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de06c9a60b
## Summary This PR passes `session_id` into Langfuse trace observations so multi-turn chat messages can be grouped under the same session in Langfuse. Changes include: - Propagate `session_id` from chat/session APIs into `dialog_service.async_chat`. - Pass `session_id` into Langfuse `start_observation(...)`. - Share Langfuse `trace_context` with chat, embedding, rerank, and TTS model bundles where applicable. - Add unit coverage to verify Langfuse observations receive `session_id`. - Update affected test stubs for the new optional Langfuse context arguments. ## Related Issue Closes: #15636 ## Change Type - [x] Feature - [x] Bug fix - [x] Test - [ ] Refactor - [ ] Documentation - [ ] Breaking change ## Real Behavior Proof Before this change: - Langfuse observations were created without `session_id`. - Multi-turn chat traces could not be grouped by session in Langfuse. After this change: - Chat/session flows pass `session_id` into `async_chat`. - Langfuse observations include `session_id`. - Related model bundles receive shared trace context and session metadata. Validation result: ```bash uv run python -m py_compile \ api/db/services/tenant_llm_service.py \ api/db/services/llm_service.py \ api/db/services/dialog_service.py \ api/db/services/conversation_service.py \ api/apps/restful_apis/chat_api.py \ test/unit_test/api/db/services/test_dialog_service_final_answer.py \ test/unit_test/api/db/services/test_dialog_service_use_sql_source_columns.py ``` Passed. ```bash uv run pytest \ test/unit_test/api/db/services/test_dialog_service_final_answer.py \ test/unit_test/api/db/services/test_dialog_service_use_sql_source_columns.py -q ``` Result: ```text 11 passed in 16.89s ``` ```bash git diff --check ``` Passed. ## Checklist - [x] Analyzed the issue requirement. - [x] Checked existing Langfuse trace integration. - [x] Implemented only the requested session grouping behavior. - [x] Added/updated unit tests. - [x] Ran focused tests successfully. - [x] Ran Python compile validation. - [x] Ran whitespace diff validation.
(1). Deploy RAGFlow services and images
https://ragflow.io/docs/build_docker_image
(2). Configure the required environment for testing
Install Python dependencies (including test dependencies):
uv sync --python 3.13 --only-group test --no-default-groups --frozen
Activate the environment:
source .venv/bin/activate
Install SDK:
uv pip install sdk/python
Modify the .env file: Add the following code:
COMPOSE_PROFILES=${COMPOSE_PROFILES},tei-cpu
TEI_MODEL=BAAI/bge-small-en-v1.5
RAGFLOW_IMAGE=infiniflow/ragflow:v0.26.0 #Replace with the image you are using
Start the container（wait two minutes）:
docker compose -f docker/docker-compose.yml up -d
(3). Test Elasticsearch
a) Run sdk tests against Elasticsearch:
export HTTP_API_TEST_LEVEL=p2
export HOST_ADDRESS=http://127.0.0.1:9380 # Ensure that this port is the API port mapped to your localhost
pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_sdk_api
b) Run http api tests against Elasticsearch:
pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_http_api
(4). Test Infinity
Modify the .env file:
DOC_ENGINE=${DOC_ENGINE:-infinity}
Start the container:
docker compose -f docker/docker-compose.yml down -v
docker compose -f docker/docker-compose.yml up -d
a) Run sdk tests against Infinity:
DOC_ENGINE=infinity pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_sdk_api
b) Run http api tests against Infinity:
DOC_ENGINE=infinity pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_http_api