id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
aba37ea9c93c-0 | Source code for langchain.agents.structured_chat.base
import re
from typing import Any, List, Optional, Sequence, Tuple
from langchain.agents.agent import Agent, AgentOutputParser
from langchain.agents.structured_chat.output_parser import (
StructuredChatOutputParserWithRetries,
)
from langchain.agents.structured_c... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
aba37ea9c93c-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
aba37ea9c93c-2 | format_instructions = format_instructions.format(tool_names=tool_names)
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 =... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
aba37ea9c93c-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/base.html |
08c22033c5ad-0 | Source code for langchain.agents.structured_chat.output_parser
from __future__ import annotations
import json
import logging
import re
from typing import Optional, Union
from langchain.agents.agent import AgentOutputParser
from langchain.agents.structured_chat.prompt import FORMAT_INSTRUCTIONS
from langchain.output_par... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/output_parser.html |
08c22033c5ad-1 | @property
def _type(self) -> str:
return "structured_chat"
[docs]class StructuredChatOutputParserWithRetries(AgentOutputParser):
"""Output parser with retries for the structured chat agent."""
base_parser: AgentOutputParser = Field(default_factory=StructuredChatOutputParser)
"""The base parser t... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/output_parser.html |
08c22033c5ad-2 | else:
return cls()
@property
def _type(self) -> str:
return "structured_chat_with_retries" | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/structured_chat/output_parser.html |
ab7f6802f47d-0 | Source code for langchain.agents.openai_functions_multi_agent.base
"""Module implements an agent that uses OpenAI's APIs function enabled API."""
import json
from json import JSONDecodeError
from typing import Any, List, Optional, Sequence, Tuple, Union
from langchain.agents import BaseMultiActionAgent
from langchain.a... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
ab7f6802f47d-1 | f"Could not parse tool input: {function_call} because "
f"the `arguments` is not valid JSON."
)
try:
tools = arguments["actions"]
except (TypeError, KeyError):
raise OutputParserException(
f"Could not parse tool input: {function_call} b... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
ab7f6802f47d-2 | return_values={"output": message.content}, log=str(message.content)
)
[docs]class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
"""An Agent driven by OpenAIs function powered API.
Args:
llm: This should be an instance of ChatOpenAI, specifically a model
that supports using `functions`... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
ab7f6802f47d-3 | enum_vals = [t.name for t in self.tools]
tool_selection = {
# OpenAI functions returns a single tool invocation
# Here we force the single tool invocation it returns to
# itself be a list of tool invocations. We do this by constructing
# a new tool that has one ar... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
ab7f6802f47d-4 | "type": "object",
"properties": t.args,
}
for t in self.tools
],
},
},
"... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
ab7f6802f47d-5 | """Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date,
along with observations
**kwargs: User inputs.
Returns:
Action specifying what tool to use.
"""
agent_scratchpad = format_to_openai_function_... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
ab7f6802f47d-6 | else:
messages = []
messages.extend(
[
*_prompts,
HumanMessagePromptTemplate.from_template("{input}"),
MessagesPlaceholder(variable_name="agent_scratchpad"),
]
)
return ChatPromptTemplate(messages=messages)
[docs... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_multi_agent/base.html |
9fe7ec8cc2f8-0 | Source code for langchain.agents.xml.base
from typing import Any, List, Tuple, Union
from langchain.agents.agent import BaseSingleActionAgent
from langchain.agents.output_parsers.xml import XMLAgentOutputParser
from langchain.agents.xml.prompt import agent_instructions
from langchain.callbacks.base import Callbacks
fro... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/xml/base.html |
9fe7ec8cc2f8-1 | **kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
log = ""
for action, observation in intermediate_steps:
log += (
f"<tool>{action.tool}</tool><tool_input>{action.tool_input}"
f"</tool_input><observation>{observation}</observation>"
)
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/xml/base.html |
cd21a57a24d0-0 | Source code for langchain.agents.openai_assistant.base
from __future__ import annotations
import json
from json import JSONDecodeError
from time import sleep
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Tuple, Union
from langchain.callbacks.manager import CallbackManager
from langchain.load im... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-1 | ) from e
OutputType = Union[
List[OpenAIAssistantAction],
OpenAIAssistantFinish,
List["ThreadMessage"],
List["RequiredActionFunctionToolCall"],
]
[docs]class OpenAIAssistantRunnable(RunnableSerializable[Dict, OutputType]):
"""Run an OpenAI Assistant.
Example using OpenAI tools:
.. code-b... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-2 | Example using custom tools and custom execution:
.. code-block:: python
from langchain_experimental.openai_assistant import OpenAIAssistantRunnable
from langchain.agents import AgentExecutor
from langchain.schema.agent import AgentFinish
from langchain.tools impor... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-3 | """OpenAI client."""
assistant_id: str
"""OpenAI assistant id."""
check_every_ms: float = 1_000.0
"""Frequency with which to check run progress in ms."""
as_agent: bool = False
"""Use as a LangChain agent, compatible with the AgentExecutor."""
[docs] @classmethod
def create_assistant(
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-4 | ) -> OutputType:
"""Invoke assistant.
Args:
input: Runnable input dict that can have:
content: User message when starting a new run.
thread_id: Existing thread to use.
run_id: Existing run to use. Should only be supplied when providing
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-5 | # Starting a new thread and a new run.
elif "thread_id" not in input:
thread = {
"messages": [
{
"role": "user",
"content": input["content"],
"file_ids": input.get(... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-6 | ) -> dict:
last_action, last_output = intermediate_steps[-1]
run = self._wait_for_run(last_action.run_id, last_action.thread_id)
required_tool_call_ids = {
tc.id for tc in run.required_action.submit_tool_outputs.tool_calls
}
tool_outputs = [
{"output": out... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-7 | import openai
messages = self.client.beta.threads.messages.list(
run.thread_id, order="asc"
)
new_messages = [msg for msg in messages if msg.run_id == run.id]
if not self.as_agent:
return new_messages
answer: Any = [
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
cd21a57a24d0-8 | run_id=run.id,
thread_id=run.thread_id,
)
)
return actions
else:
run_info = json.dumps(run.dict(), indent=2)
raise ValueError(
f"Unexpected run status: {run.status}. Full run info:\n\n{run_info})"
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_assistant/base.html |
e1b90671500f-0 | Source code for langchain.agents.openai_functions_agent.base
"""Module implements an agent that uses OpenAI's APIs function enabled API."""
from typing import Any, List, Optional, Sequence, Tuple, Union
from langchain.agents import BaseSingleActionAgent
from langchain.agents.format_scratchpad.openai_functions import (
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/base.html |
e1b90671500f-1 | """
llm: BaseLanguageModel
tools: Sequence[BaseTool]
prompt: BasePromptTemplate
[docs] def get_allowed_tools(self) -> List[str]:
"""Get allowed tools."""
return [t.name for t in self.tools]
@root_validator
def validate_llm(cls, values: dict) -> dict:
if not isinstance(valu... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/base.html |
e1b90671500f-2 | Returns:
Action specifying what tool to use.
"""
agent_scratchpad = format_to_openai_function_messages(intermediate_steps)
selected_inputs = {
k: kwargs[k] for k in self.prompt.input_variables if k != "agent_scratchpad"
}
full_inputs = dict(**selected_inpu... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/base.html |
e1b90671500f-3 | prompt = self.prompt.format_prompt(**full_inputs)
messages = prompt.to_messages()
predicted_message = await self.llm.apredict_messages(
messages, functions=self.functions, callbacks=callbacks
)
agent_decision = OpenAIFunctionsAgentOutputParser._parse_ai_message(
p... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/base.html |
e1b90671500f-4 | ) -> BasePromptTemplate:
"""Create prompt for this agent.
Args:
system_message: Message to use as the system message that will be the
first in the prompt.
extra_prompt_messages: Prompt messages that will be placed between the
system message and the... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/base.html |
e1b90671500f-5 | llm=llm,
prompt=prompt,
tools=tools,
callback_manager=callback_manager,
**kwargs,
) | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/base.html |
7599199ee261-0 | Source code for langchain.agents.openai_functions_agent.agent_token_buffer_memory
"""Memory used to save agent output AND intermediate steps."""
from typing import Any, Dict, List
from langchain.agents.format_scratchpad.openai_functions import (
format_to_openai_function_messages,
)
from langchain.memory.chat_memor... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/agent_token_buffer_memory.html |
7599199ee261-1 | human_prefix=self.human_prefix,
ai_prefix=self.ai_prefix,
)
return {self.memory_key: final_buffer}
[docs] def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, Any]) -> None:
"""Save context from this conversation to buffer. Pruned."""
input_str, output... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/openai_functions_agent/agent_token_buffer_memory.html |
cb3015333973-0 | Source code for langchain.agents.agent_toolkits.azure_cognitive_services
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,
AzureCogsImageAnalysisTo... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/azure_cognitive_services.html |
98d1f791f958-0 | Source code for langchain.agents.agent_toolkits.base
"""Toolkits for agents."""
from abc import ABC, abstractmethod
from typing import List
from langchain.pydantic_v1 import BaseModel
from langchain.tools import BaseTool
[docs]class BaseToolkit(BaseModel, ABC):
"""Base Toolkit representing a collection of related t... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/base.html |
fd8bcdd17363-0 | Source code for langchain.agents.agent_toolkits.sql.toolkit
"""Toolkit for interacting with an SQL database."""
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import Field
from langchain.schema.language_model import BaseLanguageModel
from langchain.tools ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/toolkit.html |
fd8bcdd17363-1 | )
query_sql_database_tool_description = (
"Input to this tool is a detailed and correct SQL query, output is a "
"result from the database. If the query is not correct, an error message "
"will be returned. If an error is returned, rewrite the query, check the "
"... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/toolkit.html |
105744e046ee-0 | Source code for langchain.agents.agent_toolkits.sql.base
"""SQL agent."""
from typing import Any, Dict, List, Optional, Sequence
from langchain.agents.agent import AgentExecutor, BaseSingleActionAgent
from langchain.agents.agent_toolkits.sql.prompt import (
SQL_FUNCTIONS_SUFFIX,
SQL_PREFIX,
SQL_SUFFIX,
)
fr... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/base.html |
105744e046ee-1 | agent_executor_kwargs: Optional[Dict[str, Any]] = None,
extra_tools: Sequence[BaseTool] = (),
**kwargs: Any,
) -> AgentExecutor:
"""Construct an SQL agent from an LLM and tools."""
tools = toolkit.get_tools() + list(extra_tools)
prefix = prefix.format(dialect=toolkit.dialect, top_k=top_k)
agent:... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/base.html |
105744e046ee-2 | raise ValueError(f"Agent type {agent_type} not supported at the moment.")
return AgentExecutor.from_agent_and_tools(
agent=agent,
tools=tools,
callback_manager=callback_manager,
verbose=verbose,
max_iterations=max_iterations,
max_execution_time=max_execution_time,
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/sql/base.html |
4fb9909e5464-0 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/toolkit.html |
4fb9909e5464-1 | return [
RequestsGetTool(requests_wrapper=self.requests_wrapper),
RequestsPostTool(requests_wrapper=self.requests_wrapper),
RequestsPatchTool(requests_wrapper=self.requests_wrapper),
RequestsPutTool(requests_wrapper=self.requests_wrapper),
RequestsDeleteTool(r... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/toolkit.html |
09bb1265109a-0 | Source code for langchain.agents.agent_toolkits.openapi.planner
"""Agent that interacts with OpenAPI APIs via a hierarchical planning approach."""
import json
import re
from functools import partial
from typing import Any, Callable, Dict, List, Optional
import yaml
from langchain.agents.agent import AgentExecutor
from ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-1 | #
# Requests tools with LLM-instructed extraction of truncated responses.
#
# Of course, truncating so bluntly may lose a lot of valuable
# information in the response.
# However, the goal for now is to have only a single inference step.
MAX_RESPONSE_LENGTH = 5000
"""Maximum length of the response to be returned."""
de... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-2 | response = response[: self.response_length]
return self.llm_chain.predict(
response=response, instructions=data["output_instructions"]
).strip()
async def _arun(self, text: str) -> str:
raise NotImplementedError()
[docs]class RequestsPostToolWithParsing(BaseRequestsTool, BaseTool... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-3 | """Maximum length of the response to be returned."""
llm_chain: LLMChain = Field(
default_factory=_get_default_llm_chain_factory(PARSING_PATCH_PROMPT)
)
"""LLMChain used to extract the response."""
def _run(self, text: str) -> str:
try:
data = json.loads(text)
except ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-4 | response=response, instructions=data["output_instructions"]
).strip()
async def _arun(self, text: str) -> str:
raise NotImplementedError()
[docs]class RequestsDeleteToolWithParsing(BaseRequestsTool, BaseTool):
"""A tool that sends a DELETE request and parses the response."""
name: str = "req... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-5 | partial_variables={"endpoints": "- " + "- ".join(endpoint_descriptions)},
)
chain = LLMChain(llm=llm, prompt=prompt)
tool = Tool(
name=API_PLANNER_TOOL_NAME,
description=API_PLANNER_TOOL_DESCRIPTION,
func=chain.run,
)
return tool
def _create_api_controller_agent(
api_url:... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-6 | allowed_tools=[tool.name for tool in tools],
)
return AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
def _create_api_controller_tool(
api_spec: ReducedOpenAPISpec,
requests_wrapper: RequestsWrapper,
llm: BaseLanguageModel,
) -> Tool:
"""Expose controller as a tool.
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-7 | name=API_CONTROLLER_TOOL_NAME,
func=_create_and_run_api_controller_agent,
description=API_CONTROLLER_TOOL_DESCRIPTION,
)
[docs]def create_openapi_agent(
api_spec: ReducedOpenAPISpec,
requests_wrapper: RequestsWrapper,
llm: BaseLanguageModel,
shared_memory: Optional[ReadOnlySharedMemo... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
09bb1265109a-8 | **kwargs,
)
return AgentExecutor.from_agent_and_tools(
agent=agent,
tools=tools,
callback_manager=callback_manager,
verbose=verbose,
**(agent_executor_kwargs or {}),
) | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/planner.html |
8227c3d4e30c-0 | Source code for langchain.agents.agent_toolkits.openapi.spec
"""Quick and dirty representation for OpenAPI specs."""
from dataclasses import dataclass
from typing import List, Tuple
from langchain.utils.json_schema import dereference_refs
[docs]@dataclass(frozen=True)
class ReducedOpenAPISpec:
"""A reduced OpenAPI ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/spec.html |
8227c3d4e30c-1 | if dereference:
endpoints = [
(name, description, dereference_refs(docs, full_schema=spec))
for name, description, docs in endpoints
]
# 3. Strip docs down to required request args + happy path response.
def reduce_endpoint_docs(docs: dict) -> dict:
out = {}
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/spec.html |
2d6314a8fab2-0 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/base.html |
2d6314a8fab2-1 | uses the RequestsToolkit which contains tools to make arbitrary
network requests against any URL (e.g., GET, POST, PATCH, PUT, DELETE),
Control access to who can submit issue requests using this toolkit and
what network access it has.
See https://python.langchain.com/docs/security for mo... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/openapi/base.html |
30b02ba7fec5-0 | Source code for langchain.agents.agent_toolkits.powerbi.toolkit
"""Toolkit for interacting with a Power BI dataset."""
from typing import List, Optional, Union
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.callbacks.base import BaseCallbackManager
from langchain.chains.llm import LLMChain
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html |
30b02ba7fec5-1 | output_token_limit: Optional[int] = None
tiktoken_model_name: Optional[str] = None
class Config:
"""Configuration for this pydantic object."""
arbitrary_types_allowed = True
[docs] def get_tools(self) -> List[BaseTool]:
"""Get the tools in the toolkit."""
return [
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html |
30b02ba7fec5-2 | callback_manager=self.callback_manager if self.callback_manager else None,
prompt=ChatPromptTemplate.from_messages([system_prompt, human_prompt]),
) | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/toolkit.html |
537788954283-0 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/base.html |
537788954283-1 | tools = toolkit.get_tools()
tables = powerbi.table_names if powerbi else toolkit.powerbi.table_names
agent = ZeroShotAgent(
llm_chain=LLMChain(
llm=llm,
prompt=ZeroShotAgent.create_prompt(
tools,
prefix=prefix.format(top_k=top_k).format(tables=tabl... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/base.html |
682f294b6511-0 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/chat_base.html |
682f294b6511-1 | """
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()
tables = powerbi.table_names if powerbi else toolkit.powerbi.table_na... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/powerbi/chat_base.html |
9274697715de-0 | Source code for langchain.agents.agent_toolkits.spark_sql.toolkit
"""Toolkit for interacting with Spark SQL."""
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import Field
from langchain.schema.language_model import BaseLanguageModel
from langchain.tools ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/toolkit.html |
d0da36b94272-0 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/base.html |
d0da36b94272-1 | format_instructions=format_instructions,
input_variables=input_variables,
)
llm_chain = LLMChain(
llm=llm,
prompt=prompt,
callback_manager=callback_manager,
callbacks=callbacks,
)
tool_names = [tool.name for tool in tools]
agent = ZeroShotAgent(llm_chain=llm_c... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/spark_sql/base.html |
dc53b8201c2d-0 | Source code for langchain.agents.agent_toolkits.nla.toolkit
from __future__ import annotations
from typing import Any, List, Optional, Sequence
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.agents.agent_toolkits.nla.tool import NLATool
from langchain.pydantic_v1 import Field
from langchain... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html |
dc53b8201c2d-1 | return []
http_operation_tools = []
for path in spec.paths:
for method in spec.get_methods_for_path(path):
endpoint_tool = NLATool.from_llm_and_method(
llm=llm,
path=path,
method=method,
spec=spec... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html |
dc53b8201c2d-2 | def from_llm_and_ai_plugin(
cls,
llm: BaseLanguageModel,
ai_plugin: AIPlugin,
requests: Optional[Requests] = None,
verbose: bool = False,
**kwargs: Any,
) -> NLAToolkit:
"""Instantiate the toolkit from an OpenAPI Spec URL"""
spec = OpenAPISpec.from_url... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/toolkit.html |
d4e34ba6bd43-0 | Source code for langchain.agents.agent_toolkits.nla.tool
"""Tool for interacting with a single API with natural language definition."""
from typing import Any, Optional
from langchain.agents.tools import Tool
from langchain.chains.api.openapi.chain import OpenAPIEndpointChain
from langchain.schema.language_model import... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/tool.html |
d4e34ba6bd43-1 | api_operation = APIOperation.from_openapi_spec(spec, path, method)
chain = OpenAPIEndpointChain.from_api_operation(
api_operation,
llm,
requests=requests,
verbose=verbose,
return_intermediate_steps=return_intermediate_steps,
**kwargs,
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/nla/tool.html |
8dad56dedf0c-0 | Source code for langchain.agents.agent_toolkits.jira.toolkit
from typing import Dict, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.jira.prompt import (
JIRA_CATCH_ALL_PROMPT,
JIRA_CONFLUENCE_PAGE_CREATE_PROMPT,
JIRA_GET_ALL_PROJE... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/jira/toolkit.html |
8dad56dedf0c-1 | "name": "Catch all Jira API call",
"description": JIRA_CATCH_ALL_PROMPT,
},
{
"mode": "create_page",
"name": "Create confluence page",
"description": JIRA_CONFLUENCE_PAGE_CREATE_PROMPT,
},
]
tools = [
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/jira/toolkit.html |
8e3b2eb7de53-0 | 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 langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import Extra, root_validator
fr... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/playwright/toolkit.html |
8e3b2eb7de53-1 | - Any URL (including any internal network URLs)
- And local files
If exposing to end-users, consider limiting network access to the
server that hosts the agent; in addition, consider it is advised
to create a custom NavigationTool wht an args_schema that limits the URLs
that can ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/playwright/toolkit.html |
8e3b2eb7de53-2 | tool_cls.from_browser(
sync_browser=self.sync_browser, async_browser=self.async_browser
)
for tool_cls in tool_classes
]
return cast(List[BaseTool], tools)
[docs] @classmethod
def from_browser(
cls,
sync_browser: Optional[SyncBrowser] = None... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/playwright/toolkit.html |
94f8823c0103-0 | Source code for langchain.agents.agent_toolkits.json.toolkit
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, JsonListKeysTool, JsonSpec
[docs]class JsonToo... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/toolkit.html |
d3c3dd7bc0ce-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
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/base.html |
d3c3dd7bc0ce-1 | return AgentExecutor.from_agent_and_tools(
agent=agent,
tools=tools,
callback_manager=callback_manager,
verbose=verbose,
**(agent_executor_kwargs or {}),
) | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/json/base.html |
40f4d5b2b20f-0 | Source code for langchain.agents.agent_toolkits.gmail.toolkit
from __future__ import annotations
from typing import TYPE_CHECKING, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import Field
from langchain.tools import BaseTool
from langchain.tools.gmail.create_draft import... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/gmail/toolkit.html |
40f4d5b2b20f-1 | return [
GmailCreateDraft(api_resource=self.api_resource),
GmailSendMessage(api_resource=self.api_resource),
GmailSearch(api_resource=self.api_resource),
GmailGetMessage(api_resource=self.api_resource),
GmailGetThread(api_resource=self.api_resource),
] | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/gmail/toolkit.html |
ddf6cc0f43a5-0 | Source code for langchain.agents.agent_toolkits.ainetwork.toolkit
from __future__ import annotations
from typing import TYPE_CHECKING, List, Literal, Optional
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import root_validator
from langchain.tools import BaseTool
from langchain... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/ainetwork/toolkit.html |
ddf6cc0f43a5-1 | return [
AINAppOps(),
AINOwnerOps(),
AINRuleOps(),
AINTransfer(),
AINValueOps(),
] | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/ainetwork/toolkit.html |
3b2de347de90-0 | Source code for langchain.agents.agent_toolkits.vectorstore.toolkit
"""Toolkit for interacting with a vector store."""
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.llms.openai import OpenAI
from langchain.pydantic_v1 import BaseModel, Field
from langchain.schema.la... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/toolkit.html |
3b2de347de90-1 | 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,
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/toolkit.html |
4fc31fed30af-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 ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html |
4fc31fed30af-1 | **kwargs: Additional named parameters to pass to the ZeroShotAgent.
Returns:
AgentExecutor: Returns a callable AgentExecutor object. Either you can call it or use run method with the query to get the response
""" # noqa: E501
tools = toolkit.get_tools()
prompt = ZeroShotAgent.create_prompt(tool... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html |
4fc31fed30af-2 | prefix (str, optional): The prefix prompt for the router agent. If not provided uses default ROUTER_PREFIX.
verbose (bool, optional): If you want to see the content of the scratchpad. [ Defaults to False ]
agent_executor_kwargs (Optional[Dict[str, Any]], optional): If there is any other parameter you wa... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/vectorstore/base.html |
b7fff50cad81-0 | Source code for langchain.agents.agent_toolkits.multion.toolkit
"""MultiOn agent."""
from __future__ import annotations
from typing import List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.multion.close_session import MultionCloseSession
from lan... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/multion/toolkit.html |
def8dccbc99b-0 | Source code for langchain.agents.agent_toolkits.gitlab.toolkit
"""GitHub Toolkit."""
from typing import Dict, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.gitlab.prompt import (
COMMENT_ON_ISSUE_PROMPT,
CREATE_FILE_PROMPT,
CREATE... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/gitlab/toolkit.html |
def8dccbc99b-1 | "mode": "comment_on_issue",
"name": "Comment on Issue",
"description": COMMENT_ON_ISSUE_PROMPT,
},
{
"mode": "create_pull_request",
"name": "Create Pull Request",
"description": CREATE_PULL_REQUEST_PROMPT,
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/gitlab/toolkit.html |
fb640b5d18b7-0 | Source code for langchain.agents.agent_toolkits.amadeus.toolkit
from __future__ import annotations
from typing import TYPE_CHECKING, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import Field
from langchain.tools import BaseTool
from langchain.tools.amadeus.closest_airport... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/amadeus/toolkit.html |
6f02f6fc8997-0 | Source code for langchain.agents.agent_toolkits.zapier.toolkit
"""[DEPRECATED] Zapier Toolkit."""
from typing import List
from langchain._api import warn_deprecated
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.zapier.tool import ZapierNLARunActio... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/zapier/toolkit.html |
6f02f6fc8997-1 | )
for action in actions
]
return cls(tools=tools)
[docs] def get_tools(self) -> List[BaseTool]:
"""Get the tools in the toolkit."""
warn_deprecated(
since="0.0.319",
message=(
"This tool will be deprecated on 2023-11-17. See "
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/zapier/toolkit.html |
d1aaa64ee72c-0 | Source code for langchain.agents.agent_toolkits.github.toolkit
"""GitHub Toolkit."""
from typing import Dict, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.github.prompt import (
COMMENT_ON_ISSUE_PROMPT,
CREATE_FILE_PROMPT,
CREATE... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/github/toolkit.html |
d1aaa64ee72c-1 | "mode": "comment_on_issue",
"name": "Comment on Issue",
"description": COMMENT_ON_ISSUE_PROMPT,
},
{
"mode": "create_pull_request",
"name": "Create Pull Request",
"description": CREATE_PULL_REQUEST_PROMPT,
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/github/toolkit.html |
ee5e3713bed0-0 | Source code for langchain.agents.agent_toolkits.file_management.toolkit
from __future__ import annotations
from typing import List, Optional
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import root_validator
from langchain.tools import BaseTool
from langchain.tools.file_manage... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/file_management/toolkit.html |
ee5e3713bed0-1 | Consider the following:
- Limit access to particular directories using `root_dir`.
- Use filesystem permissions to restrict access and permissions to only
the files and directories required by the agent.
- Limit the tools available to the agent to only the file operations
nec... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/file_management/toolkit.html |
5adcae62f904-0 | Source code for langchain.agents.agent_toolkits.clickup.toolkit
from typing import Dict, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.tools import BaseTool
from langchain.tools.clickup.prompt import (
CLICKUP_FOLDER_CREATE_PROMPT,
CLICKUP_GET_ALL_TEAMS_PROMPT,
CLICKUP_GET... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/clickup/toolkit.html |
5adcae62f904-1 | "description": CLICKUP_GET_TASK_ATTRIBUTE_PROMPT,
},
{
"mode": "get_teams",
"name": "Get Teams",
"description": CLICKUP_GET_ALL_TEAMS_PROMPT,
},
{
"mode": "create_task",
"name": "Create Task",... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/clickup/toolkit.html |
5adcae62f904-2 | name=action["name"],
description=action["description"],
mode=action["mode"],
api_wrapper=clickup_api_wrapper,
)
for action in operations
]
return cls(tools=tools)
[docs] def get_tools(self) -> List[BaseTool]:
"""Get the t... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/clickup/toolkit.html |
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