id stringlengths 14 15 | text stringlengths 49 2.47k | source stringlengths 61 166 |
|---|---|---|
d25444482d96-1 | },
)
tsds_client = TensorflowDatasets(
dataset_name="mlqa/en",
split_name="train",
load_max_docs=MAX_DOCS,
sample_to_document_function=mlqaen_example_to_document,
)
"""
dataset_name: str =... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/tensorflow_datasets.html |
d25444482d96-2 | for s in self.dataset.take(self.load_max_docs)
if self.sample_to_document_function is not None
)
[docs] def load(self) -> List[Document]:
"""Download a selected dataset.
Returns: a list of Documents.
"""
return list(self.lazy_load()) | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/tensorflow_datasets.html |
59a8cc85b688-0 | Source code for langchain.utilities.graphql
import json
from typing import Any, Callable, Dict, Optional
from pydantic import BaseModel, Extra, root_validator
[docs]class GraphQLAPIWrapper(BaseModel):
"""Wrapper around GraphQL API.
To use, you should have the ``gql`` python package installed.
This wrapper w... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/graphql.html |
59a8cc85b688-1 | return json.dumps(result, indent=2)
def _execute_query(self, query: str) -> Dict[str, Any]:
"""Execute a GraphQL query and return the results."""
document_node = self.gql_function(query)
result = self.gql_client.execute(document_node)
return result | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/graphql.html |
5150ba5581f8-0 | Source code for langchain.utilities.searx_search
"""Utility for using SearxNG meta search API.
SearxNG is a privacy-friendly free metasearch engine that aggregates results from
`multiple search engines
<https://docs.searxng.org/admin/engines/configured_engines.html>`_ and databases and
supports the `OpenSearch
<https:/... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-1 | :class:`SearxResults` is a convenience wrapper around the raw json result.
Example usage of the ``run`` method to make a search:
.. code-block:: python
s.run(query="what is the best search engine?")
Engine Parameters
-----------------
You can pass any `accepted searx search API
<https://docs.searxng.org/dev... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-2 | .. code-block:: python
# select the github engine and pass the search suffix
s = SearchWrapper("langchain library", query_suffix="!gh")
s = SearchWrapper("langchain library")
# select github the conventional google search syntax
s.run("large language models", query_suffix="site:g... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-3 | def _get_default_params() -> dict:
return {"language": "en", "format": "json"}
[docs]class SearxResults(dict):
"""Dict like wrapper around search api results."""
_data = ""
[docs] def __init__(self, data: str):
"""Take a raw result from Searx and make it into a dict like object."""
json_d... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-4 | Example with SSL disabled:
.. code-block:: python
from langchain.utilities import SearxSearchWrapper
# note the unsecure parameter is not needed if you pass the url scheme as
# http
searx = SearxSearchWrapper(searx_host="http://localhost:8888",
... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-5 | if categories:
values["params"]["categories"] = ",".join(categories)
searx_host = get_from_dict_or_env(values, "searx_host", "SEARX_HOST")
if not searx_host.startswith("http"):
print(
f"Warning: missing the url scheme on host \
! assuming secure ht... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-6 | ) as response:
if not response.ok:
raise ValueError("Searx API returned an error: ", response.text)
result = SearxResults(await response.text())
self._result = result
else:
async with self.aiosession.get(
... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-7 | searx.run("what is the weather in France ?", engine="qwant")
# the same result can be achieved using the `!` syntax of searx
# to select the engine using `query_suffix`
searx.run("what is the weather in France ?", query_suffix="!qwant")
"""
_params = {
... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-8 | ) -> str:
"""Asynchronously version of `run`."""
_params = {
"q": query,
}
params = {**self.params, **_params, **kwargs}
if self.query_suffix and len(self.query_suffix) > 0:
params["q"] += " " + self.query_suffix
if isinstance(query_suffix, str) an... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-9 | engines: List of engines to use for the query.
categories: List of categories to use for the query.
**kwargs: extra parameters to pass to the searx API.
Returns:
Dict with the following keys:
{
snippet: The description of the result.
... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
5150ba5581f8-10 | ]
[docs] async def aresults(
self,
query: str,
num_results: int,
engines: Optional[List[str]] = None,
query_suffix: Optional[str] = "",
**kwargs: Any,
) -> List[Dict]:
"""Asynchronously query with json results.
Uses aiohttp. See `results` for more i... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
0158369c71a0-0 | Source code for langchain.utilities.bibtex
"""Util that calls bibtexparser."""
import logging
from typing import Any, Dict, List, Mapping
from pydantic import BaseModel, Extra, root_validator
logger = logging.getLogger(__name__)
OPTIONAL_FIELDS = [
"annotate",
"booktitle",
"editor",
"howpublished",
... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/bibtex.html |
0158369c71a0-1 | import bibtexparser
with open(path) as file:
entries = bibtexparser.load(file).entries
return entries
[docs] def get_metadata(
self, entry: Mapping[str, Any], load_extra: bool = False
) -> Dict[str, Any]:
"""Get metadata for the given entry."""
publication = en... | https://api.python.langchain.com/en/latest/_modules/langchain/utilities/bibtex.html |
e5d73737ce81-0 | Source code for langchain.docstore.arbitrary_fn
from typing import Callable, Union
from langchain.docstore.base import Docstore
from langchain.schema import Document
[docs]class DocstoreFn(Docstore):
"""Langchain Docstore via arbitrary lookup function.
This is useful when:
* it's expensive to construct an ... | https://api.python.langchain.com/en/latest/_modules/langchain/docstore/arbitrary_fn.html |
013ce9284415-0 | Source code for langchain.docstore.in_memory
"""Simple in memory docstore in the form of a dict."""
from typing import Dict, List, Optional, Union
from langchain.docstore.base import AddableMixin, Docstore
from langchain.docstore.document import Document
[docs]class InMemoryDocstore(Docstore, AddableMixin):
"""Simp... | https://api.python.langchain.com/en/latest/_modules/langchain/docstore/in_memory.html |
013ce9284415-1 | """
if search not in self._dict:
return f"ID {search} not found."
else:
return self._dict[search] | https://api.python.langchain.com/en/latest/_modules/langchain/docstore/in_memory.html |
6e16e2a4f95b-0 | Source code for langchain.docstore.base
"""Interface to access to place that stores documents."""
from abc import ABC, abstractmethod
from typing import Dict, List, Union
from langchain.docstore.document import Document
[docs]class Docstore(ABC):
"""Interface to access to place that stores documents."""
[docs] @... | https://api.python.langchain.com/en/latest/_modules/langchain/docstore/base.html |
4adbd5e7b647-0 | Source code for langchain.docstore.wikipedia
"""Wrapper around wikipedia API."""
from typing import Union
from langchain.docstore.base import Docstore
from langchain.docstore.document import Document
[docs]class Wikipedia(Docstore):
"""Wrapper around wikipedia API."""
[docs] def __init__(self) -> None:
"... | https://api.python.langchain.com/en/latest/_modules/langchain/docstore/wikipedia.html |
136934ef52e8-0 | Source code for langchain.agents.agent_iterator
from __future__ import annotations
import logging
import time
from abc import ABC, abstractmethod
from asyncio import CancelledError
from functools import wraps
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
NoReturn,
Optional,
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-1 | self,
agent_executor: AgentExecutor,
inputs: Any,
callbacks: Callbacks = None,
*,
tags: Optional[list[str]] = None,
include_run_info: bool = False,
async_: bool = False,
):
"""
Initialize the AgentExecutorIterator with the given AgentExecutor,
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-2 | return self._tags
@tags.setter
@rebuild_callback_manager_on_set
def tags(self, tags: Optional[List[str]]) -> None:
"""When tags are changed after __init__, rebuild callback mgr"""
self._tags = tags
@property
def agent_executor(self) -> AgentExecutor:
return self._agent_execut... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-3 | )
[docs] def reset(self) -> None:
"""
Reset the iterator to its initial state, clearing intermediate steps,
iterations, and time elapsed.
"""
logger.debug("(Re)setting AgentExecutorIterator to fresh state")
self.intermediate_steps: list[tuple[AgentAction, str]] = []
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-4 | return self._final_outputs
@final_outputs.setter
def final_outputs(self, outputs: Optional[Dict[str, Any]]) -> None:
# have access to intermediate steps by design in iterator,
# so return only outputs may as well always be true.
self._final_outputs = None
if outputs:
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-5 | """
pass
async def _on_first_async_step(self) -> None:
"""
Perform any necessary setup for the first step of the asynchronous iterator.
"""
# on first step, need to await callback manager and start async timeout ctxmgr
if self.iterations == 0:
assert isins... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-6 | return await self._acall_next()
except StopAsyncIteration:
raise
except (TimeoutError, CancelledError):
await self.timeout_manager.__aexit__(None, None, None)
self.timeout_manager = None
return await self._astop()
except (KeyboardInterrupt, Excepti... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-7 | run_manager: Optional[CallbackManagerForChainRun],
) -> Dict[str, Union[str, List[Tuple[AgentAction, str]]]]:
"""
Process the output of the next step,
handling AgentFinish and tool return cases.
"""
logger.debug("Processing output of Agent loop step")
if isinstance(ne... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-8 | """
Process the output of the next async step,
handling AgentFinish and tool return cases.
"""
logger.debug("Processing output of async Agent loop step")
if isinstance(next_step_output, AgentFinish):
logger.debug(
"Hit AgentFinish: _areturn -> on_chain... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-9 | self.intermediate_steps,
**self.inputs,
)
assert (
isinstance(self.run_manager, CallbackManagerForChainRun)
or self.run_manager is None
)
returned_output = self.agent_executor._return(
output, self.intermediate_steps, run_manager=self.run_m... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
136934ef52e8-10 | )
next_step_output = self._execute_next_step(self.run_manager)
output = self._process_next_step_output(next_step_output, self.run_manager)
self.update_iterations()
return output
async def _acall_next(self) -> dict[str, Any]:
"""
Perform a single iteration of the async... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_iterator.html |
1ac18c9f5f4d-0 | Source code for langchain.agents.agent
"""Chain that takes in an input and produces an action and action input."""
from __future__ import annotations
import asyncio
import json
import logging
import time
from abc import abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Sequ... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-1 | return None
[docs] @abstractmethod
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Ste... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-2 | # `force` just returns a constant string
return AgentFinish(
{"output": "Agent stopped due to iteration limit or time limit."}, ""
)
else:
raise ValueError(
f"Got unsupported early_stopping_method `{early_stopping_method}`"
)
[docs]... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-3 | directory_path.mkdir(parents=True, exist_ok=True)
# Fetch dictionary to save
agent_dict = self.dict()
if save_path.suffix == ".json":
with open(file_path, "w") as f:
json.dump(agent_dict, f, indent=4)
elif save_path.suffix == ".yaml":
with open(fil... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-4 | callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[List[AgentAction], AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date,
along with the observations.
callbacks: Callbacks to run.
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-5 | Args:
file_path: Path to file to save the agent to.
Example:
.. code-block:: python
# If working with agent executor
agent.agent.save(file_path="path/agent.yaml")
"""
# Convert file to Path object.
if isinstance(file_path, str):
sav... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-6 | @property
def input_keys(self) -> List[str]:
"""Return the input keys.
Returns:
List of input keys.
"""
return list(set(self.llm_chain.input_keys) - {"intermediate_steps"})
[docs] def dict(self, **kwargs: Any) -> Dict:
"""Return dictionary representation of age... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-7 | Returns:
Action specifying what tool to use.
"""
output = await self.llm_chain.arun(
intermediate_steps=intermediate_steps,
stop=self.stop,
callbacks=callbacks,
**kwargs,
)
return self.output_parser.parse(output)
[docs] def t... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-8 | f"\n\t{self.observation_prefix.rstrip()}",
]
def _construct_scratchpad(
self, intermediate_steps: List[Tuple[AgentAction, str]]
) -> Union[str, List[BaseMessage]]:
"""Construct the scratchpad that lets the agent continue its thought process."""
thoughts = ""
for action, o... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-9 | **kwargs: User inputs.
Returns:
Action specifying what tool to use.
"""
full_inputs = self.get_full_inputs(intermediate_steps, **kwargs)
full_output = await self.llm_chain.apredict(callbacks=callbacks, **full_inputs)
agent_output = await self.output_parser.aparse(full... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-10 | prompt.suffix += "\n{agent_scratchpad}"
else:
raise ValueError(f"Got unexpected prompt type {type(prompt)}")
return values
@property
@abstractmethod
def observation_prefix(self) -> str:
"""Prefix to append the observation with."""
@property
@abstractmethod... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-11 | return cls(
llm_chain=llm_chain,
allowed_tools=tool_names,
output_parser=_output_parser,
**kwargs,
)
[docs] def return_stopped_response(
self,
early_stopping_method: str,
intermediate_steps: List[Tuple[AgentAction, str]],
**kwarg... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-12 | # we just return the full output
return AgentFinish({"output": full_output}, full_output)
else:
raise ValueError(
"early_stopping_method should be one of `force` or `generate`, "
f"got {early_stopping_method}"
)
[docs] def tool_run_loggi... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-13 | """The maximum number of steps to take before ending the execution
loop.
Setting to 'None' could lead to an infinite loop."""
max_execution_time: Optional[float] = None
"""The maximum amount of wall clock time to spend in the execution
loop.
"""
early_stopping_method: str = "force"
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-14 | tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
**kwargs: Any,
) -> AgentExecutor:
"""Create from agent and tools."""
return cls(
agent=agent, tools=tools, callback_manager=callback_manager, **kwargs
)
@root_validator()
d... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-15 | "`.save_agent(...)`"
)
[docs] def save_agent(self, file_path: Union[Path, str]) -> None:
"""Save the underlying agent."""
return self.agent.save(file_path)
[docs] def iter(
self,
inputs: Any,
callbacks: Callbacks = None,
*,
include_run_info: bool = F... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-16 | return False
return True
def _return(
self,
output: AgentFinish,
intermediate_steps: list,
run_manager: Optional[CallbackManagerForChainRun] = None,
) -> Dict[str, Any]:
if run_manager:
run_manager.on_agent_finish(output, color="green", verbose=self.ve... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-17 | output = self.agent.plan(
intermediate_steps,
callbacks=run_manager.get_child() if run_manager else None,
**inputs,
)
except OutputParserException as e:
if isinstance(self.handle_parsing_errors, bool):
raise_error = not self... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-18 | result = []
for agent_action in actions:
if run_manager:
run_manager.on_agent_action(agent_action, color="green")
# Otherwise we lookup the tool
if agent_action.tool in name_to_tool_map:
tool = name_to_tool_map[agent_action.tool]
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-19 | """Take a single step in the thought-action-observation loop.
Override this to take control of how the agent makes and acts on choices.
"""
try:
intermediate_steps = self._prepare_intermediate_steps(intermediate_steps)
# Call the LLM to see what to do.
output ... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-20 | if isinstance(output, AgentFinish):
return output
actions: List[AgentAction]
if isinstance(output, AgentAction):
actions = [output]
else:
actions = output
async def _aperform_agent_action(
agent_action: AgentAction,
) -> Tuple[Agent... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-21 | result = await asyncio.gather(
*[_aperform_agent_action(agent_action) for agent_action in actions]
)
return list(result)
def _call(
self,
inputs: Dict[str, str],
run_manager: Optional[CallbackManagerForChainRun] = None,
) -> Dict[str, Any]:
"""Run text... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-22 | if tool_return is not None:
return self._return(
tool_return, intermediate_steps, run_manager=run_manager
)
iterations += 1
time_elapsed = time.time() - start_time
output = self.agent.return_stopped_response(
sel... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-23 | return await self._areturn(
next_step_output,
intermediate_steps,
run_manager=run_manager,
)
intermediate_steps.extend(next_step_output)
if len(next_step_output) == 1:
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
1ac18c9f5f4d-24 | {self.agent.return_values[0]: observation},
"",
)
return None
def _prepare_intermediate_steps(
self, intermediate_steps: List[Tuple[AgentAction, str]]
) -> List[Tuple[AgentAction, str]]:
if (
isinstance(self.trim_intermediate_steps, int)
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
203bc18679ac-0 | Source code for langchain.agents.load_tools
# flake8: noqa
"""Load tools."""
import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain.agents.tools import Tool
from langchain.schema.language_model import BaseLanguageModel
from langchain.callbacks... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-1 | )
from langchain.tools.scenexplain.tool import SceneXplainTool
from langchain.tools.searx_search.tool import SearxSearchResults, SearxSearchRun
from langchain.tools.shell.tool import ShellTool
from langchain.tools.sleep.tool import SleepTool
from langchain.tools.wikipedia.tool import WikipediaQueryRun
from langchain.to... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-2 | return PythonREPLTool()
def _get_tools_requests_get() -> BaseTool:
return RequestsGetTool(requests_wrapper=TextRequestsWrapper())
def _get_tools_requests_post() -> BaseTool:
return RequestsPostTool(requests_wrapper=TextRequestsWrapper())
def _get_tools_requests_patch() -> BaseTool:
return RequestsPatchTool(... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-3 | )
def _get_open_meteo_api(llm: BaseLanguageModel) -> BaseTool:
chain = APIChain.from_llm_and_api_docs(llm, open_meteo_docs.OPEN_METEO_DOCS)
return Tool(
name="Open Meteo API",
description="Useful for when you want to get weather information from the OpenMeteo API. The input should be a question ... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-4 | )
return Tool(
name="TMDB API",
description="Useful for when you want to get information from The Movie Database. The input should be a question in natural language that this API can answer.",
func=chain.run,
)
def _get_podcast_api(llm: BaseLanguageModel, **kwargs: Any) -> BaseTool:
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-5 | def _get_golden_query(**kwargs: Any) -> BaseTool:
return GoldenQueryRun(api_wrapper=GoldenQueryAPIWrapper(**kwargs))
def _get_pubmed(**kwargs: Any) -> BaseTool:
return PubmedQueryRun(api_wrapper=PubMedAPIWrapper(**kwargs))
def _get_google_serper(**kwargs: Any) -> BaseTool:
return GoogleSerperRun(api_wrapper... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-6 | func=TwilioAPIWrapper(**kwargs).run,
)
def _get_searx_search(**kwargs: Any) -> BaseTool:
return SearxSearchRun(wrapper=SearxSearchWrapper(**kwargs))
def _get_searx_search_results_json(**kwargs: Any) -> BaseTool:
wrapper_kwargs = {k: v for k, v in kwargs.items() if k != "num_results"}
return SearxSearchR... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-7 | def _get_dataforseo_api_search_json(**kwargs: Any) -> BaseTool:
return DataForSeoAPISearchResults(api_wrapper=DataForSeoAPIWrapper(**kwargs))
_EXTRA_LLM_TOOLS: Dict[
str,
Tuple[Callable[[Arg(BaseLanguageModel, "llm"), KwArg(Any)], BaseTool], List[str]],
] = {
"news-api": (_get_news_api, ["news_api_key"]... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-8 | "google-serper-results-json": (
_get_google_serper_results_json,
["serper_api_key", "aiosession"],
),
"serpapi": (_get_serpapi, ["serpapi_api_key", "aiosession"]),
"dalle-image-generator": (_get_dalle_image_generator, ["openai_api_key"]),
"twilio": (_get_twilio, ["account_sid", "auth_tok... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-9 | _get_dataforseo_api_search_json,
["api_login", "api_password", "aiosession"],
),
}
def _handle_callbacks(
callback_manager: Optional[BaseCallbackManager], callbacks: Callbacks
) -> Callbacks:
if callback_manager is not None:
warnings.warn(
"callback_manager is deprecated. Please ... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-10 | token=token,
remote=remote,
**kwargs,
)
outputs = hf_tool.outputs
if set(outputs) != {"text"}:
raise NotImplementedError("Multimodal outputs not supported yet.")
inputs = hf_tool.inputs
if set(inputs) != {"text"}:
raise NotImplementedError("Multimodal inputs not suppo... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-11 | tool_names.extend(requests_method_tools)
elif name in _BASE_TOOLS:
tools.append(_BASE_TOOLS[name]())
elif name in _LLM_TOOLS:
if llm is None:
raise ValueError(f"Tool {name} requires an LLM to be provided")
tool = _LLM_TOOLS[name](llm)
tools... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
203bc18679ac-12 | return (
list(_BASE_TOOLS)
+ list(_EXTRA_OPTIONAL_TOOLS)
+ list(_EXTRA_LLM_TOOLS)
+ list(_LLM_TOOLS)
) | https://api.python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
4e7c4cc3ea04-0 | Source code for langchain.agents.loading
"""Functionality for loading agents."""
import json
import logging
from pathlib import Path
from typing import Any, List, Optional, Union
import yaml
from langchain.agents.agent import BaseMultiActionAgent, BaseSingleActionAgent
from langchain.agents.tools import Tool
from langc... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
4e7c4cc3ea04-1 | tools: List of tools this agent has access to.
**kwargs: Additional key word arguments passed to the agent executor.
Returns:
An agent executor.
"""
if "_type" not in config:
raise ValueError("Must specify an agent Type in config")
load_from_tools = config.pop("load_from_llm_and_... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
4e7c4cc3ea04-2 | del config["output_parser"]
combined_config = {**config, **kwargs}
return agent_cls(**combined_config) # type: ignore
[docs]def load_agent(
path: Union[str, Path], **kwargs: Any
) -> Union[BaseSingleActionAgent, BaseMultiActionAgent]:
"""Unified method for loading an agent from LangChainHub or local fs... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
139bd942b53f-0 | Source code for langchain.agents.initialize
"""Load agent."""
from typing import Any, Optional, Sequence
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_types import AgentType
from langchain.agents.loading import AGENT_TO_CLASS, load_agent
from langchain.callbacks.base import BaseCallbackMa... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/initialize.html |
139bd942b53f-1 | agent = AgentType.ZERO_SHOT_REACT_DESCRIPTION
if agent is not None and agent_path is not None:
raise ValueError(
"Both `agent` and `agent_path` are specified, "
"but at most only one should be."
)
if agent is not None:
if agent not in AGENT_TO_CLASS:
r... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/initialize.html |
052ab803acde-0 | Source code for langchain.agents.agent_types
from enum import Enum
[docs]class AgentType(str, Enum):
"""Enumerator with the Agent types."""
ZERO_SHOT_REACT_DESCRIPTION = "zero-shot-react-description"
REACT_DOCSTORE = "react-docstore"
SELF_ASK_WITH_SEARCH = "self-ask-with-search"
CONVERSATIONAL_REACT... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/agent_types.html |
0c4043ab951b-0 | Source code for langchain.agents.tools
"""Interface for tools."""
from typing import List, Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool, Tool, tool
[docs]class InvalidTool(BaseTool):
"""Tool that is ... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/tools.html |
61b29554c313-0 | Source code for langchain.agents.utils
from typing import Sequence
from langchain.tools.base import BaseTool
[docs]def validate_tools_single_input(class_name: str, tools: Sequence[BaseTool]) -> None:
"""Validate tools for single input."""
for tool in tools:
if not tool.is_single_input:
raise... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/utils.html |
06f177afca8c-0 | Source code for langchain.agents.schema
from typing import Any, Dict, List, Tuple
from langchain.prompts.chat import ChatPromptTemplate
from langchain.schema import AgentAction
[docs]class AgentScratchPadChatPromptTemplate(ChatPromptTemplate):
"""Chat prompt template for the agent scratchpad."""
def _construct_... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/schema.html |
5e69338ff737-0 | Source code for langchain.agents.react.base
"""Chain that implements the ReAct paper from https://arxiv.org/pdf/2210.03629.pdf."""
from typing import Any, List, Optional, Sequence
from pydantic import Field
from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser
from langchain.agents.agent_types impo... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
5e69338ff737-1 | super()._validate_tools(tools)
if len(tools) != 2:
raise ValueError(f"Exactly two tools must be specified, but got {tools}")
tool_names = {tool.name for tool in tools}
if tool_names != {"Lookup", "Search"}:
raise ValueError(
f"Tool names should be Lookup a... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
5e69338ff737-2 | raise ValueError("Cannot lookup without a successful search first")
if term.lower() != self.lookup_str:
self.lookup_str = term.lower()
self.lookup_index = 0
else:
self.lookup_index += 1
lookups = [p for p in self._paragraphs if self.lookup_str in p.lower()]
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
5e69338ff737-3 | if tool_names != {"Play"}:
raise ValueError(f"Tool name should be Play, got {tool_names}")
[docs]class ReActChain(AgentExecutor):
"""Chain that implements the ReAct paper.
Example:
.. code-block:: python
from langchain import ReActChain, OpenAI
react = ReAct(llm=OpenA... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
96ad1ff4cf8d-0 | Source code for langchain.agents.react.output_parser
import re
from typing import Union
from langchain.agents.agent import AgentOutputParser
from langchain.schema import AgentAction, AgentFinish, OutputParserException
[docs]class ReActOutputParser(AgentOutputParser):
"""Output parser for the ReAct agent."""
[docs] ... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/react/output_parser.html |
ca2956768799-0 | Source code for langchain.agents.xml.base
from typing import Any, List, Tuple, Union
from langchain.agents.agent import AgentOutputParser, BaseSingleActionAgent
from langchain.agents.xml.prompt import agent_instructions
from langchain.callbacks.base import Callbacks
from langchain.chains.llm import LLMChain
from langch... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/xml/base.html |
ca2956768799-1 | model =
"""
tools: List[BaseTool]
"""List of tools this agent has access to."""
llm_chain: LLMChain
"""Chain to use to predict action."""
@property
def input_keys(self) -> List[str]:
return ["input"]
[docs] @staticmethod
def get_default_prompt() -> ChatPromptTemplate:
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/xml/base.html |
ca2956768799-2 | callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
log = ""
for action, observation in intermediate_steps:
log += (
f"<tool>{action.tool}</tool><tool_input>{action.tool_input}"
f"</tool_input><observation>{observation... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/xml/base.html |
92c56f7f7aa0-0 | Source code for langchain.agents.openai_functions_multi_agent.base
"""Module implements an agent that uses OpenAI's APIs function enabled API."""
import json
from dataclasses import dataclass
from json import JSONDecodeError
from typing import Any, List, Optional, Sequence, Tuple, Union
from pydantic import root_valida... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
92c56f7f7aa0-1 | return [AIMessage(content=agent_action.log)]
def _create_function_message(
agent_action: AgentAction, observation: str
) -> FunctionMessage:
"""Convert agent action and observation into a function message.
Args:
agent_action: the tool invocation request from the agent
observation: the result... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
92c56f7f7aa0-2 | except JSONDecodeError:
raise OutputParserException(
f"Could not parse tool input: {function_call} because "
f"the `arguments` is not valid JSON."
)
final_tools: List[AgentAction] = []
for tool_schema in tools:
_tool_input = tool_schema... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
92c56f7f7aa0-3 | that supports using `functions`.
tools: The tools this agent has access to.
prompt: The prompt for this agent, should support agent_scratchpad as one
of the variables. For an easy way to construct this prompt, use
`OpenAIMultiFunctionsAgent.create_prompt(...)`
"""
llm: Ba... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
92c56f7f7aa0-4 | # to use.
"name": "tool_selection",
"description": "A list of actions to take.",
"parameters": {
"title": "tool_selection",
"description": "A list of actions to take.",
"type": "object",
"properties": {
... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
92c56f7f7aa0-5 | return [tool_selection]
[docs] def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[List[AgentAction], AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
92c56f7f7aa0-6 | selected_inputs = {
k: kwargs[k] for k in self.prompt.input_variables if k != "agent_scratchpad"
}
full_inputs = dict(**selected_inputs, agent_scratchpad=agent_scratchpad)
prompt = self.prompt.format_prompt(**full_inputs)
messages = prompt.to_messages()
predicted_mess... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
92c56f7f7aa0-7 | cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
ad9b89cb0316-0 | Source code for langchain.agents.self_ask_with_search.base
"""Chain that does self-ask with search."""
from typing import Any, Sequence, Union
from pydantic import Field
from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser
from langchain.agents.agent_types import AgentType
from langchain.agents.se... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/self_ask_with_search/base.html |
ad9b89cb0316-1 | raise ValueError(f"Exactly one tool must be specified, but got {tools}")
tool_names = {tool.name for tool in tools}
if tool_names != {"Intermediate Answer"}:
raise ValueError(
f"Tool name should be Intermediate Answer, got {tool_names}"
)
@property
def obs... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/self_ask_with_search/base.html |
5e6ecf77ffeb-0 | Source code for langchain.agents.self_ask_with_search.output_parser
from typing import Sequence, Union
from langchain.agents.agent import AgentOutputParser
from langchain.schema import AgentAction, AgentFinish, OutputParserException
[docs]class SelfAskOutputParser(AgentOutputParser):
"""Output parser for the self-a... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/self_ask_with_search/output_parser.html |
0bc2fb9d19be-0 | Source code for langchain.agents.structured_chat.base
import re
from typing import Any, List, Optional, Sequence, Tuple
from pydantic import Field
from langchain.agents.agent import Agent, AgentOutputParser
from langchain.agents.structured_chat.output_parser import (
StructuredChatOutputParserWithRetries,
)
from la... | https://api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
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