id stringlengths 14 16 | source stringlengths 49 117 | text stringlengths 16 2.73k |
|---|---|---|
c3f85dae222b-13 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | [docs] def save(self, file_path: Union[Path, str]) -> None:
"""Raise error - saving not supported for Agent Executors."""
raise ValueError(
"Saving not supported for agent executors. "
"If you are trying to save the agent, please use the "
"`.save_agent(...)`"
... |
c3f85dae222b-14 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | run_manager.on_agent_finish(output, color="green", verbose=self.verbose)
final_output = output.return_values
if self.return_intermediate_steps:
final_output["intermediate_steps"] = intermediate_steps
return final_output
async def _areturn(
self,
output: AgentFinis... |
c3f85dae222b-15 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | text = str(e)
if isinstance(self.handle_parsing_errors, bool):
if e.send_to_llm:
observation = str(e.observation)
text = str(e.llm_output)
else:
observation = "Invalid or incomplete response"
elif isinsta... |
c3f85dae222b-16 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | tool_run_kwargs["llm_prefix"] = ""
# We then call the tool on the tool input to get an observation
observation = tool.run(
agent_action.tool_input,
verbose=self.verbose,
color=color,
callbacks=run_manager.get... |
c3f85dae222b-17 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | text = str(e)
if isinstance(self.handle_parsing_errors, bool):
observation = "Invalid or incomplete response"
elif isinstance(self.handle_parsing_errors, str):
observation = self.handle_parsing_errors
elif callable(self.handle_parsing_errors):
... |
c3f85dae222b-18 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | # We then call the tool on the tool input to get an observation
observation = await tool.arun(
agent_action.tool_input,
verbose=self.verbose,
color=color,
callbacks=run_manager.get_child() if run_manager else None,
... |
c3f85dae222b-19 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | while self._should_continue(iterations, time_elapsed):
next_step_output = self._take_next_step(
name_to_tool_map,
color_mapping,
inputs,
intermediate_steps,
run_manager=run_manager,
)
if isinstance(next_s... |
c3f85dae222b-20 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | # Let's start tracking the number of iterations and time elapsed
iterations = 0
time_elapsed = 0.0
start_time = time.time()
# We now enter the agent loop (until it returns something).
async with asyncio_timeout(self.max_execution_time):
try:
while self... |
c3f85dae222b-21 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent.html | def _get_tool_return(
self, next_step_output: Tuple[AgentAction, str]
) -> Optional[AgentFinish]:
"""Check if the tool is a returning tool."""
agent_action, observation = next_step_output
name_to_tool_map = {tool.name: tool for tool in self.tools}
# Invalid tools won't be in ... |
a2281e9eafb6-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/loading.html | 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... |
a2281e9eafb6-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/loading.html | "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, "
"then tools must be provided"
)
return _load_agent_from_to... |
a2281e9eafb6-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/loading.html | 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)
else:
file_path = file
# Load from... |
9b4df087b96b-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | 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... |
9b4df087b96b-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | 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.utilities import PubMedAPIWrapper
from langchain.utilitie... |
9b4df087b96b-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | _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,
"requests_patch": _get_tools_requests_patch,
"requ... |
9b4df087b96b-3 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | 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 in... |
9b4df087b96b-4 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | 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 natural language that this API can answer.",
func=chain.run,
)
def _get_podcas... |
9b4df087b96b-5 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | def _get_pupmed(**kwargs: Any) -> BaseTool:
return PubmedQueryRun(api_wrapper=PubMedAPIWrapper(**kwargs))
def _get_google_serper(**kwargs: Any) -> BaseTool:
return GoogleSerperRun(api_wrapper=GoogleSerperAPIWrapper(**kwargs))
def _get_google_serper_results_json(**kwargs: Any) -> BaseTool:
return GoogleSerpe... |
9b4df087b96b-6 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | return BingSearchRun(api_wrapper=BingSearchAPIWrapper(**kwargs))
def _get_metaphor_search(**kwargs: Any) -> BaseTool:
return MetaphorSearchResults(api_wrapper=MetaphorSearchAPIWrapper(**kwargs))
def _get_ddg_search(**kwargs: Any) -> BaseTool:
return DuckDuckGoSearchRun(api_wrapper=DuckDuckGoSearchAPIWrapper(**k... |
9b4df087b96b-7 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | "google-search-results-json": (
_get_google_search_results_json,
["google_api_key", "google_cse_id", "num_results"],
),
"searx-search-results-json": (
_get_searx_search_results_json,
["searx_host", "engines", "num_results", "aiosession"],
),
"bing-search": (_get_bing_sear... |
9b4df087b96b-8 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | _get_lambda_api,
["awslambda_tool_name", "awslambda_tool_description", "function_name"],
),
"sceneXplain": (_get_scenexplain, []),
"graphql": (_get_graphql_tool, ["graphql_endpoint"]),
"openweathermap-api": (_get_openweathermap, ["openweathermap_api_key"]),
}
def _handle_callbacks(
callback_... |
9b4df087b96b-9 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | raise NotImplementedError("Multimodal outputs not supported yet.")
inputs = hf_tool.inputs
if set(inputs) != {"text"}:
raise NotImplementedError("Multimodal inputs not supported yet.")
return Tool.from_function(
hf_tool.__call__, name=hf_tool.name, description=hf_tool.description
)
[docs... |
9b4df087b96b-10 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | raise ValueError(f"Tool {name} requires an LLM to be provided")
tool = _LLM_TOOLS[name](llm)
tools.append(tool)
elif name in _EXTRA_LLM_TOOLS:
if llm is None:
raise ValueError(f"Tool {name} requires an LLM to be provided")
_get_llm_tool_func, extra... |
9b4df087b96b-11 | https://python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html | Last updated on Jun 04, 2023. |
205e737b9ace-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_types.html | 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... |
9f8a2efccdb9-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/self_ask_with_search/base.html | 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... |
9f8a2efccdb9-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/self_ask_with_search/base.html | 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 observation_prefix(self) -> str:
"""Prefix to append the observation with.""... |
64dae8923ba5-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html | 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... |
64dae8923ba5-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html | """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,
tools: Sequence[BaseTool],
prefix: str = PREFI... |
64dae8923ba5-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html | output_parser: Optional[AgentOutputParser] = None,
prefix: str = PREFIX,
suffix: str = SUFFIX,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
**kwargs: Any,
) -> Agent:
"""Construct an agent from an LLM and tools."""
... |
64dae8923ba5-3 | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html | llm = OpenAI(temperature=0)
prompt = PromptTemplate(...)
chains = [...]
mrkl = MRKLChain.from_chains(llm=llm, prompt=prompt)
"""
[docs] @classmethod
def from_chains(
cls, llm: BaseLanguageModel, chains: List[ChainConfig], **kwargs: Any
) -> AgentExecutor:
... |
64dae8923ba5-4 | https://python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html | for c in chains
]
agent = ZeroShotAgent.from_llm_and_tools(llm, tools)
return cls(agent=agent, tools=tools, **kwargs)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
b238d9ce7c54-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html | 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... |
b238d9ce7c54-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html | 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 _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
pass
@classmethod
def _get_default_outp... |
b238d9ce7c54-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html | input_variables = ["input", "agent_scratchpad"]
_memory_prompts = memory_prompts or []
messages = [
SystemMessagePromptTemplate.from_template(template),
*_memory_prompts,
HumanMessagePromptTemplate.from_template(human_message_template),
]
return ChatPr... |
b238d9ce7c54-3 | https://python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html | allowed_tools=tool_names,
output_parser=_output_parser,
**kwargs,
)
@property
def _agent_type(self) -> str:
raise ValueError
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
5edd752fc74d-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html | 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... |
5edd752fc74d-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html | 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__, tools)
[docs] @classmethod
def create... |
5edd752fc74d-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html | """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(
content=self.template_tool... |
13f6bc0acdf6-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/base.html | 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... |
13f6bc0acdf6-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/base.html | 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,
tools=tools,
callback_manager=callback_man... |
0277f2e36f00-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/toolkit.html | 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 ... |
65eeaddc89b3-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html | 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... |
65eeaddc89b3-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html | [docs] @classmethod
def from_llm_and_spec(
cls,
llm: BaseLanguageModel,
spec: OpenAPISpec,
requests: Optional[Requests] = None,
verbose: bool = False,
**kwargs: Any,
) -> NLAToolkit:
"""Instantiate the toolkit by creating tools for each operation."""
... |
65eeaddc89b3-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html | llm=llm,
spec=spec,
requests=requests,
verbose=verbose,
**kwargs,
)
[docs] @classmethod
def from_llm_and_ai_plugin_url(
cls,
llm: BaseLanguageModel,
ai_plugin_url: str,
requests: Optional[Requests] = None,
verbose: bo... |
c3e2e9a45d9a-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/python/base.html | 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... |
45d6e4d1e436-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/zapier/toolkit.html | 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... |
6c05e73cbce8-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/azure_cognitive_services/toolkit.html | 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... |
127f7f95e647-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/file_management/toolkit.html | 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... |
127f7f95e647-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/file_management/toolkit.html | [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(tool_cls(root_dir=self.ro... |
192ad0e7df49-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/playwright/toolkit.html | 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.... |
192ad0e7df49-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/playwright/toolkit.html | 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[BaseTool]:
"""Get the tools in the toolkit."""
tool_classes: List[Type[BaseBr... |
9d727ac170fb-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/base.html | 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... |
9d727ac170fb-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/base.html | 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,
tools=tools,
callback_man... |
0f3690429083-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/toolkit.html | 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... |
0f3690429083-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/toolkit.html | 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_spec: JsonSpec,
requests_wrapper: TextRequestsWrapper,
**kwargs: Any... |
dd808a785ca0-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/base.html | 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
... |
dd808a785ca0-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/base.html | agent=agent,
tools=tools,
callback_manager=callback_manager,
verbose=verbose,
**(agent_executor_kwargs or {}),
)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
12c705c929d5-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/toolkit.html | 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... |
79e0af2e3726-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/jira/toolkit.html | 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... |
1f3f12fb86b3-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/chat_base.html | 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... |
1f3f12fb86b3-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/chat_base.html | 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,
tools=tools,
system_... |
07133ad31154-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/base.html | 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... |
07133ad31154-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/base.html | 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,
input_variables=input_... |
2aa79f389206-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html | 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.... |
2aa79f389206-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html | input_variables=["tool_input", "tables", "schemas", "examples"],
),
)
return [
QueryPowerBITool(
llm_chain=chain,
powerbi=self.powerbi,
examples=self.examples,
max_iterations=self.max_iterations,
... |
db70c575911d-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/csv/base.html | 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... |
25912d1dbbb4-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/gmail/toolkit.html | 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... |
e3f8a3119413-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark/base.html | 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... |
e3f8a3119413-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark/base.html | 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_scratchpad"]
tools = [PythonAstREPLTool(locals={"df": df})]
prompt = ZeroShotAgent... |
af7b4dea533d-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html | 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,
... |
af7b4dea533d-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html | 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()
if "dfs_head" in input_variables:
dfs_head = "\n\n".... |
af7b4dea533d-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html | 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, tools
def _get_prompt_and_tools(
df: Any,
... |
af7b4dea533d-3 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html | llm: BaseLanguageModel,
df: Any,
callback_manager: Optional[BaseCallbackManager] = None,
prefix: Optional[str] = None,
suffix: Optional[str] = None,
input_variables: Optional[List[str]] = None,
verbose: bool = False,
return_intermediate_steps: bool = False,
max_iterations: Optional[int] ... |
af7b4dea533d-4 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html | **(agent_executor_kwargs or {}),
)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
7fc44e9ca9e6-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html | 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 ... |
7fc44e9ca9e6-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html | 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],
) -> AgentExecutor:
"""Construct a vectorst... |
b39686d4dd23-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/toolkit.html | 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... |
b39686d4dd23-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/toolkit.html | qa_with_sources_tool = VectorStoreQAWithSourcesTool(
name=f"{self.vectorstore_info.name}_with_sources",
description=description,
vectorstore=self.vectorstore_info.vectorstore,
llm=self.llm,
)
return [qa_tool, qa_with_sources_tool]
[docs]class VectorStoreRo... |
a98c72997ce6-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/base.html | 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... |
a98c72997ce6-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/base.html | 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,
tools=tools,
callback_manager=callback_man... |
593f9352cfa7-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/toolkit.html | 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... |
593f9352cfa7-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/toolkit.html | "Be sure that the tables actually exist by calling list_tables_sql_db "
"first! Example Input: 'table1, table2, table3'"
)
return [
QuerySQLDataBaseTool(
db=self.db, description=query_sql_database_tool_description
),
InfoSQLDatabaseTool(
... |
7b57b01bdca6-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational/base.html | 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... |
7b57b01bdca6-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational/base.html | 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]] = None,
) -> PromptTemplate:
"""Create prompt in the... |
7b57b01bdca6-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/conversational/base.html | cls,
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,
a... |
655782328839-0 | https://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html | 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... |
655782328839-1 | https://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html | 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 and Search, got {tool_names}"
)
@property
def observ... |
655782328839-2 | https://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html | 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 self.lookup_index >= len(lookups):
return "No More Results"
else:
result_prefix = f"(Result {self.lookup_index... |
655782328839-3 | https://python.langchain.com/en/latest/_modules/langchain/agents/react/base.html | from langchain import ReActChain, OpenAI
react = ReAct(llm=OpenAI())
"""
def __init__(self, llm: BaseLanguageModel, docstore: Docstore, **kwargs: Any):
"""Initialize with the LLM and a docstore."""
docstore_explorer = DocstoreExplorer(docstore)
tools = [
Tool(
... |
e4f69ab09515-0 | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html | 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] ... |
e4f69ab09515-1 | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html | 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_table_info must be an integer")
self._sample_rows_in_table_info = sample_ro... |
e4f69ab09515-2 | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html | # 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_table_names... |
e4f69ab09515-3 | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html | 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:
return list(map(self._convert_row_as_tuple, df.collect()))
[docs] def run(se... |
e4f69ab09515-4 | https://python.langchain.com/en/latest/_modules/langchain/utilities/spark_sql.html | except ImportError:
raise ValueError(
"pyspark is not installed. Please install it with `pip install pyspark`"
)
try:
return self.run(command, fetch)
except PySparkException as e:
"""Format the error message"""
return f"Error: {... |
0bed28959088-0 | https://python.langchain.com/en/latest/_modules/langchain/utilities/python.html | 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... |
87b84ea86f0a-0 | https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html | 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:
""... |
87b84ea86f0a-1 | https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html | 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 = [commands]
commands = ";".join(commands)
if self.process is no... |
87b84ea86f0a-2 | https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html | 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:
return f"Exited with error status: {self.process.exitstatus}"
output = self.process.before
... |
9563fec48070-0 | https://python.langchain.com/en/latest/_modules/langchain/utilities/google_places_api.html | 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... |
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