core[patch]: stringify tool non-content blocks (#24626)

Slightly breaking bugfix. Shouldn't cause too many issues since no
models would be able to handle non-content block ToolMessage.content
anyways.
This commit is contained in:
Bagatur 2024-07-31 16:42:38 -07:00 committed by GitHub
parent 492df75937
commit 25b93cc4c0
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2 changed files with 67 additions and 8 deletions

View File

@ -1485,14 +1485,7 @@ def _format_output(
content: Any, artifact: Any, tool_call_id: Optional[str], name: str, status: str
) -> Union[ToolMessage, Any]:
if tool_call_id:
# NOTE: This will fail to stringify lists which aren't actually content blocks
# but whose first element happens to be a string or dict. Tools should avoid
# returning such contents.
if not isinstance(content, str) and not (
isinstance(content, list)
and content
and isinstance(content[0], (str, dict))
):
if not _is_message_content_type(content):
content = _stringify(content)
return ToolMessage(
content,
@ -1505,6 +1498,26 @@ def _format_output(
return content
def _is_message_content_type(obj: Any) -> bool:
"""Check for OpenAI or Anthropic format tool message content."""
if isinstance(obj, str):
return True
elif isinstance(obj, list) and all(_is_message_content_block(e) for e in obj):
return True
else:
return False
def _is_message_content_block(obj: Any) -> bool:
"""Check for OpenAI or Anthropic format tool message content blocks."""
if isinstance(obj, str):
return True
elif isinstance(obj, dict):
return obj.get("type", None) in ("text", "image_url", "image", "json")
else:
return False
def _stringify(content: Any) -> str:
try:
return json.dumps(content)

View File

@ -32,6 +32,8 @@ from langchain_core.tools import (
StructuredTool,
Tool,
ToolException,
_is_message_content_block,
_is_message_content_type,
tool,
)
from langchain_core.utils.function_calling import convert_to_openai_function
@ -1623,3 +1625,47 @@ def test_structured_tool_with_different_pydantic_versions(pydantic_model: Any) -
"title": pydantic_model.__name__,
"type": "object",
}
valid_tool_result_blocks = [
"foo",
{"type": "text", "text": "foo"},
{"type": "text", "blah": "foo"}, # note, only 'type' key is currently checked
{"type": "image_url", "image_url": {}}, # openai format
{
"type": "image",
"source": {
"type": "base64",
"media_type": "image/jpeg",
"data": "123",
},
}, # anthropic format
{"type": "json", "json": {}}, # bedrock format
]
invalid_tool_result_blocks = [
{"text": "foo"}, # missing type
{"results": "foo"}, # not content blocks
]
@pytest.mark.parametrize(
("obj", "expected"),
[
*([[block, True] for block in valid_tool_result_blocks]),
*([[block, False] for block in invalid_tool_result_blocks]),
],
)
def test__is_message_content_block(obj: Any, expected: bool) -> None:
assert _is_message_content_block(obj) is expected
@pytest.mark.parametrize(
("obj", "expected"),
[
["foo", True],
[valid_tool_result_blocks, True],
[invalid_tool_result_blocks, False],
],
)
def test__is_message_content_type(obj: Any, expected: bool) -> None:
assert _is_message_content_type(obj) is expected