id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
0d62d0a95e0b-4 | Parse text into agent action/finish.
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... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
0d62d0a95e0b-5 | Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = No... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
0d62d0a95e0b-6 | These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
2c0b507c65ad-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... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
2c0b507c65ad-1 | 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 list of candidate model Generations into a specific format.
The return... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
2c0b507c65ad-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... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
2c0b507c65ad-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(**kwargs: Any) → Dict¶
Return dictionary representation of output parser.
classmethod from_orm(obj: Any) → Model¶
get_format_instructions() → str¶
Instructions on how the LLM output should be fo... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
2c0b507c65ad-4 | Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
parse(text: str) → Union[AgentAction, AgentFinish][source]¶
Parse text into agent action/finish.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: ... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
2c0b507c65ad-5 | stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implem... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
2c0b507c65ad-6 | property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: T... | https://api.python.langchain.com/en/latest/agents.output_parsers/langchain.agents.output_parsers.self_ask.SelfAskOutputParser.html |
42a99b141e6b-0 | langchain_experimental.smart_llm.base.SmartLLMChain¶
class langchain_experimental.smart_llm.base.SmartLLMChain[source]¶
Bases: Chain
Generalized implementation of SmartGPT (origin: https://youtu.be/wVzuvf9D9BU)
A SmartLLMChain is an LLMChain that instead of simply passing the prompt to the LLM
performs these 3 steps:
1... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-1 | Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
param critique_llm: Optional[langchain.schema.language_model.BaseLanguageModel] = None¶
LLM to use in critique step. If None given, ‘llm’ will be used.
param history: langchain_experimental.smart_llm.base.SmartLLMChai... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-2 | Prompt object to use.
param resolver_llm: Optional[langchain.schema.language_model.BaseLanguageModel] = None¶
LLM to use in resolve step. If None given, ‘llm’ will be used.
param return_intermediate_steps: bool = False¶
Whether to return ideas and critique, in addition to resolution.
param tags: Optional[List[str]] = N... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-3 | only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by thi... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-4 | Asynchronously execute the chain.
Parameters
inputs – Dictionary of 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.
return_only_outputs – Whether to return only outputs in the
response. If True, on... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-5 | Call the chain on all inputs in the list.
async arun(*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 ... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-6 | # -> "The temperature in Boise is..."
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, conf... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-7 | Subclasses should override this method if they can batch more efficiently.
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__ fr... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-8 | classmethod from_orm(obj: Any) → Model¶
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”, “openai”]
get_prompt_strings(stage: str) → List[Tuple[Type[BaseMessagePromptTemplate], str... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-9 | 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... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-10 | Prepare prompts from inputs.
resolve_prompt() → ChatPromptTemplate[source]¶
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 ma... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-11 | 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 save the chain to.
Example
chain.save(file_path="path/chain.... | https://api.python.langchain.com/en/latest/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
42a99b141e6b-12 | 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/smart_llm/langchain_experimental.smart_llm.base.SmartLLMChain.html |
8772ccf66326-0 | langchain_experimental.autonomous_agents.hugginggpt.task_planner.BasePlanner¶
class langchain_experimental.autonomous_agents.hugginggpt.task_planner.BasePlanner[source]¶
Bases: BaseModel
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be pa... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.BasePlanner.html |
8772ccf66326-1 | 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/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.BasePlanner.html |
8772ccf66326-2 | abstract plan(inputs: dict, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Plan[source]¶
Given input, decide what to do.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.BasePlanner.html |
59db890fe015-0 | langchain_experimental.autonomous_agents.autogpt.output_parser.preprocess_json_input¶
langchain_experimental.autonomous_agents.autogpt.output_parser.preprocess_json_input(input_str: str) → str[source]¶
Preprocesses a string to be parsed as json.
Replace single backslashes with double backslashes,
while leaving already ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.preprocess_json_input.html |
c4d1866848e4-0 | langchain_experimental.autonomous_agents.autogpt.agent.AutoGPT¶
class langchain_experimental.autonomous_agents.autogpt.agent.AutoGPT(ai_name: str, memory: VectorStoreRetriever, chain: LLMChain, output_parser: BaseAutoGPTOutputParser, tools: List[BaseTool], feedback_tool: Optional[HumanInputRun] = None, chat_history_mem... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.agent.AutoGPT.html |
99e00667ca84-0 | langchain_experimental.autonomous_agents.hugginggpt.hugginggpt.HuggingGPT¶
class langchain_experimental.autonomous_agents.hugginggpt.hugginggpt.HuggingGPT(llm: BaseLanguageModel, tools: List[BaseTool])[source]¶
Methods
__init__(llm, tools)
run(input)
__init__(llm: BaseLanguageModel, tools: List[BaseTool])[source]¶
run(... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.hugginggpt.HuggingGPT.html |
771716d5399f-0 | langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.load_response_generator¶
langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.load_response_generator(llm: BaseLanguageModel) → ResponseGenerator[source]¶ | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.load_response_generator.html |
24f28f75edac-0 | langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain¶
class langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain[source]¶
Bases: LLMChain
Chain to prioritize tasks.
Create a new model by parsing and validating input data from keyword argu... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-1 | param output_parser: BaseLLMOutputParser [Optional]¶
Output parser to use.
Defaults to one that takes the most likely string but does not change it
otherwise.
param prompt: BasePromptTemplate [Required]¶
Prompt object to use.
param return_final_only: bool = True¶
Whether to return only the final parsed result. Defaults... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-2 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
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... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-3 | Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-4 | Generate LLM result from inputs.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-5 | Prepare prompts from inputs.
async arun(*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 and Ch... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-6 | # -> "The temperature in Boise is..."
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, conf... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-7 | Subclasses should override this method if they can batch more efficiently.
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__ fr... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-8 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, verbose: bool = True) → LLMChain[source]¶
Get the response parser.
classmethod from_orm(obj: Any) → Model¶
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶
Create LLMChain from LLM and template.
generate(... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-9 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with e... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-10 | 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, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prepare chain outputs, and save info... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-11 | 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.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-12 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
24f28f75edac-13 | A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
cb4b33b08caf-0 | langchain_experimental.autonomous_agents.hugginggpt.task_executor.Task¶
class langchain_experimental.autonomous_agents.hugginggpt.task_executor.Task(task: str, id: int, dep: List[int], args: Dict, tool: BaseTool)[source]¶
Methods
__init__(task, id, dep, args, tool)
completed()
failed()
pending()
run()
save_product()
__... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_executor.Task.html |
c9af0bcc2575-0 | langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain¶
class langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain[source]¶
Bases: LLMChain
Chain to execute tasks.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationErr... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-1 | param output_parser: BaseLLMOutputParser [Optional]¶
Output parser to use.
Defaults to one that takes the most likely string but does not change it
otherwise.
param prompt: BasePromptTemplate [Required]¶
Prompt object to use.
param return_final_only: bool = True¶
Whether to return only the final parsed result. Defaults... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-2 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
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... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-3 | Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-4 | Generate LLM result from inputs.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-5 | Prepare prompts from inputs.
async arun(*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 and Ch... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-6 | # -> "The temperature in Boise is..."
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, conf... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-7 | Subclasses should override this method if they can batch more efficiently.
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__ fr... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-8 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, demos: List[Dict] = [{'role': 'user', 'content': "please show me a video and an image of (based on the text) 'a boy is running' and dub it"}, {'role': 'assistant', 'content': '[{{"task": "video_generator", "id": 0, "dep": [-1], "a... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-9 | Get the response parser.
classmethod from_orm(obj: Any) → Model¶
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶
Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult¶
Generate LLM result from in... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-10 | to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
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 =... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-11 | Returns
A dictionary of all inputs, including those added by the chain’s memory.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prepare chain outputs, and save info about this run to memory.
Parameters
inputs – Dictionary of chain inputs, ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-12 | 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/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
c9af0bcc2575-13 | 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/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
5ba72e9effff-0 | langchain_experimental.autonomous_agents.autogpt.prompt_generator.get_prompt¶
langchain_experimental.autonomous_agents.autogpt.prompt_generator.get_prompt(tools: List[BaseTool]) → str[source]¶
Generates a prompt string.
It includes various constraints, commands, resources, and performance evaluations.
Returns
The gener... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt_generator.get_prompt.html |
1c53815211de-0 | langchain_experimental.autonomous_agents.hugginggpt.task_planner.Step¶
class langchain_experimental.autonomous_agents.hugginggpt.task_planner.Step(task: str, id: int, dep: List[int], args: Dict[str, str], tool: BaseTool)[source]¶
Methods
__init__(task, id, dep, args, tool)
__init__(task: str, id: int, dep: List[int], a... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.Step.html |
2ef123f5cd49-0 | langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain¶
class langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain[source]¶
Bases: LLMChain
Chain to execute tasks.
Create a new model by parsing and validating input data from keyword arguments.
Raises Validatio... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-1 | Defaults to one that takes the most likely string but does not change it
otherwise.
param prompt: BasePromptTemplate [Required]¶
Prompt object to use.
param return_final_only: bool = True¶
Whether to return only the final parsed result. Defaults to True.
If false, will return a bunch of extra information about the gene... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-2 | callbacks – Callbacks to use for this chain run. These will be called in
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 c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-3 | Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-4 | Generate LLM result from inputs.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-5 | Prepare prompts from inputs.
async arun(*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 and Ch... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-6 | # -> "The temperature in Boise is..."
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, conf... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-7 | Subclasses should override this method if they can batch more efficiently.
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__ fr... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-8 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, verbose: bool = True) → LLMChain[source]¶
Get the response parser.
classmethod from_orm(obj: Any) → Model¶
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶
Create LLMChain from LLM and template.
generate(... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-9 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with e... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-10 | 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, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prepare chain outputs, and save info... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-11 | 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.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-12 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
2ef123f5cd49-13 | A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
77624b4b2fc8-0 | langchain_experimental.autonomous_agents.hugginggpt.task_executor.TaskExecutor¶
class langchain_experimental.autonomous_agents.hugginggpt.task_executor.TaskExecutor(plan: Plan)[source]¶
Load tools to execute tasks.
Methods
__init__(plan)
check_dependency(task)
completed()
describe()
failed()
pending()
run()
update_args... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_executor.TaskExecutor.html |
2791ae9f2ac5-0 | langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTAction¶
class langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTAction(name: str, args: Dict)[source]¶
Action returned by AutoGPTOutputParser.
Create new instance of AutoGPTAction(name, args)
Attributes
args
Alias for field number... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTAction.html |
d147dc5bebbc-0 | langchain_experimental.autonomous_agents.hugginggpt.task_planner.load_chat_planner¶
langchain_experimental.autonomous_agents.hugginggpt.task_planner.load_chat_planner(llm: BaseLanguageModel) → TaskPlanner[source]¶ | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.load_chat_planner.html |
901cab54624e-0 | langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain¶
class langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain[source]¶
Bases: LLMChain
Chain generating tasks.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationErr... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-1 | Defaults to one that takes the most likely string but does not change it
otherwise.
param prompt: BasePromptTemplate [Required]¶
Prompt object to use.
param return_final_only: bool = True¶
Whether to return only the final parsed result. Defaults to True.
If false, will return a bunch of extra information about the gene... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-2 | callbacks – Callbacks to use for this chain run. These will be called in
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 c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-3 | Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-4 | Generate LLM result from inputs.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-5 | Prepare prompts from inputs.
async arun(*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 and Ch... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-6 | # -> "The temperature in Boise is..."
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, conf... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-7 | Subclasses should override this method if they can batch more efficiently.
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__ fr... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-8 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, verbose: bool = True) → LLMChain[source]¶
Get the response parser.
classmethod from_orm(obj: Any) → Model¶
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶
Create LLMChain from LLM and template.
generate(... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-9 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with e... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-10 | 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, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prepare chain outputs, and save info... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-11 | 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.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-12 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
901cab54624e-13 | A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
2bc1670a6e57-0 | langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt¶
class langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt[source]¶
Bases: BaseChatPromptTemplate, BaseModel
Prompt for AutoGPT.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
2bc1670a6e57-1 | 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/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
2bc1670a6e57-2 | 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/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
2bc1670a6e57-3 | :param **kwargs: Keyword arguments to use for formatting.
Returns
PromptValue.
classmethod from_orm(obj: Any) → Model¶
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”, “openai”]
i... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
2bc1670a6e57-4 | 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... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
2bc1670a6e57-5 | 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... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
91b0d9a64af6-0 | langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerator¶
class langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerator(llm_chain: LLMChain, stop: Optional[List] = None)[source]¶
Methods
__init__(llm_chain[, stop])
generate(inputs[, callbacks])
Given inpu... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerator.html |
5302c5564fe4-0 | langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI¶
class langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI[source]¶
Bases: Chain, BaseModel
Controller model for the BabyAGI agent.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.