a1ef47710d
``AgentAppRunner`` runs one conversation turn against the dify-agent backend (instead of the legacy in-process ReAct loop): load the conversation's prior session_snapshot, build the run request (S2b), create the run, consume the event stream, and republish the assistant answer as chat queue events (``QueueLLMChunkEvent`` + ``QueueMessageEndEvent``) so the existing EasyUI chat task pipeline persists the message and streams SSE. On success the conversation session_snapshot is saved for multi-turn continuity; failures raise AgentBackendError; the answer is normalized to text (plain string or structured JSON). MVP emits the final answer as one chunk + message-end; token-level streaming is a follow-up refinement. The generator/entity/converter wiring + live-stack verification land next. Tests: 4 runner cases via the deterministic fake backend client + fake queue (success→chunk+end+session-save, prior-snapshot threading, failure raises, answer extraction). 15 agent_app unit tests green; ruff + pyrefly clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Dify Backend API
Setup and Run
Important
In the v1.3.0 release,
poetryhas been replaced withuvas the package manager for Dify API backend service.
uv and pnpm are required to run the setup and development commands below.
Using scripts (recommended)
The scripts resolve paths relative to their location, so you can run them from anywhere.
-
Run setup (copies env files and installs dependencies).
./dev/setup -
Review
api/.env,web/.env.local, anddocker/middleware.envvalues (see theSECRET_KEYnote below). -
Start middleware (PostgreSQL/Redis/Weaviate).
./dev/start-docker-compose -
Start backend (runs migrations first).
./dev/start-api -
Start Dify web service.
./dev/start-web./dev/setupand./dev/start-webinstall JavaScript dependencies through the repository root workspace, so you do not need a separatecd web && pnpm installstep. -
Set up your application by visiting
http://localhost:3000. -
Start the worker service (async and scheduler tasks, runs from
api)../dev/start-worker -
Optional: start Celery Beat (scheduled tasks).
./dev/start-beat
Environment notes
Important
When the frontend and backend run on different subdomains, set COOKIE_DOMAIN to the site’s top-level domain (e.g.,
example.com). The frontend and backend must be under the same top-level domain in order to share authentication cookies.
-
Generate a
SECRET_KEYin the.envfile.bash for Linux
sed -i "/^SECRET_KEY=/c\\SECRET_KEY=$(openssl rand -base64 42)" .envbash for Mac
secret_key=$(openssl rand -base64 42) sed -i '' "/^SECRET_KEY=/c\\ SECRET_KEY=${secret_key}" .env
Testing
-
Install dependencies for both the backend and the test environment
cd api uv sync --group dev -
Run the tests locally with mocked system environment variables in
tool.pytest_envsection inpyproject.toml, more can check Claude.mdcd api uv run pytest # Run all tests uv run pytest tests/unit_tests/ # Unit tests only uv run pytest tests/integration_tests/ # Integration tests # Code quality ./dev/reformat # Run all formatters and linters uv run ruff check --fix ./ # Fix linting issues uv run ruff format ./ # Format code uv run pyrefly check # Type checking
Generate TS stub
uv run dev/generate_swagger_specs.py --output-dir openapi
use https://jsontotable.org/openapi-to-typescript to convert to typescript