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e897d52ca95b-0 | langchain.callbacks.infino_callback.import_infino¶
langchain.callbacks.infino_callback.import_infino() → Any[source]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.infino_callback.import_infino.html |
4f127c8bb6df-0 | langchain.callbacks.utils.hash_string¶
langchain.callbacks.utils.hash_string(s: str) → str[source]¶
Hash a string using sha1.
Parameters
s (str) – The string to hash.
Returns
The hashed string.
Return type
(str) | [
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2886936bc501-0 | langchain.callbacks.tracers.langchain_v1.get_headers¶
langchain.callbacks.tracers.langchain_v1.get_headers() → Dict[str, Any][source]¶
Get the headers for the LangChain API. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.langchain_v1.get_headers.html |
fb6b3fd4e3fc-0 | langchain.callbacks.wandb_callback.import_wandb¶
langchain.callbacks.wandb_callback.import_wandb() → Any[source]¶
Import the wandb python package and raise an error if it is not installed. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.wandb_callback.import_wandb.html |
82de0b73f7ef-0 | langchain.callbacks.mlflow_callback.construct_html_from_prompt_and_generation¶
langchain.callbacks.mlflow_callback.construct_html_from_prompt_and_generation(prompt: str, generation: str) → Any[source]¶
Construct an html element from a prompt and a generation.
Parameters
prompt (str) – The prompt.
generation (str) – The generation.
Returns
The html string.
Return type
(str) | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.mlflow_callback.construct_html_from_prompt_and_generation.html |
98462a7839de-0 | langchain.callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler¶
class langchain.callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler(*, answer_prefix_tokens: Optional[List[str]] = None, strip_tokens: bool = True, stream_prefix: bool = False)[source]¶
Bases: StreamingStdOutCallbackHandler
Callback handler for streaming in agents.
Only works with agents using LLMs that support streaming.
Only the final output of the agent will be streamed.
Instantiate FinalStreamingStdOutCallbackHandler.
Parameters
answer_prefix_tokens – Token sequence that prefixes the anwer.
Default is [“Final”, “Answer”, “:”]
strip_tokens – Ignore white spaces and new lines when comparing
answer_prefix_tokens to last tokens? (to determine if answer has been
reached)
stream_prefix – Should answer prefix itself also be streamed?
Methods
__init__(*[, answer_prefix_tokens, ...])
Instantiate FinalStreamingStdOutCallbackHandler.
append_to_last_tokens(token)
check_if_answer_reached()
on_agent_action(action, **kwargs)
Run on agent action.
on_agent_finish(finish, **kwargs)
Run on agent end.
on_chain_end(outputs, **kwargs)
Run when chain ends running.
on_chain_error(error, **kwargs)
Run when chain errors.
on_chain_start(serialized, inputs, **kwargs)
Run when chain starts running.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, **kwargs)
Run when LLM ends running.
on_llm_error(error, **kwargs)
Run when LLM errors.
on_llm_new_token(token, **kwargs)
Run on new LLM token. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler.html |
98462a7839de-1 | on_llm_new_token(token, **kwargs)
Run on new LLM token.
on_llm_start(serialized, prompts, **kwargs)
Run when LLM starts running.
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, **kwargs)
Run on arbitrary text.
on_tool_end(output, **kwargs)
Run when tool ends running.
on_tool_error(error, **kwargs)
Run when tool errors.
on_tool_start(serialized, input_str, **kwargs)
Run when tool starts running.
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.
raise_error
run_inline
append_to_last_tokens(token: str) → None[source]¶
check_if_answer_reached() → bool[source]¶
on_agent_action(action: AgentAction, **kwargs: Any) → Any¶
Run on agent action.
on_agent_finish(finish: AgentFinish, **kwargs: Any) → None¶
Run on agent end.
on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None¶
Run when chain ends running.
on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None¶
Run when chain errors. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler.html |
98462a7839de-2 | Run when chain errors.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) → None¶
Run when chain starts running.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, **kwargs: Any) → None¶
Run when LLM ends running.
on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None¶
Run when LLM errors.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run on new LLM token. Only available when streaming is enabled.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Run when LLM starts running.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_text(text: str, **kwargs: Any) → None¶
Run on arbitrary text. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler.html |
98462a7839de-3 | Run on arbitrary text.
on_tool_end(output: str, **kwargs: Any) → None¶
Run when tool ends running.
on_tool_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None¶
Run when tool errors.
on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None¶
Run when tool starts running.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler.html |
5fa47c41ef8a-0 | langchain.callbacks.manager.AsyncCallbackManagerForLLMRun¶
class langchain.callbacks.manager.AsyncCallbackManagerForLLMRun(*, run_id: UUID, handlers: List[BaseCallbackHandler], inheritable_handlers: List[BaseCallbackHandler], parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: AsyncRunManager, LLMManagerMixin
Async callback manager for LLM run.
Initialize the run manager.
Parameters
run_id (UUID) – The ID of the run.
handlers (List[BaseCallbackHandler]) – The list of handlers.
inheritable_handlers (List[BaseCallbackHandler]) – The list of inheritable handlers.
parent_run_id (UUID, optional) – The ID of the parent run.
Defaults to None.
tags (Optional[List[str]]) – The list of tags.
inheritable_tags (Optional[List[str]]) – The list of inheritable tags.
Methods
__init__(*, run_id, handlers, ...[, ...])
Initialize the run manager.
get_noop_manager()
Return a manager that doesn't perform any operations.
on_llm_end(response, **kwargs)
Run when LLM ends running.
on_llm_error(error, **kwargs)
Run when LLM errors.
on_llm_new_token(token, **kwargs)
Run when LLM generates a new token.
on_text(text, **kwargs)
Run when text is received.
classmethod get_noop_manager() → BRM¶
Return a manager that doesn’t perform any operations.
Returns
The noop manager.
Return type
BaseRunManager
async on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Run when LLM ends running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManagerForLLMRun.html |
5fa47c41ef8a-1 | Run when LLM ends running.
Parameters
response (LLMResult) – The LLM result.
async on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when LLM errors.
Parameters
error (Exception or KeyboardInterrupt) – The error.
async on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run when LLM generates a new token.
Parameters
token (str) – The new token.
async on_text(text: str, **kwargs: Any) → Any¶
Run when text is received.
Parameters
text (str) – The received text.
Returns
The result of the callback.
Return type
Any | [
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a677e8e714ef-0 | langchain.callbacks.streamlit.streamlit_callback_handler.ToolRecord¶
class langchain.callbacks.streamlit.streamlit_callback_handler.ToolRecord(name, input_str)[source]¶
Bases: NamedTuple
Create new instance of ToolRecord(name, input_str)
Methods
__init__()
count(value, /)
Return number of occurrences of value.
index(value[, start, stop])
Return first index of value.
Attributes
input_str
Alias for field number 1
name
Alias for field number 0
count(value, /)¶
Return number of occurrences of value.
index(value, start=0, stop=9223372036854775807, /)¶
Return first index of value.
Raises ValueError if the value is not present.
input_str: str¶
Alias for field number 1
name: str¶
Alias for field number 0 | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.streamlit.streamlit_callback_handler.ToolRecord.html |
485509645840-0 | langchain.callbacks.tracers.stdout.ConsoleCallbackHandler¶
class langchain.callbacks.tracers.stdout.ConsoleCallbackHandler(**kwargs: Any)[source]¶
Bases: BaseTracer
Tracer that prints to the console.
Methods
__init__(**kwargs)
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, **kwargs)
End a trace for a chain run.
on_chain_error(error, *, run_id, **kwargs)
Handle an error for a chain run.
on_chain_start(serialized, inputs, *, run_id)
Start a trace for a chain run.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, *, run_id, **kwargs)
End a trace for an LLM run.
on_llm_error(error, *, run_id, **kwargs)
Handle an error for an LLM run.
on_llm_new_token(token, *, run_id[, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Start a trace for an LLM run.
on_retriever_end(documents, *, run_id, **kwargs)
Run when Retriever ends running.
on_retriever_error(error, *, run_id, **kwargs)
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.stdout.ConsoleCallbackHandler.html |
485509645840-1 | Run when Retriever starts running.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
on_tool_end(output, *, run_id, **kwargs)
End a trace for a tool run.
on_tool_error(error, *, run_id, **kwargs)
Handle an error for a tool run.
on_tool_start(serialized, input_str, *, run_id)
Start a trace for a tool run.
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.
name
raise_error
run_inline
get_breadcrumbs(run: Run) → str[source]¶
get_parents(run: Run) → List[Run][source]¶
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent end.
on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, **kwargs: Any) → None¶
End a trace for a chain run.
on_chain_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Handle an error for a chain run. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.stdout.ConsoleCallbackHandler.html |
485509645840-2 | Handle an error for a chain run.
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, **kwargs: Any) → None¶
Start a trace for a chain run.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, *, run_id: UUID, **kwargs: Any) → None¶
End a trace for an LLM run.
on_llm_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Handle an error for an LLM run.
on_llm_new_token(token: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on new LLM token. Only available when streaming is enabled.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None¶
Start a trace for an LLM run.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, **kwargs: Any) → None¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Run when Retriever errors. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.stdout.ConsoleCallbackHandler.html |
485509645840-3 | Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None¶
Run when Retriever starts running.
on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on arbitrary text.
on_tool_end(output: str, *, run_id: UUID, **kwargs: Any) → None¶
End a trace for a tool run.
on_tool_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Handle an error for a tool run.
on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None¶
Start a trace for a tool run.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
name = 'console_callback_handler'¶
raise_error: bool = False¶
run_inline: bool = False¶
run_map: Dict[str, Run]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.stdout.ConsoleCallbackHandler.html |
2b368c43c01e-0 | langchain.callbacks.aim_callback.AimCallbackHandler¶
class langchain.callbacks.aim_callback.AimCallbackHandler(repo: Optional[str] = None, experiment_name: Optional[str] = None, system_tracking_interval: Optional[int] = 10, log_system_params: bool = True)[source]¶
Bases: BaseMetadataCallbackHandler, BaseCallbackHandler
Callback Handler that logs to Aim.
Parameters
repo (str, optional) – Aim repository path or Repo object to which
Run object is bound. If skipped, default Repo is used.
experiment_name (str, optional) – Sets Run’s experiment property.
‘default’ if not specified. Can be used later to query runs/sequences.
system_tracking_interval (int, optional) – Sets the tracking interval
in seconds for system usage metrics (CPU, Memory, etc.). Set to None
to disable system metrics tracking.
log_system_params (bool, optional) – Enable/Disable logging of system
params such as installed packages, git info, environment variables, etc.
This handler will utilize the associated callback method called and formats
the input of each callback function with metadata regarding the state of LLM run
and then logs the response to Aim.
Initialize callback handler.
Methods
__init__([repo, experiment_name, ...])
Initialize callback handler.
flush_tracker([repo, experiment_name, ...])
Flush the tracker and reset the session.
get_custom_callback_meta()
on_agent_action(action, **kwargs)
Run on agent action.
on_agent_finish(finish, **kwargs)
Run when agent ends running.
on_chain_end(outputs, **kwargs)
Run when chain ends running.
on_chain_error(error, **kwargs)
Run when chain errors.
on_chain_start(serialized, inputs, **kwargs)
Run when chain starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.aim_callback.AimCallbackHandler.html |
2b368c43c01e-1 | Run when chain starts running.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, **kwargs)
Run when LLM ends running.
on_llm_error(error, **kwargs)
Run when LLM errors.
on_llm_new_token(token, **kwargs)
Run when LLM generates a new token.
on_llm_start(serialized, prompts, **kwargs)
Run when LLM starts.
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, **kwargs)
Run when agent is ending.
on_tool_end(output, **kwargs)
Run when tool ends running.
on_tool_error(error, **kwargs)
Run when tool errors.
on_tool_start(serialized, input_str, **kwargs)
Run when tool starts running.
reset_callback_meta()
Reset the callback metadata.
setup(**kwargs)
Attributes
always_verbose
Whether to call verbose callbacks even if verbose is False.
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.
raise_error
run_inline | [
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2b368c43c01e-2 | ignore_retriever
Whether to ignore retriever callbacks.
raise_error
run_inline
flush_tracker(repo: Optional[str] = None, experiment_name: Optional[str] = None, system_tracking_interval: Optional[int] = 10, log_system_params: bool = True, langchain_asset: Any = None, reset: bool = True, finish: bool = False) → None[source]¶
Flush the tracker and reset the session.
Parameters
repo (str, optional) – Aim repository path or Repo object to which
Run object is bound. If skipped, default Repo is used.
experiment_name (str, optional) – Sets Run’s experiment property.
‘default’ if not specified. Can be used later to query runs/sequences.
system_tracking_interval (int, optional) – Sets the tracking interval
in seconds for system usage metrics (CPU, Memory, etc.). Set to None
to disable system metrics tracking.
log_system_params (bool, optional) – Enable/Disable logging of system
params such as installed packages, git info, environment variables, etc.
langchain_asset – The langchain asset to save.
reset – Whether to reset the session.
finish – Whether to finish the run.
Returns – None
get_custom_callback_meta() → Dict[str, Any]¶
on_agent_action(action: AgentAction, **kwargs: Any) → Any[source]¶
Run on agent action.
on_agent_finish(finish: AgentFinish, **kwargs: Any) → None[source]¶
Run when agent ends running.
on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Run when chain ends running.
on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when chain errors. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.aim_callback.AimCallbackHandler.html |
2b368c43c01e-3 | Run when chain errors.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Run when chain starts running.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Run when LLM ends running.
on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when LLM errors.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run when LLM generates a new token.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Run when LLM starts.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_text(text: str, **kwargs: Any) → None[source]¶
Run when agent is ending. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.aim_callback.AimCallbackHandler.html |
2b368c43c01e-4 | Run when agent is ending.
on_tool_end(output: str, **kwargs: Any) → None[source]¶
Run when tool ends running.
on_tool_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when tool errors.
on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None[source]¶
Run when tool starts running.
reset_callback_meta() → None¶
Reset the callback metadata.
setup(**kwargs: Any) → None[source]¶
property always_verbose: bool¶
Whether to call verbose callbacks even if verbose is False.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.aim_callback.AimCallbackHandler.html |
856abf5b1fb9-0 | langchain.callbacks.tracers.schemas.TracerSessionBase¶
class langchain.callbacks.tracers.schemas.TracerSessionBase(*, start_time: datetime = None, name: Optional[str] = None, extra: Optional[Dict[str, Any]] = None, tenant_id: UUID)[source]¶
Bases: TracerSessionV1Base
A creation class for TracerSession.
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.datetime [Optional]¶
param tenant_id: uuid.UUID [Required]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.schemas.TracerSessionBase.html |
f2f1db571848-0 | langchain.callbacks.manager.env_var_is_set¶
langchain.callbacks.manager.env_var_is_set(env_var: str) → bool[source]¶
Check if an environment variable is set.
Parameters
env_var (str) – The name of the environment variable.
Returns
True if the environment variable is set, False otherwise.
Return type
bool | [
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7e68e58e5b8d-0 | langchain.callbacks.clearml_callback.ClearMLCallbackHandler¶
class langchain.callbacks.clearml_callback.ClearMLCallbackHandler(task_type: Optional[str] = 'inference', project_name: Optional[str] = 'langchain_callback_demo', tags: Optional[Sequence] = None, task_name: Optional[str] = None, visualize: bool = False, complexity_metrics: bool = False, stream_logs: bool = False)[source]¶
Bases: BaseMetadataCallbackHandler, BaseCallbackHandler
Callback Handler that logs to ClearML.
Parameters
job_type (str) – The type of clearml task such as “inference”, “testing” or “qc”
project_name (str) – The clearml project name
tags (list) – Tags to add to the task
task_name (str) – Name of the clearml task
visualize (bool) – Whether to visualize the run.
complexity_metrics (bool) – Whether to log complexity metrics
stream_logs (bool) – Whether to stream callback actions to ClearML
This handler will utilize the associated callback method and formats
the input of each callback function with metadata regarding the state of LLM run,
and adds the response to the list of records for both the {method}_records and
action. It then logs the response to the ClearML console.
Initialize callback handler.
Methods
__init__([task_type, project_name, tags, ...])
Initialize callback handler.
analyze_text(text)
Analyze text using textstat and spacy.
flush_tracker([name, langchain_asset, finish])
Flush the tracker and setup the session.
get_custom_callback_meta()
on_agent_action(action, **kwargs)
Run on agent action.
on_agent_finish(finish, **kwargs)
Run when agent ends running.
on_chain_end(outputs, **kwargs) | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html |
7e68e58e5b8d-1 | Run when agent ends running.
on_chain_end(outputs, **kwargs)
Run when chain ends running.
on_chain_error(error, **kwargs)
Run when chain errors.
on_chain_start(serialized, inputs, **kwargs)
Run when chain starts running.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, **kwargs)
Run when LLM ends running.
on_llm_error(error, **kwargs)
Run when LLM errors.
on_llm_new_token(token, **kwargs)
Run when LLM generates a new token.
on_llm_start(serialized, prompts, **kwargs)
Run when LLM starts.
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, **kwargs)
Run when agent is ending.
on_tool_end(output, **kwargs)
Run when tool ends running.
on_tool_error(error, **kwargs)
Run when tool errors.
on_tool_start(serialized, input_str, **kwargs)
Run when tool starts running.
reset_callback_meta()
Reset the callback metadata.
Attributes
always_verbose
Whether to call verbose callbacks even if verbose is False.
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 | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html |
7e68e58e5b8d-2 | ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
raise_error
run_inline
analyze_text(text: str) → dict[source]¶
Analyze text using textstat and spacy.
Parameters
text (str) – The text to analyze.
Returns
A dictionary containing the complexity metrics.
Return type
(dict)
flush_tracker(name: Optional[str] = None, langchain_asset: Any = None, finish: bool = False) → None[source]¶
Flush the tracker and setup the session.
Everything after this will be a new table.
Parameters
name – Name of the preformed session so far so it is identifyable
langchain_asset – The langchain asset to save.
finish – Whether to finish the run.
Returns – None
get_custom_callback_meta() → Dict[str, Any]¶
on_agent_action(action: AgentAction, **kwargs: Any) → Any[source]¶
Run on agent action.
on_agent_finish(finish: AgentFinish, **kwargs: Any) → None[source]¶
Run when agent ends running.
on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Run when chain ends running.
on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when chain errors.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Run when chain starts running.
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, **kwargs: Any) → Any¶
Run when a chat model starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html |
7e68e58e5b8d-3 | Run when a chat model starts running.
on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Run when LLM ends running.
on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when LLM errors.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run when LLM generates a new token.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Run when LLM starts.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_text(text: str, **kwargs: Any) → None[source]¶
Run when agent is ending.
on_tool_end(output: str, **kwargs: Any) → None[source]¶
Run when tool ends running.
on_tool_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when tool errors.
on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None[source]¶
Run when tool starts running.
reset_callback_meta() → None¶
Reset the callback metadata. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html |
7e68e58e5b8d-4 | reset_callback_meta() → None¶
Reset the callback metadata.
property always_verbose: bool¶
Whether to call verbose callbacks even if verbose is False.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html |
dbf7cb8d7090-0 | langchain.callbacks.manager.RunManager¶
class langchain.callbacks.manager.RunManager(*, run_id: UUID, handlers: List[BaseCallbackHandler], inheritable_handlers: List[BaseCallbackHandler], parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: BaseRunManager
Sync Run Manager.
Initialize the run manager.
Parameters
run_id (UUID) – The ID of the run.
handlers (List[BaseCallbackHandler]) – The list of handlers.
inheritable_handlers (List[BaseCallbackHandler]) – The list of inheritable handlers.
parent_run_id (UUID, optional) – The ID of the parent run.
Defaults to None.
tags (Optional[List[str]]) – The list of tags.
inheritable_tags (Optional[List[str]]) – The list of inheritable tags.
Methods
__init__(*, run_id, handlers, ...[, ...])
Initialize the run manager.
get_noop_manager()
Return a manager that doesn't perform any operations.
on_text(text, **kwargs)
Run when text is received.
classmethod get_noop_manager() → BRM¶
Return a manager that doesn’t perform any operations.
Returns
The noop manager.
Return type
BaseRunManager
on_text(text: str, **kwargs: Any) → Any[source]¶
Run when text is received.
Parameters
text (str) – The received text.
Returns
The result of the callback.
Return type
Any | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.RunManager.html |
d7380b18dda2-0 | langchain.callbacks.wandb_callback.construct_html_from_prompt_and_generation¶
langchain.callbacks.wandb_callback.construct_html_from_prompt_and_generation(prompt: str, generation: str) → Any[source]¶
Construct an html element from a prompt and a generation.
Parameters
prompt (str) – The prompt.
generation (str) – The generation.
Returns
The html element.
Return type
(wandb.Html) | [
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834ea16bb6f0-0 | langchain.callbacks.wandb_callback.load_json_to_dict¶
langchain.callbacks.wandb_callback.load_json_to_dict(json_path: Union[str, Path]) → dict[source]¶
Load json file to a dictionary.
Parameters
json_path (str) – The path to the json file.
Returns
The dictionary representation of the json file.
Return type
(dict) | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.wandb_callback.load_json_to_dict.html |
fb6f68475f7e-0 | langchain.callbacks.manager.CallbackManagerForLLMRun¶
class langchain.callbacks.manager.CallbackManagerForLLMRun(*, run_id: UUID, handlers: List[BaseCallbackHandler], inheritable_handlers: List[BaseCallbackHandler], parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: RunManager, LLMManagerMixin
Callback manager for LLM run.
Initialize the run manager.
Parameters
run_id (UUID) – The ID of the run.
handlers (List[BaseCallbackHandler]) – The list of handlers.
inheritable_handlers (List[BaseCallbackHandler]) – The list of inheritable handlers.
parent_run_id (UUID, optional) – The ID of the parent run.
Defaults to None.
tags (Optional[List[str]]) – The list of tags.
inheritable_tags (Optional[List[str]]) – The list of inheritable tags.
Methods
__init__(*, run_id, handlers, ...[, ...])
Initialize the run manager.
get_noop_manager()
Return a manager that doesn't perform any operations.
on_llm_end(response, **kwargs)
Run when LLM ends running.
on_llm_error(error, **kwargs)
Run when LLM errors.
on_llm_new_token(token, **kwargs)
Run when LLM generates a new token.
on_text(text, **kwargs)
Run when text is received.
classmethod get_noop_manager() → BRM¶
Return a manager that doesn’t perform any operations.
Returns
The noop manager.
Return type
BaseRunManager
on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Run when LLM ends running.
Parameters | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.CallbackManagerForLLMRun.html |
fb6f68475f7e-1 | Run when LLM ends running.
Parameters
response (LLMResult) – The LLM result.
on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when LLM errors.
Parameters
error (Exception or KeyboardInterrupt) – The error.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run when LLM generates a new token.
Parameters
token (str) – The new token.
on_text(text: str, **kwargs: Any) → Any¶
Run when text is received.
Parameters
text (str) – The received text.
Returns
The result of the callback.
Return type
Any | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.CallbackManagerForLLMRun.html |
f9be8890c4c2-0 | langchain.callbacks.manager.CallbackManager¶
class langchain.callbacks.manager.CallbackManager(handlers: List[BaseCallbackHandler], inheritable_handlers: Optional[List[BaseCallbackHandler]] = None, parent_run_id: Optional[UUID] = None, *, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: BaseCallbackManager
Callback manager that can be used to handle callbacks from langchain.
Initialize callback manager.
Methods
__init__(handlers[, inheritable_handlers, ...])
Initialize callback manager.
add_handler(handler[, inherit])
Add a handler to the callback manager.
add_tags(tags[, inherit])
configure([inheritable_callbacks, ...])
Configure the callback manager.
on_chain_start(serialized, inputs[, run_id])
Run when chain starts running.
on_chat_model_start(serialized, messages, ...)
Run when LLM starts running.
on_llm_start(serialized, prompts, **kwargs)
Run when LLM starts running.
on_retriever_start(query[, run_id, ...])
Run when retriever starts running.
on_tool_start(serialized, input_str[, ...])
Run when tool starts running.
remove_handler(handler)
Remove a handler from the callback manager.
remove_tags(tags)
set_handler(handler[, inherit])
Set handler as the only handler on the callback manager.
set_handlers(handlers[, inherit])
Set handlers as the only handlers on the callback manager.
Attributes
is_async
Whether the callback manager is async.
add_handler(handler: BaseCallbackHandler, inherit: bool = True) → None¶
Add a handler to the callback manager.
add_tags(tags: List[str], inherit: bool = True) → None¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.CallbackManager.html |
f9be8890c4c2-1 | add_tags(tags: List[str], inherit: bool = True) → None¶
classmethod configure(inheritable_callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, local_callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, verbose: bool = False, inheritable_tags: Optional[List[str]] = None, local_tags: Optional[List[str]] = None) → CallbackManager[source]¶
Configure the callback manager.
Parameters
inheritable_callbacks (Optional[Callbacks], optional) – The inheritable
callbacks. Defaults to None.
local_callbacks (Optional[Callbacks], optional) – The local callbacks.
Defaults to None.
verbose (bool, optional) – Whether to enable verbose mode. Defaults to False.
inheritable_tags (Optional[List[str]], optional) – The inheritable tags.
Defaults to None.
local_tags (Optional[List[str]], optional) – The local tags.
Defaults to None.
Returns
The configured callback manager.
Return type
CallbackManager
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], run_id: Optional[UUID] = None, **kwargs: Any) → CallbackManagerForChainRun[source]¶
Run when chain starts running.
Parameters
serialized (Dict[str, Any]) – The serialized chain.
inputs (Dict[str, Any]) – The inputs to the chain.
run_id (UUID, optional) – The ID of the run. Defaults to None.
Returns
The callback manager for the chain run.
Return type
CallbackManagerForChainRun
on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], **kwargs: Any) → List[CallbackManagerForLLMRun][source]¶
Run when LLM starts running.
Parameters
serialized (Dict[str, Any]) – The serialized LLM. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.CallbackManager.html |
f9be8890c4c2-2 | Parameters
serialized (Dict[str, Any]) – The serialized LLM.
messages (List[List[BaseMessage]]) – The list of messages.
run_id (UUID, optional) – The ID of the run. Defaults to None.
Returns
A callback manager for eachlist of messages as an LLM run.
Return type
List[CallbackManagerForLLMRun]
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → List[CallbackManagerForLLMRun][source]¶
Run when LLM starts running.
Parameters
serialized (Dict[str, Any]) – The serialized LLM.
prompts (List[str]) – The list of prompts.
run_id (UUID, optional) – The ID of the run. Defaults to None.
Returns
A callback manager for eachprompt as an LLM run.
Return type
List[CallbackManagerForLLMRun]
on_retriever_start(query: str, run_id: Optional[UUID] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → CallbackManagerForRetrieverRun[source]¶
Run when retriever starts running.
on_tool_start(serialized: Dict[str, Any], input_str: str, run_id: Optional[UUID] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → CallbackManagerForToolRun[source]¶
Run when tool starts running.
Parameters
serialized (Dict[str, Any]) – The serialized tool.
input_str (str) – The input to the tool.
run_id (UUID, optional) – The ID of the run. Defaults to None.
parent_run_id (UUID, optional) – The ID of the parent run. Defaults to None.
Returns
The callback manager for the tool run.
Return type | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.CallbackManager.html |
f9be8890c4c2-3 | Returns
The callback manager for the tool run.
Return type
CallbackManagerForToolRun
remove_handler(handler: BaseCallbackHandler) → None¶
Remove a handler from the callback manager.
remove_tags(tags: List[str]) → None¶
set_handler(handler: BaseCallbackHandler, inherit: bool = True) → None¶
Set handler as the only handler on the callback manager.
set_handlers(handlers: List[BaseCallbackHandler], inherit: bool = True) → None¶
Set handlers as the only handlers on the callback manager.
property is_async: bool¶
Whether the callback manager is async. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.CallbackManager.html |
450b9755f446-0 | langchain.callbacks.tracers.schemas.Run¶
class langchain.callbacks.tracers.schemas.Run(*, id: UUID, name: str, start_time: datetime, run_type: str, end_time: Optional[datetime] = None, extra: Optional[dict] = None, error: Optional[str] = None, serialized: Optional[dict] = None, events: Optional[List[Dict]] = None, inputs: dict, outputs: Optional[dict] = None, reference_example_id: Optional[UUID] = None, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, execution_order: int, child_execution_order: int, child_runs: List[Run] = None)[source]¶
Bases: RunBase
Run schema for the V2 API in the Tracer.
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 child_runs: List[langchain.callbacks.tracers.schemas.Run] [Optional]¶
param end_time: Optional[<module 'datetime' from '/home/docs/.asdf/installs/python/3.11.4/lib/python3.11/datetime.py'>] = None¶
param error: Optional[str] = None¶
param events: Optional[List[Dict]] = None¶
param execution_order: int [Required]¶
param extra: Optional[dict] = None¶
param id: uuid.UUID [Required]¶
param inputs: dict [Required]¶
param name: str [Required]¶
param outputs: Optional[dict] = None¶
param parent_run_id: Optional[uuid.UUID] = None¶
param reference_example_id: Optional[uuid.UUID] = None¶
param run_type: str [Required]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.schemas.Run.html |
450b9755f446-1 | param run_type: str [Required]¶
param serialized: Optional[dict] = None¶
param start_time: <module 'datetime' from '/home/docs/.asdf/installs/python/3.11.4/lib/python3.11/datetime.py'> [Required]¶
param tags: Optional[List[str]] [Optional]¶
validator assign_name » all fields[source]¶
Assign name to the run. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.schemas.Run.html |
249fef95378b-0 | langchain.callbacks.tracers.wandb.WandbRunArgs¶
class langchain.callbacks.tracers.wandb.WandbRunArgs[source]¶
Bases: TypedDict
Arguments for the WandbTracer.
Methods
__init__(*args, **kwargs)
clear()
copy()
fromkeys([value])
Create a new dictionary with keys from iterable and values set to value.
get(key[, default])
Return the value for key if key is in the dictionary, else default.
items()
keys()
pop(k[,d])
If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem()
Remove and return a (key, value) pair as a 2-tuple.
setdefault(key[, default])
Insert key with a value of default if key is not in the dictionary.
update([E, ]**F)
If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()
Attributes
job_type
dir
config
project
entity
reinit
tags
group
name
notes
magic
config_exclude_keys
config_include_keys
anonymous
mode
allow_val_change
resume
force
tensorboard
sync_tensorboard
monitor_gym
save_code
id
settings
clear() → None. Remove all items from D.¶
copy() → a shallow copy of D¶
fromkeys(value=None, /)¶
Create a new dictionary with keys from iterable and values set to value. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.wandb.WandbRunArgs.html |
249fef95378b-1 | Create a new dictionary with keys from iterable and values set to value.
get(key, default=None, /)¶
Return the value for key if key is in the dictionary, else default.
items() → a set-like object providing a view on D's items¶
keys() → a set-like object providing a view on D's keys¶
pop(k[, d]) → v, remove specified key and return the corresponding value.¶
If the key is not found, return the default if given; otherwise,
raise a KeyError.
popitem()¶
Remove and return a (key, value) pair as a 2-tuple.
Pairs are returned in LIFO (last-in, first-out) order.
Raises KeyError if the dict is empty.
setdefault(key, default=None, /)¶
Insert key with a value of default if key is not in the dictionary.
Return the value for key if key is in the dictionary, else default.
update([E, ]**F) → None. Update D from dict/iterable E and F.¶
If E is present and has a .keys() method, then does: for k in E: D[k] = E[k]
If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v
In either case, this is followed by: for k in F: D[k] = F[k]
values() → an object providing a view on D's values¶
allow_val_change: Optional[bool]¶
anonymous: Optional[str]¶
config: Union[Dict, str, None]¶
config_exclude_keys: Optional[List[str]]¶
config_include_keys: Optional[List[str]]¶
dir: Optional[StrPath]¶
entity: Optional[str]¶
force: Optional[bool]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.wandb.WandbRunArgs.html |
249fef95378b-2 | entity: Optional[str]¶
force: Optional[bool]¶
group: Optional[str]¶
id: Optional[str]¶
job_type: Optional[str]¶
magic: Optional[Union[dict, str, bool]]¶
mode: Optional[str]¶
monitor_gym: Optional[bool]¶
name: Optional[str]¶
notes: Optional[str]¶
project: Optional[str]¶
reinit: Optional[bool]¶
resume: Optional[Union[bool, str]]¶
save_code: Optional[bool]¶
settings: Union[WBSettings, Dict[str, Any], None]¶
sync_tensorboard: Optional[bool]¶
tags: Optional[Sequence]¶
tensorboard: Optional[bool]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.wandb.WandbRunArgs.html |
c77ee8d4b0d9-0 | langchain.callbacks.manager.AsyncCallbackManager¶
class langchain.callbacks.manager.AsyncCallbackManager(handlers: List[BaseCallbackHandler], inheritable_handlers: Optional[List[BaseCallbackHandler]] = None, parent_run_id: Optional[UUID] = None, *, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: BaseCallbackManager
Async callback manager that can be used to handle callbacks from LangChain.
Initialize callback manager.
Methods
__init__(handlers[, inheritable_handlers, ...])
Initialize callback manager.
add_handler(handler[, inherit])
Add a handler to the callback manager.
add_tags(tags[, inherit])
configure([inheritable_callbacks, ...])
Configure the async callback manager.
on_chain_start(serialized, inputs[, run_id])
Run when chain starts running.
on_chat_model_start(serialized, messages, ...)
Run when LLM starts running.
on_llm_start(serialized, prompts, **kwargs)
Run when LLM starts running.
on_retriever_start(query[, run_id, ...])
Run when retriever starts running.
on_tool_start(serialized, input_str[, ...])
Run when tool starts running.
remove_handler(handler)
Remove a handler from the callback manager.
remove_tags(tags)
set_handler(handler[, inherit])
Set handler as the only handler on the callback manager.
set_handlers(handlers[, inherit])
Set handlers as the only handlers on the callback manager.
Attributes
is_async
Return whether the handler is async.
add_handler(handler: BaseCallbackHandler, inherit: bool = True) → None¶
Add a handler to the callback manager.
add_tags(tags: List[str], inherit: bool = True) → None¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManager.html |
c77ee8d4b0d9-1 | add_tags(tags: List[str], inherit: bool = True) → None¶
classmethod configure(inheritable_callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, local_callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, verbose: bool = False, inheritable_tags: Optional[List[str]] = None, local_tags: Optional[List[str]] = None) → AsyncCallbackManager[source]¶
Configure the async callback manager.
Parameters
inheritable_callbacks (Optional[Callbacks], optional) – The inheritable
callbacks. Defaults to None.
local_callbacks (Optional[Callbacks], optional) – The local callbacks.
Defaults to None.
verbose (bool, optional) – Whether to enable verbose mode. Defaults to False.
inheritable_tags (Optional[List[str]], optional) – The inheritable tags.
Defaults to None.
local_tags (Optional[List[str]], optional) – The local tags.
Defaults to None.
Returns
The configured async callback manager.
Return type
AsyncCallbackManager
async on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], run_id: Optional[UUID] = None, **kwargs: Any) → AsyncCallbackManagerForChainRun[source]¶
Run when chain starts running.
Parameters
serialized (Dict[str, Any]) – The serialized chain.
inputs (Dict[str, Any]) – The inputs to the chain.
run_id (UUID, optional) – The ID of the run. Defaults to None.
Returns
The async callback managerfor the chain run.
Return type
AsyncCallbackManagerForChainRun
async on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], **kwargs: Any) → Any[source]¶
Run when LLM starts running.
Parameters
serialized (Dict[str, Any]) – The serialized LLM. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManager.html |
c77ee8d4b0d9-2 | Parameters
serialized (Dict[str, Any]) – The serialized LLM.
messages (List[List[BaseMessage]]) – The list of messages.
run_id (UUID, optional) – The ID of the run. Defaults to None.
Returns
The list ofasync callback managers, one for each LLM Run
corresponding to each inner message list.
Return type
List[AsyncCallbackManagerForLLMRun]
async on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → List[AsyncCallbackManagerForLLMRun][source]¶
Run when LLM starts running.
Parameters
serialized (Dict[str, Any]) – The serialized LLM.
prompts (List[str]) – The list of prompts.
run_id (UUID, optional) – The ID of the run. Defaults to None.
Returns
The list of asynccallback managers, one for each LLM Run corresponding
to each prompt.
Return type
List[AsyncCallbackManagerForLLMRun]
async on_retriever_start(query: str, run_id: Optional[UUID] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → AsyncCallbackManagerForRetrieverRun[source]¶
Run when retriever starts running.
async on_tool_start(serialized: Dict[str, Any], input_str: str, run_id: Optional[UUID] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → AsyncCallbackManagerForToolRun[source]¶
Run when tool starts running.
Parameters
serialized (Dict[str, Any]) – The serialized tool.
input_str (str) – The input to the tool.
run_id (UUID, optional) – The ID of the run. Defaults to None. | [
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c77ee8d4b0d9-3 | run_id (UUID, optional) – The ID of the run. Defaults to None.
parent_run_id (UUID, optional) – The ID of the parent run.
Defaults to None.
Returns
The async callback managerfor the tool run.
Return type
AsyncCallbackManagerForToolRun
remove_handler(handler: BaseCallbackHandler) → None¶
Remove a handler from the callback manager.
remove_tags(tags: List[str]) → None¶
set_handler(handler: BaseCallbackHandler, inherit: bool = True) → None¶
Set handler as the only handler on the callback manager.
set_handlers(handlers: List[BaseCallbackHandler], inherit: bool = True) → None¶
Set handlers as the only handlers on the callback manager.
property is_async: bool¶
Return whether the handler is async. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManager.html |
17c227e127e0-0 | langchain.callbacks.base.AsyncCallbackHandler¶
class langchain.callbacks.base.AsyncCallbackHandler[source]¶
Bases: BaseCallbackHandler
Async callback handler that can be used to handle callbacks from langchain.
Methods
__init__()
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[, parent_run_id])
Run when chain ends running.
on_chain_error(error, *, run_id[, parent_run_id])
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[, parent_run_id])
Run when LLM ends running.
on_llm_error(error, *, run_id[, parent_run_id])
Run when LLM errors.
on_llm_new_token(token, *, run_id[, ...])
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(query, *, run_id[, ...])
Run on retriever start.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.AsyncCallbackHandler.html |
17c227e127e0-1 | Run on arbitrary text.
on_tool_end(output, *, run_id[, parent_run_id])
Run when tool ends running.
on_tool_error(error, *, run_id[, parent_run_id])
Run when tool errors.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
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.
raise_error
run_inline
async on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on agent action.
async on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on agent end.
async on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run when chain ends running.
async on_chain_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run when chain errors.
async on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None[source]¶
Run when chain starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.AsyncCallbackHandler.html |
17c227e127e0-2 | Run when chain starts running.
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, **kwargs: Any) → Any[source]¶
Run when a chat model starts running.
async on_llm_end(response: LLMResult, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run when LLM ends running.
async on_llm_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run when LLM errors.
async on_llm_new_token(token: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on new LLM token. Only available when streaming is enabled.
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, **kwargs: Any) → None[source]¶
Run when LLM starts running.
async on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on retriever end.
async on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on retriever error. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.AsyncCallbackHandler.html |
17c227e127e0-3 | Run on retriever error.
async on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on retriever start.
async on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run on arbitrary text.
async on_tool_end(output: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run when tool ends running.
async on_tool_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None[source]¶
Run when tool errors.
async on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None[source]¶
Run when tool starts running.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.AsyncCallbackHandler.html |
37e2d6ff8350-0 | langchain.callbacks.flyte_callback.analyze_text¶
langchain.callbacks.flyte_callback.analyze_text(text: str, nlp: Any = None) → dict[source]¶
Analyze text using textstat and spacy.
Parameters
text (str) – The text to analyze.
nlp (spacy.lang) – The spacy language model to use for visualization.
Returns
A dictionary containing the complexity metrics and visualizationfiles serialized to HTML string.
Return type
(dict) | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.flyte_callback.analyze_text.html |
07cb0fe42555-0 | langchain.callbacks.manager.AsyncCallbackManagerForChainRun¶
class langchain.callbacks.manager.AsyncCallbackManagerForChainRun(*, run_id: UUID, handlers: List[BaseCallbackHandler], inheritable_handlers: List[BaseCallbackHandler], parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: AsyncRunManager, ChainManagerMixin
Async callback manager for chain run.
Initialize the run manager.
Parameters
run_id (UUID) – The ID of the run.
handlers (List[BaseCallbackHandler]) – The list of handlers.
inheritable_handlers (List[BaseCallbackHandler]) – The list of inheritable handlers.
parent_run_id (UUID, optional) – The ID of the parent run.
Defaults to None.
tags (Optional[List[str]]) – The list of tags.
inheritable_tags (Optional[List[str]]) – The list of inheritable tags.
Methods
__init__(*, run_id, handlers, ...[, ...])
Initialize the run manager.
get_child([tag])
Get a child callback manager.
get_noop_manager()
Return a manager that doesn't perform any operations.
on_agent_action(action, **kwargs)
Run when agent action is received.
on_agent_finish(finish, **kwargs)
Run when agent finish is received.
on_chain_end(outputs, **kwargs)
Run when chain ends running.
on_chain_error(error, **kwargs)
Run when chain errors.
on_text(text, **kwargs)
Run when text is received.
get_child(tag: Optional[str] = None) → AsyncCallbackManager[source]¶
Get a child callback manager.
Parameters
tag (str, optional) – The tag for the child callback manager. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManagerForChainRun.html |
07cb0fe42555-1 | Parameters
tag (str, optional) – The tag for the child callback manager.
Defaults to None.
Returns
The child callback manager.
Return type
AsyncCallbackManager
classmethod get_noop_manager() → BRM¶
Return a manager that doesn’t perform any operations.
Returns
The noop manager.
Return type
BaseRunManager
async on_agent_action(action: AgentAction, **kwargs: Any) → Any[source]¶
Run when agent action is received.
Parameters
action (AgentAction) – The agent action.
Returns
The result of the callback.
Return type
Any
async on_agent_finish(finish: AgentFinish, **kwargs: Any) → Any[source]¶
Run when agent finish is received.
Parameters
finish (AgentFinish) – The agent finish.
Returns
The result of the callback.
Return type
Any
async on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Run when chain ends running.
Parameters
outputs (Dict[str, Any]) – The outputs of the chain.
async on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when chain errors.
Parameters
error (Exception or KeyboardInterrupt) – The error.
async on_text(text: str, **kwargs: Any) → Any¶
Run when text is received.
Parameters
text (str) – The received text.
Returns
The result of the callback.
Return type
Any | [
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7082aa5f63f1-0 | langchain.callbacks.utils.import_spacy¶
langchain.callbacks.utils.import_spacy() → Any[source]¶
Import the spacy python package and raise an error if it is not installed. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.utils.import_spacy.html |
40de090202c1-0 | langchain.callbacks.streamlit.__init__.StreamlitCallbackHandler¶
langchain.callbacks.streamlit.__init__.StreamlitCallbackHandler(parent_container: DeltaGenerator, *, max_thought_containers: int = 4, expand_new_thoughts: bool = True, collapse_completed_thoughts: bool = True, thought_labeler: Optional[LLMThoughtLabeler] = None) → BaseCallbackHandler[source]¶
Construct a new StreamlitCallbackHandler. This CallbackHandler is geared towards
use with a LangChain Agent; it displays the Agent’s LLM and tool-usage “thoughts”
inside a series of Streamlit expanders.
Parameters
parent_container – The st.container that will contain all the Streamlit elements that the
Handler creates.
max_thought_containers – The max number of completed LLM thought containers to show at once. When this
threshold is reached, a new thought will cause the oldest thoughts to be
collapsed into a “History” expander. Defaults to 4.
expand_new_thoughts – Each LLM “thought” gets its own st.expander. This param controls whether that
expander is expanded by default. Defaults to True.
collapse_completed_thoughts – If True, LLM thought expanders will be collapsed when completed.
Defaults to True.
thought_labeler – An optional custom LLMThoughtLabeler instance. If unspecified, the handler
will use the default thought labeling logic. Defaults to None.
Returns
A new StreamlitCallbackHandler instance.
Note that this is an “auto-updating” API (if the installed version of Streamlit)
has a more recent StreamlitCallbackHandler implementation, an instance of that class
will be used. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.streamlit.__init__.StreamlitCallbackHandler.html |
7ac87b2bdbdb-0 | langchain.callbacks.tracers.schemas.TracerSessionV1Base¶
class langchain.callbacks.tracers.schemas.TracerSessionV1Base(*, start_time: datetime = None, name: Optional[str] = None, extra: Optional[Dict[str, Any]] = None)[source]¶
Bases: BaseModel
Base class for TracerSessionV1.
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.datetime [Optional]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.schemas.TracerSessionV1Base.html |
b3b1c9cceebe-0 | langchain.callbacks.aim_callback.import_aim¶
langchain.callbacks.aim_callback.import_aim() → Any[source]¶
Import the aim python package and raise an error if it is not installed. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.aim_callback.import_aim.html |
45544cbe3b38-0 | langchain.callbacks.manager.BaseRunManager¶
class langchain.callbacks.manager.BaseRunManager(*, run_id: UUID, handlers: List[BaseCallbackHandler], inheritable_handlers: List[BaseCallbackHandler], parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: RunManagerMixin
Base class for run manager (a bound callback manager).
Initialize the run manager.
Parameters
run_id (UUID) – The ID of the run.
handlers (List[BaseCallbackHandler]) – The list of handlers.
inheritable_handlers (List[BaseCallbackHandler]) – The list of inheritable handlers.
parent_run_id (UUID, optional) – The ID of the parent run.
Defaults to None.
tags (Optional[List[str]]) – The list of tags.
inheritable_tags (Optional[List[str]]) – The list of inheritable tags.
Methods
__init__(*, run_id, handlers, ...[, ...])
Initialize the run manager.
get_noop_manager()
Return a manager that doesn't perform any operations.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
classmethod get_noop_manager() → BRM[source]¶
Return a manager that doesn’t perform any operations.
Returns
The noop manager.
Return type
BaseRunManager
on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on arbitrary text. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.BaseRunManager.html |
5641469b2c04-0 | langchain.callbacks.tracers.base.TracerException¶
class langchain.callbacks.tracers.base.TracerException[source]¶
Bases: Exception
Base class for exceptions in tracers module.
add_note()¶
Exception.add_note(note) –
add a note to the exception
with_traceback()¶
Exception.with_traceback(tb) –
set self.__traceback__ to tb and return self.
args¶ | [
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79e5928df704-0 | langchain.callbacks.manager.tracing_enabled¶
langchain.callbacks.manager.tracing_enabled(session_name: str = 'default') → Generator[TracerSessionV1, None, None][source]¶
Get the Deprecated LangChainTracer in a context manager.
Parameters
session_name (str, optional) – The name of the session.
Defaults to “default”.
Returns
The LangChainTracer session.
Return type
TracerSessionV1
Example
>>> with tracing_enabled() as session:
... # Use the LangChainTracer session | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.manager.tracing_enabled.html |
5da8a1b382b8-0 | langchain.callbacks.clearml_callback.import_clearml¶
langchain.callbacks.clearml_callback.import_clearml() → Any[source]¶
Import the clearml python package and raise an error if it is not installed. | [
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d874c3997210-0 | langchain.callbacks.streamlit.streamlit_callback_handler.LLMThoughtState¶
class langchain.callbacks.streamlit.streamlit_callback_handler.LLMThoughtState(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Bases: Enum
Attributes
THINKING
RUNNING_TOOL
COMPLETE
COMPLETE = 'COMPLETE'¶
RUNNING_TOOL = 'RUNNING_TOOL'¶
THINKING = 'THINKING'¶ | [
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11badeddf9a8-0 | langchain.callbacks.base.BaseCallbackHandler¶
class langchain.callbacks.base.BaseCallbackHandler[source]¶
Bases: LLMManagerMixin, ChainManagerMixin, ToolManagerMixin, RetrieverManagerMixin, CallbackManagerMixin, RunManagerMixin
Base callback handler that can be used to handle callbacks from langchain.
Methods
__init__()
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[, parent_run_id])
Run when chain ends running.
on_chain_error(error, *, run_id[, parent_run_id])
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[, parent_run_id])
Run when LLM ends running.
on_llm_error(error, *, run_id[, parent_run_id])
Run when LLM errors.
on_llm_new_token(token, *, run_id[, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Run when LLM starts running.
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.BaseCallbackHandler.html |
11badeddf9a8-1 | Run when Retriever starts running.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
on_tool_end(output, *, run_id[, parent_run_id])
Run when tool ends running.
on_tool_error(error, *, run_id[, parent_run_id])
Run when tool errors.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
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.
raise_error
run_inline
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent end.
on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when chain ends running.
on_chain_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when chain errors.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when chain starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.BaseCallbackHandler.html |
11badeddf9a8-2 | Run when chain starts running.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when LLM ends running.
on_llm_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when LLM errors.
on_llm_new_token(token: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on new LLM token. Only available when streaming is enabled.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when LLM starts running.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.BaseCallbackHandler.html |
11badeddf9a8-3 | Run when Retriever starts running.
on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on arbitrary text.
on_tool_end(output: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when tool ends running.
on_tool_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when tool errors.
on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when tool starts running.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.BaseCallbackHandler.html |
37ab6914f384-0 | langchain.callbacks.mlflow_callback.import_mlflow¶
langchain.callbacks.mlflow_callback.import_mlflow() → Any[source]¶
Import the mlflow python package and raise an error if it is not installed. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.mlflow_callback.import_mlflow.html |
ec4477aec77b-0 | langchain.callbacks.manager.tracing_v2_enabled¶
langchain.callbacks.manager.tracing_v2_enabled(project_name: Optional[str] = None, *, example_id: Optional[Union[UUID, str]] = None) → Generator[None, None, None][source]¶
Instruct LangChain to log all runs in context to LangSmith.
Parameters
project_name (str, optional) – The name of the project.
Defaults to “default”.
example_id (str or UUID, optional) – The ID of the example.
Defaults to None.
Returns
None
Example
>>> with tracing_v2_enabled():
... # LangChain code will automatically be traced | [
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925014be33de-0 | langchain.callbacks.openai_info.OpenAICallbackHandler¶
class langchain.callbacks.openai_info.OpenAICallbackHandler[source]¶
Bases: BaseCallbackHandler
Callback Handler that tracks OpenAI info.
Methods
__init__()
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[, parent_run_id])
Run when chain ends running.
on_chain_error(error, *, run_id[, parent_run_id])
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, **kwargs)
Collect token usage.
on_llm_error(error, *, run_id[, parent_run_id])
Run when LLM errors.
on_llm_new_token(token, **kwargs)
Print out the token.
on_llm_start(serialized, prompts, **kwargs)
Print out the prompts.
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
on_tool_end(output, *, run_id[, parent_run_id])
Run when tool ends running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.openai_info.OpenAICallbackHandler.html |
925014be33de-1 | Run when tool ends running.
on_tool_error(error, *, run_id[, parent_run_id])
Run when tool errors.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
Attributes
always_verbose
Whether to call verbose callbacks even if verbose is False.
completion_tokens
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.
prompt_tokens
raise_error
run_inline
successful_requests
total_cost
total_tokens
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent end.
on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when chain ends running.
on_chain_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when chain errors.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when chain starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.openai_info.OpenAICallbackHandler.html |
925014be33de-2 | Run when chain starts running.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Collect token usage.
on_llm_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when LLM errors.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Print out the token.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Print out the prompts.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on arbitrary text. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.openai_info.OpenAICallbackHandler.html |
925014be33de-3 | Run on arbitrary text.
on_tool_end(output: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when tool ends running.
on_tool_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when tool errors.
on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when tool starts running.
property always_verbose: bool¶
Whether to call verbose callbacks even if verbose is False.
completion_tokens: int = 0¶
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
prompt_tokens: int = 0¶
raise_error: bool = False¶
run_inline: bool = False¶
successful_requests: int = 0¶
total_cost: float = 0.0¶
total_tokens: int = 0¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.openai_info.OpenAICallbackHandler.html |
ce0aa5a50e3b-0 | langchain.callbacks.tracers.evaluation.EvaluatorCallbackHandler¶
class langchain.callbacks.tracers.evaluation.EvaluatorCallbackHandler(evaluators: Sequence[RunEvaluator], max_workers: Optional[int] = None, client: Optional[LangChainPlusClient] = None, example_id: Optional[Union[UUID, str]] = None, **kwargs: Any)[source]¶
Bases: BaseTracer
A tracer that runs a run evaluator whenever a run is persisted.
Parameters
evaluators (Sequence[RunEvaluator]) – The run evaluators to apply to all top level runs.
max_workers (int, optional) – The maximum number of worker threads to use for running the evaluators.
If not specified, it will default to the number of evaluators.
client (LangChainPlusClient, optional) – The LangChainPlusClient instance to use for evaluating the runs.
If not specified, a new instance will be created.
example_id (Union[UUID, str], optional) – The example ID to be associated with the runs.
example_id¶
The example ID associated with the runs.
Type
Union[UUID, None]
client¶
The LangChainPlusClient instance used for evaluating the runs.
Type
LangChainPlusClient
evaluators¶
The sequence of run evaluators to be executed.
Type
Sequence[RunEvaluator]
executor¶
The thread pool executor used for running the evaluators.
Type
ThreadPoolExecutor
futures¶
The set of futures representing the running evaluators.
Type
Set[Future]
Methods
__init__(evaluators[, max_workers, client, ...])
on_agent_action(action, *, run_id[, ...])
Run on agent action.
on_agent_finish(finish, *, run_id[, ...])
Run on agent end. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.evaluation.EvaluatorCallbackHandler.html |
ce0aa5a50e3b-1 | Run on agent end.
on_chain_end(outputs, *, run_id, **kwargs)
End a trace for a chain run.
on_chain_error(error, *, run_id, **kwargs)
Handle an error for a chain run.
on_chain_start(serialized, inputs, *, run_id)
Start a trace for a chain run.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, *, run_id, **kwargs)
End a trace for an LLM run.
on_llm_error(error, *, run_id, **kwargs)
Handle an error for an LLM run.
on_llm_new_token(token, *, run_id[, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Start a trace for an LLM run.
on_retriever_end(documents, *, run_id, **kwargs)
Run when Retriever ends running.
on_retriever_error(error, *, run_id, **kwargs)
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
on_tool_end(output, *, run_id, **kwargs)
End a trace for a tool run.
on_tool_error(error, *, run_id, **kwargs)
Handle an error for a tool run.
on_tool_start(serialized, input_str, *, run_id)
Start a trace for a tool run.
wait_for_futures() | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.evaluation.EvaluatorCallbackHandler.html |
ce0aa5a50e3b-2 | Start a trace for a tool run.
wait_for_futures()
Wait for all futures to complete.
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.
name
raise_error
run_inline
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent end.
on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, **kwargs: Any) → None¶
End a trace for a chain run.
on_chain_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Handle an error for a chain run.
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, **kwargs: Any) → None¶
Start a trace for a chain run.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, *, run_id: UUID, **kwargs: Any) → None¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.evaluation.EvaluatorCallbackHandler.html |
ce0aa5a50e3b-3 | End a trace for an LLM run.
on_llm_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Handle an error for an LLM run.
on_llm_new_token(token: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on new LLM token. Only available when streaming is enabled.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None¶
Start a trace for an LLM run.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, **kwargs: Any) → None¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None¶
Run when Retriever starts running.
on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on arbitrary text.
on_tool_end(output: str, *, run_id: UUID, **kwargs: Any) → None¶
End a trace for a tool run.
on_tool_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, **kwargs: Any) → None¶
Handle an error for a tool run. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.evaluation.EvaluatorCallbackHandler.html |
ce0aa5a50e3b-4 | Handle an error for a tool run.
on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, **kwargs: Any) → None¶
Start a trace for a tool run.
wait_for_futures() → None[source]¶
Wait for all futures to complete.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
name = 'evaluator_callback_handler'¶
raise_error: bool = False¶
run_inline: bool = False¶
run_map: Dict[str, Run]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.tracers.evaluation.EvaluatorCallbackHandler.html |
be75dccdf176-0 | langchain.callbacks.arthur_callback.ArthurCallbackHandler¶
class langchain.callbacks.arthur_callback.ArthurCallbackHandler(arthur_model: ArthurModel)[source]¶
Bases: BaseCallbackHandler
Callback Handler that logs to Arthur platform.
Arthur helps enterprise teams optimize model operations
and performance at scale. The Arthur API tracks model
performance, explainability, and fairness across tabular,
NLP, and CV models. Our API is model- and platform-agnostic,
and continuously scales with complex and dynamic enterprise needs.
To learn more about Arthur, visit our website at
https://www.arthur.ai/ or read the Arthur docs at
https://docs.arthur.ai/
Initialize callback handler.
Methods
__init__(arthur_model)
Initialize callback handler.
from_credentials(model_id[, arthur_url, ...])
Initialize callback handler from Arthur credentials.
on_agent_action(action, **kwargs)
Do nothing when agent takes a specific action.
on_agent_finish(finish, **kwargs)
Do nothing
on_chain_end(outputs, **kwargs)
On chain end, do nothing.
on_chain_error(error, **kwargs)
Do nothing when LLM chain outputs an error.
on_chain_start(serialized, inputs, **kwargs)
On chain start, do nothing.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, **kwargs)
On LLM end, send data to Arthur.
on_llm_error(error, **kwargs)
Do nothing when LLM outputs an error.
on_llm_new_token(token, **kwargs)
On new token, pass.
on_llm_start(serialized, prompts, **kwargs)
On LLM start, save the input prompts | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.arthur_callback.ArthurCallbackHandler.html |
be75dccdf176-1 | On LLM start, save the input prompts
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, **kwargs)
Do nothing
on_tool_end(output[, observation_prefix, ...])
Do nothing when tool ends.
on_tool_error(error, **kwargs)
Do nothing when tool outputs an error.
on_tool_start(serialized, input_str, **kwargs)
Do nothing when tool starts.
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.
raise_error
run_inline
classmethod from_credentials(model_id: str, arthur_url: Optional[str] = 'https://app.arthur.ai', arthur_login: Optional[str] = None, arthur_password: Optional[str] = None) → ArthurCallbackHandler[source]¶
Initialize callback handler from Arthur credentials.
Parameters
model_id (str) – The ID of the arthur model to log to.
arthur_url (str, optional) – The URL of the Arthur instance to log to.
Defaults to “https://app.arthur.ai”.
arthur_login (str, optional) – The login to use to connect to Arthur.
Defaults to None.
arthur_password (str, optional) – The password to use to connect to
Arthur. Defaults to None.
Returns
The initialized callback handler.
Return type
ArthurCallbackHandler | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.arthur_callback.ArthurCallbackHandler.html |
be75dccdf176-2 | Returns
The initialized callback handler.
Return type
ArthurCallbackHandler
on_agent_action(action: AgentAction, **kwargs: Any) → Any[source]¶
Do nothing when agent takes a specific action.
on_agent_finish(finish: AgentFinish, **kwargs: Any) → None[source]¶
Do nothing
on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None[source]¶
On chain end, do nothing.
on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Do nothing when LLM chain outputs an error.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) → None[source]¶
On chain start, do nothing.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
On LLM end, send data to Arthur.
on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Do nothing when LLM outputs an error.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
On new token, pass.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
On LLM start, save the input prompts
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.arthur_callback.ArthurCallbackHandler.html |
be75dccdf176-3 | Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_text(text: str, **kwargs: Any) → None[source]¶
Do nothing
on_tool_end(output: str, observation_prefix: Optional[str] = None, llm_prefix: Optional[str] = None, **kwargs: Any) → None[source]¶
Do nothing when tool ends.
on_tool_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Do nothing when tool outputs an error.
on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None[source]¶
Do nothing when tool starts.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.arthur_callback.ArthurCallbackHandler.html |
a2b1f3e1c671-0 | langchain.callbacks.base.BaseCallbackManager¶
class langchain.callbacks.base.BaseCallbackManager(handlers: List[BaseCallbackHandler], inheritable_handlers: Optional[List[BaseCallbackHandler]] = None, parent_run_id: Optional[UUID] = None, *, tags: Optional[List[str]] = None, inheritable_tags: Optional[List[str]] = None)[source]¶
Bases: CallbackManagerMixin
Base callback manager that can be used to handle callbacks from LangChain.
Initialize callback manager.
Methods
__init__(handlers[, inheritable_handlers, ...])
Initialize callback manager.
add_handler(handler[, inherit])
Add a handler to the callback manager.
add_tags(tags[, inherit])
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_start(serialized, prompts, *, run_id)
Run when LLM starts running.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
remove_handler(handler)
Remove a handler from the callback manager.
remove_tags(tags)
set_handler(handler[, inherit])
Set handler as the only handler on the callback manager.
set_handlers(handlers[, inherit])
Set handlers as the only handlers on the callback manager.
Attributes
is_async
Whether the callback manager is async.
add_handler(handler: BaseCallbackHandler, inherit: bool = True) → None[source]¶
Add a handler to the callback manager.
add_tags(tags: List[str], inherit: bool = True) → None[source]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.base.BaseCallbackManager.html |
a2b1f3e1c671-1 | add_tags(tags: List[str], inherit: bool = True) → None[source]¶
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when chain starts running.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when LLM starts running.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → Any¶
Run when tool starts running.
remove_handler(handler: BaseCallbackHandler) → None[source]¶
Remove a handler from the callback manager.
remove_tags(tags: List[str]) → None[source]¶
set_handler(handler: BaseCallbackHandler, inherit: bool = True) → None[source]¶
Set handler as the only handler on the callback manager.
set_handlers(handlers: List[BaseCallbackHandler], inherit: bool = True) → None[source]¶ | [
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a2b1f3e1c671-2 | Set handlers as the only handlers on the callback manager.
property is_async: bool¶
Whether the callback manager is async. | [
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2b6fc6624ce0-0 | langchain.callbacks.whylabs_callback.WhyLabsCallbackHandler¶
class langchain.callbacks.whylabs_callback.WhyLabsCallbackHandler(logger: Logger)[source]¶
Bases: BaseCallbackHandler
WhyLabs CallbackHandler.
Initiate the rolling logger
Methods
__init__(logger)
Initiate the rolling logger
close()
flush()
from_params(*[, api_key, org_id, ...])
Instantiate whylogs Logger from params.
on_agent_action(action[, color])
Do nothing.
on_agent_finish(finish[, color])
Run on agent end.
on_chain_end(outputs, **kwargs)
Do nothing.
on_chain_error(error, **kwargs)
Do nothing.
on_chain_start(serialized, inputs, **kwargs)
Do nothing.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, **kwargs)
Pass the generated response to the logger.
on_llm_error(error, **kwargs)
Do nothing.
on_llm_new_token(token, **kwargs)
Do nothing.
on_llm_start(serialized, prompts, **kwargs)
Pass the input prompts to the logger
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, **kwargs)
Do nothing.
on_tool_end(output[, color, ...])
Do nothing.
on_tool_error(error, **kwargs)
Do nothing. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.whylabs_callback.WhyLabsCallbackHandler.html |
2b6fc6624ce0-1 | Do nothing.
on_tool_error(error, **kwargs)
Do nothing.
on_tool_start(serialized, input_str, **kwargs)
Do nothing.
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.
raise_error
run_inline
close() → None[source]¶
flush() → None[source]¶
classmethod from_params(*, api_key: Optional[str] = None, org_id: Optional[str] = None, dataset_id: Optional[str] = None, sentiment: bool = False, toxicity: bool = False, themes: bool = False) → Logger[source]¶
Instantiate whylogs Logger from params.
Parameters
api_key (Optional[str]) – WhyLabs API key. Optional because the preferred
way to specify the API key is with environment variable
WHYLABS_API_KEY.
org_id (Optional[str]) – WhyLabs organization id to write profiles to.
If not set must be specified in environment variable
WHYLABS_DEFAULT_ORG_ID.
dataset_id (Optional[str]) – The model or dataset this callback is gathering
telemetry for. If not set must be specified in environment variable
WHYLABS_DEFAULT_DATASET_ID.
sentiment (bool) – If True will initialize a model to perform
sentiment analysis compound score. Defaults to False and will not gather
this metric.
toxicity (bool) – If True will initialize a model to score
toxicity. Defaults to False and will not gather this metric.
themes (bool) – If True will initialize a model to calculate
distance to configured themes. Defaults to None and will not gather this
metric. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.whylabs_callback.WhyLabsCallbackHandler.html |
2b6fc6624ce0-2 | distance to configured themes. Defaults to None and will not gather this
metric.
on_agent_action(action: AgentAction, color: Optional[str] = None, **kwargs: Any) → Any[source]¶
Do nothing.
on_agent_finish(finish: AgentFinish, color: Optional[str] = None, **kwargs: Any) → None[source]¶
Run on agent end.
on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Do nothing.
on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Do nothing.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Do nothing.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Pass the generated response to the logger.
on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Do nothing.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Do nothing.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Pass the input prompts to the logger
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever ends running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.whylabs_callback.WhyLabsCallbackHandler.html |
2b6fc6624ce0-3 | Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_text(text: str, **kwargs: Any) → None[source]¶
Do nothing.
on_tool_end(output: str, color: Optional[str] = None, observation_prefix: Optional[str] = None, llm_prefix: Optional[str] = None, **kwargs: Any) → None[source]¶
Do nothing.
on_tool_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Do nothing.
on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None[source]¶
Do nothing.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.whylabs_callback.WhyLabsCallbackHandler.html |
4304378166df-0 | langchain.callbacks.flyte_callback.import_flytekit¶
langchain.callbacks.flyte_callback.import_flytekit() → Tuple[flytekit, renderer][source]¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.flyte_callback.import_flytekit.html |
dae693173075-0 | langchain.callbacks.utils.load_json¶
langchain.callbacks.utils.load_json(json_path: Union[str, Path]) → str[source]¶
Load json file to a string.
Parameters
json_path (str) – The path to the json file.
Returns
The string representation of the json file.
Return type
(str) | [
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5ce1afe0b95d-0 | langchain.callbacks.tracers.stdout.elapsed¶
langchain.callbacks.tracers.stdout.elapsed(run: Any) → str[source]¶
Get the elapsed time of a run.
Parameters
run – any object with a start_time and end_time attribute.
Returns
A string with the elapsed time in seconds ormilliseconds if time is less than a second. | [
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36f43f4fc9a7-0 | langchain.callbacks.wandb_callback.analyze_text¶
langchain.callbacks.wandb_callback.analyze_text(text: str, complexity_metrics: bool = True, visualize: bool = True, nlp: Any = None, output_dir: Optional[Union[str, Path]] = None) → dict[source]¶
Analyze text using textstat and spacy.
Parameters
text (str) – The text to analyze.
complexity_metrics (bool) – Whether to compute complexity metrics.
visualize (bool) – Whether to visualize the text.
nlp (spacy.lang) – The spacy language model to use for visualization.
output_dir (str) – The directory to save the visualization files to.
Returns
A dictionary containing the complexity metrics and visualizationfiles serialized in a wandb.Html element.
Return type
(dict) | [
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ffba95bcf4dd-0 | langchain.callbacks.comet_ml_callback.CometCallbackHandler¶
class langchain.callbacks.comet_ml_callback.CometCallbackHandler(task_type: Optional[str] = 'inference', workspace: Optional[str] = None, project_name: Optional[str] = None, tags: Optional[Sequence] = None, name: Optional[str] = None, visualizations: Optional[List[str]] = None, complexity_metrics: bool = False, custom_metrics: Optional[Callable] = None, stream_logs: bool = True)[source]¶
Bases: BaseMetadataCallbackHandler, BaseCallbackHandler
Callback Handler that logs to Comet.
Parameters
job_type (str) – The type of comet_ml task such as “inference”,
“testing” or “qc”
project_name (str) – The comet_ml project name
tags (list) – Tags to add to the task
task_name (str) – Name of the comet_ml task
visualize (bool) – Whether to visualize the run.
complexity_metrics (bool) – Whether to log complexity metrics
stream_logs (bool) – Whether to stream callback actions to Comet
This handler will utilize the associated callback method and formats
the input of each callback function with metadata regarding the state of LLM run,
and adds the response to the list of records for both the {method}_records and
action. It then logs the response to Comet.
Initialize callback handler.
Methods
__init__([task_type, workspace, ...])
Initialize callback handler.
flush_tracker([langchain_asset, task_type, ...])
Flush the tracker and setup the session.
get_custom_callback_meta()
on_agent_action(action, **kwargs)
Run on agent action.
on_agent_finish(finish, **kwargs)
Run when agent ends running.
on_chain_end(outputs, **kwargs) | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.comet_ml_callback.CometCallbackHandler.html |
ffba95bcf4dd-1 | Run when agent ends running.
on_chain_end(outputs, **kwargs)
Run when chain ends running.
on_chain_error(error, **kwargs)
Run when chain errors.
on_chain_start(serialized, inputs, **kwargs)
Run when chain starts running.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, **kwargs)
Run when LLM ends running.
on_llm_error(error, **kwargs)
Run when LLM errors.
on_llm_new_token(token, **kwargs)
Run when LLM generates a new token.
on_llm_start(serialized, prompts, **kwargs)
Run when LLM starts.
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, **kwargs)
Run when agent is ending.
on_tool_end(output, **kwargs)
Run when tool ends running.
on_tool_error(error, **kwargs)
Run when tool errors.
on_tool_start(serialized, input_str, **kwargs)
Run when tool starts running.
reset_callback_meta()
Reset the callback metadata.
Attributes
always_verbose
Whether to call verbose callbacks even if verbose is False.
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 | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.comet_ml_callback.CometCallbackHandler.html |
ffba95bcf4dd-2 | ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
raise_error
run_inline
flush_tracker(langchain_asset: Any = None, task_type: Optional[str] = 'inference', workspace: Optional[str] = None, project_name: Optional[str] = 'comet-langchain-demo', tags: Optional[Sequence] = None, name: Optional[str] = None, visualizations: Optional[List[str]] = None, complexity_metrics: bool = False, custom_metrics: Optional[Callable] = None, finish: bool = False, reset: bool = False) → None[source]¶
Flush the tracker and setup the session.
Everything after this will be a new table.
Parameters
name – Name of the preformed session so far so it is identifyable
langchain_asset – The langchain asset to save.
finish – Whether to finish the run.
Returns – None
get_custom_callback_meta() → Dict[str, Any]¶
on_agent_action(action: AgentAction, **kwargs: Any) → Any[source]¶
Run on agent action.
on_agent_finish(finish: AgentFinish, **kwargs: Any) → None[source]¶
Run when agent ends running.
on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Run when chain ends running.
on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when chain errors.
on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) → None[source]¶
Run when chain starts running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.comet_ml_callback.CometCallbackHandler.html |
ffba95bcf4dd-3 | Run when chain starts running.
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, **kwargs: Any) → Any¶
Run when a chat model starts running.
on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Run when LLM ends running.
on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when LLM errors.
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run when LLM generates a new token.
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Run when LLM starts.
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever ends running.
on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever errors.
on_retriever_start(query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when Retriever starts running.
on_text(text: str, **kwargs: Any) → None[source]¶
Run when agent is ending.
on_tool_end(output: str, **kwargs: Any) → None[source]¶
Run when tool ends running. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.comet_ml_callback.CometCallbackHandler.html |
ffba95bcf4dd-4 | Run when tool ends running.
on_tool_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) → None[source]¶
Run when tool errors.
on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None[source]¶
Run when tool starts running.
reset_callback_meta() → None¶
Reset the callback metadata.
property always_verbose: bool¶
Whether to call verbose callbacks even if verbose is False.
property ignore_agent: bool¶
Whether to ignore agent callbacks.
property ignore_chain: bool¶
Whether to ignore chain callbacks.
property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
property ignore_llm: bool¶
Whether to ignore LLM callbacks.
property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
raise_error: bool = False¶
run_inline: bool = False¶ | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.comet_ml_callback.CometCallbackHandler.html |
a7307815423a-0 | langchain.callbacks.streamlit.mutable_expander.ChildRecord¶
class langchain.callbacks.streamlit.mutable_expander.ChildRecord(type, kwargs, dg)[source]¶
Bases: NamedTuple
Create new instance of ChildRecord(type, kwargs, dg)
Methods
__init__()
count(value, /)
Return number of occurrences of value.
index(value[, start, stop])
Return first index of value.
Attributes
dg
Alias for field number 2
kwargs
Alias for field number 1
type
Alias for field number 0
count(value, /)¶
Return number of occurrences of value.
index(value, start=0, stop=9223372036854775807, /)¶
Return first index of value.
Raises ValueError if the value is not present.
dg: DeltaGenerator¶
Alias for field number 2
kwargs: Dict[str, Any]¶
Alias for field number 1
type: ChildType¶
Alias for field number 0 | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.streamlit.mutable_expander.ChildRecord.html |
47a0d3dcfa1f-0 | langchain.callbacks.promptlayer_callback.PromptLayerCallbackHandler¶
class langchain.callbacks.promptlayer_callback.PromptLayerCallbackHandler(pl_id_callback: Optional[Callable[[...], Any]] = None, pl_tags: Optional[List[str]] = [])[source]¶
Bases: BaseCallbackHandler
Callback handler for promptlayer.
Initialize the PromptLayerCallbackHandler.
Methods
__init__([pl_id_callback, pl_tags])
Initialize the PromptLayerCallbackHandler.
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[, parent_run_id])
Run when chain ends running.
on_chain_error(error, *, run_id[, parent_run_id])
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[, parent_run_id])
Run when LLM ends running.
on_llm_error(error, *, run_id[, parent_run_id])
Run when LLM errors.
on_llm_new_token(token, *, run_id[, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Run when LLM starts running.
on_retriever_end(documents, *, run_id[, ...])
Run when Retriever ends running.
on_retriever_error(error, *, run_id[, ...])
Run when Retriever errors. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.promptlayer_callback.PromptLayerCallbackHandler.html |
47a0d3dcfa1f-1 | Run when Retriever errors.
on_retriever_start(query, *, run_id[, ...])
Run when Retriever starts running.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
on_tool_end(output, *, run_id[, parent_run_id])
Run when tool ends running.
on_tool_error(error, *, run_id[, parent_run_id])
Run when tool errors.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
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.
raise_error
run_inline
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent end.
on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when chain ends running.
on_chain_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run when chain errors. | [
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] | https://langchain.readthedocs.io/en/latest/callbacks/langchain.callbacks.promptlayer_callback.PromptLayerCallbackHandler.html |
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