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langchain.callbacks.manager.AsyncCallbackManagerForRetrieverRun¶ class langchain.callbacks.manager.AsyncCallbackManagerForRetrieverRun(*, run_id: UUID, handlers: List[BaseCallbackHandler], inheritable_handlers: List[BaseCallbackHandler], parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, inheritabl...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManagerForRetrieverRun.html
1f9591eab472-1
on_text(text, **kwargs) Run when text is received. __init__(*, 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, metadata: Optional[Dict[str, Any]] = No...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManagerForRetrieverRun.html
1f9591eab472-2
Run when retriever errors. async on_retry(retry_state: RetryCallState, **kwargs: Any) → None¶ Run on a retry event. 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 Examples using AsyncCallbackManager...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.manager.AsyncCallbackManagerForRetrieverRun.html
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langchain.callbacks.file.FileCallbackHandler¶ class langchain.callbacks.file.FileCallbackHandler(filename: str, mode: str = 'a', color: Optional[str] = None)[source]¶ Callback Handler that writes to a file. Initialize callback handler. Attributes ignore_agent Whether to ignore agent callbacks. ignore_chain Whether to i...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.file.FileCallbackHandler.html
e350f288fc08-1
Run when Retriever ends running. on_retriever_error(error, *, run_id[, ...]) Run when Retriever errors. on_retriever_start(serialized, query, *, run_id) Run when Retriever starts running. on_retry(retry_state, *, run_id[, parent_run_id]) Run on a retry event. on_text(text[, color, end]) Run when agent ends. on_tool_end...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.file.FileCallbackHandler.html
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Print out that we are entering a chain. 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. on_ll...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.file.FileCallbackHandler.html
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Run when Retriever ends running. on_retriever_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶ Run when Retriever errors. on_retriever_start(serialized: Dict[str, Any], query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = ...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.file.FileCallbackHandler.html
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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, compl...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html
c73e90b53d06-1
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, **kwarg...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html
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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. __init__(task_type: Optional[str] = 'inference', project_name: Optional[str] = 'langchain_callback_demo', tags: Optional[Sequence] = None, ...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html
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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]] = No...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html
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Run when Retriever starts running. on_retry(retry_state: RetryCallState, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶ Run on a retry event. 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 en...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.clearml_callback.ClearMLCallbackHandler.html
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langchain.callbacks.tracers.langchain.get_client¶ langchain.callbacks.tracers.langchain.get_client() → Client[source]¶ Get the client.
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.tracers.langchain.get_client.html
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langchain.callbacks.manager.ParentRunManager¶ class langchain.callbacks.manager.ParentRunManager(*, 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, me...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.manager.ParentRunManager.html
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on_text(text, **kwargs) Run when text is received. __init__(*, 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, metadata: Optional[Dict[str, Any]] = No...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.manager.ParentRunManager.html
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Run when text is received. Parameters text (str) – The received text. Returns The result of the callback. Return type Any
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.manager.ParentRunManager.html
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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 ...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler.html
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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, **...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler.html
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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? async aiter() → AsyncIterator[str]¶ append_to_last_tokens(token: str) → None[source]¶ check_if_answer_reached() → b...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler.html
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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, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶ Run when a chat model starts running. async on...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler.html
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Run on retriever start. async on_retry(retry_state: RetryCallState, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶ Run on a retry event. 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...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler.html
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langchain.callbacks.tracers.wandb.RunProcessor¶ class langchain.callbacks.tracers.wandb.RunProcessor(wandb_module: Any, trace_module: Any)[source]¶ Handles the conversion of a LangChain Runs into a WBTraceTree. Methods __init__(wandb_module, trace_module) build_tree(runs) Builds a nested dictionary from a list of runs....
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.tracers.wandb.RunProcessor.html
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:param run: The base run to flatten. :return: The flattened list of runs. modify_serialized_iterative(runs: List[Dict[str, Any]], exact_keys: Tuple[str, ...] = (), partial_keys: Tuple[str, ...] = ()) → List[Dict[str, Any]][source]¶ Utility to modify the serialized field of a list of runs dictionaries. removes any keys ...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.tracers.wandb.RunProcessor.html
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keep_keys – The keys to keep in each run. Returns The truncated list of runs.
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.tracers.wandb.RunProcessor.html
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langchain.callbacks.utils.flatten_dict¶ langchain.callbacks.utils.flatten_dict(nested_dict: Dict[str, Any], parent_key: str = '', sep: str = '_') → Dict[str, Any][source]¶ Flattens a nested dictionary into a flat dictionary. Parameters nested_dict (dict) – The nested dictionary to flatten. parent_key (str) – The prefix...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.utils.flatten_dict.html
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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,...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.base.BaseCallbackManager.html
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Set handlers as the only handlers on the callback manager. __init__(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, metadata: Optional[Dict[str,...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.base.BaseCallbackManager.html
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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, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶ Run when LLM starts running. on_retriever_start(serialized: Dict[st...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.base.BaseCallbackManager.html
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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”. Ret...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.manager.tracing_enabled.html
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langchain.callbacks.whylabs_callback.import_langkit¶ langchain.callbacks.whylabs_callback.import_langkit(sentiment: bool = False, toxicity: bool = False, themes: bool = False) → Any[source]¶ Import the langkit python package and raise an error if it is not installed. Parameters sentiment – Whether to import the langkit...
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.whylabs_callback.import_langkit.html
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langchain.callbacks.sagemaker_callback.save_json¶ langchain.callbacks.sagemaker_callback.save_json(data: dict, file_path: str) → None[source]¶ Save dict to local file path. Parameters data (dict) – The dictionary to be saved. file_path (str) – Local file path.
https://api.python.langchain.com/en/latest/callbacks/langchain.callbacks.sagemaker_callback.save_json.html
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langchain_experimental.comprehend_moderation.base_moderation_callbacks.BaseModerationCallbackHandler¶ class langchain_experimental.comprehend_moderation.base_moderation_callbacks.BaseModerationCallbackHandler[source]¶ Attributes intent_callback pii_callback toxicity_callback Methods __init__() on_after_intent(moderatio...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_callbacks.BaseModerationCallbackHandler.html
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langchain_experimental.comprehend_moderation.base_moderation.BaseModeration¶ class langchain_experimental.comprehend_moderation.base_moderation.BaseModeration(client: Any, config: Optional[Any] = None, moderation_callback: Optional[Any] = None, unique_id: Optional[str] = None, run_manager: Optional[CallbackManagerForCh...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation.BaseModeration.html
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langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationToxicityError¶ class langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationToxicityError(message: str = 'The prompt contains toxic content and cannot be processed')[source]¶ Exception raised if Toxic entities a...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationToxicityError.html
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langchain_experimental.comprehend_moderation.intent.ComprehendIntent¶ class langchain_experimental.comprehend_moderation.intent.ComprehendIntent(client: Any, callback: Optional[Any] = None, unique_id: Optional[str] = None, chain_id: Optional[str] = None)[source]¶ Methods __init__(client[, callback, unique_id, chain_id]...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.intent.ComprehendIntent.html
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langchain_experimental.comprehend_moderation.base_moderation_config.BaseModerationConfig¶ class langchain_experimental.comprehend_moderation.base_moderation_config.BaseModerationConfig[source]¶ Bases: BaseModel Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.BaseModerationConfig.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.BaseModerationConfig.html
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classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.BaseModerationConfig.html
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langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationIntentionError¶ class langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationIntentionError(message: str = 'The prompt indicates an un-desired intent and cannot be processed')[source]¶ Exception raised if Intent...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationIntentionError.html
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langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationPiiError¶ class langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationPiiError(message: str = 'The prompt contains PII entities and cannot be processed')[source]¶ Exception raised if PII entities are detected. ...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_exceptions.ModerationPiiError.html
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langchain_experimental.comprehend_moderation.base_moderation_config.ModerationIntentConfig¶ class langchain_experimental.comprehend_moderation.base_moderation_config.ModerationIntentConfig[source]¶ Bases: BaseModel Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationIntentConfig.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationIntentConfig.html
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classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationIntentConfig.html
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langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain¶ class langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain[source]¶ Bases: Chain A subclass of Chain, designed to apply moderation to LLMs. Create a new model b...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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and at the end of every chain. At the start, memory loads variables and passes them along in the chain. At the end, it saves any returned variables. There are many different types of memory - please see memory docs for the full catalog. param metadata: Optional[Dict[str, Any]] = None¶ Optional metadata associated with ...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a chain with its use case. param unique_id: Optional[str] = None¶ A unique id that can be used to identify or group a user or session param verbose: bool [Optional]¶ Whether or not run in verbose mode. ...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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metadata – Optional metadata associated with the chain. Defaults to None include_run_info – Whether to include run info in the response. Defaults to False. Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, ...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. metadata – Optional metadata associated with the chain. Defaults to None include_run_info – Whether to include run info in the response. Defaults to False. Returns A dict of named outputs. Sho...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. **kwargs – If the chain expects multiple inputs, they can be passed in directly as keyword arguments. Returns The chain output. Example # Suppose we have a single-input chain that takes a 'que...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default im...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(**kw...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). classmethod lc_id() → List[str]¶ A unique identifier for this class for serialization purposes. The unique identifier is a ...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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memory. outputs – Dictionary of initial chain outputs. return_only_outputs – Whether to only return the chain outputs. If False, inputs are also added to the final outputs. Returns A dict of the final chain outputs. run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags:...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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context = "Weather report for Boise, Idaho on 07/03/23..." chain.run(question=question, context=context) # -> "The temperature in Boise is..." save(file_path: Union[Path, str]) → None¶ Save the chain. Expects Chain._chain_type property to be implemented and for memory to benull. Parameters file_path – Path to file to s...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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This method defines the output keys that will be used to access the output values produced by the chain or function. It ensures that the specified keys are available to access the outputs. Returns A list of output keys. Return type List[str] Note This method is considered private and may not be intended for direct exte...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.amazon_comprehend_moderation.AmazonComprehendModerationChain.html
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langchain_experimental.comprehend_moderation.pii.ComprehendPII¶ class langchain_experimental.comprehend_moderation.pii.ComprehendPII(client: Any, callback: Optional[Any] = None, unique_id: Optional[str] = None, chain_id: Optional[str] = None)[source]¶ Methods __init__(client[, callback, unique_id, chain_id]) validate(p...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.pii.ComprehendPII.html
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langchain_experimental.comprehend_moderation.base_moderation_config.ModerationPiiConfig¶ class langchain_experimental.comprehend_moderation.base_moderation_config.ModerationPiiConfig[source]¶ Bases: BaseModel Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the i...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationPiiConfig.html
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the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[boo...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationPiiConfig.html
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classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationPiiConfig.html
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langchain_experimental.comprehend_moderation.toxicity.ComprehendToxicity¶ class langchain_experimental.comprehend_moderation.toxicity.ComprehendToxicity(client: Any, callback: Optional[Any] = None, unique_id: Optional[str] = None, chain_id: Optional[str] = None)[source]¶ Methods __init__(client[, callback, unique_id, c...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.toxicity.ComprehendToxicity.html
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langchain_experimental.comprehend_moderation.base_moderation_config.ModerationToxicityConfig¶ class langchain_experimental.comprehend_moderation.base_moderation_config.ModerationToxicityConfig[source]¶ Bases: BaseModel Create a new model by parsing and validating input data from keyword arguments. Raises ValidationErro...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationToxicityConfig.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationToxicityConfig.html
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classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/comprehend_moderation/langchain_experimental.comprehend_moderation.base_moderation_config.ModerationToxicityConfig.html
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langchain_experimental.tabular_synthetic_data.base.SyntheticDataGenerator¶ class langchain_experimental.tabular_synthetic_data.base.SyntheticDataGenerator[source]¶ Bases: BaseModel Generates synthetic data using the given LLM and few-shot template. Utilizes the provided LLM to produce synthetic data based on the few-sh...
https://api.python.langchain.com/en/latest/tabular_synthetic_data/langchain_experimental.tabular_synthetic_data.base.SyntheticDataGenerator.html
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the “extra” keyword argument. Parameters subject (str) – The subject the synthetic data will be about. runs (int) – Number of times to generate the data asynchronously. extra (str) – Extra instructions for steerability in data generation. Returns List of generated synthetic data for the given subject. Return type List[...
https://api.python.langchain.com/en/latest/tabular_synthetic_data/langchain_experimental.tabular_synthetic_data.base.SyntheticDataGenerator.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/tabular_synthetic_data/langchain_experimental.tabular_synthetic_data.base.SyntheticDataGenerator.html
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Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol...
https://api.python.langchain.com/en/latest/tabular_synthetic_data/langchain_experimental.tabular_synthetic_data.base.SyntheticDataGenerator.html
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langchain_experimental.tabular_synthetic_data.openai.create_openai_data_generator¶ langchain_experimental.tabular_synthetic_data.openai.create_openai_data_generator(output_schema: Union[Dict[str, Any], Type[BaseModel]], llm: ChatOpenAI, prompt: BasePromptTemplate, output_parser: Optional[BaseLLMOutputParser] = None, **...
https://api.python.langchain.com/en/latest/tabular_synthetic_data/langchain_experimental.tabular_synthetic_data.openai.create_openai_data_generator.html
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langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute¶ class langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute[source]¶ Bases: Chain Plan and execute a chain of steps. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input ...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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The planner to use. param step_container: langchain_experimental.plan_and_execute.schema.BaseStepContainer [Optional]¶ The step container to use. param tags: Optional[List[str]] = None¶ Optional list of tags associated with the chain. Defaults to None. These tags will be associated with each call to this chain, and pas...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. metadata – Optional metadata associated with the chain. Defaults to None include_run_info – Whether to include run ...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the chain during construction, but only these runtime tags will propagate to c...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the chain during construction, but only these runtime tags will propagate to c...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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Stream all output from a runnable, as reported to the callback system. This includes all inner runs of LLMs, Retrievers, Tools, etc. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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classmethod is_lc_serializable() → bool¶ Is this class serializable? json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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Parameters inputs – Dictionary of raw inputs, or single input if chain expects only one param. Should contain all inputs specified in Chain.input_keys except for inputs that will be set by the chain’s memory. Returns A dictionary of all inputs, including those added by the chain’s memory. prep_outputs(inputs: Dict[str,...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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these runtime tags will propagate to calls to other objects. **kwargs – If the chain expects multiple inputs, they can be passed in directly as keyword arguments. Returns The chain output. Example # Suppose we have a single-input chain that takes a 'question' string: chain.run("What's the temperature in Boise, Idaho?")...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing output while input is still being generated. classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and lo...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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property output_keys: List[str]¶ Keys expected to be in the chain output. property output_schema: Type[pydantic.main.BaseModel]¶
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.agent_executor.PlanAndExecute.html
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langchain_experimental.plan_and_execute.schema.StepResponse¶ class langchain_experimental.plan_and_execute.schema.StepResponse[source]¶ Bases: BaseModel Step response. 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 vali...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.schema.StepResponse.html
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Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. classmethod from_orm(obj: Any) → Model¶ json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False,...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.schema.StepResponse.html
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langchain_experimental.plan_and_execute.executors.base.BaseExecutor¶ class langchain_experimental.plan_and_execute.executors.base.BaseExecutor[source]¶ Bases: BaseModel Base executor. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parse...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.executors.base.BaseExecutor.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.executors.base.BaseExecutor.html
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classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ abstract step(inputs: dict, callbacks: Optional[Union[List[BaseCallbackHandler], Bas...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.executors.base.BaseExecutor.html
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langchain_experimental.plan_and_execute.executors.base.ChainExecutor¶ class langchain_experimental.plan_and_execute.executors.base.ChainExecutor[source]¶ Bases: BaseExecutor Chain executor. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.executors.base.ChainExecutor.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.executors.base.ChainExecutor.html
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classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ step(inputs: dict, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallback...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.executors.base.ChainExecutor.html
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langchain_experimental.plan_and_execute.schema.Plan¶ class langchain_experimental.plan_and_execute.schema.Plan[source]¶ Bases: BaseModel Plan. 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 steps: Lis...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.schema.Plan.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.schema.Plan.html
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classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.schema.Plan.html
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langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser¶ class langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser[source]¶ Bases: PlanOutputParser Planning output parser. Create a new model by parsing and validating input data from keyword arguments. Raises Val...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser.html
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Default implementation of astream, which calls ainvoke. Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser.html
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Bind arguments to a Runnable, returning a new Runnable. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶ Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser.html
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classmethod is_lc_serializable() → bool¶ Is this class serializable? json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser.html
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Parse a list of candidate model Generations into a specific format. The return value is parsed from only the first Generation in the result, whichis assumed to be the highest-likelihood Generation. Parameters result – A list of Generations to be parsed. The Generations are assumed to be different candidate outputs for ...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser.html
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classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶ with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶ Bind config to a Runnable, returning a new Runna...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.planners.chat_planner.PlanningOutputParser.html
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langchain_experimental.plan_and_execute.schema.ListStepContainer¶ class langchain_experimental.plan_and_execute.schema.ListStepContainer[source]¶ Bases: BaseStepContainer List step container. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot ...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.schema.ListStepContainer.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/plan_and_execute/langchain_experimental.plan_and_execute.schema.ListStepContainer.html