test: restore test that was skipped due to Colang 2.0 serialization issue #1449
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Pouyanpi
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tgasser-nv
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* Initial checkin * Add nemoguardrails/server to pyright type-checking * chore(types): Type-clean embeddings/ (25 errors) (#1383) * test: restore test that was skipped due to Colang 2.0 serialization issue (#1449) * fix(llm): add fallback extraction for reasoning traces from <think> tags (#1474) Adds a compatibility layer for LLM providers that don't properly populate reasoning_content in additional_kwargs. When reasoning_content is missing, the system now falls back to extracting reasoning traces from <think>...</think> tags in the response content and removes the tags from the final output. This fixes compatibility with certain NVIDIA models (e.g., nvidia/llama-3.3-nemotron-super-49b-v1.5) in langchain-nvidia-ai-endpoints that include reasoning traces in <think> tags but fail to populate the reasoning_content field. All reasoning models using ChatNVIDIA should expose reasoning content consistently through the same interface * Clean up the config_id logic based on Traian and Greptile feedback --------- Co-authored-by: Pouyan <[email protected]>
tgasser-nv
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Oct 28, 2025
tgasser-nv
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Oct 28, 2025
* Initial checkin * Add nemoguardrails/server to pyright type-checking * chore(types): Type-clean embeddings/ (25 errors) (#1383) * test: restore test that was skipped due to Colang 2.0 serialization issue (#1449) * fix(llm): add fallback extraction for reasoning traces from <think> tags (#1474) Adds a compatibility layer for LLM providers that don't properly populate reasoning_content in additional_kwargs. When reasoning_content is missing, the system now falls back to extracting reasoning traces from <think>...</think> tags in the response content and removes the tags from the final output. This fixes compatibility with certain NVIDIA models (e.g., nvidia/llama-3.3-nemotron-super-49b-v1.5) in langchain-nvidia-ai-endpoints that include reasoning traces in <think> tags but fail to populate the reasoning_content field. All reasoning models using ChatNVIDIA should expose reasoning content consistently through the same interface * Clean up the config_id logic based on Traian and Greptile feedback --------- Co-authored-by: Pouyan <[email protected]>
Pouyanpi
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Nov 3, 2025
* Initial checkin * Add nemoguardrails/server to pyright type-checking * chore(types): Type-clean embeddings/ (25 errors) (#1383) * test: restore test that was skipped due to Colang 2.0 serialization issue (#1449) * fix(llm): add fallback extraction for reasoning traces from <think> tags (#1474) Adds a compatibility layer for LLM providers that don't properly populate reasoning_content in additional_kwargs. When reasoning_content is missing, the system now falls back to extracting reasoning traces from <think>...</think> tags in the response content and removes the tags from the final output. This fixes compatibility with certain NVIDIA models (e.g., nvidia/llama-3.3-nemotron-super-49b-v1.5) in langchain-nvidia-ai-endpoints that include reasoning traces in <think> tags but fail to populate the reasoning_content field. All reasoning models using ChatNVIDIA should expose reasoning content consistently through the same interface * Clean up the config_id logic based on Traian and Greptile feedback --------- Co-authored-by: Pouyan <[email protected]>
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restore skipped test