id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 49 117 |
|---|---|---|
a2d910173a2e-21 | try:
while self._should_continue(iterations, time_elapsed):
next_step_output = await self._atake_next_step(
name_to_tool_map,
color_mapping,
inputs,
intermediate_steps,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
a2d910173a2e-22 | agent_action, observation = next_step_output
name_to_tool_map = {tool.name: tool for tool in self.tools}
# Invalid tools won't be in the map, so we return False.
if agent_action.tool in name_to_tool_map:
if name_to_tool_map[agent_action.tool].return_direct:
return Age... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
cea63ae41e44-0 | 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 BaseSingleActionAgent
from langchain.agents.tools import Tool
from langchain.agents.types impo... | https://python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
cea63ae41e44-1 | if load_from_tools:
if llm is None:
raise ValueError(
"If `load_from_llm_and_tools` is set to True, "
"then LLM must be provided"
)
if tools is None:
raise ValueError(
"If `load_from_llm_and_tools` is set to True, "
... | https://python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
cea63ae41e44-2 | ):
return hub_result
else:
return _load_agent_from_file(path, **kwargs)
def _load_agent_from_file(
file: Union[str, Path], **kwargs: Any
) -> BaseSingleActionAgent:
"""Load agent from file."""
# Convert file to Path object.
if isinstance(file, str):
file_path = Path(file)
... | https://python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
d4aa5cd5aecb-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.base_language import BaseLanguageModel
from langchain.callbacks.base im... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-1 | from langchain.tools.shell.tool import ShellTool
from langchain.tools.wikipedia.tool import WikipediaQueryRun
from langchain.tools.wolfram_alpha.tool import WolframAlphaQueryRun
from langchain.tools.openweathermap.tool import OpenWeatherMapQueryRun
from langchain.utilities import ArxivAPIWrapper
from langchain.utilitie... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-2 | def _get_terminal() -> BaseTool:
return ShellTool()
_BASE_TOOLS: Dict[str, Callable[[], BaseTool]] = {
"python_repl": _get_python_repl,
"requests": _get_tools_requests_get, # preserved for backwards compatability
"requests_get": _get_tools_requests_get,
"requests_post": _get_tools_requests_post,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-3 | coroutine=LLMMathChain.from_llm(llm=llm).arun,
)
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... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-4 | chain = APIChain.from_llm_and_api_docs(
llm,
tmdb_docs.TMDB_DOCS,
headers={"Authorization": f"Bearer {tmdb_bearer_token}"},
)
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 ... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-5 | return WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper(**kwargs))
def _get_arxiv(**kwargs: Any) -> BaseTool:
return ArxivQueryRun(api_wrapper=ArxivAPIWrapper(**kwargs))
def _get_google_serper(**kwargs: Any) -> BaseTool:
return GoogleSerperRun(api_wrapper=GoogleSerperAPIWrapper(**kwargs))
def _get_google_serpe... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-6 | return SearxSearchResults(wrapper=SearxSearchWrapper(**wrapper_kwargs), **kwargs)
def _get_bing_search(**kwargs: Any) -> BaseTool:
return BingSearchRun(api_wrapper=BingSearchAPIWrapper(**kwargs))
def _get_metaphor_search(**kwargs: Any) -> BaseTool:
return MetaphorSearchResults(api_wrapper=MetaphorSearchAPIWrapp... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-7 | "wolfram-alpha": (_get_wolfram_alpha, ["wolfram_alpha_appid"]),
"google-search": (_get_google_search, ["google_api_key", "google_cse_id"]),
"google-search-results-json": (
_get_google_search_results_json,
["google_api_key", "google_cse_id", "num_results"],
),
"searx-search-results-json":... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-8 | ),
"human": (_get_human_tool, ["prompt_func", "input_func"]),
"awslambda": (
_get_lambda_api,
["awslambda_tool_name", "awslambda_tool_description", "function_name"],
),
"sceneXplain": (_get_scenexplain, []),
"graphql": (_get_graphql_tool, ["graphql_endpoint"]),
"openweathermap-ap... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-9 | model_repo_id=model_repo_id,
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 NotImplemen... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-10 | ]
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)
... | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d4aa5cd5aecb-11 | return (
list(_BASE_TOOLS)
+ list(_EXTRA_OPTIONAL_TOOLS)
+ list(_EXTRA_LLM_TOOLS)
+ list(_LLM_TOOLS)
)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
7f5b2503e62f-0 | Source code for langchain.agents.agent_types
from enum import Enum
[docs]class AgentType(str, Enum):
ZERO_SHOT_REACT_DESCRIPTION = "zero-shot-react-description"
REACT_DOCSTORE = "react-docstore"
SELF_ASK_WITH_SEARCH = "self-ask-with-search"
CONVERSATIONAL_REACT_DESCRIPTION = "conversational-react-descri... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_types.html |
814fe927731f-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://python.langchain.com/en/latest/_modules/langchain/agents/self_ask_with_search/base.html |
814fe927731f-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://python.langchain.com/en/latest/_modules/langchain/agents/self_ask_with_search/base.html |
a8d347aef8ed-0 | Source code for langchain.agents.mrkl.base
"""Attempt to implement MRKL systems as described in arxiv.org/pdf/2205.00445.pdf."""
from __future__ import annotations
from typing import Any, Callable, List, NamedTuple, Optional, Sequence
from pydantic import Field
from langchain.agents.agent import Agent, AgentExecutor, A... | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
a8d347aef8ed-1 | @property
def observation_prefix(self) -> str:
"""Prefix to append the observation with."""
return "Observation: "
@property
def llm_prefix(self) -> str:
"""Prefix to append the llm call with."""
return "Thought:"
[docs] @classmethod
def create_prompt(
cls,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
a8d347aef8ed-2 | llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
output_parser: Optional[AgentOutputParser] = None,
prefix: str = PREFIX,
suffix: str = SUFFIX,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variable... | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
a8d347aef8ed-3 | Example:
.. code-block:: python
from langchain import OpenAI, MRKLChain
from langchain.chains.mrkl.base import ChainConfig
llm = OpenAI(temperature=0)
prompt = PromptTemplate(...)
chains = [...]
mrkl = MRKLChain.from_chains(llm=llm, prompt=... | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
a8d347aef8ed-4 | ]
mrkl = MRKLChain.from_chains(llm, chains)
"""
tools = [
Tool(
name=c.action_name,
func=c.action,
description=c.action_description,
)
for c in chains
]
agent = ZeroShotAgent.from_llm_and_... | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
ca36bc409a1f-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://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
ca36bc409a1f-1 | if agent_scratchpad:
return (
f"This was your previous work "
f"(but I haven't seen any of it! I only see what "
f"you return as final answer):\n{agent_scratchpad}"
)
else:
return agent_scratchpad
@classmethod
def _valid... | https://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
ca36bc409a1f-2 | template = "\n\n".join([prefix, formatted_tools, format_instructions, suffix])
if input_variables is None:
input_variables = ["input", "agent_scratchpad"]
_memory_prompts = memory_prompts or []
messages = [
SystemMessagePromptTemplate.from_template(template),
... | https://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
ca36bc409a1f-3 | )
tool_names = [tool.name for tool in tools]
_output_parser = output_parser or cls._get_default_output_parser(llm=llm)
return cls(
llm_chain=llm_chain,
allowed_tools=tool_names,
output_parser=_output_parser,
**kwargs,
)
@property
de... | https://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
06a75d609a82-0 | Source code for langchain.agents.conversational_chat.base
"""An agent designed to hold a conversation in addition to using tools."""
from __future__ import annotations
from typing import Any, List, Optional, Sequence, Tuple
from pydantic import Field
from langchain.agents.agent import Agent, AgentOutputParser
from lang... | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
06a75d609a82-1 | return "Observation: "
@property
def llm_prefix(self) -> str:
"""Prefix to append the llm call with."""
return "Thought:"
@classmethod
def _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
super()._validate_tools(tools)
validate_tools_single_input(cls.__name__, too... | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
06a75d609a82-2 | ) -> List[BaseMessage]:
"""Construct the scratchpad that lets the agent continue its thought process."""
thoughts: List[BaseMessage] = []
for action, observation in intermediate_steps:
thoughts.append(AIMessage(content=action.log))
human_message = HumanMessage(
... | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
06a75d609a82-3 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
69235be6ec59-0 | Source code for langchain.agents.agent_toolkits.spark_sql.base
"""Spark SQL agent."""
from typing import Any, Dict, List, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.spark_sql.prompt import SQL_PREFIX, SQL_SUFFIX
from langchain.agents.agent_toolkits.spark_sql.toolkit i... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/base.html |
69235be6ec59-1 | )
llm_chain = LLMChain(
llm=llm,
prompt=prompt,
callback_manager=callback_manager,
)
tool_names = [tool.name for tool in tools]
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
return AgentExecutor.from_agent_and_tools(
agent=agent,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/base.html |
68a1e1b12f0b-0 | Source code for langchain.agents.agent_toolkits.spark_sql.toolkit
"""Toolkit for interacting with Spark SQL."""
from typing import List
from pydantic import Field
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.base_language import BaseLanguageModel
from langchain.tools import BaseTool
from ... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/toolkit.html |
92819d8d879f-0 | Source code for langchain.agents.agent_toolkits.nla.toolkit
"""Toolkit for interacting with API's using natural language."""
from __future__ import annotations
from typing import Any, List, Optional, Sequence
from pydantic import Field
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.agents.a... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html |
92819d8d879f-1 | )
http_operation_tools.append(endpoint_tool)
return http_operation_tools
[docs] @classmethod
def from_llm_and_spec(
cls,
llm: BaseLanguageModel,
spec: OpenAPISpec,
requests: Optional[Requests] = None,
verbose: bool = False,
**kwargs: Any,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html |
92819d8d879f-2 | spec = OpenAPISpec.from_url(ai_plugin.api.url)
# TODO: Merge optional Auth information with the `requests` argument
return cls.from_llm_and_spec(
llm=llm,
spec=spec,
requests=requests,
verbose=verbose,
**kwargs,
)
[docs] @classmethod... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html |
e3526c941a3f-0 | Source code for langchain.agents.agent_toolkits.python.base
"""Python agent."""
from typing import Any, Dict, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.python.prompt import PREFIX
from langchain.agents.mrkl.base import ZeroShotAgent
from langchain.base_language impor... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/python/base.html |
4b26522d10e2-0 | Source code for langchain.agents.agent_toolkits.zapier.toolkit
"""Zapier Toolkit."""
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.zapier.tool import ZapierNLARunAction
from langchain.utilities.zapier import ZapierNLAWrappe... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/zapier/toolkit.html |
75e3990c850f-0 | Source code for langchain.agents.agent_toolkits.azure_cognitive_services.toolkit
from __future__ import annotations
import sys
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools.azure_cognitive_services import (
AzureCogsFormRecognizerTool,
AzureCogsImageAn... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/azure_cognitive_services/toolkit.html |
9b7a8f480f99-0 | Source code for langchain.agents.agent_toolkits.file_management.toolkit
"""Toolkit for interacting with the local filesystem."""
from __future__ import annotations
from typing import List, Optional
from pydantic import root_validator
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools impo... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/file_management/toolkit.html |
9b7a8f480f99-1 | )
return values
[docs] def get_tools(self) -> List[BaseTool]:
"""Get the tools in the toolkit."""
allowed_tools = self.selected_tools or _FILE_TOOLS.keys()
tools: List[BaseTool] = []
for tool in allowed_tools:
tool_cls = _FILE_TOOLS[tool]
tools.append(t... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/file_management/toolkit.html |
1c2394e23300-0 | Source code for langchain.agents.agent_toolkits.playwright.toolkit
"""Playwright web browser toolkit."""
from __future__ import annotations
from typing import TYPE_CHECKING, List, Optional, Type, cast
from pydantic import Extra, root_validator
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/playwright/toolkit.html |
1c2394e23300-1 | """Check that the arguments are valid."""
lazy_import_playwright_browsers()
if values.get("async_browser") is None and values.get("sync_browser") is None:
raise ValueError("Either async_browser or sync_browser must be specified.")
return values
[docs] def get_tools(self) -> List[B... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/playwright/toolkit.html |
a87ff55696d0-0 | Source code for langchain.agents.agent_toolkits.openapi.base
"""OpenAPI spec agent."""
from typing import Any, Dict, List, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.openapi.prompt import (
OPENAPI_PREFIX,
OPENAPI_SUFFIX,
)
from langchain.agents.agent_toolkits... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/base.html |
a87ff55696d0-1 | input_variables=input_variables,
)
llm_chain = LLMChain(
llm=llm,
prompt=prompt,
callback_manager=callback_manager,
)
tool_names = [tool.name for tool in tools]
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
return AgentExecutor.from_agent_... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/base.html |
0b96dbf2d76c-0 | Source code for langchain.agents.agent_toolkits.openapi.toolkit
"""Requests toolkit."""
from __future__ import annotations
from typing import Any, List
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.agents.agent_toolkits.json.base import crea... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/toolkit.html |
0b96dbf2d76c-1 | func=self.json_agent.run,
description=DESCRIPTION,
)
request_toolkit = RequestsToolkit(requests_wrapper=self.requests_wrapper)
return [*request_toolkit.get_tools(), json_agent_tool]
[docs] @classmethod
def from_llm(
cls,
llm: BaseLanguageModel,
json_spe... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/toolkit.html |
522d4e922f96-0 | Source code for langchain.agents.agent_toolkits.json.base
"""Json agent."""
from typing import Any, Dict, List, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX
from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/base.html |
522d4e922f96-1 | return AgentExecutor.from_agent_and_tools(
agent=agent,
tools=tools,
callback_manager=callback_manager,
verbose=verbose,
**(agent_executor_kwargs or {}),
)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/base.html |
3b75827cc5df-0 | Source code for langchain.agents.agent_toolkits.json.toolkit
"""Toolkit for interacting with a JSON spec."""
from __future__ import annotations
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.json.tool import JsonGetValueTool... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/toolkit.html |
8c6139006b28-0 | Source code for langchain.agents.agent_toolkits.jira.toolkit
"""Jira Toolkit."""
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.jira.tool import JiraAction
from langchain.utilities.jira import JiraAPIWrapper
[docs]class Jira... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/jira/toolkit.html |
981a4c90b86d-0 | Source code for langchain.agents.agent_toolkits.powerbi.chat_base
"""Power BI agent."""
from typing import Any, Dict, List, Optional
from langchain.agents import AgentExecutor
from langchain.agents.agent import AgentOutputParser
from langchain.agents.agent_toolkits.powerbi.prompt import (
POWERBI_CHAT_PREFIX,
P... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/chat_base.html |
981a4c90b86d-1 | """
if toolkit is None:
if powerbi is None:
raise ValueError("Must provide either a toolkit or powerbi dataset")
toolkit = PowerBIToolkit(powerbi=powerbi, llm=llm, examples=examples)
tools = toolkit.get_tools()
agent = ConversationalChatAgent.from_llm_and_tools(
llm=llm,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/chat_base.html |
8b10bdd7d2d6-0 | Source code for langchain.agents.agent_toolkits.powerbi.base
"""Power BI agent."""
from typing import Any, Dict, List, Optional
from langchain.agents import AgentExecutor
from langchain.agents.agent_toolkits.powerbi.prompt import (
POWERBI_PREFIX,
POWERBI_SUFFIX,
)
from langchain.agents.agent_toolkits.powerbi.t... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/base.html |
8b10bdd7d2d6-1 | tools = toolkit.get_tools()
agent = ZeroShotAgent(
llm_chain=LLMChain(
llm=llm,
prompt=ZeroShotAgent.create_prompt(
tools,
prefix=prefix.format(top_k=top_k),
suffix=suffix,
format_instructions=format_instructions,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/base.html |
119df904a53a-0 | Source code for langchain.agents.agent_toolkits.powerbi.toolkit
"""Toolkit for interacting with a Power BI dataset."""
from typing import List, Optional
from pydantic import Field
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.base_language import BaseLanguageModel
from langchain.callbacks.... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html |
119df904a53a-1 | prompt=PromptTemplate(
template=QUESTION_TO_QUERY,
input_variables=["tool_input", "tables", "schemas", "examples"],
),
)
return [
QueryPowerBITool(
llm_chain=chain,
powerbi=self.powerbi,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html |
4093ceb62907-0 | Source code for langchain.agents.agent_toolkits.csv.base
"""Agent for working with csvs."""
from typing import Any, List, Optional, Union
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent
from langchain.base_language import BaseLanguag... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/csv/base.html |
31d455d7af14-0 | Source code for langchain.agents.agent_toolkits.gmail.toolkit
from __future__ import annotations
from typing import TYPE_CHECKING, List
from pydantic import Field
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.gmail.create_draft import GmailCreateD... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/gmail/toolkit.html |
3a0850d81ae8-0 | Source code for langchain.agents.agent_toolkits.spark.base
"""Agent for working with pandas objects."""
from typing import Any, Dict, List, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.spark.prompt import PREFIX, SUFFIX
from langchain.agents.mrkl.base import ZeroShotAge... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark/base.html |
3a0850d81ae8-1 | ) -> AgentExecutor:
"""Construct a spark agent from an LLM and dataframe."""
if not _validate_spark_df(df) and not _validate_spark_connect_df(df):
raise ValueError("Spark is not installed. run `pip install pyspark`.")
if input_variables is None:
input_variables = ["df", "input", "agent_scrat... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark/base.html |
7ffa58dff56c-0 | Source code for langchain.agents.agent_toolkits.pandas.base
"""Agent for working with pandas objects."""
from typing import Any, Dict, List, Optional, Tuple
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.pandas.prompt import (
MULTI_DF_PREFIX,
PREFIX,
SUFFIX_NO_DF,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html |
7ffa58dff56c-1 | df_locals = {}
for i, dataframe in enumerate(dfs):
df_locals[f"df{i + 1}"] = dataframe
tools = [PythonAstREPLTool(locals=df_locals)]
prompt = ZeroShotAgent.create_prompt(
tools, prefix=prefix, suffix=suffix_to_use, input_variables=input_variables
)
partial_prompt = prompt.partial()
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html |
7ffa58dff56c-2 | prompt = ZeroShotAgent.create_prompt(
tools, prefix=prefix, suffix=suffix_to_use, input_variables=input_variables
)
partial_prompt = prompt.partial()
if "df_head" in input_variables:
partial_prompt = partial_prompt.partial(df_head=str(df.head().to_markdown()))
return partial_prompt, tool... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html |
7ffa58dff56c-3 | include_df_in_prompt=include_df_in_prompt,
)
[docs]def create_pandas_dataframe_agent(
llm: BaseLanguageModel,
df: Any,
callback_manager: Optional[BaseCallbackManager] = None,
prefix: Optional[str] = None,
suffix: Optional[str] = None,
input_variables: Optional[List[str]] = None,
verb... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html |
7ffa58dff56c-4 | return_intermediate_steps=return_intermediate_steps,
max_iterations=max_iterations,
max_execution_time=max_execution_time,
early_stopping_method=early_stopping_method,
**(agent_executor_kwargs or {}),
)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last upda... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html |
9c4980117a85-0 | Source code for langchain.agents.agent_toolkits.vectorstore.base
"""VectorStore agent."""
from typing import Any, Dict, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.vectorstore.prompt import PREFIX, ROUTER_PREFIX
from langchain.agents.agent_toolkits.vectorstore.toolkit ... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html |
9c4980117a85-1 | )
[docs]def create_vectorstore_router_agent(
llm: BaseLanguageModel,
toolkit: VectorStoreRouterToolkit,
callback_manager: Optional[BaseCallbackManager] = None,
prefix: str = ROUTER_PREFIX,
verbose: bool = False,
agent_executor_kwargs: Optional[Dict[str, Any]] = None,
**kwargs: Dict[str, Any]... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html |
d0b8b025aef3-0 | Source code for langchain.agents.agent_toolkits.vectorstore.toolkit
"""Toolkit for interacting with a vector store."""
from typing import List
from pydantic import BaseModel, Field
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.base_language import BaseLanguageModel
from langchain.llms.open... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/toolkit.html |
d0b8b025aef3-1 | self.vectorstore_info.name, self.vectorstore_info.description
)
qa_with_sources_tool = VectorStoreQAWithSourcesTool(
name=f"{self.vectorstore_info.name}_with_sources",
description=description,
vectorstore=self.vectorstore_info.vectorstore,
llm=self.llm,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/toolkit.html |
81f65623fd5f-0 | Source code for langchain.agents.agent_toolkits.sql.base
"""SQL agent."""
from typing import Any, Dict, List, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.sql.prompt import SQL_PREFIX, SQL_SUFFIX
from langchain.agents.agent_toolkits.sql.toolkit import SQLDatabaseToolkit... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/base.html |
81f65623fd5f-1 | )
llm_chain = LLMChain(
llm=llm,
prompt=prompt,
callback_manager=callback_manager,
)
tool_names = [tool.name for tool in tools]
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
return AgentExecutor.from_agent_and_tools(
agent=agent,
... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/base.html |
2c5e20965857-0 | Source code for langchain.agents.agent_toolkits.sql.toolkit
"""Toolkit for interacting with a SQL database."""
from typing import List
from pydantic import Field
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.base_language import BaseLanguageModel
from langchain.sql_database import SQLDatab... | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/toolkit.html |
5095068df567-0 | Source code for langchain.agents.conversational.base
"""An agent designed to hold a conversation in addition to using tools."""
from __future__ import annotations
from typing import Any, List, Optional, Sequence
from pydantic import Field
from langchain.agents.agent import Agent, AgentOutputParser
from langchain.agents... | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational/base.html |
5095068df567-1 | [docs] @classmethod
def create_prompt(
cls,
tools: Sequence[BaseTool],
prefix: str = PREFIX,
suffix: str = SUFFIX,
format_instructions: str = FORMAT_INSTRUCTIONS,
ai_prefix: str = "AI",
human_prefix: str = "Human",
input_variables: Optional[List[str... | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational/base.html |
5095068df567-2 | super()._validate_tools(tools)
validate_tools_single_input(cls.__name__, tools)
[docs] @classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
output_parser: Optional[Agent... | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational/base.html |
1a7a07310cc9-0 | 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://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
1a7a07310cc9-1 | 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://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
1a7a07310cc9-2 | 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()]
if len(lookups) == 0:
return "No Results"
elif sel... | https://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
1a7a07310cc9-3 | 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=OpenAI())
"""
def __init__(self, llm... | https://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
9146411db376-0 | Source code for langchain.utilities.spark_sql
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Iterable, List, Optional
if TYPE_CHECKING:
from pyspark.sql import DataFrame, Row, SparkSession
[docs]class SparkSQL:
def __init__(
self,
spark_session: Optional[SparkSession] ... | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html |
9146411db376-1 | f"ignore_tables {missing_tables} not found in database"
)
usable_tables = self.get_usable_table_names()
self._usable_tables = set(usable_tables) if usable_tables else self._all_tables
if not isinstance(sample_rows_in_table_info, int):
raise TypeError("sample_rows_in_t... | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html |
9146411db376-2 | )
# Ignore the data source provider and options to reduce the number of tokens.
using_clause_index = statement.find("USING")
return statement[:using_clause_index] + ";"
[docs] def get_table_info(self, table_names: Optional[List[str]] = None) -> str:
all_table_names = self.get_usable_t... | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html |
9146411db376-3 | f"{self._sample_rows_in_table_info} rows from {table} table:\n"
f"{columns_str}\n"
f"{sample_rows_str}"
)
def _convert_row_as_tuple(self, row: Row) -> tuple:
return tuple(map(str, row.asDict().values()))
def _get_dataframe_results(self, df: DataFrame) -> list:
ret... | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html |
9146411db376-4 | If the statement throws an error, the error message is returned.
"""
try:
from pyspark.errors import PySparkException
except ImportError:
raise ValueError(
"pyspark is not installed. Please install it with `pip install pyspark`"
)
try:
... | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html |
f9218833d2ed-0 | Source code for langchain.utilities.python
import sys
from io import StringIO
from typing import Dict, Optional
from pydantic import BaseModel, Field
[docs]class PythonREPL(BaseModel):
"""Simulates a standalone Python REPL."""
globals: Optional[Dict] = Field(default_factory=dict, alias="_globals")
locals: O... | https://python.langchain.com/en/latest/_modules/langchain/utilities/python.html |
41aa4b86750a-0 | Source code for langchain.utilities.bash
"""Wrapper around subprocess to run commands."""
from __future__ import annotations
import platform
import re
import subprocess
from typing import TYPE_CHECKING, List, Union
from uuid import uuid4
if TYPE_CHECKING:
import pexpect
def _lazy_import_pexpect() -> pexpect:
""... | https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html |
41aa4b86750a-1 | # Set the custom prompt
process.sendline("PS1=" + prompt)
process.expect_exact(prompt, timeout=10)
return process
[docs] def run(self, commands: Union[str, List[str]]) -> str:
"""Run commands and return final output."""
if isinstance(commands, str):
commands = [com... | https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html |
41aa4b86750a-2 | self.process.expect(self.prompt, timeout=10)
self.process.sendline("")
try:
self.process.expect([self.prompt, pexpect.EOF], timeout=10)
except pexpect.TIMEOUT:
return f"Timeout error while executing command {command}"
if self.process.after == pexpect.EOF:
... | https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html |
bbbcae0ed7de-0 | Source code for langchain.utilities.google_places_api
"""Chain that calls Google Places API.
"""
import logging
from typing import Any, Dict, Optional
from pydantic import BaseModel, Extra, root_validator
from langchain.utils import get_from_dict_or_env
[docs]class GooglePlacesAPIWrapper(BaseModel):
"""Wrapper arou... | https://python.langchain.com/en/latest/_modules/langchain/utilities/google_places_api.html |
bbbcae0ed7de-1 | except ImportError:
raise ImportError(
"Could not import googlemaps python package. "
"Please install it with `pip install googlemaps`."
)
return values
[docs] def run(self, query: str) -> str:
"""Run Places search and get k number of places tha... | https://python.langchain.com/en/latest/_modules/langchain/utilities/google_places_api.html |
bbbcae0ed7de-2 | "formatted_address", "Unknown"
)
phone_number = place_details.get("result", {}).get(
"formatted_phone_number", "Unknown"
)
website = place_details.get("result", {}).get("website", "Unknown")
formatted_details = (
f"{name}\nAddre... | https://python.langchain.com/en/latest/_modules/langchain/utilities/google_places_api.html |
ba0c4b2dda5d-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://python.langchain.com/en/latest/_modules/langchain/utilities/graphql.html |
ba0c4b2dda5d-1 | result = self._execute_query(query)
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)
retur... | https://python.langchain.com/en/latest/_modules/langchain/utilities/graphql.html |
144320f4bd6f-0 | Source code for langchain.utilities.duckduckgo_search
"""Util that calls DuckDuckGo Search.
No setup required. Free.
https://pypi.org/project/duckduckgo-search/
"""
from typing import Dict, List, Optional
from pydantic import BaseModel, Extra
from pydantic.class_validators import root_validator
[docs]class DuckDuckGoSe... | https://python.langchain.com/en/latest/_modules/langchain/utilities/duckduckgo_search.html |
144320f4bd6f-1 | )
if results is None or len(results) == 0:
return ["No good DuckDuckGo Search Result was found"]
snippets = [result["body"] for result in results]
return snippets
[docs] def run(self, query: str) -> str:
snippets = self.get_snippets(query)
return " ".join(snippets)... | https://python.langchain.com/en/latest/_modules/langchain/utilities/duckduckgo_search.html |
382b78a907e2-0 | Source code for langchain.utilities.apify
from typing import Any, Callable, Dict, Optional
from pydantic import BaseModel, root_validator
from langchain.document_loaders import ApifyDatasetLoader
from langchain.document_loaders.base import Document
from langchain.utils import get_from_dict_or_env
[docs]class ApifyWrapp... | https://python.langchain.com/en/latest/_modules/langchain/utilities/apify.html |
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