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## Summary Fixes #15215 — attachments uploaded to an agent were not reaching the LLM. When a user uploads a file in an agent chat, `canvas.run` parses it into the `sys.files` global (text content for documents, `data:image/...` URIs for images — see `agent/canvas.py:752-768`). But the LLM/Agent component's `_prepare_prompt_variables` only substitutes variables the user's prompt template explicitly references via `{var}` placeholders. The default prompt is `[{"role": "user", "content": "{sys.query}"}]` with no `{sys.files}`, so the parsed attachment content never reaches the model. In the reporter's logs, this is why the agent saw only the bare query `附件 摘要 attachment summary` and went searching the dataset instead of reading the uploaded PDF. ## Fix `agent/component/llm.py` — added `_collect_sys_files()` and an auto-injection step in `_prepare_prompt_variables`: - If `sys.files` is non-empty **and** neither `sys_prompt` nor any entry in `prompts` already contains `{sys.files}` (no double-injection), split the entries into text vs. `data:image/...` URIs. - Image URIs are merged into `self.imgs`, which the existing logic uses to switch the chat model to `IMAGE2TEXT` and pass `images=...` to `async_chat`. - Text content is appended to the last `user` role message in `msg`, mirroring how `dialog_service.async_chat_solo` handles attachments for the non-agent chat path (`api/db/services/dialog_service.py:318-321`). Both `LLM._invoke_async` and `Agent._invoke_async` (tool-using) go through `_prepare_prompt_variables`, so plain LLM nodes and Agent nodes are fixed in both streaming and non-streaming paths. ## Test plan - [ ] Upload a PDF attachment to an agent with the default `{sys.query}` prompt and ask "summarize the attachment" — the model should answer from the file content rather than searching the knowledge base. - [ ] Upload an image attachment to an agent and ask about its contents — the model should switch to the vision-capable LLM and answer from the image. - [ ] Verify that an agent whose prompt **does** include `{sys.files}` still works and does **not** include the file content twice. - [ ] Verify that an agent run with no attachments behaves unchanged. - [ ] Run `uv run pytest` to make sure no existing tests regress. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [ ] New Feature (non-breaking change which adds functionality) - [ ] Documentation Update - [ ] Refactoring - [ ] Performance Improvement - [ ] Other (please describe): --------- Co-authored-by: yzc <yuzhichang@gmail.com>
(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=${COMPOSE_PROFILES},tei-cpu
TEI_MODEL=BAAI/bge-small-en-v1.5
RAGFLOW_IMAGE=infiniflow/ragflow:v0.26.2 #Replace with the image you are using
Start the container（wait two minutes）:
docker compose -f docker/docker-compose.yml up -d
(3). Test Elasticsearch
a) Run sdk tests against Elasticsearch:
export HTTP_API_TEST_LEVEL=p2
export HOST_ADDRESS=http://127.0.0.1:9380 # Ensure that this port is the API port mapped to your localhost
pytest -s --tb=short --level=${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