id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
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bb3cfc7163e5-0 | langchain.agents.agent_toolkits.powerbi.base.create_pbi_agent¶ | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.base.create_pbi_agent.html |
bb3cfc7163e5-1 | langchain.agents.agent_toolkits.powerbi.base.create_pbi_agent(llm: BaseLanguageModel, toolkit: Optional[PowerBIToolkit] = None, powerbi: Optional[PowerBIDataset] = None, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = 'You are an agent designed to help users interact with a PowerBI Dataset.\n\nAge... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.base.create_pbi_agent.html |
bb3cfc7163e5-2 | Input: the input to the action\nObservation: the result of the action\n... (this Thought/Action/Action Input/Observation can repeat N times)\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question', examples: Optional[str] = None, input_variables: Optional[List[str]] = None,... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.base.create_pbi_agent.html |
bb3cfc7163e5-3 | Construct a Power BI agent from an LLM and tools.
Examples using create_pbi_agent¶
PowerBI Dataset | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.base.create_pbi_agent.html |
64e8cad7263f-0 | langchain.agents.output_parsers.self_ask.SelfAskOutputParser¶
class langchain.agents.output_parsers.self_ask.SelfAskOutputParser[source]¶
Bases: AgentOutputParser
Parses self-ask style LLM calls.
Expects output to be in one of two formats.
If the output signals that an action should be taken,
should be in the below for... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-1 | Subclasses should override this method if they can run asynchronously.
async aparse(text: str) → T¶
Parse a single string model output into some structure.
Parameters
text – String output of a language model.
Returns
Structured output.
async aparse_result(result: List[Generation], *, partial: bool = False) → T¶
Parse a... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-2 | 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 implementation of atransform, which buffers input and calls astream.
Subcla... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-3 | classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-4 | Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate input.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “open... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-5 | 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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-6 | parse_result(result: List[Generation], *, partial: bool = False) → T¶
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 pars... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-7 | input is still being generated.
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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-8 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
64e8cad7263f-9 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
cee1e72e860b-0 | langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing¶
class langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing[source]¶
Bases: BaseRequestsTool, BaseTool
Requests PATCH tool with LLM-instructed extraction of truncated responses.
Create a new model by parsing and validat... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-1 | Optional metadata associated with the tool. Defaults to None
This metadata will be associated with each call to this tool,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a tool with its use case.
param name: str = 'requests_patch'¶
Tool name.
param ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-2 | Default implementation of ainvoke, calls invoke from a thread.
The default implementation allows usage of async code even if
the runnable did not implement a native async version of invoke.
Subclasses should override this method if they can run asynchronously.
async arun(tool_input: Union[str, Dict], verbose: Optional[... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-3 | 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 implementation of atransform, which buffers input and calls astream.
Subcla... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-4 | classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-5 | Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate output to the runnable.
Runnables th... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-6 | 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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-7 | run(tool_input: Union[str, Dict], verbose: Optional[bool] = None, start_color: Optional[str] = 'green', color: Optional[str] = 'green', callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name: Optional[st... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-8 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'Exception'>,)) → RunnableWithFallbacksT[Input, Output]¶
Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A se... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
cee1e72e860b-9 | between retries
stop_after_attempt – The maximum number of attempts to make before giving up
Returns
A new Runnable that retries the original runnable on exceptions.
with_types(*, input_type: Optional[Type[Input]] = None, output_type: Optional[Type[Output]] = None) → Runnable[Input, Output]¶
Bind input and output types... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing.html |
a3a53c80d599-0 | langchain.agents.load_tools.load_huggingface_tool¶
langchain.agents.load_tools.load_huggingface_tool(task_or_repo_id: str, model_repo_id: Optional[str] = None, token: Optional[str] = None, remote: bool = False, **kwargs: Any) → BaseTool[source]¶
Loads a tool from the HuggingFace Hub.
Parameters
task_or_repo_id – Task o... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.load_tools.load_huggingface_tool.html |
7d4060db05ea-0 | langchain.agents.tools.InvalidTool¶
class langchain.agents.tools.InvalidTool[source]¶
Bases: BaseTool
Tool that is run when invalid tool name is encountered by agent.
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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-1 | These tags will be associated with each call to this tool,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a tool with its use case.
param verbose: bool = False¶
Whether to log the tool’s progress.
__call__(tool_input: str, callbacks: Optional[Union[... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-2 | Run the tool asynchronously.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optio... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-3 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-4 | 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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-5 | Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input: Union[str, Dict], config: Optional[RunnableConfig] = None, **kwargs: Any) → Any¶
Transform a single input into an output. Override to implement.
Parameters
input – The input to the... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-6 | by calling invoke() with each input.
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 = No... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-7 | 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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-8 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
7d4060db05ea-9 | A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
f9c832c9d788-0 | langchain.agents.schema.AgentScratchPadChatPromptTemplate¶
class langchain.agents.schema.AgentScratchPadChatPromptTemplate[source]¶
Bases: ChatPromptTemplate
Chat prompt template for the agent scratchpad.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-1 | The default implementation allows usage of async code even if
the runnable did not implement a native async version of invoke.
Subclasses should override this method if they can run asynchronously.
append(message: Union[BaseMessagePromptTemplate, BaseMessage, BaseChatPromptTemplate, Tuple[str, str], Tuple[Type, str], s... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-2 | Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if they can start producing output while
input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-3 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-4 | :param **kwargs: Keyword arguments to use for formatting.
Returns
PromptValue.
classmethod from_messages(messages: Sequence[Union[BaseMessagePromptTemplate, BaseMessage, BaseChatPromptTemplate, Tuple[str, str], Tuple[Type, str], str]]) → ChatPromptTemplate¶
Create a chat prompt template from a variety of message format... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-5 | Returns
a chat prompt template
Notes
Deprecated since version 0.0.260: Use from_messages classmethod instead.
classmethod from_strings(string_messages: List[Tuple[Type[BaseMessagePromptTemplate], str]]) → ChatPromptTemplate¶
[Deprecated] Create a chat prompt template from a list of (role class, template) tuples.
Param... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-6 | For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and con... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-7 | 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 ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-8 | template2.format_messages(input="hello")
save(file_path: Union[Path, str]) → None¶
Save prompt to file.
Parameters
file_path – path to file.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-9 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
f9c832c9d788-10 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Type[langchain.schema.runnable.utils.Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Any¶
The type of output this runnable produces specified as a type annotation.
property confi... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
25416d713962-0 | langchain.agents.output_parsers.openai_tools.OpenAIToolAgentAction¶
class langchain.agents.output_parsers.openai_tools.OpenAIToolAgentAction[source]¶
Bases: AgentActionMessageLog
Override init to support instantiation by position for backward compat.
param log: str [Required]¶
Additional information to log about the ac... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_tools.OpenAIToolAgentAction.html |
25416d713962-1 | Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_tools.OpenAIToolAgentAction.html |
25416d713962-2 | classmethod is_lc_serializable() → bool¶
Return whether or not the class is 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 ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_tools.OpenAIToolAgentAction.html |
25416d713962-3 | to_json_not_implemented() → SerializedNotImplemented¶
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¶
property lc_attributes: Dict¶
List of attribute names that should be included in the seri... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_tools.OpenAIToolAgentAction.html |
5c73b47dd8f8-0 | langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser¶
class langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser[source]¶
Bases: AgentOutputParser
Parses a message into agent action/finish.
Is meant to be used with OpenAI models, as it relies on the specific
fun... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-1 | 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 ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-2 | Subclasses should override this method if they can start producing output while
input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs invoke... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-3 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-4 | For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and con... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-5 | 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 ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-6 | The prompt is largely provided in the event the OutputParser wants
to retry or fix the output in some way, and needs information from
the prompt to do so.
Parameters
completion – String output of a language model.
prompt – Input PromptValue.
Returns
Structured output
classmethod schema(by_alias: bool = True, ref_templa... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-7 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
5c73b47dd8f8-8 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Any¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.output_parser.T]¶
The type of output this runnable produces specified as a type annotation.
property config_spe... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser.html |
98108f15b41f-0 | langchain_experimental.agents.agent_toolkits.pandas.base.create_pandas_dataframe_agent¶
langchain_experimental.agents.agent_toolkits.pandas.base.create_pandas_dataframe_agent(llm: BaseLanguageModel, df: Any, agent_type: AgentType = AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager: Optional[BaseCallbackManager] =... | lang/api.python.langchain.com/en/latest/agents/langchain_experimental.agents.agent_toolkits.pandas.base.create_pandas_dataframe_agent.html |
41b5912b71cd-0 | langchain.agents.structured_chat.base.StructuredChatAgent¶
class langchain.agents.structured_chat.base.StructuredChatAgent[source]¶
Bases: Agent
Structured Chat Agent.
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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
41b5912b71cd-1 | 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 creating
the new model: you should trust this data
deep – set to True to make a deep co... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
41b5912b71cd-2 | deep – set to True to make a deep copy of the model
Returns
new model instance
classmethod create_prompt(tools: Sequence[BaseTool], prefix: str = 'Respond to the human as helpfully and accurately as possible. You have access to the following tools:', suffix: str = 'Begin! Reminder to ALWAYS respond with a valid json bl... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
41b5912b71cd-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of agent.
classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, prefix: str = 'Respond to the human as helpfully and accurat... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
41b5912b71cd-4 | Construct an agent from an LLM and tools.
classmethod from_orm(obj: Any) → Model¶
get_allowed_tools() → Optional[List[str]]¶
get_full_inputs(intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → Dict[str, Any]¶
Create the full inputs for the LLMChain from intermediate steps.
json(*, include: Optional[Unio... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
41b5912b71cd-5 | Parameters
intermediate_steps – Steps the LLM has taken to date,
along with observations
callbacks – Callbacks to run.
**kwargs – User inputs.
Returns
Action specifying what tool to use.
return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → AgentFinish¶
... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
9125645cd7ff-0 | langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent¶ | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
9125645cd7ff-1 | langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent(llm: BaseChatModel, toolkit: Optional[PowerBIToolkit] = None, powerbi: Optional[PowerBIDataset] = None, callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, prefix: str = 'Assistant is a large l... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
9125645cd7ff-2 | blob with a single action, and NOTHING else):\n\n{{{{input}}}}\n", examples: Optional[str] = None, input_variables: Optional[List[str]] = None, memory: Optional[BaseChatMemory] = None, top_k: int = 10, verbose: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Any) → AgentExecutor[source]¶ | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
9125645cd7ff-3 | Construct a Power BI agent from a Chat LLM and tools.
If you supply only a toolkit and no Power BI dataset, the same LLM is used for both. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
429fba8e9b66-0 | langchain.agents.format_scratchpad.openai_functions.format_to_openai_functions¶
langchain.agents.format_scratchpad.openai_functions.format_to_openai_functions(intermediate_steps: Sequence[Tuple[AgentAction, str]]) → List[BaseMessage]¶
Convert (AgentAction, tool output) tuples into FunctionMessages.
Parameters
intermedi... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.format_scratchpad.openai_functions.format_to_openai_functions.html |
05fc35184a5f-0 | langchain.agents.react.base.DocstoreExplorer¶
class langchain.agents.react.base.DocstoreExplorer(docstore: Docstore)[source]¶
Class to assist with exploration of a document store.
Initialize with a docstore, and set initial document to None.
Methods
__init__(docstore)
Initialize with a docstore, and set initial documen... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.DocstoreExplorer.html |
71424031e398-0 | langchain.agents.chat.base.ChatAgent¶
class langchain.agents.chat.base.ChatAgent[source]¶
Bases: Agent
Chat Agent.
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 allowed_tools: Optional[List[str]] = N... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
71424031e398-1 | 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 creating
the new model: you should trust this data
deep – set to True to make a deep co... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
71424031e398-2 | deep – set to True to make a deep copy of the model
Returns
new model instance
classmethod create_prompt(tools: Sequence[BaseTool], system_message_prefix: str = 'Answer the following questions as best you can. You have access to the following tools:', system_message_suffix: str = 'Begin! Reminder to always use the exac... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
71424031e398-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of agent.
classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, system_message_prefix: str = 'Answer the following questions... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
71424031e398-4 | Construct an agent from an LLM and tools.
classmethod from_orm(obj: Any) → Model¶
get_allowed_tools() → Optional[List[str]]¶
get_full_inputs(intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → Dict[str, Any]¶
Create the full inputs for the LLMChain from intermediate steps.
json(*, include: Optional[Unio... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
71424031e398-5 | Parameters
intermediate_steps – Steps the LLM has taken to date,
along with observations
callbacks – Callbacks to run.
**kwargs – User inputs.
Returns
Action specifying what tool to use.
return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → AgentFinish¶
... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
fb4758a96bfb-0 | langchain.agents.output_parsers.json.JSONAgentOutputParser¶
class langchain.agents.output_parsers.json.JSONAgentOutputParser[source]¶
Bases: AgentOutputParser
Parses tool invocations and final answers in JSON format.
Expects output to be in one of two formats.
If the output signals that an action should be taken,
shoul... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-1 | Parameters
text – String output of a language model.
Returns
Structured output.
async aparse_result(result: List[Generation], *, partial: bool = False) → T¶
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 ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-2 | 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 implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if th... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-3 | classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-4 | Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate input.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “open... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-5 | 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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-6 | parse_result(result: List[Generation], *, partial: bool = False) → T¶
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 pars... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-7 | input is still being generated.
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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-8 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
fb4758a96bfb-9 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.json.JSONAgentOutputParser.html |
4b5c4b7b4e01-0 | langchain.agents.conversational_chat.base.ConversationalChatAgent¶
class langchain.agents.conversational_chat.base.ConversationalChatAgent[source]¶
Bases: Agent
An agent designed to hold a conversation in addition to using tools.
Create a new model by parsing and validating input data from keyword arguments.
Raises Val... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
4b5c4b7b4e01-1 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
4b5c4b7b4e01-2 | deep – set to True to make a deep copy of the model
Returns
new model instance
classmethod create_prompt(tools: Sequence[BaseTool], system_message: str = 'Assistant is a large language model trained by OpenAI.\n\nAssistant is designed to be able to assist with a wide range of tasks, from answering simple questions to p... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
4b5c4b7b4e01-3 | Create a prompt for this class.
dict(**kwargs: Any) → Dict¶
Return dictionary representation of agent. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
4b5c4b7b4e01-4 | classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, system_message: str = 'Assistant is a large language model trained by OpenAI.\n\nAssistant is designed to be able to assist with a ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
4b5c4b7b4e01-5 | Construct an agent from an LLM and tools.
classmethod from_orm(obj: Any) → Model¶
get_allowed_tools() → Optional[List[str]]¶
get_full_inputs(intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → Dict[str, Any]¶
Create the full inputs for the LLMChain from intermediate steps.
json(*, include: Optional[Unio... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
4b5c4b7b4e01-6 | Parameters
intermediate_steps – Steps the LLM has taken to date,
along with observations
callbacks – Callbacks to run.
**kwargs – User inputs.
Returns
Action specifying what tool to use.
return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → AgentFinish¶
... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
d50359699a96-0 | langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit¶
class langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with local files.
Security Notice: This toolkit provides methods to interact with local files.If providin... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit.html |
d50359699a96-1 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit.html |
d50359699a96-2 | Get the tools in the toolkit.
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_defaults: bool = False, exclude_none: bool ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit.html |
2c439e6382c7-0 | langchain.agents.agent_toolkits.sql.base.create_sql_agent¶ | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.base.create_sql_agent.html |
2c439e6382c7-1 | langchain.agents.agent_toolkits.sql.base.create_sql_agent(llm: BaseLanguageModel, toolkit: SQLDatabaseToolkit, agent_type: AgentType = AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = 'You are an agent designed to interact with a SQL database.\nGiven an input ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.base.create_sql_agent.html |
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