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BaseTool cannot handle unbound functions with a "self" parameter.

langchain-ai/langchain#34900·146784·Python·182 天未动·6 条评论·上游最近活跃 ·池内状态:可认领
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上游 issue 正文

### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x] This is not related to the langchain-community package. - [x] I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS. ### Package (Required) - [ ] langchain - [ ] langchain-openai - [ ] langchain-anthropic - [ ] langchain-classic - [x] langchain-core - [ ] langchain-model-profiles - [ ] langchain-tests - [ ] langchain-text-splitters - [ ] langchain-chroma - [ ] langchain-deepseek - [ ] langchain-exa - [ ] langchain-fireworks - [ ] langchain-groq - [ ] langchain-huggingface - [ ] langchain-mistralai - [ ] langchain-nomic - [ ] langchain-ollama - [ ] langchain-perplexity - [ ] langchain-prompty - [ ] langchain-qdrant - [ ] langchain-xai - [ ] Other / not sure / general ### Reproduction Steps / Example Code (Python) ```python from langchain_core.tools import StructuredTool def func(**kwargs) -> str: return f"{kwargs}" tool = StructuredTool( name="test_tool", func=func, args_schema={ "type": "object", "properties": {}, }, ) tool_input = { "self": 2, "other": 3, } # while unconventional, our function is perfectly valid result = func(**tool_input) print("Result of func:", result) # works result = tool.invoke(tool_input) # TypeError: StructuredTool._run() got multiple values for argument 'self' ``` ### Error Message and Stack Trace (if applicable) ```shell Result of func: {'self': 2, 'other': 3} Traceback (most recent call last): File "/home/andrei/python-sdks/coded-playground/.stuffs/test4.py", line 29, in <module> result = tool.invoke(tool_input) ^^^^^^…
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