text-zinc-800",
)}
>
{session.title || "Untitled chat"}
</Text>
</div>
<Text variant="small" className="text-neutral-400">
{formatDate(session.updated_at)}
</Text>
</div>
</button>
))
)}
</div>
{currentSessionId && (
<div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
<Button
variant="primary"
size="small"
onClick={onNewChat}
className="w-full"
leftIcon={<PlusIcon width="1rem" height="1rem" />}
>
New Chat
</Button>
</div>
)}
</Drawer.Content>
</Drawer.Portal>
</Drawer.Root>
);
}

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@@ -1,54 +0,0 @@
import { cn } from "@/lib/utils";
import { AnimatePresence, motion } from "framer-motion";
interface Props {
text: string;
className?: string;
}
export function MorphingTextAnimation({ text, className }: Props) {
const letters = text.split("");
return (
<div className={cn(className)}>
<AnimatePresence mode="popLayout" initial={false}>
<motion.div key={text} className="whitespace-nowrap">
<motion.span className="inline-flex overflow-hidden">
{letters.map((char, index) => (
<motion.span
key={`${text}-${index}`}
initial={{
opacity: 0,
y: 8,
rotateX: "80deg",
filter: "blur(6px)",
}}
animate={{
opacity: 1,
y: 0,
rotateX: "0deg",
filter: "blur(0px)",
}}
exit={{
opacity: 0,
y: -8,
rotateX: "-80deg",
filter: "blur(6px)",
}}
style={{ willChange: "transform" }}
transition={{
delay: 0.015 * index,
type: "spring",
bounce: 0.5,
}}
className="inline-block"
>
{char === " " ? "\u00A0" : char}
</motion.span>
))}
</motion.span>
</motion.div>
</AnimatePresence>
</div>
);
}

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@@ -1,69 +0,0 @@
.loader {
position: relative;
animation: rotate 1s infinite;
}
.loader::before,
.loader::after {
border-radius: 50%;
content: "";
display: block;
/* 40% of container size */
height: 40%;
width: 40%;
}
.loader::before {
animation: ball1 1s infinite;
background-color: #a1a1aa; /* zinc-400 */
box-shadow: calc(var(--spacing)) 0 0 #18181b; /* zinc-900 */
margin-bottom: calc(var(--gap));
}
.loader::after {
animation: ball2 1s infinite;
background-color: #18181b; /* zinc-900 */
box-shadow: calc(var(--spacing)) 0 0 #a1a1aa; /* zinc-400 */
}
@keyframes rotate {
0% {
transform: rotate(0deg) scale(0.8);
}
50% {
transform: rotate(360deg) scale(1.2);
}
100% {
transform: rotate(720deg) scale(0.8);
}
}
@keyframes ball1 {
0% {
box-shadow: calc(var(--spacing)) 0 0 #18181b;
}
50% {
box-shadow: 0 0 0 #18181b;
margin-bottom: 0;
transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
}
100% {
box-shadow: calc(var(--spacing)) 0 0 #18181b;
margin-bottom: calc(var(--gap));
}
}
@keyframes ball2 {
0% {
box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
}
50% {
box-shadow: 0 0 0 #a1a1aa;
margin-top: calc(var(--ball-size) * -1);
transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
}
100% {
box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
margin-top: 0;
}
}

View File

@@ -1,28 +0,0 @@
import { cn } from "@/lib/utils";
import styles from "./OrbitLoader.module.css";
interface Props {
size?: number;
className?: string;
}
export function OrbitLoader({ size = 24, className }: Props) {
const ballSize = Math.round(size * 0.4);
const spacing = Math.round(size * 0.6);
const gap = Math.round(size * 0.2);
return (
<div
className={cn(styles.loader, className)}
style={
{
width: size,
height: size,
"--ball-size": `${ballSize}px`,
"--spacing": `${spacing}px`,
"--gap": `${gap}px`,
} as React.CSSProperties
}
/>
);
}

View File

@@ -1,26 +0,0 @@
import { cn } from "@/lib/utils";
interface Props {
value: number;
label?: string;
className?: string;
}
export function ProgressBar({ value, label, className }: Props) {
const clamped = Math.min(100, Math.max(0, value));
return (
<div className={cn("flex flex-col gap-1.5", className)}>
<div className="flex items-center justify-between text-xs text-neutral-500">
<span>{label ?? "Working on it..."}</span>
<span>{Math.round(clamped)}%</span>
</div>
<div className="h-2 w-full overflow-hidden rounded-full bg-neutral-200">
<div
className="h-full rounded-full bg-neutral-900 transition-[width] duration-300 ease-out"
style={{ width: `${clamped}%` }}
/>
</div>
</div>
);
}

View File

@@ -1,34 +0,0 @@
.loader {
position: relative;
display: inline-block;
flex-shrink: 0;
}
.loader::before,
.loader::after {
content: "";
box-sizing: border-box;
width: 100%;
height: 100%;
border-radius: 50%;
background: currentColor;
position: absolute;
left: 0;
top: 0;
animation: ripple 2s linear infinite;
}
.loader::after {
animation-delay: 1s;
}
@keyframes ripple {
0% {
transform: scale(0);
opacity: 1;
}
100% {
transform: scale(1);
opacity: 0;
}
}

View File

@@ -1,16 +0,0 @@
import { cn } from "@/lib/utils";
import styles from "./PulseLoader.module.css";
interface Props {
size?: number;
className?: string;
}
export function PulseLoader({ size = 24, className }: Props) {
return (
<div
className={cn(styles.loader, className)}
style={{ width: size, height: size }}
/>
);
}

View File

@@ -1,35 +0,0 @@
.loader {
width: 48px;
height: 48px;
display: inline-block;
position: relative;
}
.loader::after,
.loader::before {
content: "";
box-sizing: border-box;
width: 100%;
height: 100%;
border-radius: 50%;
background: currentColor;
position: absolute;
left: 0;
top: 0;
animation: animloader 2s linear infinite;
}
.loader::after {
animation-delay: 1s;
}
@keyframes animloader {
0% {
transform: scale(0);
opacity: 1;
}
100% {
transform: scale(1);
opacity: 0;
}
}

View File

@@ -1,16 +0,0 @@
import { cn } from "@/lib/utils";
import styles from "./ScaleLoader.module.css";
interface Props {
size?: number;
className?: string;
}
export function ScaleLoader({ size = 48, className }: Props) {
return (
<div
className={cn(styles.loader, className)}
style={{ width: size, height: size }}
/>
);
}

View File

@@ -1,57 +0,0 @@
.loader {
position: relative;
display: inline-block;
flex-shrink: 0;
transform: rotateZ(45deg);
perspective: 1000px;
border-radius: 50%;
color: currentColor;
}
.loader::before,
.loader::after {
content: "";
display: block;
position: absolute;
top: 0;
left: 0;
width: inherit;
height: inherit;
border-radius: 50%;
transform: rotateX(70deg);
animation: spin 1s linear infinite;
}
.loader::after {
color: var(--spinner-accent, #a855f7);
transform: rotateY(70deg);
animation-delay: 0.4s;
}
@keyframes spin {
0%,
100% {
box-shadow: 0.2em 0 0 0 currentColor;
}
12% {
box-shadow: 0.2em 0.2em 0 0 currentColor;
}
25% {
box-shadow: 0 0.2em 0 0 currentColor;
}
37% {
box-shadow: -0.2em 0.2em 0 0 currentColor;
}
50% {
box-shadow: -0.2em 0 0 0 currentColor;
}
62% {
box-shadow: -0.2em -0.2em 0 0 currentColor;
}
75% {
box-shadow: 0 -0.2em 0 0 currentColor;
}
87% {
box-shadow: 0.2em -0.2em 0 0 currentColor;
}
}

View File

@@ -1,16 +0,0 @@
import { cn } from "@/lib/utils";
import styles from "./SpinnerLoader.module.css";
interface Props {
size?: number;
className?: string;
}
export function SpinnerLoader({ size = 24, className }: Props) {
return (
<div
className={cn(styles.loader, className)}
style={{ width: size, height: size }}
/>
);
}

View File

@@ -1,235 +0,0 @@
import { Link } from "@/components/atoms/Link/Link";
import { Text } from "@/components/atoms/Text/Text";
import { cn } from "@/lib/utils";
/* ------------------------------------------------------------------ */
/* Layout */
/* ------------------------------------------------------------------ */
export function ContentGrid({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return <div className={cn("grid gap-2", className)}>{children}</div>;
}
/* ------------------------------------------------------------------ */
/* Card */
/* ------------------------------------------------------------------ */
export function ContentCard({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<div
className={cn(
"rounded-lg bg-gradient-to-r from-purple-500/30 to-blue-500/30 p-[1px]",
className,
)}
>
<div className="rounded-lg bg-neutral-100 p-3">{children}</div>
</div>
);
}
/** Flex row with a left content area (`children`) and an optional rightside `action`. */
export function ContentCardHeader({
children,
action,
className,
}: {
children: React.ReactNode;
action?: React.ReactNode;
className?: string;
}) {
return (
<div className={cn("flex items-start justify-between gap-2", className)}>
<div className="min-w-0">{children}</div>
{action}
</div>
);
}
export function ContentCardTitle({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<Text
variant="body-medium"
className={cn("truncate text-zinc-800", className)}
>
{children}
</Text>
);
}
export function ContentCardSubtitle({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<Text
variant="small"
className={cn("mt-0.5 truncate font-mono text-zinc-800", className)}
>
{children}
</Text>
);
}
export function ContentCardDescription({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<Text variant="body" className={cn("mt-2 text-zinc-800", className)}>
{children}
</Text>
);
}
/* ------------------------------------------------------------------ */
/* Text */
/* ------------------------------------------------------------------ */
export function ContentMessage({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<Text variant="body" className={cn("text-zinc-800", className)}>
{children}
</Text>
);
}
export function ContentHint({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<Text variant="small" className={cn("text-neutral-500", className)}>
{children}
</Text>
);
}
/* ------------------------------------------------------------------ */
/* Code / data */
/* ------------------------------------------------------------------ */
export function ContentCodeBlock({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<pre
className={cn(
"whitespace-pre-wrap rounded-lg border bg-black p-3 text-xs text-neutral-200",
className,
)}
>
{children}
</pre>
);
}
/* ------------------------------------------------------------------ */
/* Inline elements */
/* ------------------------------------------------------------------ */
export function ContentBadge({
children,
className,
}: {
children: React.ReactNode;
className?: string;
}) {
return (
<Text
variant="small"
as="span"
className={cn(
"shrink-0 rounded-full border bg-muted px-2 py-0.5 text-[11px] text-zinc-800",
className,
)}
>
{children}
</Text>
);
}
export function ContentLink({
href,
children,
className,
...rest
}: Omit<React.ComponentProps<typeof Link>, "className"> & {
className?: string;
}) {
return (
<Link
variant="primary"
isExternal
href={href}
className={cn("shrink-0 text-xs text-purple-500", className)}
{...rest}
>
{children}
</Link>
);
}
/* ------------------------------------------------------------------ */
/* Lists */
/* ------------------------------------------------------------------ */
export function ContentSuggestionsList({
items,
max = 5,
className,
}: {
items: string[];
max?: number;
className?: string;
}) {
if (items.length === 0) return null;
return (
<ul
className={cn(
"mt-2 list-disc space-y-1 pl-5 font-sans text-[0.75rem] leading-[1.125rem] text-zinc-800",
className,
)}
>
{items.slice(0, max).map((s) => (
<li key={s}>{s}</li>
))}
</ul>
);
}

View File

@@ -1,102 +0,0 @@
"use client";
import { cn } from "@/lib/utils";
import { CaretDownIcon } from "@phosphor-icons/react";
import { AnimatePresence, motion, useReducedMotion } from "framer-motion";
import { useId } from "react";
import { useToolAccordion } from "./useToolAccordion";
interface Props {
icon: React.ReactNode;
title: React.ReactNode;
titleClassName?: string;
description?: React.ReactNode;
children: React.ReactNode;
className?: string;
defaultExpanded?: boolean;
expanded?: boolean;
onExpandedChange?: (expanded: boolean) => void;
}
export function ToolAccordion({
icon,
title,
titleClassName,
description,
children,
className,
defaultExpanded,
expanded,
onExpandedChange,
}: Props) {
const shouldReduceMotion = useReducedMotion();
const contentId = useId();
const { isExpanded, toggle } = useToolAccordion({
expanded,
defaultExpanded,
onExpandedChange,
});
return (
<div
className={cn(
"mt-2 w-full rounded-lg border border-slate-200 bg-slate-100 px-3 py-2",
className,
)}
>
<button
type="button"
aria-expanded={isExpanded}
aria-controls={contentId}
onClick={toggle}
className="flex w-full items-center justify-between gap-3 py-1 text-left"
>
<div className="flex min-w-0 items-center gap-3">
<span className="flex shrink-0 items-center text-gray-800">
{icon}
</span>
<div className="min-w-0">
<p
className={cn(
"truncate text-sm font-medium text-gray-800",
titleClassName,
)}
>
{title}
</p>
{description && (
<p className="truncate text-xs text-slate-800">{description}</p>
)}
</div>
</div>
<CaretDownIcon
className={cn(
"h-4 w-4 shrink-0 text-slate-500 transition-transform",
isExpanded && "rotate-180",
)}
weight="bold"
/>
</button>
<AnimatePresence initial={false}>
{isExpanded && (
<motion.div
id={contentId}
initial={{ height: 0, opacity: 0, filter: "blur(10px)" }}
animate={{ height: "auto", opacity: 1, filter: "blur(0px)" }}
exit={{ height: 0, opacity: 0, filter: "blur(10px)" }}
transition={
shouldReduceMotion
? { duration: 0 }
: { type: "spring", bounce: 0.35, duration: 0.55 }
}
className="overflow-hidden"
style={{ willChange: "height, opacity, filter" }}
>
<div className="pb-2 pt-3">{children}</div>
</motion.div>
)}
</AnimatePresence>
</div>
);
}

View File

@@ -1,32 +0,0 @@
import { useState } from "react";
interface UseToolAccordionOptions {
expanded?: boolean;
defaultExpanded?: boolean;
onExpandedChange?: (expanded: boolean) => void;
}
interface UseToolAccordionResult {
isExpanded: boolean;
toggle: () => void;
}
export function useToolAccordion({
expanded,
defaultExpanded = false,
onExpandedChange,
}: UseToolAccordionOptions): UseToolAccordionResult {
const [uncontrolledExpanded, setUncontrolledExpanded] =
useState(defaultExpanded);
const isControlled = typeof expanded === "boolean";
const isExpanded = isControlled ? expanded : uncontrolledExpanded;
function toggle() {
const next = !isExpanded;
if (!isControlled) setUncontrolledExpanded(next);
onExpandedChange?.(next);
}
return { isExpanded, toggle };
}

View File

@@ -0,0 +1,56 @@
"use client";
import { create } from "zustand";
interface CopilotStoreState {
isStreaming: boolean;
isSwitchingSession: boolean;
isCreatingSession: boolean;
isInterruptModalOpen: boolean;
pendingAction: (() => void) | null;
}
interface CopilotStoreActions {
setIsStreaming: (isStreaming: boolean) => void;
setIsSwitchingSession: (isSwitchingSession: boolean) => void;
setIsCreatingSession: (isCreating: boolean) => void;
openInterruptModal: (onConfirm: () => void) => void;
confirmInterrupt: () => void;
cancelInterrupt: () => void;
}
type CopilotStore = CopilotStoreState & CopilotStoreActions;
export const useCopilotStore = create<CopilotStore>((set, get) => ({
isStreaming: false,
isSwitchingSession: false,
isCreatingSession: false,
isInterruptModalOpen: false,
pendingAction: null,
setIsStreaming(isStreaming) {
set({ isStreaming });
},
setIsSwitchingSession(isSwitchingSession) {
set({ isSwitchingSession });
},
setIsCreatingSession(isCreatingSession) {
set({ isCreatingSession });
},
openInterruptModal(onConfirm) {
set({ isInterruptModalOpen: true, pendingAction: onConfirm });
},
confirmInterrupt() {
const { pendingAction } = get();
set({ isInterruptModalOpen: false, pendingAction: null });
if (pendingAction) pendingAction();
},
cancelInterrupt() {
set({ isInterruptModalOpen: false, pendingAction: null });
},
}));

View File

@@ -1,26 +1,6 @@
import { User } from "@supabase/supabase-js";
import type { User } from "@supabase/supabase-js";
export function getInputPlaceholder(width?: number) {
if (!width) return "What's your role and what eats up most of your day?";
if (width < 500) {
return "I'm a chef and I hate...";
}
if (width <= 1080) {
return "What's your role and what eats up most of your day?";
}
return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
}
export function getQuickActions() {
return [
"I don't know where to start, just ask me stuff",
"I do the same thing every week and it's killing me",
"Help me find where I'm wasting my time",
];
}
export function getGreetingName(user?: User | null) {
export function getGreetingName(user?: User | null): string {
if (!user) return "there";
const metadata = user.user_metadata as Record<string, unknown> | undefined;
const fullName = metadata?.full_name;
@@ -36,3 +16,30 @@ export function getGreetingName(user?: User | null) {
}
return "there";
}
export function buildCopilotChatUrl(prompt: string): string {
const trimmed = prompt.trim();
if (!trimmed) return "/copilot/chat";
const encoded = encodeURIComponent(trimmed);
return `/copilot/chat?prompt=${encoded}`;
}
export function getQuickActions(): string[] {
return [
"I don't know where to start, just ask me stuff",
"I do the same thing every week and it's killing me",
"Help me find where I'm wasting my time",
];
}
export function getInputPlaceholder(width?: number) {
if (!width) return "What's your role and what eats up most of your day?";
if (width < 500) {
return "I'm a chef and I hate...";
}
if (width <= 1080) {
return "What's your role and what eats up most of your day?";
}
return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
}

View File

@@ -1,128 +0,0 @@
import type { UIMessage, UIDataTypes, UITools } from "ai";
interface SessionChatMessage {
role: string;
content: string | null;
tool_call_id: string | null;
tool_calls: unknown[] | null;
}
function coerceSessionChatMessages(
rawMessages: unknown[],
): SessionChatMessage[] {
return rawMessages
.map((m) => {
if (!m || typeof m !== "object") return null;
const msg = m as Record<string, unknown>;
const role = typeof msg.role === "string" ? msg.role : null;
if (!role) return null;
return {
role,
content:
typeof msg.content === "string"
? msg.content
: msg.content == null
? null
: String(msg.content),
tool_call_id:
typeof msg.tool_call_id === "string"
? msg.tool_call_id
: msg.tool_call_id == null
? null
: String(msg.tool_call_id),
tool_calls: Array.isArray(msg.tool_calls) ? msg.tool_calls : null,
};
})
.filter((m): m is SessionChatMessage => m !== null);
}
function safeJsonParse(value: string): unknown {
try {
return JSON.parse(value) as unknown;
} catch {
return value;
}
}
function toToolInput(rawArguments: unknown): unknown {
if (typeof rawArguments === "string") {
const trimmed = rawArguments.trim();
return trimmed ? safeJsonParse(trimmed) : {};
}
if (rawArguments && typeof rawArguments === "object") return rawArguments;
return {};
}
export function convertChatSessionMessagesToUiMessages(
sessionId: string,
rawMessages: unknown[],
): UIMessage<unknown, UIDataTypes, UITools>[] {
const messages = coerceSessionChatMessages(rawMessages);
const toolOutputsByCallId = new Map<string, unknown>();
for (const msg of messages) {
if (msg.role !== "tool") continue;
if (!msg.tool_call_id) continue;
if (msg.content == null) continue;
toolOutputsByCallId.set(msg.tool_call_id, msg.content);
}
const uiMessages: UIMessage<unknown, UIDataTypes, UITools>[] = [];
messages.forEach((msg, index) => {
if (msg.role === "tool") return;
if (msg.role !== "user" && msg.role !== "assistant") return;
const parts: UIMessage<unknown, UIDataTypes, UITools>["parts"] = [];
if (typeof msg.content === "string" && msg.content.trim()) {
parts.push({ type: "text", text: msg.content, state: "done" });
}
if (msg.role === "assistant" && Array.isArray(msg.tool_calls)) {
for (const rawToolCall of msg.tool_calls) {
if (!rawToolCall || typeof rawToolCall !== "object") continue;
const toolCall = rawToolCall as {
id?: unknown;
function?: { name?: unknown; arguments?: unknown };
};
const toolCallId = String(toolCall.id ?? "").trim();
const toolName = String(toolCall.function?.name ?? "").trim();
if (!toolCallId || !toolName) continue;
const input = toToolInput(toolCall.function?.arguments);
const output = toolOutputsByCallId.get(toolCallId);
if (output !== undefined) {
parts.push({
type: `tool-${toolName}`,
toolCallId,
state: "output-available",
input,
output: typeof output === "string" ? safeJsonParse(output) : output,
});
} else {
parts.push({
type: `tool-${toolName}`,
toolCallId,
state: "input-available",
input,
});
}
}
}
if (parts.length === 0) return;
uiMessages.push({
id: `${sessionId}-${index}`,
role: msg.role,
parts,
});
});
return uiMessages;
}

View File

@@ -0,0 +1,13 @@
"use client";
import { FeatureFlagPage } from "@/services/feature-flags/FeatureFlagPage";
import { Flag } from "@/services/feature-flags/use-get-flag";
import { type ReactNode } from "react";
import { CopilotShell } from "./components/CopilotShell/CopilotShell";
export default function CopilotLayout({ children }: { children: ReactNode }) {
return (
<FeatureFlagPage flag={Flag.CHAT} whenDisabled="/library">
<CopilotShell>{children}</CopilotShell>
</FeatureFlagPage>
);
}

View File

@@ -1,13 +1,149 @@
"use client";
import { FeatureFlagPage } from "@/services/feature-flags/FeatureFlagPage";
import { Flag } from "@/services/feature-flags/use-get-flag";
import { CopilotPage } from "./CopilotPage";
import { Button } from "@/components/atoms/Button/Button";
import { Skeleton } from "@/components/atoms/Skeleton/Skeleton";
import { Text } from "@/components/atoms/Text/Text";
import { Chat } from "@/components/contextual/Chat/Chat";
import { ChatInput } from "@/components/contextual/Chat/components/ChatInput/ChatInput";
import { Dialog } from "@/components/molecules/Dialog/Dialog";
import { useEffect, useState } from "react";
import { useCopilotStore } from "./copilot-page-store";
import { getInputPlaceholder } from "./helpers";
import { useCopilotPage } from "./useCopilotPage";
export default function CopilotPage() {
const { state, handlers } = useCopilotPage();
const isInterruptModalOpen = useCopilotStore((s) => s.isInterruptModalOpen);
const confirmInterrupt = useCopilotStore((s) => s.confirmInterrupt);
const cancelInterrupt = useCopilotStore((s) => s.cancelInterrupt);
const [inputPlaceholder, setInputPlaceholder] = useState(
getInputPlaceholder(),
);
useEffect(() => {
const handleResize = () => {
setInputPlaceholder(getInputPlaceholder(window.innerWidth));
};
handleResize();
window.addEventListener("resize", handleResize);
return () => window.removeEventListener("resize", handleResize);
}, []);
const { greetingName, quickActions, isLoading, hasSession, initialPrompt } =
state;
const {
handleQuickAction,
startChatWithPrompt,
handleSessionNotFound,
handleStreamingChange,
} = handlers;
if (hasSession) {
return (
<div className="flex h-full flex-col">
<Chat
className="flex-1"
initialPrompt={initialPrompt}
onSessionNotFound={handleSessionNotFound}
onStreamingChange={handleStreamingChange}
/>
<Dialog
title="Interrupt current chat?"
styling={{ maxWidth: 300, width: "100%" }}
controlled={{
isOpen: isInterruptModalOpen,
set: (open) => {
if (!open) cancelInterrupt();
},
}}
onClose={cancelInterrupt}
>
<Dialog.Content>
<div className="flex flex-col gap-4">
<Text variant="body">
The current chat response will be interrupted. Are you sure you
want to continue?
</Text>
<Dialog.Footer>
<Button
type="button"
variant="outline"
onClick={cancelInterrupt}
>
Cancel
</Button>
<Button
type="button"
variant="primary"
onClick={confirmInterrupt}
>
Continue
</Button>
</Dialog.Footer>
</div>
</Dialog.Content>
</Dialog>
</div>
);
}
export default function Page() {
return (
<FeatureFlagPage flag={Flag.CHAT} whenDisabled="/library">
<CopilotPage />
</FeatureFlagPage>
<div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-3 py-5 md:px-6 md:py-10">
<div className="w-full text-center">
{isLoading ? (
<div className="mx-auto max-w-2xl">
<Skeleton className="mx-auto mb-3 h-8 w-64" />
<Skeleton className="mx-auto mb-8 h-6 w-80" />
<div className="mb-8">
<Skeleton className="mx-auto h-14 w-full rounded-lg" />
</div>
<div className="flex flex-wrap items-center justify-center gap-3">
{Array.from({ length: 4 }).map((_, i) => (
<Skeleton key={i} className="h-9 w-48 rounded-md" />
))}
</div>
</div>
) : (
<>
<div className="mx-auto max-w-3xl">
<Text
variant="h3"
className="mb-1 !text-[1.375rem] text-zinc-700"
>
Hey, <span className="text-violet-600">{greetingName}</span>
</Text>
<Text variant="h3" className="mb-8 !font-normal">
Tell me about your work I&apos;ll find what to automate.
</Text>
<div className="mb-6">
<ChatInput
onSend={startChatWithPrompt}
placeholder={inputPlaceholder}
/>
</div>
</div>
<div className="flex flex-wrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
{quickActions.map((action) => (
<Button
key={action}
type="button"
variant="outline"
size="small"
onClick={() => handleQuickAction(action)}
className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
>
{action}
</Button>
))}
</div>
</>
)}
</div>
</div>
);
}

View File

@@ -1,235 +0,0 @@
"use client";
import { WarningDiamondIcon } from "@phosphor-icons/react";
import type { ToolUIPart } from "ai";
import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
import {
ContentCardDescription,
ContentCodeBlock,
ContentGrid,
ContentHint,
ContentLink,
ContentMessage,
} from "../../components/ToolAccordion/AccordionContent";
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
import {
ClarificationQuestionsCard,
ClarifyingQuestion,
} from "./components/ClarificationQuestionsCard";
import {
AccordionIcon,
formatMaybeJson,
getAnimationText,
getCreateAgentToolOutput,
isAgentPreviewOutput,
isAgentSavedOutput,
isClarificationNeededOutput,
isErrorOutput,
isOperationInProgressOutput,
isOperationPendingOutput,
isOperationStartedOutput,
ToolIcon,
truncateText,
type CreateAgentToolOutput,
} from "./helpers";
export interface CreateAgentToolPart {
type: string;
toolCallId: string;
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}
interface Props {
part: CreateAgentToolPart;
}
function getAccordionMeta(output: CreateAgentToolOutput) {
const icon = <AccordionIcon />;
if (isAgentSavedOutput(output)) {
return { icon, title: output.agent_name };
}
if (isAgentPreviewOutput(output)) {
return {
icon,
title: output.agent_name,
description: `${output.node_count} block${output.node_count === 1 ? "" : "s"}`,
};
}
if (isClarificationNeededOutput(output)) {
const questions = output.questions ?? [];
return {
icon,
title: "Needs clarification",
description: `${questions.length} question${questions.length === 1 ? "" : "s"}`,
expanded: true,
};
}
if (
isOperationStartedOutput(output) ||
isOperationPendingOutput(output) ||
isOperationInProgressOutput(output)
) {
return {
icon: <OrbitLoader size={32} />,
title: "Creating agent, this may take a few minutes. Sit back and relax.",
};
}
return {
icon: (
<WarningDiamondIcon size={32} weight="light" className="text-red-500" />
),
title: "Error",
titleClassName: "text-red-500",
};
}
export function CreateAgentTool({ part }: Props) {
const text = getAnimationText(part);
const { onSend } = useCopilotChatActions();
const isStreaming =
part.state === "input-streaming" || part.state === "input-available";
const output = getCreateAgentToolOutput(part);
const isError =
part.state === "output-error" || (!!output && isErrorOutput(output));
const isOperating =
!!output &&
(isOperationStartedOutput(output) ||
isOperationPendingOutput(output) ||
isOperationInProgressOutput(output));
const progress = useAsymptoticProgress(isOperating);
const hasExpandableContent =
part.state === "output-available" &&
!!output &&
(isOperationStartedOutput(output) ||
isOperationPendingOutput(output) ||
isOperationInProgressOutput(output) ||
isAgentPreviewOutput(output) ||
isAgentSavedOutput(output) ||
isClarificationNeededOutput(output) ||
isErrorOutput(output));
function handleClarificationAnswers(answers: Record<string, string>) {
const questions =
output && isClarificationNeededOutput(output)
? (output.questions ?? [])
: [];
const contextMessage = questions
.map((q) => {
const answer = answers[q.keyword] || "";
return `> ${q.question}\n\n${answer}`;
})
.join("\n\n");
onSend(
`**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
);
}
return (
<div className="py-2">
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ToolIcon isStreaming={isStreaming} isError={isError} />
<MorphingTextAnimation
text={text}
className={isError ? "text-red-500" : undefined}
/>
</div>
{hasExpandableContent && output && (
<ToolAccordion {...getAccordionMeta(output)}>
{isOperating && (
<ContentGrid>
<ProgressBar value={progress} className="max-w-[280px]" />
<ContentHint>
This could take a few minutes, grab a coffee
</ContentHint>
</ContentGrid>
)}
{isAgentSavedOutput(output) && (
<ContentGrid>
<ContentMessage>{output.message}</ContentMessage>
<div className="flex flex-wrap gap-2">
<ContentLink href={output.library_agent_link}>
Open in library
</ContentLink>
<ContentLink href={output.agent_page_link}>
Open in builder
</ContentLink>
</div>
<ContentCodeBlock>
{truncateText(
formatMaybeJson({ agent_id: output.agent_id }),
800,
)}
</ContentCodeBlock>
</ContentGrid>
)}
{isAgentPreviewOutput(output) && (
<ContentGrid>
<ContentMessage>{output.message}</ContentMessage>
{output.description?.trim() && (
<ContentCardDescription>
{output.description}
</ContentCardDescription>
)}
<ContentCodeBlock>
{truncateText(formatMaybeJson(output.agent_json), 1600)}
</ContentCodeBlock>
</ContentGrid>
)}
{isClarificationNeededOutput(output) && (
<ClarificationQuestionsCard
questions={(output.questions ?? []).map((q) => {
const item: ClarifyingQuestion = {
question: q.question,
keyword: q.keyword,
};
const example =
typeof q.example === "string" && q.example.trim()
? q.example.trim()
: null;
if (example) item.example = example;
return item;
})}
message={output.message}
onSubmitAnswers={handleClarificationAnswers}
/>
)}
{isErrorOutput(output) && (
<ContentGrid>
<ContentMessage>{output.message}</ContentMessage>
{output.error && (
<ContentCodeBlock>
{formatMaybeJson(output.error)}
</ContentCodeBlock>
)}
{output.details && (
<ContentCodeBlock>
{formatMaybeJson(output.details)}
</ContentCodeBlock>
)}
</ContentGrid>
)}
</ToolAccordion>
)}
</div>
);
}

View File

@@ -1,186 +0,0 @@
import type { AgentPreviewResponse } from "@/app/api/__generated__/models/agentPreviewResponse";
import type { AgentSavedResponse } from "@/app/api/__generated__/models/agentSavedResponse";
import type { ClarificationNeededResponse } from "@/app/api/__generated__/models/clarificationNeededResponse";
import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
import type { OperationInProgressResponse } from "@/app/api/__generated__/models/operationInProgressResponse";
import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
import { ResponseType } from "@/app/api/__generated__/models/responseType";
import {
PlusCircleIcon,
PlusIcon,
WarningDiamondIcon,
} from "@phosphor-icons/react";
import type { ToolUIPart } from "ai";
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
export type CreateAgentToolOutput =
| OperationStartedResponse
| OperationPendingResponse
| OperationInProgressResponse
| AgentPreviewResponse
| AgentSavedResponse
| ClarificationNeededResponse
| ErrorResponse;
function parseOutput(output: unknown): CreateAgentToolOutput | null {
if (!output) return null;
if (typeof output === "string") {
const trimmed = output.trim();
if (!trimmed) return null;
try {
return parseOutput(JSON.parse(trimmed) as unknown);
} catch {
return null;
}
}
if (typeof output === "object") {
const type = (output as { type?: unknown }).type;
if (
type === ResponseType.operation_started ||
type === ResponseType.operation_pending ||
type === ResponseType.operation_in_progress ||
type === ResponseType.agent_preview ||
type === ResponseType.agent_saved ||
type === ResponseType.clarification_needed ||
type === ResponseType.error
) {
return output as CreateAgentToolOutput;
}
if ("operation_id" in output && "tool_name" in output)
return output as OperationStartedResponse | OperationPendingResponse;
if ("tool_call_id" in output) return output as OperationInProgressResponse;
if ("agent_json" in output && "agent_name" in output)
return output as AgentPreviewResponse;
if ("agent_id" in output && "library_agent_id" in output)
return output as AgentSavedResponse;
if ("questions" in output) return output as ClarificationNeededResponse;
if ("error" in output || "details" in output)
return output as ErrorResponse;
}
return null;
}
export function getCreateAgentToolOutput(
part: unknown,
): CreateAgentToolOutput | null {
if (!part || typeof part !== "object") return null;
return parseOutput((part as { output?: unknown }).output);
}
export function isOperationStartedOutput(
output: CreateAgentToolOutput,
): output is OperationStartedResponse {
return (
output.type === ResponseType.operation_started ||
("operation_id" in output && "tool_name" in output)
);
}
export function isOperationPendingOutput(
output: CreateAgentToolOutput,
): output is OperationPendingResponse {
return output.type === ResponseType.operation_pending;
}
export function isOperationInProgressOutput(
output: CreateAgentToolOutput,
): output is OperationInProgressResponse {
return (
output.type === ResponseType.operation_in_progress ||
"tool_call_id" in output
);
}
export function isAgentPreviewOutput(
output: CreateAgentToolOutput,
): output is AgentPreviewResponse {
return output.type === ResponseType.agent_preview || "agent_json" in output;
}
export function isAgentSavedOutput(
output: CreateAgentToolOutput,
): output is AgentSavedResponse {
return (
output.type === ResponseType.agent_saved || "agent_page_link" in output
);
}
export function isClarificationNeededOutput(
output: CreateAgentToolOutput,
): output is ClarificationNeededResponse {
return (
output.type === ResponseType.clarification_needed || "questions" in output
);
}
export function isErrorOutput(
output: CreateAgentToolOutput,
): output is ErrorResponse {
return output.type === ResponseType.error || "error" in output;
}
export function getAnimationText(part: {
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}): string {
switch (part.state) {
case "input-streaming":
case "input-available":
return "Creating a new agent";
case "output-available": {
const output = parseOutput(part.output);
if (!output) return "Creating a new agent";
if (isOperationStartedOutput(output)) return "Agent creation started";
if (isOperationPendingOutput(output)) return "Agent creation in progress";
if (isOperationInProgressOutput(output))
return "Agent creation already in progress";
if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
if (isClarificationNeededOutput(output)) return "Needs clarification";
return "Error creating agent";
}
case "output-error":
return "Error creating agent";
default:
return "Creating a new agent";
}
}
export function ToolIcon({
isStreaming,
isError,
}: {
isStreaming?: boolean;
isError?: boolean;
}) {
if (isError) {
return (
<WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
);
}
if (isStreaming) {
return <OrbitLoader size={24} />;
}
return <PlusIcon size={14} weight="regular" className="text-neutral-400" />;
}
export function AccordionIcon() {
return <PlusCircleIcon size={32} weight="light" />;
}
export function formatMaybeJson(value: unknown): string {
if (typeof value === "string") return value;
try {
return JSON.stringify(value, null, 2);
} catch {
return String(value);
}
}
export function truncateText(text: string, maxChars: number): string {
const trimmed = text.trim();
if (trimmed.length <= maxChars) return trimmed;
return `${trimmed.slice(0, maxChars).trimEnd()}`;
}

View File

@@ -1,231 +0,0 @@
"use client";
import { WarningDiamondIcon } from "@phosphor-icons/react";
import type { ToolUIPart } from "ai";
import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
import {
ContentCardDescription,
ContentCodeBlock,
ContentGrid,
ContentHint,
ContentLink,
ContentMessage,
} from "../../components/ToolAccordion/AccordionContent";
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
import {
ClarificationQuestionsCard,
ClarifyingQuestion,
} from "../CreateAgent/components/ClarificationQuestionsCard";
import {
AccordionIcon,
formatMaybeJson,
getAnimationText,
getEditAgentToolOutput,
isAgentPreviewOutput,
isAgentSavedOutput,
isClarificationNeededOutput,
isErrorOutput,
isOperationInProgressOutput,
isOperationPendingOutput,
isOperationStartedOutput,
ToolIcon,
truncateText,
type EditAgentToolOutput,
} from "./helpers";
export interface EditAgentToolPart {
type: string;
toolCallId: string;
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}
interface Props {
part: EditAgentToolPart;
}
function getAccordionMeta(output: EditAgentToolOutput): {
icon: React.ReactNode;
title: string;
titleClassName?: string;
description?: string;
} {
const icon = <AccordionIcon />;
if (isAgentSavedOutput(output)) {
return { icon, title: output.agent_name };
}
if (isAgentPreviewOutput(output)) {
return {
icon,
title: output.agent_name,
description: `${output.node_count} block${output.node_count === 1 ? "" : "s"}`,
};
}
if (isClarificationNeededOutput(output)) {
const questions = output.questions ?? [];
return {
icon,
title: "Needs clarification",
description: `${questions.length} question${questions.length === 1 ? "" : "s"}`,
};
}
if (
isOperationStartedOutput(output) ||
isOperationPendingOutput(output) ||
isOperationInProgressOutput(output)
) {
return { icon: <OrbitLoader size={32} />, title: "Editing agent" };
}
return {
icon: (
<WarningDiamondIcon size={32} weight="light" className="text-red-500" />
),
title: "Error",
titleClassName: "text-red-500",
};
}
export function EditAgentTool({ part }: Props) {
const text = getAnimationText(part);
const { onSend } = useCopilotChatActions();
const isStreaming =
part.state === "input-streaming" || part.state === "input-available";
const output = getEditAgentToolOutput(part);
const isError =
part.state === "output-error" || (!!output && isErrorOutput(output));
const isOperating =
!!output &&
(isOperationStartedOutput(output) ||
isOperationPendingOutput(output) ||
isOperationInProgressOutput(output));
const progress = useAsymptoticProgress(isOperating);
const hasExpandableContent =
part.state === "output-available" &&
!!output &&
(isOperationStartedOutput(output) ||
isOperationPendingOutput(output) ||
isOperationInProgressOutput(output) ||
isAgentPreviewOutput(output) ||
isAgentSavedOutput(output) ||
isClarificationNeededOutput(output) ||
isErrorOutput(output));
function handleClarificationAnswers(answers: Record<string, string>) {
const questions =
output && isClarificationNeededOutput(output)
? (output.questions ?? [])
: [];
const contextMessage = questions
.map((q) => {
const answer = answers[q.keyword] || "";
return `> ${q.question}\n\n${answer}`;
})
.join("\n\n");
onSend(
`**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with editing the agent.`,
);
}
return (
<div className="py-2">
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ToolIcon isStreaming={isStreaming} isError={isError} />
<MorphingTextAnimation
text={text}
className={isError ? "text-red-500" : undefined}
/>
</div>
{hasExpandableContent && output && (
<ToolAccordion {...getAccordionMeta(output)}>
{isOperating && (
<ContentGrid>
<ProgressBar value={progress} className="max-w-[280px]" />
<ContentHint>
This could take a few minutes, grab a coffee
</ContentHint>
</ContentGrid>
)}
{isAgentSavedOutput(output) && (
<ContentGrid>
<ContentMessage>{output.message}</ContentMessage>
<div className="flex flex-wrap gap-2">
<ContentLink href={output.library_agent_link}>
Open in library
</ContentLink>
<ContentLink href={output.agent_page_link}>
Open in builder
</ContentLink>
</div>
<ContentCodeBlock>
{truncateText(
formatMaybeJson({ agent_id: output.agent_id }),
800,
)}
</ContentCodeBlock>
</ContentGrid>
)}
{isAgentPreviewOutput(output) && (
<ContentGrid>
<ContentMessage>{output.message}</ContentMessage>
{output.description?.trim() && (
<ContentCardDescription>
{output.description}
</ContentCardDescription>
)}
<ContentCodeBlock>
{truncateText(formatMaybeJson(output.agent_json), 1600)}
</ContentCodeBlock>
</ContentGrid>
)}
{isClarificationNeededOutput(output) && (
<ClarificationQuestionsCard
questions={(output.questions ?? []).map((q) => {
const item: ClarifyingQuestion = {
question: q.question,
keyword: q.keyword,
};
const example =
typeof q.example === "string" && q.example.trim()
? q.example.trim()
: null;
if (example) item.example = example;
return item;
})}
message={output.message}
onSubmitAnswers={handleClarificationAnswers}
/>
)}
{isErrorOutput(output) && (
<ContentGrid>
<ContentMessage>{output.message}</ContentMessage>
{output.error && (
<ContentCodeBlock>
{formatMaybeJson(output.error)}
</ContentCodeBlock>
)}
{output.details && (
<ContentCodeBlock>
{formatMaybeJson(output.details)}
</ContentCodeBlock>
)}
</ContentGrid>
)}
</ToolAccordion>
)}
</div>
);
}

View File

@@ -1,188 +0,0 @@
import type { AgentPreviewResponse } from "@/app/api/__generated__/models/agentPreviewResponse";
import type { AgentSavedResponse } from "@/app/api/__generated__/models/agentSavedResponse";
import type { ClarificationNeededResponse } from "@/app/api/__generated__/models/clarificationNeededResponse";
import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
import type { OperationInProgressResponse } from "@/app/api/__generated__/models/operationInProgressResponse";
import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
import { ResponseType } from "@/app/api/__generated__/models/responseType";
import {
NotePencilIcon,
PencilLineIcon,
WarningDiamondIcon,
} from "@phosphor-icons/react";
import type { ToolUIPart } from "ai";
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
export type EditAgentToolOutput =
| OperationStartedResponse
| OperationPendingResponse
| OperationInProgressResponse
| AgentPreviewResponse
| AgentSavedResponse
| ClarificationNeededResponse
| ErrorResponse;
function parseOutput(output: unknown): EditAgentToolOutput | null {
if (!output) return null;
if (typeof output === "string") {
const trimmed = output.trim();
if (!trimmed) return null;
try {
return parseOutput(JSON.parse(trimmed) as unknown);
} catch {
return null;
}
}
if (typeof output === "object") {
const type = (output as { type?: unknown }).type;
if (
type === ResponseType.operation_started ||
type === ResponseType.operation_pending ||
type === ResponseType.operation_in_progress ||
type === ResponseType.agent_preview ||
type === ResponseType.agent_saved ||
type === ResponseType.clarification_needed ||
type === ResponseType.error
) {
return output as EditAgentToolOutput;
}
if ("operation_id" in output && "tool_name" in output)
return output as OperationStartedResponse | OperationPendingResponse;
if ("tool_call_id" in output) return output as OperationInProgressResponse;
if ("agent_json" in output && "agent_name" in output)
return output as AgentPreviewResponse;
if ("agent_id" in output && "library_agent_id" in output)
return output as AgentSavedResponse;
if ("questions" in output) return output as ClarificationNeededResponse;
if ("error" in output || "details" in output)
return output as ErrorResponse;
}
return null;
}
export function getEditAgentToolOutput(
part: unknown,
): EditAgentToolOutput | null {
if (!part || typeof part !== "object") return null;
return parseOutput((part as { output?: unknown }).output);
}
export function isOperationStartedOutput(
output: EditAgentToolOutput,
): output is OperationStartedResponse {
return (
output.type === ResponseType.operation_started ||
("operation_id" in output && "tool_name" in output)
);
}
export function isOperationPendingOutput(
output: EditAgentToolOutput,
): output is OperationPendingResponse {
return output.type === ResponseType.operation_pending;
}
export function isOperationInProgressOutput(
output: EditAgentToolOutput,
): output is OperationInProgressResponse {
return (
output.type === ResponseType.operation_in_progress ||
"tool_call_id" in output
);
}
export function isAgentPreviewOutput(
output: EditAgentToolOutput,
): output is AgentPreviewResponse {
return output.type === ResponseType.agent_preview || "agent_json" in output;
}
export function isAgentSavedOutput(
output: EditAgentToolOutput,
): output is AgentSavedResponse {
return (
output.type === ResponseType.agent_saved || "agent_page_link" in output
);
}
export function isClarificationNeededOutput(
output: EditAgentToolOutput,
): output is ClarificationNeededResponse {
return (
output.type === ResponseType.clarification_needed || "questions" in output
);
}
export function isErrorOutput(
output: EditAgentToolOutput,
): output is ErrorResponse {
return output.type === ResponseType.error || "error" in output;
}
export function getAnimationText(part: {
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}): string {
switch (part.state) {
case "input-streaming":
case "input-available":
return "Editing the agent";
case "output-available": {
const output = parseOutput(part.output);
if (!output) return "Editing the agent";
if (isOperationStartedOutput(output)) return "Agent update started";
if (isOperationPendingOutput(output)) return "Agent update in progress";
if (isOperationInProgressOutput(output))
return "Agent update already in progress";
if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
if (isClarificationNeededOutput(output)) return "Needs clarification";
return "Error editing agent";
}
case "output-error":
return "Error editing agent";
default:
return "Editing the agent";
}
}
export function ToolIcon({
isStreaming,
isError,
}: {
isStreaming?: boolean;
isError?: boolean;
}) {
if (isError) {
return (
<WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
);
}
if (isStreaming) {
return <OrbitLoader size={24} />;
}
return (
<PencilLineIcon size={14} weight="regular" className="text-neutral-400" />
);
}
export function AccordionIcon() {
return <NotePencilIcon size={32} weight="light" />;
}
export function formatMaybeJson(value: unknown): string {
if (typeof value === "string") return value;
try {
return JSON.stringify(value, null, 2);
} catch {
return String(value);
}
}
export function truncateText(text: string, maxChars: number): string {
const trimmed = text.trim();
if (trimmed.length <= maxChars) return trimmed;
return `${trimmed.slice(0, maxChars).trimEnd()}`;
}

View File

@@ -1,127 +0,0 @@
"use client";
import { ToolUIPart } from "ai";
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
import {
ContentBadge,
ContentCard,
ContentCardDescription,
ContentCardHeader,
ContentCardTitle,
ContentGrid,
ContentLink,
} from "../../components/ToolAccordion/AccordionContent";
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
import {
AccordionIcon,
getAgentHref,
getAnimationText,
getFindAgentsOutput,
getSourceLabelFromToolType,
isAgentsFoundOutput,
isErrorOutput,
ToolIcon,
} from "./helpers";
export interface FindAgentsToolPart {
type: string;
toolCallId: string;
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}
interface Props {
part: FindAgentsToolPart;
}
export function FindAgentsTool({ part }: Props) {
const text = getAnimationText(part);
const output = getFindAgentsOutput(part);
const isStreaming =
part.state === "input-streaming" || part.state === "input-available";
const isError =
part.state === "output-error" || (!!output && isErrorOutput(output));
const query =
typeof part.input === "object" && part.input !== null
? String((part.input as { query?: unknown }).query ?? "").trim()
: "";
const agentsFoundOutput =
part.state === "output-available" && output && isAgentsFoundOutput(output)
? output
: null;
const hasAgents =
!!agentsFoundOutput &&
agentsFoundOutput.agents.length > 0 &&
(typeof agentsFoundOutput.count !== "number" ||
agentsFoundOutput.count > 0);
const totalCount = agentsFoundOutput ? agentsFoundOutput.count : 0;
const { source } = getSourceLabelFromToolType(part.type);
const scopeText =
source === "library"
? "in your library"
: source === "marketplace"
? "in marketplace"
: "";
const accordionDescription = `Found ${totalCount}${scopeText ? ` ${scopeText}` : ""}${
query ? ` for "${query}"` : ""
}`;
return (
<div className="py-2">
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ToolIcon
toolType={part.type}
isStreaming={isStreaming}
isError={isError}
/>
<MorphingTextAnimation
text={text}
className={isError ? "text-red-500" : undefined}
/>
</div>
{hasAgents && agentsFoundOutput && (
<ToolAccordion
icon={<AccordionIcon toolType={part.type} />}
title="Agent results"
description={accordionDescription}
>
<ContentGrid className="sm:grid-cols-2">
{agentsFoundOutput.agents.map((agent) => {
const href = getAgentHref(agent);
const agentSource =
agent.source === "library"
? "Library"
: agent.source === "marketplace"
? "Marketplace"
: null;
return (
<ContentCard key={agent.id}>
<ContentCardHeader
action={
href ? <ContentLink href={href}>Open</ContentLink> : null
}
>
<div className="flex items-center gap-2">
<ContentCardTitle>{agent.name}</ContentCardTitle>
{agentSource && (
<ContentBadge>{agentSource}</ContentBadge>
)}
</div>
<ContentCardDescription className="mt-1 line-clamp-2">
{agent.description}
</ContentCardDescription>
</ContentCardHeader>
</ContentCard>
);
})}
</ContentGrid>
</ToolAccordion>
)}
</div>
);
}

View File

@@ -1,187 +0,0 @@
import type { AgentInfo } from "@/app/api/__generated__/models/agentInfo";
import type { AgentsFoundResponse } from "@/app/api/__generated__/models/agentsFoundResponse";
import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
import type { NoResultsResponse } from "@/app/api/__generated__/models/noResultsResponse";
import { ResponseType } from "@/app/api/__generated__/models/responseType";
import {
FolderOpenIcon,
MagnifyingGlassIcon,
SquaresFourIcon,
StorefrontIcon,
} from "@phosphor-icons/react";
import { ToolUIPart } from "ai";
export interface FindAgentInput {
query: string;
}
export type FindAgentsOutput =
| AgentsFoundResponse
| NoResultsResponse
| ErrorResponse;
export type FindAgentsToolType =
| "tool-find_agent"
| "tool-find_library_agent"
| (string & {});
function parseOutput(output: unknown): FindAgentsOutput | null {
if (!output) return null;
if (typeof output === "string") {
const trimmed = output.trim();
if (!trimmed) return null;
try {
return parseOutput(JSON.parse(trimmed) as unknown);
} catch {
return null;
}
}
if (typeof output === "object") {
const type = (output as { type?: unknown }).type;
if (
type === ResponseType.agents_found ||
type === ResponseType.no_results ||
type === ResponseType.error
) {
return output as FindAgentsOutput;
}
if ("agents" in output && "count" in output)
return output as AgentsFoundResponse;
if ("suggestions" in output && !("error" in output))
return output as NoResultsResponse;
if ("error" in output || "details" in output)
return output as ErrorResponse;
}
return null;
}
export function getFindAgentsOutput(part: unknown): FindAgentsOutput | null {
if (!part || typeof part !== "object") return null;
return parseOutput((part as { output?: unknown }).output);
}
export function isAgentsFoundOutput(
output: FindAgentsOutput,
): output is AgentsFoundResponse {
return output.type === ResponseType.agents_found || "agents" in output;
}
export function isNoResultsOutput(
output: FindAgentsOutput,
): output is NoResultsResponse {
return (
output.type === ResponseType.no_results ||
("suggestions" in output && !("error" in output))
);
}
export function isErrorOutput(
output: FindAgentsOutput,
): output is ErrorResponse {
return output.type === ResponseType.error || "error" in output;
}
export function getSourceLabelFromToolType(toolType?: FindAgentsToolType): {
source: "marketplace" | "library" | "unknown";
label: string;
} {
if (toolType === "tool-find_library_agent") {
return { source: "library", label: "Library" };
}
if (toolType === "tool-find_agent") {
return { source: "marketplace", label: "Marketplace" };
}
return { source: "unknown", label: "Agents" };
}
export function getAnimationText(part: {
type?: FindAgentsToolType;
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}): string {
const { source } = getSourceLabelFromToolType(part.type);
const query = (part.input as FindAgentInput | undefined)?.query?.trim();
// Action phrase matching legacy ToolCallMessage
const actionPhrase =
source === "library"
? "Looking for library agents"
: "Looking for agents in the marketplace";
const queryText = query ? ` matching "${query}"` : "";
switch (part.state) {
case "input-streaming":
case "input-available":
return `${actionPhrase}${queryText}`;
case "output-available": {
const output = parseOutput(part.output);
if (!output) {
return `${actionPhrase}${queryText}`;
}
if (isNoResultsOutput(output)) {
return `No agents found${queryText}`;
}
if (isAgentsFoundOutput(output)) {
const count = output.count ?? output.agents?.length ?? 0;
return `Found ${count} agent${count === 1 ? "" : "s"}${queryText}`;
}
if (isErrorOutput(output)) {
return `Error finding agents${queryText}`;
}
return `${actionPhrase}${queryText}`;
}
case "output-error":
return `Error finding agents${queryText}`;
default:
return actionPhrase;
}
}
export function getAgentHref(agent: AgentInfo): string | null {
if (agent.source === "library") {
return `/library/agents/${encodeURIComponent(agent.id)}`;
}
const [creator, slug, ...rest] = agent.id.split("/");
if (!creator || !slug || rest.length > 0) return null;
return `/marketplace/agent/${encodeURIComponent(creator)}/${encodeURIComponent(slug)}`;
}
export function ToolIcon({
toolType,
isStreaming,
isError,
}: {
toolType?: FindAgentsToolType;
isStreaming?: boolean;
isError?: boolean;
}) {
const { source } = getSourceLabelFromToolType(toolType);
const IconComponent =
source === "library" ? MagnifyingGlassIcon : SquaresFourIcon;
return (
<IconComponent
size={14}
weight="regular"
className={
isError
? "text-red-500"
: isStreaming
? "text-neutral-500"
: "text-neutral-400"
}
/>
);
}
export function AccordionIcon({ toolType }: { toolType?: FindAgentsToolType }) {
const { source } = getSourceLabelFromToolType(toolType);
const IconComponent = source === "library" ? FolderOpenIcon : StorefrontIcon;
return <IconComponent size={32} weight="light" />;
}

View File

@@ -1,92 +0,0 @@
"use client";
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
import {
ContentCard,
ContentCardDescription,
ContentCardTitle,
} from "../../components/ToolAccordion/AccordionContent";
import type { BlockListResponse } from "@/app/api/__generated__/models/blockListResponse";
import type { BlockInfoSummary } from "@/app/api/__generated__/models/blockInfoSummary";
import { ToolUIPart } from "ai";
import { HorizontalScroll } from "@/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll";
import {
AccordionIcon,
getAnimationText,
parseOutput,
ToolIcon,
} from "./helpers";
export interface FindBlockInput {
query: string;
}
export type FindBlockOutput = BlockListResponse;
export interface FindBlockToolPart {
type: string;
toolName?: string;
toolCallId: string;
state: ToolUIPart["state"];
input?: FindBlockInput | unknown;
output?: string | FindBlockOutput | unknown;
title?: string;
}
interface Props {
part: FindBlockToolPart;
}
function BlockCard({ block }: { block: BlockInfoSummary }) {
return (
<ContentCard className="w-48 shrink-0">
<ContentCardTitle>{block.name}</ContentCardTitle>
<ContentCardDescription className="mt-1 line-clamp-2">
{block.description}
</ContentCardDescription>
</ContentCard>
);
}
export function FindBlocksTool({ part }: Props) {
const text = getAnimationText(part);
const isStreaming =
part.state === "input-streaming" || part.state === "input-available";
const isError = part.state === "output-error";
const parsed =
part.state === "output-available" ? parseOutput(part.output) : null;
const hasBlocks = !!parsed && parsed.blocks.length > 0;
const query = (part.input as FindBlockInput | undefined)?.query?.trim();
const accordionDescription = parsed
? `Found ${parsed.count} block${parsed.count === 1 ? "" : "s"}${query ? ` for "${query}"` : ""}`
: undefined;
return (
<div className="py-2">
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ToolIcon isStreaming={isStreaming} isError={isError} />
<MorphingTextAnimation
text={text}
className={isError ? "text-red-500" : undefined}
/>
</div>
{hasBlocks && parsed && (
<ToolAccordion
icon={<AccordionIcon />}
title="Block results"
description={accordionDescription}
>
<HorizontalScroll dependencyList={[parsed.blocks.length]}>
{parsed.blocks.map((block) => (
<BlockCard key={block.id} block={block} />
))}
</HorizontalScroll>
</ToolAccordion>
)}
</div>
);
}

View File

@@ -1,75 +0,0 @@
import type { BlockListResponse } from "@/app/api/__generated__/models/blockListResponse";
import { ResponseType } from "@/app/api/__generated__/models/responseType";
import { CubeIcon, PackageIcon } from "@phosphor-icons/react";
import { FindBlockInput, FindBlockToolPart } from "./FindBlocks";
export function parseOutput(output: unknown): BlockListResponse | null {
if (!output) return null;
if (typeof output === "string") {
const trimmed = output.trim();
if (!trimmed) return null;
try {
return parseOutput(JSON.parse(trimmed) as unknown);
} catch {
return null;
}
}
if (typeof output === "object") {
const type = (output as { type?: unknown }).type;
if (type === ResponseType.block_list || "blocks" in output) {
return output as BlockListResponse;
}
}
return null;
}
export function getAnimationText(part: FindBlockToolPart): string {
const query = (part.input as FindBlockInput | undefined)?.query?.trim();
const queryText = query ? ` matching "${query}"` : "";
switch (part.state) {
case "input-streaming":
case "input-available":
return `Searching for blocks${queryText}`;
case "output-available": {
const parsed = parseOutput(part.output);
if (parsed) {
return `Found ${parsed.count} block${parsed.count === 1 ? "" : "s"}${queryText}`;
}
return `Searching for blocks${queryText}`;
}
case "output-error":
return `Error finding blocks${queryText}`;
default:
return "Searching for blocks";
}
}
export function ToolIcon({
isStreaming,
isError,
}: {
isStreaming?: boolean;
isError?: boolean;
}) {
return (
<PackageIcon
size={14}
weight="regular"
className={
isError
? "text-red-500"
: isStreaming
? "text-neutral-500"
: "text-neutral-400"
}
/>
);
}
export function AccordionIcon() {
return <CubeIcon size={32} weight="light" />;
}

View File

@@ -1,86 +0,0 @@
"use client";
import type { ToolUIPart } from "ai";
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
import { ContentMessage } from "../../components/ToolAccordion/AccordionContent";
import {
getAccordionMeta,
getAnimationText,
getRunAgentToolOutput,
isRunAgentAgentDetailsOutput,
isRunAgentErrorOutput,
isRunAgentExecutionStartedOutput,
isRunAgentNeedLoginOutput,
isRunAgentSetupRequirementsOutput,
ToolIcon,
} from "./helpers";
import { ExecutionStartedCard } from "./components/ExecutionStartedCard/ExecutionStartedCard";
import { AgentDetailsCard } from "./components/AgentDetailsCard/AgentDetailsCard";
import { SetupRequirementsCard } from "./components/SetupRequirementsCard/SetupRequirementsCard";
import { ErrorCard } from "./components/ErrorCard/ErrorCard";
export interface RunAgentToolPart {
type: string;
toolCallId: string;
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}
interface Props {
part: RunAgentToolPart;
}
export function RunAgentTool({ part }: Props) {
const text = getAnimationText(part);
const isStreaming =
part.state === "input-streaming" || part.state === "input-available";
const output = getRunAgentToolOutput(part);
const isError =
part.state === "output-error" ||
(!!output && isRunAgentErrorOutput(output));
const hasExpandableContent =
part.state === "output-available" &&
!!output &&
(isRunAgentExecutionStartedOutput(output) ||
isRunAgentAgentDetailsOutput(output) ||
isRunAgentSetupRequirementsOutput(output) ||
isRunAgentNeedLoginOutput(output) ||
isRunAgentErrorOutput(output));
return (
<div className="py-2">
<div className="flex items-center gap-2 text-sm text-muted-foreground">
<ToolIcon isStreaming={isStreaming} isError={isError} />
<MorphingTextAnimation
text={text}
className={isError ? "text-red-500" : undefined}
/>
</div>
{hasExpandableContent && output && (
<ToolAccordion {...getAccordionMeta(output)}>
{isRunAgentExecutionStartedOutput(output) && (
<ExecutionStartedCard output={output} />
)}
{isRunAgentAgentDetailsOutput(output) && (
<AgentDetailsCard output={output} />
)}
{isRunAgentSetupRequirementsOutput(output) && (
<SetupRequirementsCard output={output} />
)}
{isRunAgentNeedLoginOutput(output) && (
<ContentMessage>{output.message}</ContentMessage>
)}
{isRunAgentErrorOutput(output) && <ErrorCard output={output} />}
</ToolAccordion>
)}
</div>
);
}

View File

@@ -1,116 +0,0 @@
"use client";
import type { AgentDetailsResponse } from "@/app/api/__generated__/models/agentDetailsResponse";
import { Button } from "@/components/atoms/Button/Button";
import { Text } from "@/components/atoms/Text/Text";
import { FormRenderer } from "@/components/renderers/InputRenderer/FormRenderer";
import { AnimatePresence, motion } from "framer-motion";
import { useState } from "react";
import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
import { ContentMessage } from "../../../../components/ToolAccordion/AccordionContent";
import { buildInputSchema } from "./helpers";
interface Props {
output: AgentDetailsResponse;
}
export function AgentDetailsCard({ output }: Props) {
const { onSend } = useCopilotChatActions();
const [showInputForm, setShowInputForm] = useState(false);
const [inputValues, setInputValues] = useState<Record<string, unknown>>({});
function handleRunWithExamples() {
onSend(
`Run the agent "${output.agent.name}" with placeholder/example values so I can test it.`,
);
}
function handleRunWithInputs() {
const nonEmpty = Object.fromEntries(
Object.entries(inputValues).filter(
([, v]) => v !== undefined && v !== null && v !== "",
),
);
onSend(
`Run the agent "${output.agent.name}" with these inputs: ${JSON.stringify(nonEmpty, null, 2)}`,
);
setShowInputForm(false);
setInputValues({});
}
return (
<div className="grid gap-2">
<ContentMessage>
Run this agent with example values or your own inputs.
</ContentMessage>
<div className="flex gap-2 pt-4">
<Button size="small" className="w-fit" onClick={handleRunWithExamples}>
Run with example values
</Button>
<Button
variant="outline"
size="small"
className="w-fit"
onClick={() => setShowInputForm((prev) => !prev)}
>
Run with my inputs
</Button>
</div>
<AnimatePresence initial={false}>
{showInputForm && buildInputSchema(output.agent.inputs) && (
<motion.div
initial={{ height: 0, opacity: 0, filter: "blur(6px)" }}
animate={{ height: "auto", opacity: 1, filter: "blur(0px)" }}
exit={{ height: 0, opacity: 0, filter: "blur(6px)" }}
transition={{
height: { type: "spring", bounce: 0.15, duration: 0.5 },
opacity: { duration: 0.25 },
filter: { duration: 0.2 },
}}
className="overflow-hidden"
style={{ willChange: "height, opacity, filter" }}
>
<div className="mt-4 rounded-2xl border bg-background p-3 pt-4">
<Text variant="body-medium">Enter your inputs</Text>
<FormRenderer
jsonSchema={buildInputSchema(output.agent.inputs)!}
handleChange={(v) => setInputValues(v.formData ?? {})}
uiSchema={{
"ui:submitButtonOptions": { norender: true },
}}
initialValues={inputValues}
formContext={{
showHandles: false,
size: "small",
}}
/>
<div className="-mt-8 flex gap-2">
<Button
variant="primary"
size="small"
className="w-fit"
onClick={handleRunWithInputs}
>
Run
</Button>
<Button
variant="secondary"
size="small"
className="w-fit"
onClick={() => {
setShowInputForm(false);
setInputValues({});
}}
>
Cancel
</Button>
</div>
</div>
</motion.div>
)}
</AnimatePresence>
</div>
);
}

View File

@@ -1,8 +0,0 @@
import type { RJSFSchema } from "@rjsf/utils";
export function buildInputSchema(inputs: unknown): RJSFSchema | null {
if (!inputs || typeof inputs !== "object") return null;
const properties = inputs as RJSFSchema["properties"];
if (!properties || Object.keys(properties).length === 0) return null;
return inputs as RJSFSchema;
}

View File

@@ -1,27 +0,0 @@
"use client";
import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
import {
ContentCodeBlock,
ContentGrid,
ContentMessage,
} from "../../../../components/ToolAccordion/AccordionContent";
import { formatMaybeJson } from "../../helpers";
interface Props {
output: ErrorResponse;
}
export function ErrorCard({ output }: Props) {
return (
<ContentGrid>
<ContentMessage>{output.message}</ContentMessage>
{output.error && (
<ContentCodeBlock>{formatMaybeJson(output.error)}</ContentCodeBlock>
)}
{output.details && (
<ContentCodeBlock>{formatMaybeJson(output.details)}</ContentCodeBlock>
)}
</ContentGrid>
);
}

View File

@@ -1,39 +0,0 @@
"use client";
import type { ExecutionStartedResponse } from "@/app/api/__generated__/models/executionStartedResponse";
import { Button } from "@/components/atoms/Button/Button";
import { useRouter } from "next/navigation";
import {
ContentCard,
ContentCardDescription,
ContentCardSubtitle,
ContentCardTitle,
ContentGrid,
} from "../../../../components/ToolAccordion/AccordionContent";
interface Props {
output: ExecutionStartedResponse;
}
export function ExecutionStartedCard({ output }: Props) {
const router = useRouter();
return (
<ContentGrid>
<ContentCard>
<ContentCardTitle>Execution started</ContentCardTitle>
<ContentCardSubtitle>{output.execution_id}</ContentCardSubtitle>
<ContentCardDescription>{output.message}</ContentCardDescription>
{output.library_agent_link && (
<Button
size="small"
className="mt-3"
onClick={() => router.push(output.library_agent_link!)}
>
View Execution
</Button>
)}
</ContentCard>
</ContentGrid>
);
}

View File

@@ -1,105 +0,0 @@
"use client";
import { useState } from "react";
import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
import { Button } from "@/components/atoms/Button/Button";
import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
import {
ContentBadge,
ContentCardDescription,
ContentCardTitle,
ContentMessage,
} from "../../../../components/ToolAccordion/AccordionContent";
import { coerceCredentialFields, coerceExpectedInputs } from "./helpers";
interface Props {
output: SetupRequirementsResponse;
}
export function SetupRequirementsCard({ output }: Props) {
const { onSend } = useCopilotChatActions();
const [inputCredentials, setInputCredentials] = useState<
Record<string, CredentialsMetaInput | undefined>
>({});
const [hasSent, setHasSent] = useState(false);
const { credentialFields, requiredCredentials } = coerceCredentialFields(
output.setup_info.user_readiness?.missing_credentials,
);
const expectedInputs = coerceExpectedInputs(
(output.setup_info.requirements as Record<string, unknown>)?.inputs,
);
function handleCredentialChange(key: string, value?: CredentialsMetaInput) {
setInputCredentials((prev) => ({ ...prev, [key]: value }));
}
const isAllComplete =
credentialFields.length > 0 &&
[...requiredCredentials].every((key) => !!inputCredentials[key]);
function handleProceed() {
setHasSent(true);
onSend(
"I've configured the required credentials. Please check if everything is ready and proceed with running the agent.",
);
}
return (
<div className="grid gap-2">
<ContentMessage>{output.message}</ContentMessage>
{credentialFields.length > 0 && (
<div className="rounded-2xl border bg-background p-3">
<CredentialsGroupedView
credentialFields={credentialFields}
requiredCredentials={requiredCredentials}
inputCredentials={inputCredentials}
inputValues={{}}
onCredentialChange={handleCredentialChange}
/>
{isAllComplete && !hasSent && (
<Button
variant="primary"
size="small"
className="mt-3 w-full"
onClick={handleProceed}
>
Proceed
</Button>
)}
</div>
)}
{expectedInputs.length > 0 && (
<div className="rounded-2xl border bg-background p-3">
<ContentCardTitle className="text-xs">
Expected inputs
</ContentCardTitle>
<div className="mt-2 grid gap-2">
{expectedInputs.map((input) => (
<div key={input.name} className="rounded-xl border p-2">
<div className="flex items-center justify-between gap-2">
<ContentCardTitle className="text-xs">
{input.title}
</ContentCardTitle>
<ContentBadge>
{input.required ? "Required" : "Optional"}
</ContentBadge>
</div>
<ContentCardDescription className="mt-1">
{input.name} &bull; {input.type}
{input.description ? ` \u2022 ${input.description}` : ""}
</ContentCardDescription>
</div>
))}
</div>
</div>
)}
</div>
);
}

View File

@@ -1,116 +0,0 @@
import type { CredentialField } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
const VALID_CREDENTIAL_TYPES = new Set([
"api_key",
"oauth2",
"user_password",
"host_scoped",
]);
/**
* Transforms raw missing_credentials from SetupRequirementsResponse
* into CredentialField[] tuples compatible with CredentialsGroupedView.
*
* Each CredentialField is [key, schema] where schema matches
* BlockIOCredentialsSubSchema shape.
*/
export function coerceCredentialFields(rawMissingCredentials: unknown): {
credentialFields: CredentialField[];
requiredCredentials: Set<string>;
} {
const missing =
rawMissingCredentials && typeof rawMissingCredentials === "object"
? (rawMissingCredentials as Record<string, unknown>)
: {};
const credentialFields: CredentialField[] = [];
const requiredCredentials = new Set<string>();
Object.entries(missing).forEach(([key, value]) => {
if (!value || typeof value !== "object") return;
const cred = value as Record<string, unknown>;
const provider =
typeof cred.provider === "string" ? cred.provider.trim() : "";
if (!provider) return;
const types =
Array.isArray(cred.types) && cred.types.length > 0
? cred.types
: typeof cred.type === "string"
? [cred.type]
: [];
const credentialTypes = types
.map((t) => (typeof t === "string" ? t.trim() : ""))
.filter((t) => VALID_CREDENTIAL_TYPES.has(t));
if (credentialTypes.length === 0) return;
const scopes = Array.isArray(cred.scopes)
? cred.scopes.filter((s): s is string => typeof s === "string")
: undefined;
const schema = {
type: "object" as const,
properties: {},
credentials_provider: [provider],
credentials_types: credentialTypes,
credentials_scopes: scopes,
};
credentialFields.push([key, schema]);
requiredCredentials.add(key);
});
return { credentialFields, requiredCredentials };
}
export function coerceExpectedInputs(rawInputs: unknown): Array<{
name: string;
title: string;
type: string;
description?: string;
required: boolean;
}> {
if (!Array.isArray(rawInputs)) return [];
const results: Array<{
name: string;
title: string;
type: string;
description?: string;
required: boolean;
}> = [];
rawInputs.forEach((value, index) => {
if (!value || typeof value !== "object") return;
const input = value as Record<string, unknown>;
const name =
typeof input.name === "string" && input.name.trim()
? input.name.trim()
: `input-${index}`;
const title =
typeof input.title === "string" && input.title.trim()
? input.title.trim()
: name;
const type = typeof input.type === "string" ? input.type : "unknown";
const description =
typeof input.description === "string" && input.description.trim()
? input.description.trim()
: undefined;
const required = Boolean(input.required);
const item: {
name: string;
title: string;
type: string;
description?: string;
required: boolean;
} = { name, title, type, required };
if (description) item.description = description;
results.push(item);
});
return results;
}

View File

@@ -1,248 +0,0 @@
import type { AgentDetailsResponse } from "@/app/api/__generated__/models/agentDetailsResponse";
import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
import type { ExecutionStartedResponse } from "@/app/api/__generated__/models/executionStartedResponse";
import type { NeedLoginResponse } from "@/app/api/__generated__/models/needLoginResponse";
import { ResponseType } from "@/app/api/__generated__/models/responseType";
import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
import {
PlayIcon,
RocketLaunchIcon,
WarningDiamondIcon,
} from "@phosphor-icons/react";
import type { ToolUIPart } from "ai";
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
export interface RunAgentInput {
username_agent_slug?: string;
library_agent_id?: string;
inputs?: Record<string, unknown>;
use_defaults?: boolean;
schedule_name?: string;
cron?: string;
timezone?: string;
}
export type RunAgentToolOutput =
| SetupRequirementsResponse
| ExecutionStartedResponse
| AgentDetailsResponse
| NeedLoginResponse
| ErrorResponse;
const RUN_AGENT_OUTPUT_TYPES = new Set<string>([
ResponseType.setup_requirements,
ResponseType.execution_started,
ResponseType.agent_details,
ResponseType.need_login,
ResponseType.error,
]);
export function isRunAgentSetupRequirementsOutput(
output: RunAgentToolOutput,
): output is SetupRequirementsResponse {
return (
output.type === ResponseType.setup_requirements ||
("setup_info" in output && typeof output.setup_info === "object")
);
}
export function isRunAgentExecutionStartedOutput(
output: RunAgentToolOutput,
): output is ExecutionStartedResponse {
return (
output.type === ResponseType.execution_started || "execution_id" in output
);
}
export function isRunAgentAgentDetailsOutput(
output: RunAgentToolOutput,
): output is AgentDetailsResponse {
return output.type === ResponseType.agent_details || "agent" in output;
}
export function isRunAgentNeedLoginOutput(
output: RunAgentToolOutput,
): output is NeedLoginResponse {
return output.type === ResponseType.need_login;
}
export function isRunAgentErrorOutput(
output: RunAgentToolOutput,
): output is ErrorResponse {
return output.type === ResponseType.error || "error" in output;
}
function parseOutput(output: unknown): RunAgentToolOutput | null {
if (!output) return null;
if (typeof output === "string") {
const trimmed = output.trim();
if (!trimmed) return null;
try {
return parseOutput(JSON.parse(trimmed) as unknown);
} catch {
return null;
}
}
if (typeof output === "object") {
const type = (output as { type?: unknown }).type;
if (typeof type === "string" && RUN_AGENT_OUTPUT_TYPES.has(type)) {
return output as RunAgentToolOutput;
}
if ("execution_id" in output) return output as ExecutionStartedResponse;
if ("setup_info" in output) return output as SetupRequirementsResponse;
if ("agent" in output) return output as AgentDetailsResponse;
if ("error" in output || "details" in output)
return output as ErrorResponse;
if (type === ResponseType.need_login) return output as NeedLoginResponse;
}
return null;
}
export function getRunAgentToolOutput(
part: unknown,
): RunAgentToolOutput | null {
if (!part || typeof part !== "object") return null;
return parseOutput((part as { output?: unknown }).output);
}
function getAgentIdentifierText(
input: RunAgentInput | undefined,
): string | null {
if (!input) return null;
const slug = input.username_agent_slug?.trim();
if (slug) return slug;
const libraryId = input.library_agent_id?.trim();
if (libraryId) return `Library agent ${libraryId}`;
return null;
}
export function getAnimationText(part: {
state: ToolUIPart["state"];
input?: unknown;
output?: unknown;
}): string {
const input = part.input as RunAgentInput | undefined;
const agentIdentifier = getAgentIdentifierText(input);
const isSchedule = Boolean(
input?.schedule_name?.trim() || input?.cron?.trim(),
);
const actionPhrase = isSchedule
? "Scheduling the agent to run"
: "Running the agent";
const identifierText = agentIdentifier ? ` "${agentIdentifier}"` : "";
switch (part.state) {
case "input-streaming":
case "input-available":
return `${actionPhrase}${identifierText}`;
case "output-available": {
const output = parseOutput(part.output);
if (!output) return `${actionPhrase}${identifierText}`;
if (isRunAgentExecutionStartedOutput(output)) {
return `Started "${output.graph_name}"`;
}
if (isRunAgentAgentDetailsOutput(output)) {
return `Agent inputs needed for "${output.agent.name}"`;
}
if (isRunAgentSetupRequirementsOutput(output)) {
return `Setup needed for "${output.setup_info.agent_name}"`;
}
if (isRunAgentNeedLoginOutput(output))
return "Sign in required to run agent";
return "Error running agent";
}
case "output-error":
return "Error running agent";
default:
return actionPhrase;
}
}
export function ToolIcon({
isStreaming,
isError,
}: {
isStreaming?: boolean;
isError?: boolean;
}) {
if (isError) {
return (
<WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
);
}
if (isStreaming) {
return <OrbitLoader size={24} />;
}
return <PlayIcon size={14} weight="regular" className="text-neutral-400" />;
}
export function AccordionIcon() {
return <RocketLaunchIcon size={28} weight="light" />;
}
export function formatMaybeJson(value: unknown): string {
if (typeof value === "string") return value;
try {
return JSON.stringify(value, null, 2);
} catch {
return String(value);
}
}
export function getAccordionMeta(output: RunAgentToolOutput): {
icon: React.ReactNode;
title: string;
titleClassName?: string;
description?: string;
} {
const icon = <AccordionIcon />;
if (isRunAgentExecutionStartedOutput(output)) {
const statusText =
typeof output.status === "string" && output.status.trim()
? output.status.trim()
: "started";
return {
icon: <OrbitLoader size={28} className="text-neutral-700" />,
title: output.graph_name,
description: `Status: ${statusText}`,
};
}
if (isRunAgentAgentDetailsOutput(output)) {
return {
icon,
title: output.agent.name,
description: "Inputs required",
};
}
if (isRunAgentSetupRequirementsOutput(output)) {
const missingCredsCount = Object.keys(
(output.setup_info.user_readiness?.missing_credentials ?? {}) as Record<
string,
unknown
>,
).length;
return {
icon,
title: output.setup_info.agent_name,
description:
missingCredsCount > 0
? `Missing ${missingCredsCount} credential${missingCredsCount === 1 ? "" : "s"}`
: output.message,
};
}
if (isRunAgentNeedLoginOutput(output)) {
return { icon, title: "Sign in required" };
}
return {
icon: (
<WarningDiamondIcon size={28} weight="light" className="text-red-500" />
),
title: "Error",
titleClassName: "text-red-500",
};
}

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