id stringlengths 14 15 | text stringlengths 35 2.51k | source stringlengths 61 154 |
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927a88a8937f-0 | langchain.experimental.autonomous_agents.autogpt.output_parser.AutoGPTAction¶
class langchain.experimental.autonomous_agents.autogpt.output_parser.AutoGPTAction(name, args)[source]¶
Bases: NamedTuple
Create new instance of AutoGPTAction(name, args)
Methods
__init__()
count(value, /)
Return number of occurrences of valu... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.output_parser.AutoGPTAction.html |
6580bfa076e6-0 | langchain.experimental.plan_and_execute.schema.Step¶
class langchain.experimental.plan_and_execute.schema.Step(*, value: str)[source]¶
Bases: BaseModel
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 v... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.plan_and_execute.schema.Step.html |
3b427c7259b1-0 | langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain¶
class langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
3b427c7259b1-1 | There are many different types of memory - please see memory docs
for the full catalog.
param output_key: str = 'text'¶
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 [Require... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
3b427c7259b1-2 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to include run info in the response. Defaults
to False.
async aapply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[Base... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
3b427c7259b1-3 | Generate LLM result from inputs.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallba... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
3b427c7259b1-4 | Create outputs from response.
dict(**kwargs: Any) → Dict¶
Return dictionary representation of chain.
classmethod from_llm(llm: BaseLanguageModel, verbose: bool = True) → LLMChain[source]¶
Get the response parser.
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶
Create LLMChain from LLM and tem... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
3b427c7259b1-5 | Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, **kwargs: Any) → str¶
Run the chain as text in, text out or multiple variables, text out.
save(file_path: Union[Path, str]) → None¶
... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_creation.TaskCreationChain.html |
10546f797014-0 | langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain¶
class langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Opti... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
10546f797014-1 | There are many different types of memory - please see memory docs
for the full catalog.
param output_key: str = 'text'¶
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 [Require... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
10546f797014-2 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to include run info in the response. Defaults
to False.
async aapply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[Base... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
10546f797014-3 | Generate LLM result from inputs.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallba... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
10546f797014-4 | Create outputs from response.
dict(**kwargs: Any) → Dict¶
Return dictionary representation of chain.
classmethod from_llm(llm: BaseLanguageModel, verbose: bool = True) → LLMChain[source]¶
Get the response parser.
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶
Create LLMChain from LLM and tem... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
10546f797014-5 | Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, **kwargs: Any) → str¶
Run the chain as text in, text out or multiple variables, text out.
save(file_path: Union[Path, str]) → None¶
... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.task_execution.TaskExecutionChain.html |
084e9893b2a9-0 | langchain.experimental.llms.rellm_decoder.RELLM¶
class langchain.experimental.llms.rellm_decoder.RELLM(*, cache: Optional[bool] = None, verbose: bool = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, tags: Optional[List[str... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.rellm_decoder.RELLM.html |
084e9893b2a9-1 | Check Cache and run the LLM on the given prompt and input.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → LLMResult¶
Run the LLM on the given prompt and input.
... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.rellm_decoder.RELLM.html |
084e9893b2a9-2 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → LLMResult¶
Take in a list of prompt values and return an LLMResult.
get_num_tokens(text: str) → int... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.rellm_decoder.RELLM.html |
084e9893b2a9-3 | constructor.
property lc_namespace: List[str]¶
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]¶
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 t... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.rellm_decoder.RELLM.html |
84aaffdf5197-0 | langchain.experimental.plan_and_execute.schema.PlanOutputParser¶
class langchain.experimental.plan_and_execute.schema.PlanOutputParser[source]¶
Bases: BaseOutputParser
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a vali... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.plan_and_execute.schema.PlanOutputParser.html |
b692c16784e0-0 | langchain.experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser¶
class langchain.experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser[source]¶
Bases: BaseOutputParser
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if ... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
b692c16784e0-1 | property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
extra = 'ignore'¶ | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.output_parser.BaseAutoGPTOutputParser.html |
9b1194f2bd29-0 | langchain.experimental.plan_and_execute.planners.base.LLMPlanner¶
class langchain.experimental.plan_and_execute.planners.base.LLMPlanner(*, llm_chain: LLMChain, output_parser: PlanOutputParser, stop: Optional[List] = None)[source]¶
Bases: BasePlanner
Create a new model by parsing and validating input data from keyword ... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.plan_and_execute.planners.base.LLMPlanner.html |
671210717557-0 | langchain.experimental.generative_agents.generative_agent.GenerativeAgent¶
class langchain.experimental.generative_agents.generative_agent.GenerativeAgent(*, name: str, age: Optional[int] = None, traits: str = 'N/A', status: str, memory: GenerativeAgentMemory, llm: BaseLanguageModel, verbose: bool = False, summary: str... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.generative_agents.generative_agent.GenerativeAgent.html |
671210717557-1 | Permanent traits to ascribe to the character.
param verbose: bool = False¶
chain(prompt: PromptTemplate) → LLMChain[source]¶
generate_dialogue_response(observation: str, now: Optional[datetime] = None) → Tuple[bool, str][source]¶
React to a given observation.
generate_reaction(observation: str, now: Optional[datetime] ... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.generative_agents.generative_agent.GenerativeAgent.html |
44ac4d809d21-0 | langchain.experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser¶
class langchain.experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser[source]¶
Bases: BaseAutoGPTOutputParser
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if t... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser.html |
44ac4d809d21-1 | property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
extra = 'ignore'¶ | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.output_parser.AutoGPTOutputParser.html |
831e625db8dd-0 | langchain.experimental.llms.jsonformer_decoder.JsonFormer¶
class langchain.experimental.llms.jsonformer_decoder.JsonFormer(*, cache: Optional[bool] = None, verbose: bool = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, tag... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.jsonformer_decoder.JsonFormer.html |
831e625db8dd-1 | param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → str¶
Check Cache and run the LLM on the given prompt and input.
async agenerate(prompts: List[st... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.jsonformer_decoder.JsonFormer.html |
831e625db8dd-2 | Construct the pipeline object from model_id and task.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → LLMResult¶
Run the LLM on the given prompt and input.
generate_pro... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.jsonformer_decoder.JsonFormer.html |
831e625db8dd-3 | This allows users to pass in None as verbose to access the global setting.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
property lc_attributes: Dict¶
Return a list of attribute names that should be included in the
serialized kwargs. These attr... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.jsonformer_decoder.JsonFormer.html |
1400d4ecb3d6-0 | langchain.experimental.autonomous_agents.autogpt.prompt_generator.get_prompt¶
langchain.experimental.autonomous_agents.autogpt.prompt_generator.get_prompt(tools: List[BaseTool]) → str[source]¶
This function generates a prompt string.
It includes various constraints, commands, resources, and performance evaluations.
Ret... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.prompt_generator.get_prompt.html |
4cddf6888d78-0 | langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI¶
class langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, ... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
4cddf6888d78-1 | There are many different types of memory - please see memory docs
for the full catalog.
param tags: Optional[List[str]] = None¶
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 ... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
4cddf6888d78-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
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, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
4cddf6888d78-3 | Execute a task.
classmethod from_llm(llm: BaseLanguageModel, vectorstore: VectorStore, verbose: bool = False, task_execution_chain: Optional[Chain] = None, **kwargs: Dict[str, Any]) → BabyAGI[source]¶
Initialize the BabyAGI Controller.
get_next_task(result: str, task_description: str, objective: str) → List[Dict][sourc... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
4cddf6888d78-4 | This allows users to pass in None as verbose to access the global setting.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
property input_keys: List[str]¶
Input keys this chain expects.
property lc_attributes: Dict¶
Return a list of attribute nam... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI.html |
4fe62f0bb946-0 | langchain.experimental.plan_and_execute.executors.base.ChainExecutor¶
class langchain.experimental.plan_and_execute.executors.base.ChainExecutor(*, chain: Chain)[source]¶
Bases: BaseExecutor
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot b... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.plan_and_execute.executors.base.ChainExecutor.html |
780edbba953b-0 | langchain.experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt¶
class langchain.experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt(*, input_variables: List[str], output_parser: Optional[BaseOutputParser] = None, partial_variables: Mapping[str, Union[str, Callable[[], str]]] = None, ai_name: str, ai_role... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
780edbba953b-1 | Format kwargs into a list of messages.
format_prompt(**kwargs: Any) → PromptValue¶
Create Chat Messages.
partial(**kwargs: Union[str, Callable[[], str]]) → BasePromptTemplate¶
Return a partial of the prompt template.
save(file_path: Union[Path, str]) → None¶
Save the prompt.
Parameters
file_path – Path to directory to ... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.autonomous_agents.autogpt.prompt.AutoGPTPrompt.html |
7132b8c349c9-0 | langchain.experimental.llms.rellm_decoder.import_rellm¶
langchain.experimental.llms.rellm_decoder.import_rellm() → rellm[source]¶
Lazily import rellm. | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.llms.rellm_decoder.import_rellm.html |
abea71de3fe9-0 | langchain.experimental.plan_and_execute.planners.chat_planner.load_chat_planner¶
langchain.experimental.plan_and_execute.planners.chat_planner.load_chat_planner(llm: BaseLanguageModel, system_prompt: str = "Let's first understand the problem and devise a plan to solve the problem. Please output the plan starting with t... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.plan_and_execute.planners.chat_planner.load_chat_planner.html |
bb8421ceddbe-0 | langchain.experimental.plan_and_execute.schema.Plan¶
class langchain.experimental.plan_and_execute.schema.Plan(*, steps: List[Step])[source]¶
Bases: BaseModel
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.
... | https://api.python.langchain.com/en/latest/experimental/langchain.experimental.plan_and_execute.schema.Plan.html |
973196172085-0 | langchain.cache.SQLiteCache¶
class langchain.cache.SQLiteCache(database_path: str = '.langchain.db')[source]¶
Bases: SQLAlchemyCache
Cache that uses SQLite as a backend.
Initialize by creating the engine and all tables.
Methods
__init__([database_path])
Initialize by creating the engine and all tables.
clear(**kwargs)
... | https://api.python.langchain.com/en/latest/cache/langchain.cache.SQLiteCache.html |
4dc7992557df-0 | langchain.cache.BaseCache¶
class langchain.cache.BaseCache[source]¶
Bases: ABC
Base interface for cache.
Methods
__init__()
clear(**kwargs)
Clear cache that can take additional keyword arguments.
lookup(prompt, llm_string)
Look up based on prompt and llm_string.
update(prompt, llm_string, return_val)
Update cache based... | https://api.python.langchain.com/en/latest/cache/langchain.cache.BaseCache.html |
749781a81e8f-0 | langchain.cache.RedisCache¶
class langchain.cache.RedisCache(redis_: Any)[source]¶
Bases: BaseCache
Cache that uses Redis as a backend.
Initialize by passing in Redis instance.
Methods
__init__(redis_)
Initialize by passing in Redis instance.
clear(**kwargs)
Clear cache.
lookup(prompt, llm_string)
Look up based on prom... | https://api.python.langchain.com/en/latest/cache/langchain.cache.RedisCache.html |
1618c09e37fc-0 | langchain.cache.InMemoryCache¶
class langchain.cache.InMemoryCache[source]¶
Bases: BaseCache
Cache that stores things in memory.
Initialize with empty cache.
Methods
__init__()
Initialize with empty cache.
clear(**kwargs)
Clear cache.
lookup(prompt, llm_string)
Look up based on prompt and llm_string.
update(prompt, llm... | https://api.python.langchain.com/en/latest/cache/langchain.cache.InMemoryCache.html |
c6ee11fb34fe-0 | langchain.cache.GPTCache¶
class langchain.cache.GPTCache(init_func: Optional[Union[Callable[[Any, str], None], Callable[[Any], None]]] = None)[source]¶
Bases: BaseCache
Cache that uses GPTCache as a backend.
Initialize by passing in init function (default: None).
Parameters
init_func (Optional[Callable[[Any], None]]) –... | https://api.python.langchain.com/en/latest/cache/langchain.cache.GPTCache.html |
c6ee11fb34fe-1 | Update cache.
First, retrieve the corresponding cache object using the llm_string parameter,
and then store the prompt and return_val in the cache object. | https://api.python.langchain.com/en/latest/cache/langchain.cache.GPTCache.html |
b7c75081d3b5-0 | langchain.cache.RedisSemanticCache¶
class langchain.cache.RedisSemanticCache(redis_url: str, embedding: Embeddings, score_threshold: float = 0.2)[source]¶
Bases: BaseCache
Cache that uses Redis as a vector-store backend.
Initialize by passing in the init GPTCache func
Parameters
redis_url (str) – URL to connect to Redi... | https://api.python.langchain.com/en/latest/cache/langchain.cache.RedisSemanticCache.html |
4fbf0feadf7e-0 | langchain.cache.SQLAlchemyCache¶
class langchain.cache.SQLAlchemyCache(engine: ~sqlalchemy.engine.base.Engine, cache_schema: ~typing.Type[~langchain.cache.FullLLMCache] = <class 'langchain.cache.FullLLMCache'>)[source]¶
Bases: BaseCache
Cache that uses SQAlchemy as a backend.
Initialize by creating all tables.
Methods
... | https://api.python.langchain.com/en/latest/cache/langchain.cache.SQLAlchemyCache.html |
09fb0a319b07-0 | langchain.cache.FullLLMCache¶
class langchain.cache.FullLLMCache(**kwargs)[source]¶
Bases: Base
SQLite table for full LLM Cache (all generations).
A simple constructor that allows initialization from kwargs.
Sets attributes on the constructed instance using the names and
values in kwargs.
Only keys that are present as
... | https://api.python.langchain.com/en/latest/cache/langchain.cache.FullLLMCache.html |
d1ace03f0eb4-0 | langchain.cache.MomentoCache¶
class langchain.cache.MomentoCache(cache_client: momento.CacheClient, cache_name: str, *, ttl: Optional[timedelta] = None, ensure_cache_exists: bool = True)[source]¶
Bases: BaseCache
Cache that uses Momento as a backend. See https://gomomento.com/
Instantiate a prompt cache using Momento a... | https://api.python.langchain.com/en/latest/cache/langchain.cache.MomentoCache.html |
d1ace03f0eb4-1 | Clear the cache.
Raises
SdkException – Momento service or network error
classmethod from_client_params(cache_name: str, ttl: timedelta, *, configuration: Optional[momento.config.Configuration] = None, auth_token: Optional[str] = None, **kwargs: Any) → MomentoCache[source]¶
Construct cache from CacheClient parameters.
l... | https://api.python.langchain.com/en/latest/cache/langchain.cache.MomentoCache.html |
60814dbf96b5-0 | langchain.sql_database.truncate_word¶
langchain.sql_database.truncate_word(content: Any, *, length: int, suffix: str = '...') → str[source]¶
Truncate a string to a certain number of words, based on the max string
length. | https://api.python.langchain.com/en/latest/sql_database/langchain.sql_database.truncate_word.html |
7cf08c4325ec-0 | langchain.input.get_colored_text¶
langchain.input.get_colored_text(text: str, color: str) → str[source]¶
Get colored text. | https://api.python.langchain.com/en/latest/input/langchain.input.get_colored_text.html |
4745a96804b8-0 | langchain.input.get_color_mapping¶
langchain.input.get_color_mapping(items: List[str], excluded_colors: Optional[List] = None) → Dict[str, str][source]¶
Get mapping for items to a support color. | https://api.python.langchain.com/en/latest/input/langchain.input.get_color_mapping.html |
f51b5fb56912-0 | langchain.input.get_bolded_text¶
langchain.input.get_bolded_text(text: str) → str[source]¶
Get bolded text. | https://api.python.langchain.com/en/latest/input/langchain.input.get_bolded_text.html |
1ea1ddbfb55a-0 | langchain.input.print_text¶
langchain.input.print_text(text: str, color: Optional[str] = None, end: str = '', file: Optional[TextIO] = None) → None[source]¶
Print text with highlighting and no end characters. | https://api.python.langchain.com/en/latest/input/langchain.input.print_text.html |
1452414a222a-0 | langchain.tools.sleep.tool.SleepTool¶
class langchain.tools.sleep.tool.SleepTool(*, name: str = 'sleep', description: str = 'Make agent sleep for a specified number of seconds.', args_schema: ~typing.Type[~pydantic.main.BaseModel] = <class 'langchain.tools.sleep.tool.SleepInput'>, return_direct: bool = False, verbose: ... | https://api.python.langchain.com/en/latest/tools/langchain.tools.sleep.tool.SleepTool.html |
1452414a222a-1 | Handle the content of the ToolException thrown.
param name: str = 'sleep'¶
The unique name of the tool that clearly communicates its purpose.
param return_direct: bool = False¶
Whether to return the tool’s output directly. Setting this to True means
that after the tool is called, the AgentExecutor will stop looping.
pa... | https://api.python.langchain.com/en/latest/tools/langchain.tools.sleep.tool.SleepTool.html |
d65284a1993c-0 | langchain.tools.bing_search.tool.BingSearchResults¶
class langchain.tools.bing_search.tool.BingSearchResults(*, name: str = 'Bing Search Results JSON', description: str = 'A wrapper around Bing Search. Useful for when you need to answer questions about current events. Input should be a search query. Output is a JSON ar... | https://api.python.langchain.com/en/latest/tools/langchain.tools.bing_search.tool.BingSearchResults.html |
d65284a1993c-1 | You can provide few-shot examples as a part of the description.
param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False¶
Handle the content of the ToolException thrown.
param name: str = 'Bing Search Results JSON'¶
The unique name of the tool that clearly communicates its purpose.
pa... | https://api.python.langchain.com/en/latest/tools/langchain.tools.bing_search.tool.BingSearchResults.html |
eb323c870022-0 | langchain.tools.file_management.read.ReadFileTool¶
class langchain.tools.file_management.read.ReadFileTool(*, name: str = 'read_file', description: str = 'Read file from disk', args_schema: ~typing.Type[~pydantic.main.BaseModel] = <class 'langchain.tools.file_management.read.ReadFileInput'>, return_direct: bool = False... | https://api.python.langchain.com/en/latest/tools/langchain.tools.file_management.read.ReadFileTool.html |
eb323c870022-1 | Handle the content of the ToolException thrown.
param name: str = 'read_file'¶
The unique name of the tool that clearly communicates its purpose.
param return_direct: bool = False¶
Whether to return the tool’s output directly. Setting this to True means
that after the tool is called, the AgentExecutor will stop looping... | https://api.python.langchain.com/en/latest/tools/langchain.tools.file_management.read.ReadFileTool.html |
6aae43eec976-0 | langchain.tools.file_management.file_search.FileSearchTool¶
class langchain.tools.file_management.file_search.FileSearchTool(*, name: str = 'file_search', description: str = 'Recursively search for files in a subdirectory that match the regex pattern', args_schema: ~typing.Type[~pydantic.main.BaseModel] = <class 'langc... | https://api.python.langchain.com/en/latest/tools/langchain.tools.file_management.file_search.FileSearchTool.html |
6aae43eec976-1 | You can provide few-shot examples as a part of the description.
param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False¶
Handle the content of the ToolException thrown.
param name: str = 'file_search'¶
The unique name of the tool that clearly communicates its purpose.
param return_di... | https://api.python.langchain.com/en/latest/tools/langchain.tools.file_management.file_search.FileSearchTool.html |
6aae43eec976-2 | property is_single_input: bool¶
Whether the tool only accepts a single input.
model Config¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/tools/langchain.tools.file_management.file_search.FileSearchTool.html |
859a1f994224-0 | langchain.tools.playwright.utils.create_async_playwright_browser¶
langchain.tools.playwright.utils.create_async_playwright_browser(headless: bool = True) → AsyncBrowser[source]¶
Create a async playwright browser.
Parameters
headless – Whether to run the browser in headless mode. Defaults to True.
Returns
The playwright... | https://api.python.langchain.com/en/latest/tools/langchain.tools.playwright.utils.create_async_playwright_browser.html |
f0ba9422b248-0 | langchain.tools.spark_sql.tool.BaseSparkSQLTool¶
class langchain.tools.spark_sql.tool.BaseSparkSQLTool(*, db: SparkSQL)[source]¶
Bases: BaseModel
Base tool for interacting with Spark SQL.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be p... | https://api.python.langchain.com/en/latest/tools/langchain.tools.spark_sql.tool.BaseSparkSQLTool.html |
141f3858c3eb-0 | langchain.tools.ddg_search.tool.DuckDuckGoSearchRun¶
class langchain.tools.ddg_search.tool.DuckDuckGoSearchRun(*, name: str = 'duckduckgo_search', description: str = 'A wrapper around DuckDuckGo Search. Useful for when you need to answer questions about current events. Input should be a search query.', args_schema: Opt... | https://api.python.langchain.com/en/latest/tools/langchain.tools.ddg_search.tool.DuckDuckGoSearchRun.html |
141f3858c3eb-1 | You can provide few-shot examples as a part of the description.
param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False¶
Handle the content of the ToolException thrown.
param name: str = 'duckduckgo_search'¶
The unique name of the tool that clearly communicates its purpose.
param ret... | https://api.python.langchain.com/en/latest/tools/langchain.tools.ddg_search.tool.DuckDuckGoSearchRun.html |
d465988bd083-0 | langchain.tools.azure_cognitive_services.text2speech.AzureCogsText2SpeechTool¶
class langchain.tools.azure_cognitive_services.text2speech.AzureCogsText2SpeechTool(*, name: str = 'azure_cognitive_services_text2speech', description: str = 'A wrapper around Azure Cognitive Services Text2Speech. Useful for when you need to... | https://api.python.langchain.com/en/latest/tools/langchain.tools.azure_cognitive_services.text2speech.AzureCogsText2SpeechTool.html |
d465988bd083-1 | Used to tell the model how/when/why to use the tool.
You can provide few-shot examples as a part of the description.
param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False¶
Handle the content of the ToolException thrown.
param name: str = 'azure_cognitive_services_text2speech'¶
The ... | https://api.python.langchain.com/en/latest/tools/langchain.tools.azure_cognitive_services.text2speech.AzureCogsText2SpeechTool.html |
d465988bd083-2 | Whether the tool only accepts a single input.
model Config¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/tools/langchain.tools.azure_cognitive_services.text2speech.AzureCogsText2SpeechTool.html |
acb2cd49d22a-0 | langchain.tools.file_management.write.WriteFileInput¶
class langchain.tools.file_management.write.WriteFileInput(*, file_path: str, text: str, append: bool = False)[source]¶
Bases: BaseModel
Input for WriteFileTool.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError i... | https://api.python.langchain.com/en/latest/tools/langchain.tools.file_management.write.WriteFileInput.html |
f0b866f887ef-0 | langchain.tools.jira.tool.JiraAction¶
class langchain.tools.jira.tool.JiraAction(*, name: str = '', description: str = '', args_schema: Optional[Type[BaseModel]] = None, return_direct: bool = False, verbose: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manage... | https://api.python.langchain.com/en/latest/tools/langchain.tools.jira.tool.JiraAction.html |
f0b866f887ef-1 | that after the tool is called, the AgentExecutor will stop looping.
param verbose: bool = False¶
Whether to log the tool’s progress.
__call__(tool_input: str, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → str¶
Make tool callable.
async arun(tool_input: Union[str, Dict], verbose: O... | https://api.python.langchain.com/en/latest/tools/langchain.tools.jira.tool.JiraAction.html |
35933aab1e61-0 | langchain.tools.openapi.utils.api_models.APIRequestBody¶
class langchain.tools.openapi.utils.api_models.APIRequestBody(*, description: Optional[str] = None, properties: List[APIRequestBodyProperty], media_type: str)[source]¶
Bases: BaseModel
A model for a request body.
Create a new model by parsing and validating input... | https://api.python.langchain.com/en/latest/tools/langchain.tools.openapi.utils.api_models.APIRequestBody.html |
a78ecf68e867-0 | langchain.tools.office365.create_draft_message.CreateDraftMessageSchema¶
class langchain.tools.office365.create_draft_message.CreateDraftMessageSchema(*, body: str, to: List[str], subject: str, cc: Optional[List[str]] = None, bcc: Optional[List[str]] = None)[source]¶
Bases: BaseModel
Create a new model by parsing and v... | https://api.python.langchain.com/en/latest/tools/langchain.tools.office365.create_draft_message.CreateDraftMessageSchema.html |
90b02250b27e-0 | langchain.tools.powerbi.tool.InfoPowerBITool¶
class langchain.tools.powerbi.tool.InfoPowerBITool(*, name: str = 'schema_powerbi', description: str = '\n Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables.\n Be sure that the tables actually exist by callin... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.InfoPowerBITool.html |
90b02250b27e-1 | Used to tell the model how/when/why to use the tool.
You can provide few-shot examples as a part of the description.
param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False¶
Handle the content of the ToolException thrown.
param name: str = 'schema_powerbi'¶
The unique name of the too... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.InfoPowerBITool.html |
90b02250b27e-2 | model Config[source]¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶ | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.InfoPowerBITool.html |
5dab04ce68a7-0 | langchain.tools.sql_database.tool.BaseSQLDatabaseTool¶
class langchain.tools.sql_database.tool.BaseSQLDatabaseTool(*, db: SQLDatabase)[source]¶
Bases: BaseModel
Base tool for interacting with a SQL database.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the in... | https://api.python.langchain.com/en/latest/tools/langchain.tools.sql_database.tool.BaseSQLDatabaseTool.html |
c19a0ffc83e3-0 | langchain.tools.powerbi.tool.QueryPowerBITool¶ | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-1 | class langchain.tools.powerbi.tool.QueryPowerBITool(*, name: str = 'query_powerbi', description: str = '\n Input to this tool is a detailed question about the dataset, output is a result from the dataset. It will try to answer the question using the dataset, and if it cannot, it will ask for clarification.\n\n Ex... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-2 | functions require one or more arguments, which can include tables, columns, expressions, and values. However, some functions, such as PI, do not require any arguments, but always require parentheses to indicate the null argument. For example, you must always type PI(), not PI. You can also nest functions within other f... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-3 | which can then be passed as an argument to other measure expressions. Once resultant values have been calculated for a variable expression, those values do not change, even if the variable is referenced in another expression.\n\nFILTER(<table>,<filter>) - Returns a table that represents a subset of another table or exp... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-4 | (<column>) - these are all variantions of count functions.\nAVERAGE(<column>), AVERAGEA(<column>), AVERAGEX(<table>,<expression>) - these are all variantions of average functions.\nMAX(<column>), MAXA(<column>), MAXX(<table>,<expression>) - these are all variantions of max functions.\nMIN(<column>), MINA(<column>), MIN... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-5 | Sometimes you will get a question, a DAX query and a error, in that case you need to rewrite the DAX query to get the correct answer.\n\nThe following tables exist: {tables}\n\nand the schema\'s for some are given here:\n{schemas}\n\nExamples:\n{examples}\n\nQuestion: {tool_input}\nDAX: \n', examples: Optional[str] = '... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-6 | Bases: BaseTool
Tool for querying a Power BI Dataset.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param args_schema: Optional[Type[BaseModel]] = None¶
Pydantic model class to validate and parse the tool’... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-7 | Handle the content of the ToolException thrown.
param llm_chain: langchain.chains.llm.LLMChain [Required]¶
param max_iterations: int = 5¶
param name: str = 'query_powerbi'¶
The unique name of the tool that clearly communicates its purpose.
param powerbi: langchain.utilities.powerbi.PowerBIDataset [Required]¶
param retu... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-8 | param template: Optional[str] = '\nAnswer the question below with a DAX query that can be sent to Power BI. DAX queries have a simple syntax comprised of just one required keyword, EVALUATE, and several optional keywords: ORDER BY, START AT, DEFINE, MEASURE, VAR, TABLE, and COLUMN. Each keyword defines a statement used... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-9 | ORDER BY <expression> ASC or DESC START AT <value> or <parameter> - The optional START AT keyword is used inside an ORDER BY clause. It defines the value at which the query results begin.\nDEFINE MEASURE | VAR; EVALUATE <table> - The optional DEFINE keyword introduces one or more calculated entity definitions that exis... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-10 | you nest the DISTINCT function within a formula, to get a list of distinct values that can be passed to another function and then counted, summed, or used for other operations.\nDISTINCT(<table>) - Returns a table by removing duplicate rows from another table or expression.\n\nAggregation functions, names with a A in i... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-11 | date2, <interval>) - Returns the difference between two date values, in the specified interval, that can be SECOND, MINUTE, HOUR, DAY, WEEK, MONTH, QUARTER, YEAR.\nDATEVALUE(<date_text>) - Returns a date value that represents the specified date.\nYEAR(<date>), QUARTER(<date>), MONTH(<date>), DAY(<date>), HOUR(<date>), ... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
c19a0ffc83e3-12 | param verbose: bool = False¶
Whether to log the tool’s progress.
__call__(tool_input: str, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → str¶
Make tool callable.
async arun(tool_input: Union[str, Dict], verbose: Optional[bool] = None, start_color: Optional[str] = 'green', color: O... | https://api.python.langchain.com/en/latest/tools/langchain.tools.powerbi.tool.QueryPowerBITool.html |
82828e0e406a-0 | langchain.tools.scenexplain.tool.SceneXplainTool¶
class langchain.tools.scenexplain.tool.SceneXplainTool(*, name: str = 'image_explainer', description: str = 'An Image Captioning Tool: Use this tool to generate a detailed caption for an image. The input can be an image file of any format, and the output will be a text ... | https://api.python.langchain.com/en/latest/tools/langchain.tools.scenexplain.tool.SceneXplainTool.html |
82828e0e406a-1 | Used to tell the model how/when/why to use the tool.
You can provide few-shot examples as a part of the description.
param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False¶
Handle the content of the ToolException thrown.
param name: str = 'image_explainer'¶
The unique name of the to... | https://api.python.langchain.com/en/latest/tools/langchain.tools.scenexplain.tool.SceneXplainTool.html |
82828e0e406a-2 | Configuration for this pydantic object.
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/tools/langchain.tools.scenexplain.tool.SceneXplainTool.html |
90710128a3a4-0 | langchain.tools.bing_search.tool.BingSearchRun¶
class langchain.tools.bing_search.tool.BingSearchRun(*, name: str = 'bing_search', description: str = 'A wrapper around Bing Search. Useful for when you need to answer questions about current events. Input should be a search query.', args_schema: Optional[Type[BaseModel]]... | https://api.python.langchain.com/en/latest/tools/langchain.tools.bing_search.tool.BingSearchRun.html |
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