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content blocks in stream

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This commit is contained in:
Chester Curme 2025-03-11 16:56:24 -04:00
parent 7445085ac2
commit f48a3c661a
2 changed files with 34 additions and 46 deletions
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9
libs/partners/openai/langchain_openai/chat_models/base.py
View File

@ -359,11 +359,11 @@ def _convert_delta_to_message_chunk(
def _convert_responses_chunk_to_generation_chunk( def _convert_responses_chunk_to_generation_chunk(
chunk: Any, chunk: Any,
) -> Optional[ChatGenerationChunk]: ) -> Optional[ChatGenerationChunk]:
content = "" content = []
generation_info = None generation_info = None
usage_metadata = None usage_metadata = None
if chunk.type == "response.output_text.delta": if chunk.type == "response.output_text.delta":
content = chunk.delta content += [{"type": "text", "text": chunk.delta, "index": chunk.content_index}]
elif chunk.type == "response.completed": elif chunk.type == "response.completed":
token_usage = chunk.response.usage.model_dump() if chunk.response.usage else {} token_usage = chunk.response.usage.model_dump() if chunk.response.usage else {}
usage_metadata = _create_usage_metadata_responses(token_usage) usage_metadata = _create_usage_metadata_responses(token_usage)
@ -372,7 +372,10 @@ def _convert_responses_chunk_to_generation_chunk(
return None return None
return ChatGenerationChunk( return ChatGenerationChunk(
message=AIMessageChunk(content=content, usage_metadata=usage_metadata), message=AIMessageChunk(
content=content, # type: ignore[arg-type]
usage_metadata=usage_metadata,
),
generation_info=generation_info, generation_info=generation_info,
) )

71
libs/partners/openai/tests/integration_tests/chat_models/test_base.py
View File

@ -1230,12 +1230,7 @@ def test_structured_output_and_tools() -> None:
assert tool_call["name"] == "GenerateUsername" assert tool_call["name"] == "GenerateUsername"
def test_web_search() -> None: def _check_response(response: Optional[BaseMessage]) -> None:
llm = ChatOpenAI(model="gpt-4o")
response = llm.invoke(
"What was a positive news story from today?",
tools=[{"type": "web_search_preview"}],
)
assert isinstance(response, AIMessage) assert isinstance(response, AIMessage)
assert isinstance(response.content, list) assert isinstance(response.content, list)
for block in response.content: for block in response.content:
@ -1253,19 +1248,26 @@ def test_web_search() -> None:
assert response.usage_metadata["output_tokens"] > 0 assert response.usage_metadata["output_tokens"] > 0
assert response.usage_metadata["total_tokens"] > 0 assert response.usage_metadata["total_tokens"] > 0
assert response.response_metadata["model_name"] assert response.response_metadata["model_name"]
def test_web_search() -> None:
llm = ChatOpenAI(model="gpt-4o")
response = llm.invoke(
"What was a positive news story from today?",
tools=[{"type": "web_search_preview"}],
)
_check_response(response)
assert response.response_metadata["status"] assert response.response_metadata["status"]
# Test streaming # Test streaming
# full: Optional[BaseMessageChunk] = None full: Optional[BaseMessageChunk] = None
# for chunk in llm.stream( for chunk in llm.stream(
# "What was a positive news story from today?", "What was a positive news story from today?",
# tools=[{"type": "web_search_preview"}], tools=[{"type": "web_search_preview"}],
# ): ):
# assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
# full = chunk if full is None else full + chunk full = chunk if full is None else full + chunk
# assert isinstance(full, AIMessageChunk) _check_response(full)
# assert full.content
# assert full.usage_metadata
async def test_web_search_async() -> None: async def test_web_search_async() -> None:
@ -1274,32 +1276,15 @@ async def test_web_search_async() -> None:
"What was a positive news story from today?", "What was a positive news story from today?",
tools=[{"type": "web_search_preview"}], tools=[{"type": "web_search_preview"}],
) )
assert isinstance(response, AIMessage) _check_response(response)
assert isinstance(response.content, list)
for block in response.content:
assert isinstance(block, dict)
if block["type"] == "text":
assert isinstance(block["text"], str)
for annotation in block["annotations"]:
for key in ["end_index", "start_index", "title", "type", "url"]:
assert key in annotation
text_content = response.text()
assert isinstance(text_content, str)
assert text_content
assert response.usage_metadata
assert response.usage_metadata["input_tokens"] > 0
assert response.usage_metadata["output_tokens"] > 0
assert response.usage_metadata["total_tokens"] > 0
assert response.response_metadata["model_name"]
assert response.response_metadata["status"] assert response.response_metadata["status"]
# full: Optional[BaseMessageChunk] = None full: Optional[BaseMessageChunk] = None
# async for chunk in llm.astream( async for chunk in llm.astream(
# "What was a positive news story from today?", "What was a positive news story from today?",
# tools=[{"type": "web_search_preview"}], tools=[{"type": "web_search_preview"}],
# ): ):
# assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
# full = chunk if full is None else full + chunk full = chunk if full is None else full + chunk
# assert isinstance(full, AIMessageChunk) assert isinstance(full, AIMessageChunk)
# assert full.content _check_response(response)
# assert full.usage_metadata