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Fix gemini/anthropic on_llm_end payload #197

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Merged
veithly merged 2 commits into from
Dec 3, 2025
Merged

Fix gemini/anthropic on_llm_end payload #197

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b935b60
Fix gemini/anthropic on_llm_end payload
helloissariel Dec 3, 2025
7dfd1b7
change anthropic max_tokens
helloissariel Dec 3, 2025
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2 changes: 1 addition & 1 deletion spoon_ai/llm/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -335,7 +335,7 @@ def _get_provider_defaults(self, provider_name: str) -> Dict[str, Any]:
'anthropic': {
'model': 'claude-sonnet-4-20250514',
'base_url': 'https://api.anthropic.com',
'max_tokens': 200000,
'max_tokens': 63000, # Claude Sonnet-4 supports max_token of context <64000
'temperature': 0.1, # Lower temperature for Claude
**{k: v for k, v in common_defaults.items() if k != 'temperature'}
},
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19 changes: 11 additions & 8 deletions spoon_ai/llm/providers/anthropic_provider.py
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Expand Up @@ -330,15 +330,18 @@ async def chat_stream(self, messages: List[Message],callbacks: Optional[List] =
usage_data["cache_read_input_tokens"] = chunk.usage.cache_read_input_tokens

# Trigger on_llm_end callback
final_response = LLMResponse(
content=full_content,
provider="anthropic",
model=model,
finish_reason=finish_reason or "stop",
native_finish_reason=finish_reason or "stop",
tool_calls=[],
usage=usage_data,
metadata={}
)
await callback_manager.on_llm_end(
response=LLMResponseChunk(
content=full_content,
provider="anthropic",
model=model,
finish_reason=finish_reason,
tool_calls=[],
usage=usage_data
),
response=final_response,
run_id=run_id
)

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19 changes: 11 additions & 8 deletions spoon_ai/llm/providers/gemini_provider.py
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Original file line number Diff line number Diff line change
Expand Up @@ -343,15 +343,18 @@ async def chat_stream(self, messages: List[Message],callbacks: Optional[List] =
yield response_chunk

# Trigger on_llm_end callback
final_response = LLMResponse(
content=full_content,
provider="gemini",
model=model,
finish_reason=finish_reason or "stop",
native_finish_reason=finish_reason or "stop",
tool_calls=[],
usage=usage_data,
metadata={}
)
await callback_manager.on_llm_end(
response=LLMResponseChunk(
content=full_content,
provider="gemini",
model=model,
finish_reason=finish_reason,
tool_calls=[],
usage=usage_data
),
response=final_response,
run_id=run_id
)

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