Tony20100/langchain_full huggingface dataset:
Parameters
error (BaseException) – 
kwargs (Any) – 
Return type
None
on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run when LLM generates a new token.
Parameters
token (str) – 
kwargs (Any) – 
Return type
None
on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Run when LLM starts.
Parameters
serialized (Dict[str, Any]) – 
prompts (List[str]) – 
kwargs (Any) – 
Return type
None
on_retriever_end(documents: Sequence[Document], **kwargs: Any) → Any[source]¶
Run when Retriever ends running.
Parameters
documents (Sequence[Document]) – 
kwargs (Any) – 
Return type
Any
on_retriever_error(error: BaseException, **kwargs: Any) → Any[source]¶
Run when Retriever errors.
Parameters
error (BaseException) – 
kwargs (Any) – 
Return type
Any
on_retriever_start(serialized: Dict[str, Any], query: str, **kwargs: Any) → Any[source]¶
Run when Retriever starts running.
Parameters
serialized (Dict[str, Any]) – 
query (str) – 
kwargs (Any) – 
Return type
Any
on_retry(retry_state: RetryCallState, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on a retry event.
Parameters
retry_state (RetryCallState) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
kwargs (Any) – 
Return type
Any
on_text(text: str, **kwargs: Any) → None[source]¶
Run when text is received.
Parameters
text (str) – 
kwargs (Any) – 
Return type
None
on_tool_end(output: Any, **kwargs: Any) → None[source]¶
Run when tool ends running.
Parameters
output (Any) – 
kwargs (Any) – 
Return type
None
on_tool_error(error: BaseException, **kwargs: Any) → None[source]¶
Run when tool errors.
Parameters
error (BaseException) – 
kwargs (Any) – 
Return type
None
on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None[source]¶
Run when tool starts running.
Parameters
serialized (Dict[str, Any]) – 
input_str (str) – 
kwargs (Any) – 
Return type
None
reset_callback_meta() → None¶
Reset the callback metadata.
Return type
None
Examples using MlflowCallbackHandler¶
MLflow
langchain_community.callbacks.bedrock_anthropic_callback.BedrockAnthropicTokenUsageCallbackHandler¶
class langchain_community.callbacks.bedrock_anthropic_callback.BedrockAnthropicTokenUsageCallbackHandler[source]¶
Callback Handler that tracks bedrock anthropic info.
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.
ignore_retry
Whether to ignore retry callbacks.
prompt_tokens
raise_error
run_inline
successful_requests
total_cost
total_tokens
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. :param error: The error that occurred. :type error: BaseException :param kwargs: Additional keyword arguments. - response (LLMResult): The response which was generated before                    the error occurred. :type kwargs: Any.
langchain.callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler¶
class langchain.callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler(*, answer_prefix_tokens: Optional[List[str]] = None, strip_tokens: bool = True, stream_prefix: bool = False)[source]¶
Callback handler that returns an async iterator.
Only the final output of the agent will be iterated.
Instantiate AsyncFinalIteratorCallbackHandler.
Parameters
answer_prefix_tokens (Optional[List[str]]) – Token sequence that prefixes the answer.
Default is [“Final”, “Answer”, “:”]
strip_tokens (bool) – Ignore white spaces and new lines when comparing
answer_prefix_tokens to last tokens? (to determine if answer has been
reached)
stream_prefix (bool) – Should answer prefix itself also be streamed?
Attributes
always_verbose
ignore_agent
Whether to ignore agent callbacks.
ignore_chain
Whether to ignore chain callbacks.
ignore_chat_model
Whether to ignore chat model callbacks.
ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
ignore_retry
Whether to ignore retry callbacks.
raise_error
run_inline
Methods
__init__(*[, answer_prefix_tokens, ...])
Instantiate AsyncFinalIteratorCallbackHandler.
aiter()
append_to_last_tokens(token)
check_if_answer_reached()
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[, ...])
Run when chain ends running.
on_chain_error(error, *, run_id[, ...])
Run when chain errors.
on_chain_start(serialized, inputs, *, run_id)
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)
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.
on_llm_start(serialized, prompts, **kwargs)
Run when LLM starts running.
on_retriever_end(documents, *, run_id[, ...])
Run on retriever end.
on_retriever_error(error, *, run_id[, ...])
Run on retriever error.
on_retriever_start(serialized, query, *, run_id)
Run on retriever start.
on_retry(retry_state, *, run_id[, parent_run_id])
Run on a retry event.
on_text(text, *, run_id[, parent_run_id, tags])
Run on arbitrary text.
on_tool_end(output, *, run_id[, ...])
Run when tool ends running.
on_tool_error(error, *, run_id[, ...])
Run when tool errors.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
__init__(*, answer_prefix_tokens: Optional[List[str]] = None, strip_tokens: bool = True, stream_prefix: bool = False) → None[source]¶
Instantiate AsyncFinalIteratorCallbackHandler.
Parameters
answer_prefix_tokens (Optional[List[str]]) – Token sequence that prefixes the answer.
Default is [“Final”, “Answer”, “:”]
Default is [“Final”, “Answer”, “:”]
strip_tokens (bool) – Ignore white spaces and new lines when comparing
answer_prefix_tokens to last tokens? (to determine if answer has been
reached)
stream_prefix (bool) – Should answer prefix itself also be streamed?
Return type
None
async aiter() → AsyncIterator[str]¶
Return type
AsyncIterator[str]
append_to_last_tokens(token: str) → None[source]¶
Parameters
token (str) – 
Return type
None
check_if_answer_reached() → bool[source]¶
Return type
bool
async on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on agent action.
Parameters
action (AgentAction) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on agent end.
Parameters
finish (AgentFinish) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run when chain ends running.
Parameters
outputs (Dict[str, Any]) –
Run when chain ends running.
Parameters
outputs (Dict[str, Any]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_chain_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run when chain errors.
Parameters
error (BaseException) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
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, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → None¶
Run when chain starts running.
Parameters
serialized (Dict[str, Any]) – 
inputs (Dict[str, Any]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
async on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Run when a chat model starts running.
Run when a chat model starts running.
ATTENTION: This method is called for chat models. If you’re implementinga handler for a non-chat model, you should use on_llm_start instead.
Parameters
serialized (Dict[str, Any]) – 
messages (List[List[BaseMessage]]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
Any
async on_llm_end(response: LLMResult, **kwargs: Any) → None[source]¶
Run when LLM ends running.
Parameters
response (LLMResult) – 
kwargs (Any) – 
Return type
None
async on_llm_error(error: BaseException, **kwargs: Any) → None¶
Run when LLM errors.
Parameters
error (BaseException) – The error that occurred.
kwargs (Any) – Additional keyword arguments.
- response (LLMResult): The response which was generated before
the error occurred.
Return type
None
async on_llm_new_token(token: str, **kwargs: Any) → None[source]¶
Run on new LLM token. Only available when streaming is enabled.
Parameters
token (str) – 
kwargs (Any) – 
Return type
None
async on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None[source]¶
Run when LLM starts running.
ATTENTION: This method is called for non-chat models (regular LLMs). Ifyou’re implementing a handler for a chat model,
you should use on_chat_model_start instead.
Parameters
serialized (Dict[str, Any]) – 
prompts (List[str]) –
serialized (Dict[str, Any]) – 
prompts (List[str]) – 
kwargs (Any) – 
Return type
None
async on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on retriever end.
Parameters
documents (Sequence[Document]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_retriever_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on retriever error.
Parameters
error (BaseException) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_retriever_start(serialized: Dict[str, Any], query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → None¶
Run on retriever start.
Parameters
serialized (Dict[str, Any]) – 
query (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
kwargs (Any) – 
Return type
None
async on_retry(retry_state: RetryCallState, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on a retry event.
Parameters
retry_state (RetryCallState) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Any
async on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on arbitrary text.
Parameters
text (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_tool_end(output: Any, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run when tool ends running.
Parameters
output (Any) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_tool_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run when tool errors.
Parameters
error (BaseException) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
kwargs (Any) – 
Return type
None
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, metadata: Optional[Dict[str, Any]] = None, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → None¶
Run when tool starts running.
Parameters
serialized (Dict[str, Any]) – 
input_str (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
None
langchain_community.callbacks.tracers.wandb.WandbTracer¶
class langchain_community.callbacks.tracers.wandb.WandbTracer(run_args: Optional[WandbRunArgs] = None, **kwargs: Any)[source]¶
Callback Handler that logs to Weights and Biases.
This handler will log the model architecture and run traces to Weights and Biases.
This will ensure that all LangChain activity is logged to W&B.
Initializes the WandbTracer.
Parameters
run_args (Optional[WandbRunArgs]) – (dict, optional) Arguments to pass to wandb.init(). If not
provided, wandb.init() will be called with no arguments. Please
refer to the wandb.init for more details.
kwargs (Any) – 
To use W&B to monitor all LangChain activity, add this tracer like any other
LangChain callback:
```
from wandb.integration.langchain import WandbTracer
tracer = WandbTracer()
chain = LLMChain(llm, callbacks=[tracer])
# …end of notebook / script:
tracer.finish()
```
Attributes
ignore_agent
Whether to ignore agent callbacks.
ignore_chain
Whether to ignore chain callbacks.
ignore_chat_model
Whether to ignore chat model callbacks.
ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
ignore_retry
Whether to ignore retry callbacks.
raise_error
run_inline
Methods
__init__([run_args])
Initializes the WandbTracer.
finish()
Waits for all asynchronous processes to finish and data to upload.
on_agent_action(action, *, run_id[, ...])
Run on agent action.
on_agent_finish(finish, *, run_id[, ...])
Run on agent end.
Run on agent end.
on_chain_end(outputs, *, run_id[, inputs])
End a trace for a chain run.
on_chain_error(error, *[, inputs])
Handle an error for a chain run.
on_chain_start(serialized, inputs, *, run_id)
Start a trace for a chain run.
on_chat_model_start(serialized, messages, *, ...)
Start a trace for an LLM run.
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, *[, chunk, ...])
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(serialized, query, *, run_id)
Run when Retriever starts running.
on_retry(retry_state, *, run_id, **kwargs)
Run on a retry event.
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.
Handle an error for a tool run.
on_tool_start(serialized, input_str, *, run_id)
Start a trace for a tool run.
__init__(run_args: Optional[WandbRunArgs] = None, **kwargs: Any) → None[source]¶
Initializes the WandbTracer.
Parameters
run_args (Optional[WandbRunArgs]) – (dict, optional) Arguments to pass to wandb.init(). If not
provided, wandb.init() will be called with no arguments. Please
refer to the wandb.init for more details.
kwargs (Any) – 
Return type
None
To use W&B to monitor all LangChain activity, add this tracer like any other
LangChain callback:
```
from wandb.integration.langchain import WandbTracer
tracer = WandbTracer()
chain = LLMChain(llm, callbacks=[tracer])
# …end of notebook / script:
tracer.finish()
```
finish() → None[source]¶
Waits for all asynchronous processes to finish and data to upload.
Proxy for wandb.finish().
Return type
None
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
Parameters
action (AgentAction) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Any
on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent end.
Parameters
finish (AgentFinish) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) –
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Any
on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → Run¶
End a trace for a chain run.
Parameters
outputs (Dict[str, Any]) – 
run_id (UUID) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
Run
on_chain_error(error: BaseException, *, inputs: Optional[Dict[str, Any]] = None, run_id: UUID, **kwargs: Any) → Run¶
Handle an error for a chain run.
Parameters
error (BaseException) – 
inputs (Optional[Dict[str, Any]]) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
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, metadata: Optional[Dict[str, Any]] = None, run_type: Optional[str] = None, name: Optional[str] = None, **kwargs: Any) → Run¶
Start a trace for a chain run.
Parameters
serialized (Dict[str, Any]) – 
inputs (Dict[str, Any]) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
run_type (Optional[str]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
Run
name (Optional[str]) – 
kwargs (Any) – 
Return type
Run
on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → Run¶
Start a trace for an LLM run.
Parameters
serialized (Dict[str, Any]) – 
messages (List[List[BaseMessage]]) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
Run
on_llm_end(response: LLMResult, *, run_id: UUID, **kwargs: Any) → Run¶
End a trace for an LLM run.
Parameters
response (LLMResult) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_llm_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run¶
Handle an error for an LLM run.
Parameters
error (BaseException) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_llm_new_token(token: str, *, chunk: Optional[Union[GenerationChunk, ChatGenerationChunk]] = None, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Run¶
Run on new LLM token. Only available when streaming is enabled.
Parameters
token (str) –
Parameters
token (str) – 
chunk (Optional[Union[GenerationChunk, ChatGenerationChunk]]) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Run
on_llm_start(serialized: Dict[str, Any], prompts: List[str], *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → Run¶
Start a trace for an LLM run.
Parameters
serialized (Dict[str, Any]) – 
prompts (List[str]) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
Run
on_retriever_end(documents: Sequence[Document], *, run_id: UUID, **kwargs: Any) → Run¶
Run when Retriever ends running.
Parameters
documents (Sequence[Document]) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_retriever_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run¶
Run when Retriever errors.
Parameters
error (BaseException) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_retriever_start(serialized: Dict[str, Any], query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → Run¶
Run when Retriever starts running.
Parameters
serialized (Dict[str, Any]) – 
query (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
Run
on_retry(retry_state: RetryCallState, *, run_id: UUID, **kwargs: Any) → Run¶
Run on a retry event.
Parameters
retry_state (RetryCallState) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on arbitrary text.
Parameters
text (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Any
on_tool_end(output: Any, *, run_id: UUID, **kwargs: Any) → Run¶
End a trace for a tool run.
Parameters
output (Any) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_tool_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run¶
Handle an error for a tool run.
Parameters
error (BaseException) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
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, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → Run¶
Start a trace for a tool run.
Parameters
serialized (Dict[str, Any]) – 
input_str (str) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
Run
langchain_community.callbacks.streamlit.streamlit_callback_handler.ToolRecord¶
class langchain_community.callbacks.streamlit.streamlit_callback_handler.ToolRecord(name: str, input_str: str)[source]¶
Tool record as a NamedTuple.
Create new instance of ToolRecord(name, input_str)
Attributes
input_str
Alias for field number 1
name
Alias for field number 0
Methods
__init__()
count(value, /)
Return number of occurrences of value.
index(value[, start, stop])
Return first index of value.
Parameters
name (str) – 
input_str (str) – 
__init__()¶
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.