Tony20100/langchain_full huggingface dataset:
Parameters
outputs (Dict[str, Any]) – 
run_id (UUID) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
async on_chain_error(error: BaseException, *, inputs: Optional[Dict[str, Any]] = None, run_id: UUID, **kwargs: Any) → None¶
Run when chain errors.
Parameters
error (BaseException) – 
inputs (Optional[Dict[str, Any]]) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
None
async on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, run_type: Optional[str] = None, name: Optional[str] = None, **kwargs: Any) → None¶
Run when chain starts running.
Parameters
serialized (Dict[str, Any]) – 
inputs (Dict[str, Any]) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
run_type (Optional[str]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
None
async on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → Any¶
Run when a chat model starts running.
Run when a chat model starts running.
ATTENTION: This method is called for chat models. If you’re implementinga handler for a non-chat model, you should use on_llm_start instead.
Parameters
serialized (Dict[str, Any]) – 
messages (List[List[BaseMessage]]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
Any
async on_llm_end(response: LLMResult, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run when LLM ends running.
Parameters
response (LLMResult) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_llm_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run when LLM errors.
Parameters
error (BaseException) – The error that occurred.
kwargs (Any) – Additional keyword arguments.
- response (LLMResult): The response which was generated before
the error occurred.
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
Return type
None
tags (Optional[List[str]]) – 
Return type
None
async on_llm_new_token(token: str, *, chunk: Optional[Union[GenerationChunk, ChatGenerationChunk]] = None, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None¶
Run on new LLM token. Only available when streaming is enabled.
Parameters
token (str) – 
chunk (Optional[Union[GenerationChunk, ChatGenerationChunk]]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
None
async on_llm_start(serialized: Dict[str, Any], prompts: List[str], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → None¶
Run when LLM starts running.
ATTENTION: This method is called for non-chat models (regular LLMs). Ifyou’re implementing a handler for a chat model,
you should use on_chat_model_start instead.
Parameters
serialized (Dict[str, Any]) – 
prompts (List[str]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
async on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on retriever end.
Parameters
documents (Sequence[Document]) – 
run_id (UUID) –
Parameters
documents (Sequence[Document]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_retriever_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on retriever error.
Parameters
error (BaseException) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_retriever_start(serialized: Dict[str, Any], query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → None¶
Run on retriever start.
Parameters
serialized (Dict[str, Any]) – 
query (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
None
async on_retry(retry_state: RetryCallState, *, run_id: UUID, **kwargs: Any) → None¶
Run on a retry event.
Parameters
retry_state (RetryCallState) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
None
run_id (UUID) – 
kwargs (Any) – 
Return type
None
async on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on arbitrary text.
Parameters
text (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_tool_end(output: Any, *, run_id: UUID, **kwargs: Any) → None¶
Run when tool ends running.
Parameters
output (Any) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
None
async on_tool_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run when tool errors.
Parameters
error (BaseException) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → None¶
Run when tool starts running.
Parameters
serialized (Dict[str, Any]) – 
input_str (str) – 
run_id (UUID) –
langchain_core.tracers.base.AsyncBaseTracer¶
class langchain_core.tracers.base.AsyncBaseTracer(*, _schema_format: Literal['original', 'streaming_events', 'original+chat'] = 'original', **kwargs: Any)[source]¶
Async Base interface for tracers.
Initialize the tracer.
Parameters
_schema_format (Literal['original', 'streaming_events', 'original+chat']) – Primarily changes how the inputs and outputs are
handled. For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
’original+chat’ is a format that is the same as ‘original’except it does NOT raise an attribute error on_chat_model_start
kwargs (Any) – Additional keyword arguments that will be passed to
the super class.
Attributes
ignore_agent
Whether to ignore agent callbacks.
ignore_chain
Whether to ignore chain callbacks.
ignore_chat_model
Whether to ignore chat model callbacks.
ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
ignore_retry
Whether to ignore retry callbacks.
raise_error
run_inline
Methods
__init__(*[, _schema_format])
Initialize the tracer.
on_agent_action(action, *, run_id[, ...])
Run on agent action.
on_agent_finish(finish, *, run_id[, ...])
Run on agent end.
on_chain_end(outputs, *, run_id[, inputs])
Run when chain ends running.
on_chain_error(error, *[, inputs])
Run when chain ends running.
on_chain_error(error, *[, inputs])
Run when chain errors.
on_chain_start(serialized, inputs, *, run_id)
Run when chain starts running.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, *, run_id[, ...])
Run when LLM ends running.
on_llm_error(error, *, run_id[, ...])
Run when LLM errors.
on_llm_new_token(token, *[, chunk, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Run when LLM starts running.
on_retriever_end(documents, *, run_id[, ...])
Run on retriever end.
on_retriever_error(error, *, run_id[, ...])
Run on retriever error.
on_retriever_start(serialized, query, *, run_id)
Run on retriever start.
on_retry(retry_state, *, run_id, **kwargs)
Run on a retry event.
on_text(text, *, run_id[, parent_run_id, tags])
Run on arbitrary text.
on_tool_end(output, *, run_id, **kwargs)
Run when tool ends running.
on_tool_error(error, *, run_id[, ...])
Run when tool errors.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
__init__(*, _schema_format: Literal['original', 'streaming_events', 'original+chat'] = 'original', **kwargs: Any) → None¶
Initialize the tracer.
Parameters
_schema_format (Literal['original', 'streaming_events', 'original+chat']) – Primarily changes how the inputs and outputs are
handled. For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
’original+chat’ is a format that is the same as ‘original’except it does NOT raise an attribute error on_chat_model_start
kwargs (Any) – Additional keyword arguments that will be passed to
the super class.
Return type
None
async on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on agent action.
Parameters
action (AgentAction) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on agent end.
Parameters
finish (AgentFinish) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
kwargs (Any) – 
Return type
None
async on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → None[source]¶
Run when chain ends running.
Parameters
outputs (Dict[str, Any]) – 
run_id (UUID) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
async on_chain_error(error: BaseException, *, inputs: Optional[Dict[str, Any]] = None, run_id: UUID, **kwargs: Any) → None[source]¶
Run when chain errors.
Parameters
error (BaseException) – 
inputs (Optional[Dict[str, Any]]) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
None
async on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, run_type: Optional[str] = None, name: Optional[str] = None, **kwargs: Any) → None[source]¶
Run when chain starts running.
Parameters
serialized (Dict[str, Any]) – 
inputs (Dict[str, Any]) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
run_type (Optional[str]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
None
name (Optional[str]) – 
kwargs (Any) – 
Return type
None
async on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → Any[source]¶
Run when a chat model starts running.
ATTENTION: This method is called for chat models. If you’re implementinga handler for a non-chat model, you should use on_llm_start instead.
Parameters
serialized (Dict[str, Any]) – 
messages (List[List[BaseMessage]]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
Any
async on_llm_end(response: LLMResult, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None[source]¶
Run when LLM ends running.
Parameters
response (LLMResult) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_llm_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None[source]¶
Run when LLM errors.
Parameters
error (BaseException) – The error that occurred.
Parameters
error (BaseException) – The error that occurred.
kwargs (Any) – Additional keyword arguments.
- response (LLMResult): The response which was generated before
the error occurred.
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
Return type
None
async on_llm_new_token(token: str, *, chunk: Optional[Union[GenerationChunk, ChatGenerationChunk]] = None, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on new LLM token. Only available when streaming is enabled.
Parameters
token (str) – 
chunk (Optional[Union[GenerationChunk, ChatGenerationChunk]]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
None
async on_llm_start(serialized: Dict[str, Any], prompts: List[str], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → None[source]¶
Run when LLM starts running.
ATTENTION: This method is called for non-chat models (regular LLMs). Ifyou’re implementing a handler for a chat model,
you should use on_chat_model_start instead.
Parameters
serialized (Dict[str, Any]) – 
prompts (List[str]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
kwargs (Any) – 
Return type
None
async on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None[source]¶
Run on retriever end.
Parameters
documents (Sequence[Document]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_retriever_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None[source]¶
Run on retriever error.
Parameters
error (BaseException) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_retriever_start(serialized: Dict[str, Any], query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → None[source]¶
Run on retriever start.
Parameters
serialized (Dict[str, Any]) – 
query (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
None
name (Optional[str]) – 
kwargs (Any) – 
Return type
None
async on_retry(retry_state: RetryCallState, *, run_id: UUID, **kwargs: Any) → None[source]¶
Run on a retry event.
Parameters
retry_state (RetryCallState) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
None
async on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on arbitrary text.
Parameters
text (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_tool_end(output: Any, *, run_id: UUID, **kwargs: Any) → None[source]¶
Run when tool ends running.
Parameters
output (Any) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
None
async on_tool_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None[source]¶
Run when tool errors.
Parameters
error (BaseException) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
kwargs (Any) – 
Return type
None
async on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → None[source]¶
Run when tool starts running.
Parameters
serialized (Dict[str, Any]) – 
input_str (str) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
langchain_core.tracers.schemas.TracerSession¶
class langchain_core.tracers.schemas.TracerSession[source]¶
Bases: TracerSessionBase
[Deprecated] TracerSessionV1 schema for the V2 API.
Notes
Deprecated since version 0.1.0.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param extra: Optional[Dict[str, Any]] = None¶
param id: UUID [Required]¶
param name: Optional[str] = None¶
param start_time: datetime [Optional]¶
param tenant_id: UUID [Required]¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
langchain_core.tracers.schemas.TracerSessionBase¶
class langchain_core.tracers.schemas.TracerSessionBase[source]¶
Bases: TracerSessionV1Base
[Deprecated] Base class for TracerSession.
Notes
Deprecated since version 0.1.0.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param extra: Optional[Dict[str, Any]] = None¶
param name: Optional[str] = None¶
param start_time: datetime [Optional]¶
param tenant_id: UUID [Required]¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
langchain_core.tracers.schemas.BaseRun¶
class langchain_core.tracers.schemas.BaseRun[source]¶
Bases: BaseModel
[Deprecated] Base class for Run.
Notes
Deprecated since version 0.1.0: Use Run instead.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param child_execution_order: int [Required]¶
param end_time: datetime [Optional]¶
param error: Optional[str] = None¶
param execution_order: int [Required]¶
param extra: Optional[Dict[str, Any]] = None¶
param parent_uuid: Optional[str] = None¶
param serialized: Dict[str, Any] [Required]¶
param session_id: int [Required]¶
param start_time: datetime [Optional]¶
param uuid: str [Required]¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
langchain_core.tracers.stdout.ConsoleCallbackHandler¶
class langchain_core.tracers.stdout.ConsoleCallbackHandler(**kwargs: Any)[source]¶
Tracer that prints to the console.
Initialize the tracer.
Parameters
_schema_format – Primarily changes how the inputs and outputs are
handled. For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
’original+chat’ is a format that is the same as ‘original’except it does NOT raise an attribute error on_chat_model_start
kwargs (Any) – Additional keyword arguments that will be passed to
the super class.
Attributes
ignore_agent
Whether to ignore agent callbacks.
ignore_chain
Whether to ignore chain callbacks.
ignore_chat_model
Whether to ignore chat model callbacks.
ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
ignore_retry
Whether to ignore retry callbacks.
name
raise_error
run_inline
Methods
__init__(**kwargs)
Initialize the tracer.
get_breadcrumbs(run)
get_parents(run)
on_agent_action(action, *, run_id[, ...])
Run on agent action.
on_agent_finish(finish, *, run_id[, ...])
Run on agent end.
on_chain_end(outputs, *, run_id[, inputs])
End a trace for a chain run.
on_chain_error(error, *[, inputs])
Handle an error for a chain run.
on_chain_start(serialized, inputs, *, run_id)