id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 50 116 |
|---|---|---|
5c927e361f46-7 | output_parser: AgentOutputParser
allowed_tools: Set[str] = set()
[docs] def get_allowed_tools(self) -> Set[str]:
return self.allowed_tools
@property
def return_values(self) -> List[str]:
return ["output"]
def _fix_text(self, text: str) -> str:
"""Fix the text."""
raise... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-8 | """
full_inputs = self.get_full_inputs(intermediate_steps, **kwargs)
full_output = self.llm_chain.predict(callbacks=callbacks, **full_inputs)
return self.output_parser.parse(full_output)
[docs] async def aplan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
c... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-9 | @root_validator()
def validate_prompt(cls, values: Dict) -> Dict:
"""Validate that prompt matches format."""
prompt = values["llm_chain"].prompt
if "agent_scratchpad" not in prompt.input_variables:
logger.warning(
"`agent_scratchpad` should be a variable in prompt... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-10 | llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
output_parser: Optional[AgentOutputParser] = None,
**kwargs: Any,
) -> Agent:
"""Construct an agent from an LLM and tools."""
cls._validate_tools(tools)
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-11 | thoughts += (
"\n\nI now need to return a final answer based on the previous steps:"
)
new_inputs = {"agent_scratchpad": thoughts, "stop": self._stop}
full_inputs = {**kwargs, **new_inputs}
full_output = self.llm_chain.predict(**full_inputs)
# ... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-12 | agent: Union[BaseSingleActionAgent, BaseMultiActionAgent]
tools: Sequence[BaseTool]
return_intermediate_steps: bool = False
max_iterations: Optional[int] = 15
max_execution_time: Optional[float] = None
early_stopping_method: str = "force"
handle_parsing_errors: bool = False
[docs] @classmetho... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-13 | raise ValueError(
"Tools that have `return_direct=True` are not allowed "
"in multi-action agents"
)
return values
[docs] def save(self, file_path: Union[Path, str]) -> None:
"""Raise error - saving not supported for Agent Executors.... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-14 | 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.verbose)
final_output = output.return_values
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-15 | **inputs,
)
except Exception as e:
if not self.handle_parsing_errors:
raise e
text = str(e).split("`")[1]
observation = "Invalid or incomplete response"
output = AgentAction("_Exception", observation, text)
tool_run_kwargs =... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-16 | )
else:
tool_run_kwargs = self.agent.tool_run_logging_kwargs()
observation = InvalidTool().run(
agent_action.tool,
verbose=self.verbose,
color=None,
callbacks=run_manager.get_child() if run_manage... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-17 | **tool_run_kwargs,
)
return [(output, observation)]
# If the tool chosen is the finishing tool, then we end and return.
if isinstance(output, AgentFinish):
return output
actions: List[AgentAction]
if isinstance(output, AgentAction):
actions... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-18 | 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:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-19 | if tool_return is not None:
return self._return(tool_return, intermediate_steps)
iterations += 1
time_elapsed = time.time() - start_time
output = self.agent.return_stopped_response(
self.early_stopping_method, intermediate_steps, **inputs
)
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
5c927e361f46-20 | intermediate_steps.extend(next_step_output)
if len(next_step_output) == 1:
next_step_action = next_step_output[0]
# See if tool should return directly
tool_return = self._get_tool_return(next_step_action)
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent.html |
f89cce295255-0 | Source code for langchain.agents.loading
"""Functionality for loading agents."""
import json
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 import AGENT_TO_CLA... | https:///python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
f89cce295255-1 | "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... | https:///python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
f89cce295255-2 | """Load agent from file."""
# Convert file to Path object.
if isinstance(file, str):
file_path = Path(file)
else:
file_path = file
# Load from either json or yaml.
if file_path.suffix == ".json":
with open(file_path) as f:
config = json.load(f)
elif file_path.... | https:///python.langchain.com/en/latest/_modules/langchain/agents/loading.html |
d45a7b1ce8e6-0 | 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.callbacks.base import BaseCallbackManager
from langchain.chains.api imp... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-1 | from langchain.utilities.bing_search import BingSearchAPIWrapper
from langchain.utilities.duckduckgo_search import DuckDuckGoSearchAPIWrapper
from langchain.utilities.google_search import GoogleSearchAPIWrapper
from langchain.utilities.google_serper import GoogleSerperAPIWrapper
from langchain.utilities.awslambda impor... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-2 | "requests_delete": _get_tools_requests_delete,
"terminal": _get_terminal,
}
def _get_pal_math(llm: BaseLLM) -> BaseTool:
return Tool(
name="PAL-MATH",
description="A language model that is really good at solving complex word math problems. Input should be a fully worded hard word math problem.",... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-3 | func=chain.run,
)
_LLM_TOOLS: Dict[str, Callable[[BaseLLM], BaseTool]] = {
"pal-math": _get_pal_math,
"pal-colored-objects": _get_pal_colored_objects,
"llm-math": _get_llm_math,
"open-meteo-api": _get_open_meteo_api,
}
def _get_news_api(llm: BaseLLM, **kwargs: Any) -> BaseTool:
news_api_key = kw... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-4 | listen_api_key = kwargs["listen_api_key"]
chain = APIChain.from_llm_and_api_docs(
llm,
podcast_docs.PODCAST_DOCS,
headers={"X-ListenAPI-Key": listen_api_key},
)
return Tool(
name="Podcast API",
description="Use the Listen Notes Podcast API to search all podcasts or ep... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-5 | )
def _get_google_search_results_json(**kwargs: Any) -> BaseTool:
return GoogleSearchResults(api_wrapper=GoogleSearchAPIWrapper(**kwargs))
def _get_serpapi(**kwargs: Any) -> BaseTool:
return Tool(
name="Search",
description="A search engine. Useful for when you need to answer questions about cur... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-6 | ] = {
"news-api": (_get_news_api, ["news_api_key"]),
"tmdb-api": (_get_tmdb_api, ["tmdb_bearer_token"]),
"podcast-api": (_get_podcast_api, ["listen_api_key"]),
}
_EXTRA_OPTIONAL_TOOLS: Dict[str, Tuple[Callable[[KwArg(Any)], BaseTool], List[str]]] = {
"wolfram-alpha": (_get_wolfram_alpha, ["wolfram_alpha... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-7 | ),
"human": (_get_human_tool, ["prompt_func", "input_func"]),
"awslambda": (
_get_lambda_api,
["awslambda_tool_name", "awslambda_tool_description", "function_name"],
),
"sceneXplain": (_get_scenexplain, []),
}
[docs]def load_tools(
tool_names: List[str],
llm: Optional[BaseLLM] = ... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-8 | tool = _LLM_TOOLS[name](llm)
if callback_manager is not None:
tool.callback_manager = callback_manager
tools.append(tool)
elif name in _EXTRA_LLM_TOOLS:
if llm is None:
raise ValueError(f"Tool {name} requires an LLM to be provided")
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
d45a7b1ce8e6-9 | + list(_LLM_TOOLS)
)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/agents/load_tools.html |
6e5ba8cb8c29-0 | 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 |
53f66f9fd96e-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 |
53f66f9fd96e-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 |
0f0f64794ff6-0 | 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 |
0f0f64794ff6-1 | @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 |
0f0f64794ff6-2 | 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 |
0f0f64794ff6-3 | 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 |
0f0f64794ff6-4 | ]
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 |
10c75015d3d2-0 | 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 (
StructuredChatOutputParser,
StructuredChatOu... | https:///python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
10c75015d3d2-1 | 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... | https:///python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
10c75015d3d2-2 | ]
if input_variables is None:
input_variables = ["input", "agent_scratchpad"]
return ChatPromptTemplate(input_variables=input_variables, messages=messages)
[docs] @classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
41ad86eec50f-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 |
41ad86eec50f-1 | @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__, tools)
[docs] @classmethod
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
41ad86eec50f-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 |
41ad86eec50f-3 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
170b68b18d01-0 | 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 |
170b68b18d01-1 | **kwargs,
)
http_operation_tools.append(endpoint_tool)
return http_operation_tools
[docs] @classmethod
def from_llm_and_spec(
cls,
llm: BaseLLM,
spec: OpenAPISpec,
requests: Optional[Requests] = None,
verbose: bool = False,
*... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html |
170b68b18d01-2 | 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 |
67680af5978b-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.callbacks.base impo... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/python/base.html |
d61fcfb17f4c-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 |
aaa72343d73a-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 |
aaa72343d73a-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 |
d31c51bdf2b1-0 | 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 |
d31c51bdf2b1-1 | """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 |
64c19ecdefae-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 |
64c19ecdefae-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 |
5937096f52cd-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 |
5937096f52cd-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: BaseLLM,
json_spec: JsonSpe... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/toolkit.html |
b3527005485c-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 |
b3527005485c-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 02, 2023. | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/base.html |
161eee782550-0 | 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 |
e90dcdddb7d1-0 | 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 |
b7bf7e964b80-0 | 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 |
b7bf7e964b80-1 | """
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 |
eee5d5be15db-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 |
eee5d5be15db-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 |
e267866f94fb-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 |
e267866f94fb-1 | prompt=PromptTemplate(
template=QUESTION_TO_QUERY,
input_variables=["tool_input", "tables", "schemas", "examples"],
),
)
return [
QueryPowerBITool(powerbi=self.powerbi),
InfoPowerBITool(powerbi=self.powerbi),
... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html |
8490680886fd-0 | Source code for langchain.agents.agent_toolkits.csv.base
"""Agent for working with csvs."""
from typing import Any, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent
from langchain.llms.base import BaseLLM
[docs]def create_csv... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/csv/base.html |
df65e82ab011-0 | Source code for langchain.agents.agent_toolkits.pandas.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.pandas.prompt import PREFIX, SUFFIX
from langchain.agents.mrkl.base import ZeroShotA... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html |
df65e82ab011-1 | tools, prefix=prefix, suffix=suffix, input_variables=input_variables
)
partial_prompt = prompt.partial(df=str(df.head().to_markdown()))
llm_chain = LLMChain(
llm=llm,
prompt=partial_prompt,
callback_manager=callback_manager,
)
tool_names = [tool.name for tool in tools]
ag... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/pandas/base.html |
abf17e9ebadf-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 |
abf17e9ebadf-1 | )
[docs]def create_vectorstore_router_agent(
llm: BaseLLM,
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],
) -> Age... | https:///python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html |
da77897a3789-0 | 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 |
da77897a3789-1 | 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 |
e6110299a666-0 | 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 |
e6110299a666-1 | 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/sql/base.html |
7ec791772f97-0 | 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 |
803e9522ff1e-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 |
803e9522ff1e-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 |
803e9522ff1e-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 |
dfeb96a0c61c-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 |
dfeb96a0c61c-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 |
dfeb96a0c61c-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 |
dfeb96a0c61c-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 |
d8ae66cc6af4-0 | 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 |
67cf54661e75-0 | 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 |
67cf54661e75-1 | # 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 |
67cf54661e75-2 | 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 |
2212631dee3e-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 |
2212631dee3e-1 | except ImportError:
raise ValueError(
"Could not import googlemaps python packge. "
"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 that ... | https:///python.langchain.com/en/latest/_modules/langchain/utilities/google_places_api.html |
2212631dee3e-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 |
365412f4423f-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 |
365412f4423f-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 " ".join(snippets)
[docs] def results(self, query: str, num_results: int) -> List[Dict[str, str]]:
"""Run query through D... | https:///python.langchain.com/en/latest/_modules/langchain/utilities/duckduckgo_search.html |
05aec7942165-0 | 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 |
05aec7942165-1 | *,
build: Optional[str] = None,
memory_mbytes: Optional[int] = None,
timeout_secs: Optional[int] = None,
) -> ApifyDatasetLoader:
"""Run an Actor on the Apify platform and wait for results to be ready.
Args:
actor_id (str): The ID or name of the Actor on the Apify... | https:///python.langchain.com/en/latest/_modules/langchain/utilities/apify.html |
05aec7942165-2 | memory_mbytes: Optional[int] = None,
timeout_secs: Optional[int] = None,
) -> ApifyDatasetLoader:
"""Run an Actor on the Apify platform and wait for results to be ready.
Args:
actor_id (str): The ID or name of the Actor on the Apify platform.
run_input (Dict): The inp... | https:///python.langchain.com/en/latest/_modules/langchain/utilities/apify.html |
9dd0ae5d44fd-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:///python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
9dd0ae5d44fd-1 | Other methods are are available for convenience.
: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 `accept... | https:///python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
9dd0ae5d44fd-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:///python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
9dd0ae5d44fd-3 | return {"language": "en", "format": "json"}
[docs]class SearxResults(dict):
"""Dict like wrapper around search api results."""
_data = ""
def __init__(self, data: str):
"""Take a raw result from Searx and make it into a dict like object."""
json_data = json.loads(data)
super().__init... | https:///python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
9dd0ae5d44fd-4 | .. 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",
un... | https:///python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
9dd0ae5d44fd-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:///python.langchain.com/en/latest/_modules/langchain/utilities/searx_search.html |
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