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fix(langchain): extract model name for ChatHuggingFace #1728

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fix(langchain): extract model name for ChatHuggingFace #1728

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fix(langchain): extract model name for ChatHuggingFace
vismaytiwari Jun 28, 2026
df65690
test(langchain): cover all ChatHuggingFace backends in model-name test
vismaytiwari Jun 28, 2026
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1 change: 1 addition & 0 deletions langfuse/langchain/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -97,6 +97,7 @@ def _extract_model_name(
("ChatCohere", "model", None),
("Cohere", "model", None),
("HuggingFaceHub", "model", None),
("ChatHuggingFace", "model_id", None),
("ChatAnyscale", "model_name", None),
("TextGen", "model", "text-gen"),
("Ollama", "model", None),
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33 changes: 33 additions & 0 deletions tests/unit/test_langchain_utils.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,33 @@
"""Unit tests for langfuse.langchain.utils model-name extraction."""

from langfuse.langchain.utils import _extract_model_name


def _chat_huggingface_serialized(model_id: str) -> dict:
"""Mirror ``langchain_core.load.dumpd(ChatHuggingFace(...))``.

ChatHuggingFace is not LangChain-serializable, so it serializes to a
``not_implemented`` stub with no ``kwargs``; the model id is only available
inside the ``repr`` string as ``model_id='...'``.
"""
return {
"lc": 1,
"type": "not_implemented",
"id": [
"langchain_huggingface",
"chat_models",
"huggingface",
"ChatHuggingFace",
],
"repr": (
f"ChatHuggingFace(llm=HuggingFaceEndpoint(repo_id='{model_id}', "
f"model='{model_id}', task='text-generation'), model_id='{model_id}')"
),
"name": "ChatHuggingFace",
}


def test_extract_model_name_chat_huggingface():
serialized = _chat_huggingface_serialized("Qwen/Qwen2.5-Coder-32B-Instruct")

Comment on lines +30 to +43

@greptile-apps greptile-apps Bot Jun 28, 2026

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P2 Test only covers HuggingFaceEndpoint backend shape

The PR description correctly notes that ChatHuggingFace works with three backends — HuggingFaceEndpoint, HuggingFaceHub, and HuggingFacePipeline. HuggingFacePipeline itself has a model_id attribute in its own repr, so a wrapped repr could look like ChatHuggingFace(llm=HuggingFacePipeline(model_id='...', ...), model_id='...'). The regex uses re.search (first match), meaning it would pick up the inner HuggingFacePipeline's model_id rather than ChatHuggingFace's. In practice both should be the same value, but adding a parameterised test for each backend shape would guard against any future repr change where the two values might differ.

Prompt To Fix With AI 
This is a comment left during a code review.
Path: tests/unit/test_langchain_utils.py
Line: 29-32

Comment:
**Test only covers HuggingFaceEndpoint backend shape**

The PR description correctly notes that `ChatHuggingFace` works with three backends — `HuggingFaceEndpoint`, `HuggingFaceHub`, and `HuggingFacePipeline`. `HuggingFacePipeline` itself has a `model_id` attribute in its own repr, so a wrapped repr could look like `ChatHuggingFace(llm=HuggingFacePipeline(model_id='...', ...), model_id='...')`. The regex uses `re.search` (first match), meaning it would pick up the inner `HuggingFacePipeline`'s `model_id` rather than `ChatHuggingFace`'s. In practice both should be the same value, but adding a parameterised test for each backend shape would guard against any future repr change where the two values might differ.

How can I resolve this? If you propose a fix, please make it concise.

@vismaytiwari vismaytiwari Jun 28, 2026

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Good catch. I parameterised the test to cover all three backends (HuggingFaceEndpoint, HuggingFaceHub, HuggingFacePipeline). The HuggingFacePipeline case specifically exercises the double model_id repr you flagged, where re.search matches the inner one; since both ids resolve to the same model the extracted value is correct, and the test now guards against future drift between them.

assert _extract_model_name(serialized) == "Qwen/Qwen2.5-Coder-32B-Instruct"