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core[major]: On Tool End Observation Casting Fix (#18798)

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This PR updates the on_tool_end handlers to return the raw output from the tool instead of casting it to a string. 

This is technically a breaking change, though it's impact is expected to be somewhat minimal. It will fix behavior in `astream_events` as well.

Fixes the following issue #18760 raised by @eyurtsev

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
This commit is contained in:
Mohammad Mohtashim
2024-03-11 19:59:04 +05:00
committed by GitHub
parent a96a6e0f2c
commit 43db4cd20e
20 changed files with 42 additions and 34 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
libs/community/langchain_community/callbacks/aim_callback.py
View File

@@ -314,8 +314,9 @@ class AimCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
self._run.track(aim.Text(input_str), name="on_tool_start", context=resp)
def on_tool_end(self, output: str, **kwargs: Any) -> None:
def on_tool_end(self, output: Any, **kwargs: Any) -> None:
"""Run when tool ends running."""
output = str(output)
aim = import_aim()
self.step += 1
self.tool_ends += 1

2
libs/community/langchain_community/callbacks/argilla_callback.py
View File

@@ -328,7 +328,7 @@ class ArgillaCallbackHandler(BaseCallbackHandler):
def on_tool_end(
self,
output: str,
output: Any,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,

2
libs/community/langchain_community/callbacks/arize_callback.py
View File

@@ -196,7 +196,7 @@ class ArizeCallbackHandler(BaseCallbackHandler):
def on_tool_end(
self,
output: str,
output: Any,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,

2
libs/community/langchain_community/callbacks/arthur_callback.py
View File

@@ -279,7 +279,7 @@ class ArthurCallbackHandler(BaseCallbackHandler):
def on_tool_end(
self,
output: str,
output: Any,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,

3
libs/community/langchain_community/callbacks/clearml_callback.py
View File

@@ -243,8 +243,9 @@ class ClearMLCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
if self.stream_logs:
self.logger.report_text(resp)
def on_tool_end(self, output: str, **kwargs: Any) -> None:
def on_tool_end(self, output: Any, **kwargs: Any) -> None:
"""Run when tool ends running."""
output = str(output)
self.step += 1
self.tool_ends += 1
self.ends += 1

3
libs/community/langchain_community/callbacks/comet_ml_callback.py
View File

@@ -303,8 +303,9 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
resp.update({"input_str": input_str})
self.action_records.append(resp)
def on_tool_end(self, output: str, **kwargs: Any) -> None:
def on_tool_end(self, output: Any, **kwargs: Any) -> None:
"""Run when tool ends running."""
output = str(output)
self.step += 1
self.tool_ends += 1
self.ends += 1

2
libs/community/langchain_community/callbacks/confident_callback.py
View File

@@ -162,7 +162,7 @@ class DeepEvalCallbackHandler(BaseCallbackHandler):
def on_tool_end(
self,
output: str,
output: Any,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,

3
libs/community/langchain_community/callbacks/llmonitor_callback.py
View File

@@ -465,13 +465,14 @@ class LLMonitorCallbackHandler(BaseCallbackHandler):
def on_tool_end(
self,
output: str,
output: Any,
*,
run_id: UUID,
parent_run_id: Union[UUID, None] = None,
tags: Union[List[str], None] = None,
**kwargs: Any,
) -> None:
output = str(output)
if self.__has_valid_config is False:
return
try:

3
libs/community/langchain_community/callbacks/mlflow_callback.py
View File

@@ -518,8 +518,9 @@ class MlflowCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
self.records["action_records"].append(resp)
self.mlflg.jsonf(resp, f"tool_start_{tool_starts}")
def on_tool_end(self, output: str, **kwargs: Any) -> None:
def on_tool_end(self, output: Any, **kwargs: Any) -> None:
"""Run when tool ends running."""
output = str(output)
self.metrics["step"] += 1
self.metrics["tool_ends"] += 1
self.metrics["ends"] += 1

3
libs/community/langchain_community/callbacks/sagemaker_callback.py
View File

@@ -186,8 +186,9 @@ class SageMakerCallbackHandler(BaseCallbackHandler):
self.jsonf(resp, self.temp_dir, f"tool_start_{tool_starts}")
def on_tool_end(self, output: str, **kwargs: Any) -> None:
def on_tool_end(self, output: Any, **kwargs: Any) -> None:
"""Run when tool ends running."""
output = str(output)
self.metrics["step"] += 1
self.metrics["tool_ends"] += 1
self.metrics["ends"] += 1

7
libs/community/langchain_community/callbacks/streamlit/streamlit_callback_handler.py
View File

@@ -183,13 +183,13 @@ class LLMThought:
def on_tool_end(
self,
output: str,
output: Any,
color: Optional[str] = None,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,
) -> None:
self._container.markdown(f"**{output}**")
self._container.markdown(f"**{str(output)}**")
def on_tool_error(self, error: BaseException, **kwargs: Any) -> None:
self._container.markdown("**Tool encountered an error...**")
@@ -363,12 +363,13 @@ class StreamlitCallbackHandler(BaseCallbackHandler):
def on_tool_end(
self,
output: str,
output: Any,
color: Optional[str] = None,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,
) -> None:
output = str(output)
self._require_current_thought().on_tool_end(
output, color, observation_prefix, llm_prefix, **kwargs
)

3
libs/community/langchain_community/callbacks/wandb_callback.py
View File

@@ -356,8 +356,9 @@ class WandbCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
if self.stream_logs:
self.run.log(resp)
def on_tool_end(self, output: str, **kwargs: Any) -> None:
def on_tool_end(self, output: Any, **kwargs: Any) -> None:
"""Run when tool ends running."""
output = str(output)
self.step += 1
self.tool_ends += 1
self.ends += 1