id stringlengths 14 15 | text stringlengths 49 2.47k | source stringlengths 61 166 |
|---|---|---|
03dab7c1d615-6 | text generation models and BaseMessages for chat models).
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
callbacks – Callbacks to pass through. Used for executing additional
functionality, such as logging or streaming, throughout generation.
**kwarg... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html |
03dab7c1d615-7 | json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html |
03dab7c1d615-8 | to the model provider API call.
Returns
Top model prediction as a string.
predict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶
Pass a message sequence to the model and return a message prediction.
Use this method when passing in chat messages. If you want ... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html |
03dab7c1d615-9 | classmethod validate(value: Any) → Model¶
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.Runnable[~langchain.schema.runnable.Input, ~langchain.schema.runnable.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException]] = (<class 'Exception'>,)) → RunnableWithFallbacks[Input, Out... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html |
2e89ba466a9c-0 | langchain.chat_models.openai.acompletion_with_retry¶
async langchain.chat_models.openai.acompletion_with_retry(llm: ChatOpenAI, run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any) → Any[source]¶
Use tenacity to retry the async completion call. | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.acompletion_with_retry.html |
5d455554fb16-0 | langchain.chat_models.mlflow_ai_gateway.ChatParams¶
class langchain.chat_models.mlflow_ai_gateway.ChatParams[source]¶
Bases: BaseModel
Parameters for the MLflow AI Gateway LLM.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to fo... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.mlflow_ai_gateway.ChatParams.html |
5d455554fb16-1 | 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/chat_models/langchain.chat_models.mlflow_ai_gateway.ChatParams.html |
5d455554fb16-2 | classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.mlflow_ai_gateway.ChatParams.html |
5cb63c49141d-0 | langchain.chat_models.fake.FakeListChatModel¶
class langchain.chat_models.fake.FakeListChatModel[source]¶
Bases: SimpleChatModel
Fake ChatModel for testing purposes.
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 ... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
5cb63c49141d-1 | Top Level call
async agenerate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → LLMResult¶
Asynchronously pass a sequence of prompts and return model generations.
This method should make use of batche... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
5cb63c49141d-2 | Use this method when calling pure text generation models and only the topcandidate generation is needed.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
**kwargs – Arbitrary additional keyword argu... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
5cb63c49141d-3 | 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/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
5cb63c49141d-4 | This method should make use of batched calls for models that expose a batched
API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion ... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
5cb63c49141d-5 | Parameters
text – The string input to tokenize.
Returns
A list of ids corresponding to the tokens in the text, in order they occurin the text.
invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessageChunk¶
json(*... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
5cb63c49141d-6 | Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a string.... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
5cb63c49141d-7 | classmethod validate(value: Any) → Model¶
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.Runnable[~langchain.schema.runnable.Input, ~langchain.schema.runnable.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException]] = (<class 'Exception'>,)) → RunnableWithFallbacks[Input, Out... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeListChatModel.html |
ec5bf7857fac-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 |
e4bb4368e913-0 | 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 |
e26cff0dc76c-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 |
e26cff0dc76c-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 |
e26cff0dc76c-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 |
d71514a838f6-0 | 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 |
d71514a838f6-1 | 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 |
d71514a838f6-2 | 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 |
091336c085a8-0 | 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 |
091336c085a8-1 | 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_creation.TaskCreationChain.html |
091336c085a8-2 | 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 |
091336c085a8-3 | 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, only new keys generated by this chai... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
091336c085a8-4 | Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → Sequence[Union[str, List[str], Dict[str, str]]]¶
Call apply and then parse the results.
async apredict(callbacks: Optional[Union[List[Ba... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
091336c085a8-5 | 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 calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
additi... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
091336c085a8-6 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
091336c085a8-7 | Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult¶
Generate LLM result from inputs.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None) → Dict[str, Any]¶
json(*, include: Optional[Union[AbstractSetIn... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
091336c085a8-8 | Returns
Completion from LLM.
Example
completion = llm.predict(adjective="funny")
predict_and_parse(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Union[str, List[str], Dict[str, Any]]¶
Call predict and then parse the results.
prep_inputs(inputs: Union[Dict[str, Any],... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
091336c085a8-9 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
091336c085a8-10 | Example
chain.save(file_path="path/chain.yaml")
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¶
stream(input: Input, config: Optiona... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
7ccd0e5342e2-0 | 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 |
7ccd0e5342e2-1 | 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 |
7ccd0e5342e2-2 | 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¶
save_context(inputs: Dict[str, Any], outputs: Dict[str, str]) → None¶
Save context from this conversation to buff... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory.html |
5ece60f04e3b-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 |
ba42acbd47e2-0 | 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 |
ba42acbd47e2-1 | Bind arguments to a Runnable, returning a new Runnable.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
ba42acbd47e2-2 | json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
ba42acbd47e2-3 | Parse the output of an LLM call with the input prompt for context.
The prompt is largely provided in the event the OutputParser wants
to retry or fix the output in some way, and needs information from
the prompt to do so.
Parameters
completion – String output of a language model.
prompt – Input PromptValue.
Returns
Str... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
ba42acbd47e2-4 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
e789a1f09c55-0 | 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 |
041c953c6f1a-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 |
041c953c6f1a-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 |
041c953c6f1a-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.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-3 | 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, only new keys generated by this chai... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-4 | Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → Sequence[Union[str, List[str], Dict[str, str]]]¶
Call apply and then parse the results.
async apredict(callbacks: Optional[Union[List[Ba... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-5 | 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 calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
additi... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-6 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-7 | Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult¶
Generate LLM result from inputs.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None) → Dict[str, Any]¶
json(*, include: Optional[Union[AbstractSetIn... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-8 | Returns
Completion from LLM.
Example
completion = llm.predict(adjective="funny")
predict_and_parse(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Union[str, List[str], Dict[str, Any]]¶
Call predict and then parse the results.
prep_inputs(inputs: Union[Dict[str, Any],... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-9 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
041c953c6f1a-10 | Example
chain.save(file_path="path/chain.yaml")
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¶
stream(input: Input, config: Optiona... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain.html |
2d81ebe7bf0d-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 |
b154cd5276a0-0 | 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 |
b154cd5276a0-1 | 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 |
b154cd5276a0-2 | 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_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-3 | 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, only new keys generated by this chai... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-4 | Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → Sequence[Union[str, List[str], Dict[str, str]]]¶
Call apply and then parse the results.
async apredict(callbacks: Optional[Union[List[Ba... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-5 | 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 calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
additi... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-6 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-7 | Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult¶
Generate LLM result from inputs.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None) → Dict[str, Any]¶
json(*, include: Optional[Union[AbstractSetIn... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-8 | Returns
Completion from LLM.
Example
completion = llm.predict(adjective="funny")
predict_and_parse(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Union[str, List[str], Dict[str, Any]]¶
Call predict and then parse the results.
prep_inputs(inputs: Union[Dict[str, Any],... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-9 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
b154cd5276a0-10 | Example
chain.save(file_path="path/chain.yaml")
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¶
stream(input: Input, config: Optiona... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain.html |
068e69d54747-0 | 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 |
068e69d54747-1 | 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_execution.TaskExecutionChain.html |
068e69d54747-2 | 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 |
068e69d54747-3 | 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, only new keys generated by this chai... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
068e69d54747-4 | Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → Sequence[Union[str, List[str], Dict[str, str]]]¶
Call apply and then parse the results.
async apredict(callbacks: Optional[Union[List[Ba... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
068e69d54747-5 | 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 calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
additi... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
068e69d54747-6 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
068e69d54747-7 | Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult¶
Generate LLM result from inputs.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None) → Dict[str, Any]¶
json(*, include: Optional[Union[AbstractSetIn... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
068e69d54747-8 | Returns
Completion from LLM.
Example
completion = llm.predict(adjective="funny")
predict_and_parse(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Union[str, List[str], Dict[str, Any]]¶
Call predict and then parse the results.
prep_inputs(inputs: Union[Dict[str, Any],... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
068e69d54747-9 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
068e69d54747-10 | Example
chain.save(file_path="path/chain.yaml")
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¶
stream(input: Input, config: Optiona... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
7209a95522c5-0 | 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 |
7209a95522c5-1 | Bind arguments to a Runnable, returning a new Runnable.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
7209a95522c5-2 | :param **kwargs: Keyword arguments to use for formatting.
Returns
PromptValue.
classmethod from_orm(obj: Any) → Model¶
invoke(input: Dict, config: langchain.schema.runnable.RunnableConfig | None = None) → PromptValue¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
7209a95522c5-3 | Example:
.. code-block:: python
prompt.save(file_path=”path/prompt.yaml”)
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¶
stream(inp... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
27043d01985f-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 |
546547029102-0 | 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 |
a44f67f7a91f-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 |
a44f67f7a91f-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 |
a44f67f7a91f-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.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-3 | 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, only new keys generated by this chai... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-4 | Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → Sequence[Union[str, List[str], Dict[str, str]]]¶
Call apply and then parse the results.
async apredict(callbacks: Optional[Union[List[Ba... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-5 | 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 calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
additi... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-6 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-7 | # -> {“_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], "arg... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-8 | 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 |
a44f67f7a91f-9 | Format prompt with kwargs and pass to LLM.
Parameters
callbacks – Callbacks to pass to LLMChain
**kwargs – Keys to pass to prompt template.
Returns
Completion from LLM.
Example
completion = llm.predict(adjective="funny")
predict_and_parse(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-10 | Prepare prompts from inputs.
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.__c... | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-11 | 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.hugginggpt.task_planner.TaskPlaningChain.html |
a44f67f7a91f-12 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/autonomous_agents/langchain_experimental.autonomous_agents.hugginggpt.task_planner.TaskPlaningChain.html |
b62506395220-0 | 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 |
f43360e90592-0 | 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 |
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