id stringlengths 14 15 | text stringlengths 49 2.47k | source stringlengths 61 166 |
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f830f5a4f196-1 | bind(**kwargs: Any) → Runnable[Input, Output]¶
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 othe... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.output_parser.ChatOutputParser.html |
f830f5a4f196-2 | 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 = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.output_parser.ChatOutputParser.html |
f830f5a4f196-3 | Parse the output of an LLM call with the input prompt for context.
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
Str... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.output_parser.ChatOutputParser.html |
f830f5a4f196-4 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.output_parser.ChatOutputParser.html |
aaffe75b85e9-0 | langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo¶
class langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo[source]¶
Bases: BaseModel
Information about a VectorStore.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input da... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo.html |
aaffe75b85e9-1 | 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/agents/langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo.html |
aaffe75b85e9-2 | 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/agents/langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo.html |
670cb5e79471-0 | langchain.agents.agent_toolkits.json.toolkit.JsonToolkit¶
class langchain.agents.agent_toolkits.json.toolkit.JsonToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with a JSON spec.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot b... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.json.toolkit.JsonToolkit.html |
670cb5e79471-1 | 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/agents/langchain.agents.agent_toolkits.json.toolkit.JsonToolkit.html |
670cb5e79471-2 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmet... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.json.toolkit.JsonToolkit.html |
a7e636655b54-0 | langchain.agents.mrkl.base.MRKLChain¶
class langchain.agents.mrkl.base.MRKLChain[source]¶
Bases: AgentExecutor
Chain that implements the MRKL system.
Example
from langchain import OpenAI, MRKLChain
from langchain.chains.mrkl.base import ChainConfig
llm = OpenAI(temperature=0)
prompt = PromptTemplate(...)
chains = [...]... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-1 | How to handle errors raised by the agent’s output parser.Defaults to False, which raises the error.
sIf true, the error will be sent back to the LLM as an observation.
If a string, the string itself will be sent to the LLM as an observation.
If a callable function, the function will be called with the exception
as an a... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-2 | These tags will be associated with each call to this chain,
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 tools: Sequence[BaseTool] [Required]¶
The valid tools the agent can call.
param trim_intermediate_steps: Unio... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-3 | 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/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-4 | 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. Should contain all outputs specified inChain.output_keys.
async ainvok... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-5 | directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'question' string:
await chain.arun("What's the temperature in Boise, Idaho?")
# -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' s... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-6 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-7 | llm = OpenAI(temperature=0)
search = SerpAPIWrapper()
llm_math_chain = LLMMathChain(llm=llm)
chains = [
ChainConfig(
action_name = "Search",
action=search.search,
action_description="useful for searching"
),
ChainConfig(
action_name="Calculator",
action=llm_math_chain... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-8 | lookup_tool(name: str) → BaseTool¶
Lookup tool by name.
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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-9 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
a7e636655b54-10 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None) → Iterator[Output]¶
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedN... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.MRKLChain.html |
1f9db276b5a3-0 | langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
1f9db276b5a3-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
1f9db276b5a3-2 | 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: Dict[str, Any]) → AgentExecut... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
1f9db276b5a3-3 | 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. | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent.html |
3b7233c82a58-0 | langchain.agents.agent_toolkits.openapi.base.create_openapi_agent¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.base.create_openapi_agent.html |
3b7233c82a58-1 | langchain.agents.agent_toolkits.openapi.base.create_openapi_agent(llm: BaseLanguageModel, toolkit: OpenAPIToolkit, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = "You are an agent designed to answer questions by making web requests to an API given the openapi spec.\n\nIf the question does not see... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.base.create_openapi_agent.html |
3b7233c82a58-2 | 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', input_variables: Optional[List[str]] = None, max_iterations: Optional[int] =... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.base.create_openapi_agent.html |
3b7233c82a58-3 | Construct an OpenAPI agent from an LLM and tools.
Examples using create_openapi_agent¶
OpenAPI agents | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.base.create_openapi_agent.html |
fe093dad4744-0 | langchain.agents.agent.BaseMultiActionAgent¶
class langchain.agents.agent.BaseMultiActionAgent[source]¶
Bases: BaseModel
Base Multi Action Agent class.
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.
abstrac... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.BaseMultiActionAgent.html |
fe093dad4744-1 | 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(**kwargs: Any) → Dict[source]¶
Return dictionary representation of agent.
classmethod from_orm(obj: Any) → Model¶
get_allowed_tools() → Optional[List[str]][source]¶
json(*, include: Optional[Uni... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.BaseMultiActionAgent.html |
fe093dad4744-2 | Parameters
intermediate_steps – Steps the LLM has taken to date,
along with the observations.
callbacks – Callbacks to run.
**kwargs – User inputs.
Returns
Actions specifying what tool to use.
return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → AgentFi... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.BaseMultiActionAgent.html |
2d7ca93ef278-0 | langchain.agents.agent_toolkits.conversational_retrieval.tool.create_retriever_tool¶
langchain.agents.agent_toolkits.conversational_retrieval.tool.create_retriever_tool(retriever: BaseRetriever, name: str, description: str) → Tool[source]¶
Create a tool to do retrieval of documents.
Parameters
retriever – The retriever... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.conversational_retrieval.tool.create_retriever_tool.html |
4f48a8ea2f2c-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 a Local Files.
Create a new model by parsing and validating input data from keyword arguments.
Raise... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit.html |
4f48a8ea2f2c-1 | 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/agents/langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit.html |
4f48a8ea2f2c-2 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmet... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.file_management.toolkit.FileManagementToolkit.html |
60db1480680f-0 | langchain.agents.load_tools.load_tools¶
langchain.agents.load_tools.load_tools(tool_names: List[str], llm: Optional[BaseLanguageModel] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → List[BaseTool][source]¶
Load tools based on their name.
Parameters
tool_names... | https://api.python.langchain.com/en/latest/agents/langchain.agents.load_tools.load_tools.html |
f578275289da-0 | langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_agent¶
langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_agent(llm: BaseLanguageModel, toolkit: VectorStoreToolkit, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = 'You are an agent designed to answer questions a... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_agent.html |
56a98a92c723-0 | langchain.agents.agent_iterator.AgentExecutorIterator¶
class langchain.agents.agent_iterator.AgentExecutorIterator(agent_executor: AgentExecutor, inputs: Any, callbacks: Callbacks = None, *, tags: Optional[list[str]] = None, include_run_info: bool = False, async_: bool = False)[source]¶
Iterator for AgentExecutor.
Init... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_iterator.AgentExecutorIterator.html |
56a98a92c723-1 | raise_stopiteration(output: Any) → NoReturn[source]¶
Raise a StopIteration exception with the given output.
reset() → None[source]¶
Reset the iterator to its initial state, clearing intermediate steps,
iterations, and time elapsed.
update_iterations() → None[source]¶
Increment the number of iterations and update the ti... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_iterator.AgentExecutorIterator.html |
4be0203aa506-0 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.load_tools.load_huggingface_tool.html |
04d6bf0034c4-0 | langchain.agents.mrkl.output_parser.MRKLOutputParser¶
class langchain.agents.mrkl.output_parser.MRKLOutputParser[source]¶
Bases: AgentOutputParser
MRKL Output parser for the chat agent.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be par... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.output_parser.MRKLOutputParser.html |
04d6bf0034c4-1 | 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/agents/langchain.agents.mrkl.output_parser.MRKLOutputParser.html |
04d6bf0034c4-2 | 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 = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.output_parser.MRKLOutputParser.html |
04d6bf0034c4-3 | Parse the output of an LLM call with the input prompt for context.
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
Str... | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.output_parser.MRKLOutputParser.html |
04d6bf0034c4-4 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.output_parser.MRKLOutputParser.html |
7acb785033ff-0 | langchain.agents.agent_toolkits.openapi.spec.dereference_refs¶
langchain.agents.agent_toolkits.openapi.spec.dereference_refs(spec_obj: dict, full_spec: dict) → Union[dict, list][source]¶
Try to substitute $refs.
The goal is to get the complete docs for each endpoint in context for now.
In the few OpenAPI specs I studie... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.spec.dereference_refs.html |
175734bb9d60-0 | langchain.agents.xml.base.XMLAgentOutputParser¶
class langchain.agents.xml.base.XMLAgentOutputParser[source]¶
Bases: AgentOutputParser
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.
async abatch(inputs: Lis... | https://api.python.langchain.com/en/latest/agents/langchain.agents.xml.base.XMLAgentOutputParser.html |
175734bb9d60-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.xml.base.XMLAgentOutputParser.html |
175734bb9d60-2 | 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 = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/agents/langchain.agents.xml.base.XMLAgentOutputParser.html |
175734bb9d60-3 | Parse the output of an LLM call with the input prompt for context.
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
Str... | https://api.python.langchain.com/en/latest/agents/langchain.agents.xml.base.XMLAgentOutputParser.html |
175734bb9d60-4 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/agents/langchain.agents.xml.base.XMLAgentOutputParser.html |
d2fff81355ae-0 | langchain.agents.agent_toolkits.multion.toolkit.MultionToolkit¶
class langchain.agents.agent_toolkits.multion.toolkit.MultionToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with the Browser Agent
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the in... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.multion.toolkit.MultionToolkit.html |
d2fff81355ae-1 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
get_tools() → List[BaseTool][source]¶
Get the tools in the toolkit.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[A... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.multion.toolkit.MultionToolkit.html |
3d434d19fbdf-0 | langchain.agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing¶
class langchain.agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing[source]¶
Bases: BaseRequestsTool, BaseTool
Requests POST tool with LLM-instructed extraction of truncated responses.
Create a new model by parsing and validating... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing.html |
3d434d19fbdf-1 | 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_post'¶
Tool name.
param requests_wrapper: TextRequestsWrapper [Required]¶
param respon... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing.html |
3d434d19fbdf-2 | async arun(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, **kwargs: Any)... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing.html |
3d434d19fbdf-3 | 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/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing.html |
3d434d19fbdf-4 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(tool_input: Union[str, Dict], verbose: Optional[bool] = None, start_color: Optional[str] = 'green', color: Op... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing.html |
ed53b2acb4f9-0 | langchain.agents.react.base.ReActDocstoreAgent¶
class langchain.agents.react.base.ReActDocstoreAgent[source]¶
Bases: Agent
Agent for the ReAct chain.
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 all... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActDocstoreAgent.html |
ed53b2acb4f9-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActDocstoreAgent.html |
ed53b2acb4f9-2 | 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/agents/langchain.agents.react.base.ReActDocstoreAgent.html |
ed53b2acb4f9-3 | 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 llm_prefix: str¶
Prefix to append the LLM call with.
property observation_prefix: str¶
Prefix to append the observation with.
property... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActDocstoreAgent.html |
25cecfb6b0c3-0 | langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent¶
class langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent[source]¶
Bases: Agent
Agent for the self-ask-with-search paper.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input d... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent.html |
25cecfb6b0c3-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent.html |
25cecfb6b0c3-2 | 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/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent.html |
25cecfb6b0c3-3 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
tool_run_logging_kwargs() → Dict¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent.html |
2a061b3031ee-0 | langchain.agents.agent.ExceptionTool¶
class langchain.agents.agent.ExceptionTool[source]¶
Bases: BaseTool
Tool that just returns the query.
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 args_schema: ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
2a061b3031ee-1 | param verbose: bool = False¶
Whether to log the tool’s progress.
__call__(tool_input: str, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → str¶
Make tool callable.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurre... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
2a061b3031ee-2 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
2a061b3031ee-3 | 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 = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
2a061b3031ee-4 | stream(input: Input, config: Optional[RunnableConfig] = None) → Iterator[Output]¶
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_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
867b299c70f2-0 | langchain.agents.conversational.output_parser.ConvoOutputParser¶
class langchain.agents.conversational.output_parser.ConvoOutputParser[source]¶
Bases: AgentOutputParser
Output parser for the conversational agent.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if t... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
867b299c70f2-1 | bind(**kwargs: Any) → Runnable[Input, Output]¶
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 othe... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
867b299c70f2-2 | 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 = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
867b299c70f2-3 | Parse the output of an LLM call with the input prompt for context.
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
Str... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
867b299c70f2-4 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
46dbdc0d5bad-0 | langchain.agents.utils.validate_tools_single_input¶
langchain.agents.utils.validate_tools_single_input(class_name: str, tools: Sequence[BaseTool]) → None[source]¶
Validate tools for single input. | https://api.python.langchain.com/en/latest/agents/langchain.agents.utils.validate_tools_single_input.html |
b4be35bfa727-0 | langchain.agents.agent_toolkits.nla.tool.NLATool¶
class langchain.agents.agent_toolkits.nla.tool.NLATool[source]¶
Bases: Tool
Natural Language API Tool.
Initialize tool.
param args_schema: Optional[Type[BaseModel]] = None¶
Pydantic model class to validate and parse the tool’s input arguments.
param callback_manager: Op... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.nla.tool.NLATool.html |
b4be35bfa727-1 | Optional list of tags associated with the tool. Defaults to None
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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.nla.tool.NLATool.html |
b4be35bfa727-2 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.nla.tool.NLATool.html |
b4be35bfa727-3 | Initialize tool from a function.
classmethod from_llm_and_method(llm: BaseLanguageModel, path: str, method: str, spec: OpenAPISpec, requests: Optional[Requests] = None, verbose: bool = False, return_intermediate_steps: bool = False, **kwargs: Any) → NLATool[source]¶
Instantiate the tool from the specified path and meth... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.nla.tool.NLATool.html |
b4be35bfa727-4 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(tool_input: Union[str, Dict], verbose: Optional[bool] = None, start_color: Optional[str] = 'green', color: Op... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.nla.tool.NLATool.html |
3dd513730c06-0 | langchain.agents.agent.AgentExecutor¶
class langchain.agents.agent.AgentExecutor[source]¶
Bases: Chain
Agent that is using tools.
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 agent: Union[BaseSingle... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-1 | If a callable function, the function will be called with the exception
as an argument, and the result of that function will be passed to the agentas an observation.
param max_execution_time: Optional[float] = None¶
The maximum amount of wall clock time to spend in the execution
loop.
param max_iterations: Optional[int]... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-2 | The valid tools the agent can call.
param trim_intermediate_steps: Union[int, Callable[[List[Tuple[AgentAction, str]]], List[Tuple[AgentAction, str]]]] = -1¶
param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to langchain.... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-3 | 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, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]¶
async acall(inputs: Union[Dict[str, Any], Any], return_on... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-4 | Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None) → Dict[str, Any]¶
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dic... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-5 | # -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-6 | 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(**kwargs: Any) → Dict¶
Dictionary representation of chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
**kwargs – Keyword arguments passed to defaul... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-7 | 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().
lookup_tool(name: str) → BaseTool[source]¶
Lookup tool by name.
classmethod parse_file(path: Union[str, Path], *, content_t... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-8 | Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-9 | save(file_path: Union[Path, str]) → None[source]¶
Raise error - saving not supported for Agent Executors.
save_agent(file_path: Union[Path, str]) → None[source]¶
Save the underlying agent.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*,... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
3dd513730c06-10 | property lc_serializable: bool¶
Return whether or not the class is serializable.
Examples using AgentExecutor¶
Jina
PowerBI Dataset Agent
SQL Database Agent
JSON Agent
BabyAGI with Tools
Plug-and-Plai
Wikibase Agent
SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base
Custom Agent with PlugIn Retrieval
... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentExecutor.html |
74b2c646f85f-0 | langchain.agents.agent.BaseSingleActionAgent¶
class langchain.agents.agent.BaseSingleActionAgent[source]¶
Bases: BaseModel
Base Single Action Agent class.
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.
abst... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.BaseSingleActionAgent.html |
74b2c646f85f-1 | 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(**kwargs: Any) → Dict[source]¶
Return dictionary representation of agent.
classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbac... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.BaseSingleActionAgent.html |
74b2c646f85f-2 | abstract plan(intermediate_steps: List[Tuple[AgentAction, str]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Union[AgentAction, AgentFinish][source]¶
Given input, decided what to do.
Parameters
intermediate_steps – Steps the LLM has taken to date,
along with obser... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.BaseSingleActionAgent.html |
9c01371aed57-0 | langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent¶
class langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent[source]¶
Bases: BaseSingleActionAgent
An Agent driven by OpenAIs function powered API.
Parameters
llm – This should be an instance of ChatOpenAI, specifically a model
that supports ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
9c01371aed57-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
9c01371aed57-2 | Construct an agent from an LLM and tools.
classmethod from_orm(obj: Any) → Model¶
get_allowed_tools() → List[str][source]¶
Get allowed tools.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_d... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
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