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### What problem does this PR solve? Fixes #15427. All LiteLLM-routed chats fail with: - Anthropic: `litellm.BadRequestError: AnthropicException - {"type":"invalid_request_error","message":"model_type: Extra inputs are not permitted"}` - OpenAI: `litellm.BadRequestError: OpenAIException - Unknown parameter: 'model_type'` This is a regression from v0.25.4. #### Root cause A chat assistant's `llm_setting` is forwarded to the model as `gen_conf`. `llm_setting` can legitimately carry RAGFlow-internal metadata such as `model_type` (the chat REST APIs in `api/apps/restful_apis/` read it back out of `llm_setting`), so that key ends up inside `gen_conf`. `Base._clean_conf` (OpenAI-compatible providers) already **whitelists** the keys it forwards, so direct-OpenAI providers were unaffected. `LiteLLMBase._clean_conf` only dropped `max_tokens` and passed everything else straight through to `litellm.acompletion`, which forwarded `model_type` to the upstream provider — and Anthropic / OpenAI reject it. Because both Claude and GPT route through LiteLLM, every chat broke. #### Fix - Extract the allowed-key set into a shared `ALLOWED_GEN_CONF_KEYS` constant and reuse it in `Base._clean_conf`. - Apply the same whitelist in `LiteLLMBase._clean_conf`, plus the LiteLLM-specific reasoning params (`thinking`, `reasoning_effort`, `extra_body`) that the model-family policies inject for reasoning models. This covers all four LiteLLM completion paths (`async_chat`, `async_chat_streamly`, `async_chat_with_tools`, `async_chat_streamly_with_tools`), since they all route through `_clean_conf`. #### Tests Adds `test/unit_test/rag/llm/test_clean_conf_whitelist.py` covering both backends: `model_type` (and other stray keys) are dropped, genuine generation params and `thinking` survive, `max_tokens` is removed, and the whitelist invariants hold. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Added test cases
(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=${COMPOSE_PROFILES},tei-cpu
TEI_MODEL=BAAI/bge-small-en-v1.5
RAGFLOW_IMAGE=infiniflow/ragflow:v0.25.6 #Replace with the image you are using
Start the container（wait two minutes）:
docker compose -f docker/docker-compose.yml up -d
(3). Test Elasticsearch
a) Run sdk tests against Elasticsearch:
export HTTP_API_TEST_LEVEL=p2
export HOST_ADDRESS=http://127.0.0.1:9380 # Ensure that this port is the API port mapped to your localhost
pytest -s --tb=short --level=${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