id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
5302c5564fe4-1 | Optional list of tags associated with the chain. Defaults to None.
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 task_creation_chain: langchain.chains.base... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-2 | addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-3 | 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.baby_agi.BabyAGI.html |
5302c5564fe4-4 | with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as the
sole positional argument.
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 call... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-5 | 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[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-6 | 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/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-7 | Initialize the BabyAGI Controller.
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_next_task(result: str, task_description: ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-8 | 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.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-9 | Prioritize tasks.
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 and Chain.__call__ is th... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-10 | 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.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
5302c5564fe4-11 | 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/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
e65e771e6ee5-0 | langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlanner¶
class langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlanner[source]¶
Bases: BasePlanner
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlanner.html |
e65e771e6ee5-1 | 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(*, 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/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlanner.html |
e65e771e6ee5-2 | plan(inputs: dict, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Plan[source]¶
Given input, decided what to do.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True,... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlanner.html |
e7444ef2f832-0 | langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser¶
class langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser[source]¶
Bases: BaseOutputParser
Base Output parser for AutoGPT.
Create a new model by parsing and validating input data from keyword argum... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
e7444ef2f832-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
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 str... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
e7444ef2f832-2 | Default implementation of batch, which calls invoke N times.
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) → Mode... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
e7444ef2f832-3 | namespace is [“langchain”, “llms”, “openai”]
invoke(input: Union[str, BaseMessage], config: Optional[RunnableConfig] = None) → T¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
e7444ef2f832-4 | 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¶
parse_result(result: List[Generation], *, partial: bool = False) → T¶
Parse a list of candidate model Generations... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
e7444ef2f832-5 | 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.autogpt.output_parser.BaseAutoGPTOutputParser.html |
e7444ef2f832-6 | 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.autogpt.output_parser.BaseAutoGPTOutputParser.html |
ed66f4656f05-0 | langchain_experimental.autonomous_agents.autogpt.prompt_generator.PromptGenerator¶
class langchain_experimental.autonomous_agents.autogpt.prompt_generator.PromptGenerator[source]¶
A class for generating custom prompt strings.
Does this based on constraints, commands, resources, and performance evaluations.
Initialize t... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt_generator.PromptGenerator.html |
46852330b1ea-0 | langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain¶
class langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain[source]¶
Bases: LLMChain
Chain to execute tasks.
Create a new model by parsing and validating input data from keyword argum... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-8 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, verbose: bool = True) → LLMChain[source]¶
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... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-9 | 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 each input.
classmethod parse_file... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-10 | 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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-11 | 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.repsonse_generator.ResponseGenerationChain.html |
46852330b1ea-12 | 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.repsonse_generator.ResponseGenerationChain.html |
82367659dee7-0 | langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser¶
class langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser[source]¶
Bases: BaseAutoGPTOutputParser
Output parser for AutoGPT.
Create a new model by parsing and validating input data from keyword arguments.
... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser.html |
82367659dee7-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
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 str... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser.html |
82367659dee7-2 | Default implementation of batch, which calls invoke N times.
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) → Mode... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser.html |
82367659dee7-3 | namespace is [“langchain”, “llms”, “openai”]
invoke(input: Union[str, BaseMessage], config: Optional[RunnableConfig] = None) → T¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser.html |
82367659dee7-4 | 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¶
parse_result(result: List[Generation], *, partial: bool = False) → T¶
Parse a list of candidate model Generations... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser.html |
82367659dee7-5 | 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.autogpt.output_parser.AutoGPTOutputParser.html |
82367659dee7-6 | 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.autogpt.output_parser.AutoGPTOutputParser.html |
824b2cd136f4-0 | langchain_experimental.autonomous_agents.hugginggpt.task_planner.PlanningOutputParser¶
class langchain_experimental.autonomous_agents.hugginggpt.task_planner.PlanningOutputParser[source]¶
Bases: BaseModel
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.PlanningOutputParser.html |
824b2cd136f4-1 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False,... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.PlanningOutputParser.html |
9d4d09425e86-0 | langchain_experimental.autonomous_agents.hugginggpt.task_planner.Plan¶
class langchain_experimental.autonomous_agents.hugginggpt.task_planner.Plan(steps: List[Step])[source]¶
Methods
__init__(steps)
__init__(steps: List[Step])[source]¶ | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.Plan.html |
6e34aab7ecb9-0 | langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory¶
class langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory[source]¶
Bases: BaseChatMemory
Memory for AutoGPT.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory.html |
6e34aab7ecb9-1 | 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.autogpt.memory.AutoGPTMemory.html |
6e34aab7ecb9-2 | The unique identifier is a list of strings that describes the path
to the object.
load_memory_variables(inputs: Dict[str, Any]) → Dict[str, Any][source]¶
Return key-value pairs given the text input to the chain.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', ... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory.html |
caca62d909f2-0 | langchain.load.load.loads¶
langchain.load.load.loads(text: str, *, secrets_map: Optional[Dict[str, str]] = None, valid_namespaces: Optional[List[str]] = None) → Any[source]¶
Revive a LangChain class from a JSON string.
Equivalent to load(json.loads(text)).
Parameters
text – The string to load.
secrets_map – A map of se... | https://api.python.langchain.com/en/latest/load/langchain.load.load.loads.html |
df90ada0c795-0 | langchain.load.serializable.SerializedSecret¶
class langchain.load.serializable.SerializedSecret[source]¶
Serialized secret.
lc: int¶
id: List[str]¶
type: Literal['secret']¶ | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.SerializedSecret.html |
184561f4db70-0 | langchain.load.dump.dumpd¶
langchain.load.dump.dumpd(obj: Any) → Dict[str, Any][source]¶
Return a json dict representation of an object. | https://api.python.langchain.com/en/latest/load/langchain.load.dump.dumpd.html |
21d5236fc8d7-0 | langchain.load.serializable.BaseSerialized¶
class langchain.load.serializable.BaseSerialized[source]¶
Base class for serialized objects.
lc: int¶
id: List[str]¶ | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.BaseSerialized.html |
aa8acde6a0de-0 | langchain.load.serializable.SerializedConstructor¶
class langchain.load.serializable.SerializedConstructor[source]¶
Serialized constructor.
lc: int¶
id: List[str]¶
type: Literal['constructor']¶
kwargs: Dict[str, Any]¶ | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.SerializedConstructor.html |
42b492e763d4-0 | langchain.load.serializable.SerializedNotImplemented¶
class langchain.load.serializable.SerializedNotImplemented[source]¶
Serialized not implemented.
lc: int¶
id: List[str]¶
type: Literal['not_implemented']¶
repr: Optional[str]¶ | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.SerializedNotImplemented.html |
08abe632163e-0 | langchain.load.serializable.Serializable¶
class langchain.load.serializable.Serializable[source]¶
Bases: BaseModel, ABC
Serializable base 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.
classmethod co... | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.Serializable.html |
08abe632163e-1 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
classmethod get_lc_namespace() → List[str][source]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespac... | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.Serializable.html |
08abe632163e-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¶
to_json() → Union[SerializedConstructor, SerializedNotImplemented][source]¶
to_json_... | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.Serializable.html |
fb604054c489-0 | langchain.load.dump.default¶
langchain.load.dump.default(obj: Any) → Any[source]¶
Return a default value for a Serializable object or
a SerializedNotImplemented object. | https://api.python.langchain.com/en/latest/load/langchain.load.dump.default.html |
96732a272efd-0 | langchain.load.serializable.to_json_not_implemented¶
langchain.load.serializable.to_json_not_implemented(obj: object) → SerializedNotImplemented[source]¶
Serialize a “not implemented” object.
Parameters
obj – object to serialize
Returns
SerializedNotImplemented | https://api.python.langchain.com/en/latest/load/langchain.load.serializable.to_json_not_implemented.html |
64a6fe4ca917-0 | langchain.load.dump.dumps¶
langchain.load.dump.dumps(obj: Any, *, pretty: bool = False) → str[source]¶
Return a json string representation of an object. | https://api.python.langchain.com/en/latest/load/langchain.load.dump.dumps.html |
48cf6ce30510-0 | langchain.load.load.Reviver¶
class langchain.load.load.Reviver(secrets_map: Optional[Dict[str, str]] = None, valid_namespaces: Optional[List[str]] = None)[source]¶
Reviver for JSON objects.
Methods
__init__([secrets_map, valid_namespaces])
__init__(secrets_map: Optional[Dict[str, str]] = None, valid_namespaces: Optiona... | https://api.python.langchain.com/en/latest/load/langchain.load.load.Reviver.html |
eb737e543608-0 | langchain.load.load.load¶
langchain.load.load.load(obj: Any, *, secrets_map: Optional[Dict[str, str]] = None, valid_namespaces: Optional[List[str]] = None) → Any[source]¶
Revive a LangChain class from a JSON object. Use this if you already
have a parsed JSON object, eg. from json.load or orjson.loads.
Parameters
obj – ... | https://api.python.langchain.com/en/latest/load/langchain.load.load.load.html |
c7d1f9dd141b-0 | langchain_experimental.pal_chain.base.PALChain¶
class langchain_experimental.pal_chain.base.PALChain[source]¶
Bases: Chain
Implements Program-Aided Language Models (PAL).
This class implements the Program-Aided Language Models (PAL) for generating code
solutions. PAL is a technique described in the paper “Program-Aided... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-1 | param llm_chain: LLMChain [Required]¶
param memory: Optional[BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called at the start
and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-2 | will be printed to the console. Defaults to langchain.verbose value.
__call__(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, run_name... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-3 | Default implementation of abatch, which calls ainvoke N times.
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: Optiona... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-4 | 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, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Call the chain on all inputs i... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-5 | # 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 Boise is..."
async astream(input: Inp... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-6 | 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 of batch, which calls invoke N times.
Subclasses should override this method if they can ba... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-7 | **kwargs – Keyword arguments passed to default pydantic.BaseModel.dict
method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_colored_object_prompt(llm: BaseLanguageModel, **kwargs: Any) → PALChain[source]¶
Load PAL ... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-8 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-9 | Parameters
inputs – Dictionary of raw inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
Returns
A dictionary of all inputs, including those added by the chain’s memory.
prep_outputs(inputs: Dict[str,... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-10 | 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/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-11 | 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/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
c7d1f9dd141b-12 | For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html |
423ade11a507-0 | langchain_experimental.pal_chain.base.PALValidation¶
class langchain_experimental.pal_chain.base.PALValidation(solution_expression_name: Optional[str] = None, solution_expression_type: Optional[type] = None, allow_imports: bool = False, allow_command_exec: bool = False)[source]¶
Initialize a PALValidation instance.
Par... | https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALValidation.html |
57b72a3cbcf9-0 | langchain.indexes.vectorstore.VectorStoreIndexWrapper¶
class langchain.indexes.vectorstore.VectorStoreIndexWrapper[source]¶
Bases: BaseModel
Wrapper around a vectorstore for easy access.
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/indexes/langchain.indexes.vectorstore.VectorStoreIndexWrapper.html |
57b72a3cbcf9-1 | 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/indexes/langchain.indexes.vectorstore.VectorStoreIndexWrapper.html |
57b72a3cbcf9-2 | query(question: str, llm: Optional[BaseLanguageModel] = None, retriever_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Any) → str[source]¶
Query the vectorstore.
query_with_sources(question: str, llm: Optional[BaseLanguageModel] = None, retriever_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Any) → dict[source... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.vectorstore.VectorStoreIndexWrapper.html |
93bc5da7c1e5-0 | langchain.indexes.vectorstore.VectorstoreIndexCreator¶
class langchain.indexes.vectorstore.VectorstoreIndexCreator[source]¶
Bases: BaseModel
Logic for creating indexes.
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 val... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.vectorstore.VectorstoreIndexCreator.html |
93bc5da7c1e5-1 | 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/indexes/langchain.indexes.vectorstore.VectorstoreIndexCreator.html |
93bc5da7c1e5-2 | 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/indexes/langchain.indexes.vectorstore.VectorstoreIndexCreator.html |
5c9543e8fe0c-0 | langchain.indexes.base.RecordManager¶
class langchain.indexes.base.RecordManager(namespace: str)[source]¶
An abstract base class representing the interface for a record manager.
Initialize the record manager.
Parameters
namespace (str) – The namespace for the record manager.
Methods
__init__(namespace)
Initialize the r... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.base.RecordManager.html |
5c9543e8fe0c-1 | Returns
The current server time as a float timestamp.
abstract list_keys(*, before: Optional[float] = None, after: Optional[float] = None, group_ids: Optional[Sequence[str]] = None, limit: Optional[int] = None) → List[str][source]¶
List records in the database based on the provided filters.
Parameters
before – Filter t... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.base.RecordManager.html |
92b5ce8b0e2a-0 | langchain.indexes.graph.GraphIndexCreator¶
class langchain.indexes.graph.GraphIndexCreator[source]¶
Bases: BaseModel
Functionality to create graph index.
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... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.graph.GraphIndexCreator.html |
92b5ce8b0e2a-1 | param llm: Optional[langchain.schema.language_model.BaseLanguageModel] = None¶
async afrom_text(text: str, prompt: BasePromptTemplate = PromptTemplate(input_variables=['text'], template="You are a networked intelligence helping a human track knowledge triples about all relevant people, things, concepts, etc. and integr... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.graph.GraphIndexCreator.html |
92b5ce8b0e2a-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/indexes/langchain.indexes.graph.GraphIndexCreator.html |
92b5ce8b0e2a-3 | classmethod from_orm(obj: Any) → Model¶
from_text(text: str, prompt: BasePromptTemplate = PromptTemplate(input_variables=['text'], template="You are a networked intelligence helping a human track knowledge triples about all relevant people, things, concepts, etc. and integrating them with your knowledge stored within y... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.graph.GraphIndexCreator.html |
92b5ce8b0e2a-4 | Create graph index from text.
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 ... | https://api.python.langchain.com/en/latest/indexes/langchain.indexes.graph.GraphIndexCreator.html |
c8d638a186f8-0 | langchain.memory.chat_message_histories.sql.SQLChatMessageHistory¶
class langchain.memory.chat_message_histories.sql.SQLChatMessageHistory(session_id: str, connection_string: str, table_name: str = 'message_store', session_id_field_name: str = 'session_id', custom_message_converter: Optional[BaseMessageConverter] = Non... | https://api.python.langchain.com/en/latest/memory/langchain.memory.chat_message_histories.sql.SQLChatMessageHistory.html |
4ac1d2c8a5d4-0 | langchain.memory.chat_message_histories.xata.XataChatMessageHistory¶
class langchain.memory.chat_message_histories.xata.XataChatMessageHistory(session_id: str, db_url: str, api_key: str, branch_name: str = 'main', table_name: str = 'messages', create_table: bool = True)[source]¶
Chat message history stored in a Xata da... | https://api.python.langchain.com/en/latest/memory/langchain.memory.chat_message_histories.xata.XataChatMessageHistory.html |
e85c23bfe0fb-0 | langchain.memory.entity.BaseEntityStore¶
class langchain.memory.entity.BaseEntityStore[source]¶
Bases: BaseModel, ABC
Abstract base class for Entity store.
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.
abs... | https://api.python.langchain.com/en/latest/memory/langchain.memory.entity.BaseEntityStore.html |
e85c23bfe0fb-1 | abstract delete(key: str) → None[source]¶
Delete entity value from store.
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, exclude... | https://api.python.langchain.com/en/latest/memory/langchain.memory.entity.BaseEntityStore.html |
e85c23bfe0fb-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/memory/langchain.memory.entity.BaseEntityStore.html |
1b12af95b3c7-0 | langchain.memory.buffer_window.ConversationBufferWindowMemory¶
class langchain.memory.buffer_window.ConversationBufferWindowMemory[source]¶
Bases: BaseChatMemory
Buffer for storing conversation memory inside a limited size window.
Create a new model by parsing and validating input data from keyword arguments.
Raises Va... | https://api.python.langchain.com/en/latest/memory/langchain.memory.buffer_window.ConversationBufferWindowMemory.html |
1b12af95b3c7-1 | 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/memory/langchain.memory.buffer_window.ConversationBufferWindowMemory.html |
1b12af95b3c7-2 | The unique identifier is a list of strings that describes the path
to the object.
load_memory_variables(inputs: Dict[str, Any]) → Dict[str, Any][source]¶
Return history buffer.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickl... | https://api.python.langchain.com/en/latest/memory/langchain.memory.buffer_window.ConversationBufferWindowMemory.html |
1b12af95b3c7-3 | 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”}
Examples using ConversationBufferWindowMemory¶
Figma
Op... | https://api.python.langchain.com/en/latest/memory/langchain.memory.buffer_window.ConversationBufferWindowMemory.html |
a76e3cc5c1f7-0 | langchain.memory.summary.ConversationSummaryMemory¶
class langchain.memory.summary.ConversationSummaryMemory[source]¶
Bases: BaseChatMemory, SummarizerMixin
Conversation summarizer to chat memory.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data ca... | https://api.python.langchain.com/en/latest/memory/langchain.memory.summary.ConversationSummaryMemory.html |
a76e3cc5c1f7-1 | 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/memory/langchain.memory.summary.ConversationSummaryMemory.html |
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