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openai: lint

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Chester Curme 2025-07-11 14:07:47 -04:00
parent 679a9e7c8f
commit ce369125f3
3 changed files with 45 additions and 52 deletions
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58
libs/partners/openai/langchain_openai/chat_models/_compat.py
View File

@ -68,27 +68,17 @@ formats. The functions are used internally by ChatOpenAI.
import json
from collections.abc import Iterable
from typing import TYPE_CHECKING, Any, Union, cast
from typing import Any, Union, cast
from langchain_core.messages import (
AIMessage,
AIMessageChunk,
DocumentCitation,
NonStandardAnnotation,
ReasoningContentBlock,
UrlCitation,
is_data_content_block,
)
if TYPE_CHECKING:
from langchain_core.messages import (
Base64ContentBlock,
NonStandardContentBlock,
ReasoningContentBlock,
TextContentBlock,
ToolCallContentBlock,
)
_FUNCTION_CALL_IDS_MAP_KEY = "__openai_function_call_ids__"
@ -284,15 +274,13 @@ def _convert_to_v1_from_chat_completions(message: AIMessage) -> AIMessage:
"""Mutate a Chat Completions message to v1 format."""
if isinstance(message.content, str):
if message.content:
block: TextContentBlock = {"type": "text", "text": message.content}
message.content = [block]
message.content = [{"type": "text", "text": message.content}]
else:
message.content = []
for tool_call in message.tool_calls:
if id_ := tool_call.get("id"):
tool_call_block: ToolCallContentBlock = {"type": "tool_call", "id": id_}
message.content.append(tool_call_block)
message.content.append({"type": "tool_call", "id": id_})
if "tool_calls" in message.additional_kwargs:
_ = message.additional_kwargs.pop("tool_calls")
@ -336,31 +324,31 @@ def _convert_annotation_to_v1(
annotation_type = annotation.get("type")
if annotation_type == "url_citation":
new_annotation: UrlCitation = {"type": "url_citation", "url": annotation["url"]}
url_citation: UrlCitation = {"type": "url_citation", "url": annotation["url"]}
for field in ("title", "start_index", "end_index"):
if field in annotation:
new_annotation[field] = annotation[field]
return new_annotation
url_citation[field] = annotation[field]
return url_citation
elif annotation_type == "file_citation":
new_annotation: DocumentCitation = {"type": "document_citation"}
document_citation: DocumentCitation = {"type": "document_citation"}
if "filename" in annotation:
new_annotation["title"] = annotation["filename"]
document_citation["title"] = annotation["filename"]
for field in ("file_id", "index"): # OpenAI-specific
if field in annotation:
new_annotation[field] = annotation[field]
return new_annotation
document_citation[field] = annotation[field] # type: ignore[literal-required]
return document_citation
# TODO: standardise container_file_citation?
else:
new_annotation: NonStandardAnnotation = {
non_standard_annotation: NonStandardAnnotation = {
"type": "non_standard_annotation",
"value": annotation,
}
return new_annotation
return non_standard_annotation
def _explode_reasoning(block: dict[str, Any]) -> Iterable[ReasoningContentBlock]:
def _explode_reasoning(block: dict[str, Any]) -> Iterable[dict[str, Any]]:
if block.get("type") != "reasoning" or "summary" not in block:
yield block
return
@ -383,7 +371,7 @@ def _explode_reasoning(block: dict[str, Any]) -> Iterable[ReasoningContentBlock]
new_block["reasoning"] = part.get("text", "")
if idx == 0:
new_block.update(first_only)
yield cast(ReasoningContentBlock, new_block)
yield new_block
def _convert_to_v1_from_responses(message: AIMessage) -> AIMessage:
@ -393,6 +381,8 @@ def _convert_to_v1_from_responses(message: AIMessage) -> AIMessage:
def _iter_blocks() -> Iterable[dict[str, Any]]:
for block in message.content:
if not isinstance(block, dict):
continue
block_type = block.get("type")
if block_type == "text":
@ -408,11 +398,7 @@ def _convert_to_v1_from_responses(message: AIMessage) -> AIMessage:
elif block_type == "image_generation_call" and (
result := block.get("result")
):
new_block: Base64ContentBlock = {
"type": "image",
"source_type": "base64",
"data": result,
}
new_block = {"type": "image", "source_type": "base64", "data": result}
if output_format := block.get("output_format"):
new_block["mime_type"] = f"image/{output_format}"
for extra_key in (
@ -430,10 +416,7 @@ def _convert_to_v1_from_responses(message: AIMessage) -> AIMessage:
yield new_block
elif block_type == "function_call":
new_block: ToolCallContentBlock = {
"type": "tool_call",
"id": block.get("call_id", ""),
}
new_block = {"type": "tool_call", "id": block.get("call_id", "")}
if "id" in block:
new_block["item_id"] = block["id"]
for extra_key in ("arguments", "name", "index"):
@ -442,10 +425,7 @@ def _convert_to_v1_from_responses(message: AIMessage) -> AIMessage:
yield new_block
else:
new_block: NonStandardContentBlock = {
"type": "non_standard",
"value": block,
}
new_block = {"type": "non_standard", "value": block}
if "index" in new_block["value"]:
new_block["index"] = new_block["value"].pop("index")
yield new_block

6
libs/partners/openai/langchain_openai/chat_models/base.py
View File

@ -3803,7 +3803,7 @@ def _construct_lc_result_from_responses_api(
)
if image_generation_call.output_format:
mime_type = f"image/{image_generation_call.output_format}"
for block in message.content:
for block in message.beta_content: # type: ignore[assignment]
# OK to mutate output message
if (
block.get("type") == "image"
@ -4009,7 +4009,7 @@ def _convert_responses_chunk_to_generation_chunk(
}
)
else:
block = {"type": "reasoning", "reasoning": ""}
block: dict = {"type": "reasoning", "reasoning": ""}
if chunk.summary_index > 0:
_advance(chunk.output_index, chunk.summary_index)
block["id"] = chunk.item_id
@ -4050,7 +4050,7 @@ def _convert_responses_chunk_to_generation_chunk(
_convert_to_v03_ai_message(message, has_reasoning=has_reasoning),
)
elif output_version == "v1":
message = _convert_to_v1_from_responses(message)
message = cast(AIMessageChunk, _convert_to_v1_from_responses(message))
else:
pass
return (

33
libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py
View File

@ -472,6 +472,7 @@ def test_code_interpreter(output_version: Literal["v0", "responses/v1", "v1"]) -
"content": "Write and run code to answer the question: what is 3^3?",
}
response = llm_with_tools.invoke([input_message])
assert isinstance(response, AIMessage)
_check_response(response)
if output_version == "v0":
tool_outputs = [
@ -481,12 +482,16 @@ def test_code_interpreter(output_version: Literal["v0", "responses/v1", "v1"]) -
]
elif output_version == "responses/v1":
tool_outputs = [
item for item in response.content if item["type"] == "code_interpreter_call"
item
for item in response.content
if isinstance(item, dict) and item["type"] == "code_interpreter_call"
]
else:
# v1
tool_outputs = [
item["value"] for item in response.content if item["type"] == "non_standard"
item["value"]
for item in response.beta_content
if item["type"] == "non_standard"
]
assert tool_outputs[0]["type"] == "code_interpreter_call"
assert len(tool_outputs) == 1
@ -511,11 +516,15 @@ def test_code_interpreter(output_version: Literal["v0", "responses/v1", "v1"]) -
]
elif output_version == "responses/v1":
tool_outputs = [
item for item in response.content if item["type"] == "code_interpreter_call"
item
for item in response.content
if isinstance(item, dict) and item["type"] == "code_interpreter_call"
]
else:
tool_outputs = [
item["value"] for item in response.content if item["type"] == "non_standard"
item["value"]
for item in response.beta_content
if item["type"] == "non_standard"
]
assert tool_outputs[0]["type"] == "code_interpreter_call"
assert tool_outputs
@ -675,14 +684,16 @@ def test_image_generation_streaming(output_version: str) -> None:
tool_output = next(
block
for block in complete_ai_message.content
if block["type"] == "image_generation_call"
if isinstance(block, dict) and block["type"] == "image_generation_call"
)
assert set(tool_output.keys()).issubset(expected_keys)
else:
# v1
standard_keys = {"type", "source_type", "data", "id", "status", "index"}
tool_output = next(
block for block in complete_ai_message.content if block["type"] == "image"
block
for block in complete_ai_message.beta_content
if block["type"] == "image"
)
assert set(standard_keys).issubset(tool_output.keys())
@ -711,6 +722,7 @@ def test_image_generation_multi_turn(output_version: str) -> None:
{"role": "user", "content": "Draw a random short word in green font."}
]
ai_message = llm_with_tools.invoke(chat_history)
assert isinstance(ai_message, AIMessage)
_check_response(ai_message)
expected_keys = {
@ -732,13 +744,13 @@ def test_image_generation_multi_turn(output_version: str) -> None:
tool_output = next(
block
for block in ai_message.content
if block["type"] == "image_generation_call"
if isinstance(block, dict) and block["type"] == "image_generation_call"
)
assert set(tool_output.keys()).issubset(expected_keys)
else:
standard_keys = {"type", "source_type", "data", "id", "status"}
tool_output = next(
block for block in ai_message.content if block["type"] == "image"
block for block in ai_message.beta_content if block["type"] == "image"
)
assert set(standard_keys).issubset(tool_output.keys())
@ -774,6 +786,7 @@ def test_image_generation_multi_turn(output_version: str) -> None:
)
ai_message2 = llm_with_tools.invoke(chat_history)
assert isinstance(ai_message2, AIMessage)
_check_response(ai_message2)
if output_version == "v0":
@ -783,12 +796,12 @@ def test_image_generation_multi_turn(output_version: str) -> None:
tool_output = next(
block
for block in ai_message2.content
if block["type"] == "image_generation_call"
if isinstance(block, dict) and block["type"] == "image_generation_call"
)
assert set(tool_output.keys()).issubset(expected_keys)
else:
standard_keys = {"type", "source_type", "data", "id", "status"}
tool_output = next(
block for block in ai_message2.content if block["type"] == "image"
block for block in ai_message2.beta_content if block["type"] == "image"
)
assert set(standard_keys).issubset(tool_output.keys())