Jordan Hury Jordanh1996
Jordanh1996
/ repro_empty_tool_result.py
Last active
April 26, 2026 13:38
Reproduction: langchain-google-vertexai _merge_messages drops tool_result for empty ToolMessage content
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| """Reproduction: _merge_messages in langchain-google-vertexai silently drops | |
| tool_result when ToolMessage has empty content (content=[]). | |
| Bug: | |
| _merge_messages in langchain_google_vertexai/_anthropic_utils.py treats | |
| ToolMessage(content=[]) as pre-formatted tool_result blocks because | |
| Python's `all(predicate for x in [])` returns True on an empty iterable. | |
| The empty list becomes HumanMessage([]), which then gets merged into the | |
| next HumanMessage, silently dropping the tool_result. The Anthropic API |
Jordanh1996
/ repro_prompt_too_long.py
Created
March 27, 2026 20:57
Reproduction: SummarizationMiddleware token underestimation with ChatAnthropicVertex
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| """Reproduction: SummarizationMiddleware token underestimation with ChatAnthropicVertex. | |
| LangChain's _get_approximate_token_counter checks model._llm_type == "anthropic-chat", | |
| but ChatAnthropicVertex._llm_type returns "anthropic-chat-vertexai". This causes the | |
| token counter to use 4.0 chars/token instead of 3.3, underestimating by ~16%. | |
| The summarization middleware never triggers, and the API rejects the prompt. | |
| Additionally: | |
| - use_usage_metadata_scaling is gated on response_metadata["model_provider"], which | |
| ChatAnthropicVertex never sets. The scaling safety net is a no-op. |