id stringlengths 14 16 | text stringlengths 31 2.41k | source stringlengths 53 121 |
|---|---|---|
673b0af0f98b-0 | Source code for langchain.tools.brave_search.tool
from __future__ import annotations
from typing import Any, Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.utilities.brave_search import Brav... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/brave_search/tool.html |
4009eadee54c-0 | Source code for langchain.tools.powerbi.tool
"""Tools for interacting with a Power BI dataset."""
import logging
from time import perf_counter
from typing import Any, Dict, Optional, Tuple
from pydantic import Field, validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackMan... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/powerbi/tool.html |
4009eadee54c-1 | def validate_llm_chain_input_variables( # pylint: disable=E0213
cls, llm_chain: LLMChain
) -> LLMChain:
"""Make sure the LLM chain has the correct input variables."""
if llm_chain.prompt.input_variables != [
"tool_input",
"tables",
"schemas",
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/powerbi/tool.html |
4009eadee54c-2 | tables=self.powerbi.get_table_names(),
schemas=self.powerbi.get_schemas(),
examples=self.examples,
)
except Exception as exc: # pylint: disable=broad-except
self.session_cache[tool_input] = f"Error on call to LLM: {exc}"
return self.session_ca... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/powerbi/tool.html |
4009eadee54c-3 | async def _arun(
self,
tool_input: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
**kwargs: Any,
) -> str:
"""Execute the query, return the results or an error message."""
if cache := self._check_cache(tool_input):
logger.debug("Found c... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/powerbi/tool.html |
4009eadee54c-4 | return self.session_cache[tool_input]
iterations = kwargs.get("iterations", 0)
if error and iterations < self.max_iterations:
return await self._arun(
tool_input=RETRY_RESPONSE.format(
tool_input=tool_input, query=query, error=error
),
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/powerbi/tool.html |
4009eadee54c-5 | Example Input: "table1, table2, table3"
""" # noqa: E501
powerbi: PowerBIDataset = Field(exclude=True)
class Config:
"""Configuration for this pydantic object."""
arbitrary_types_allowed = True
def _run(
self,
tool_input: str,
run_manager: Optional[CallbackManage... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/powerbi/tool.html |
4009eadee54c-6 | run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Get the names of the tables."""
return ", ".join(self.powerbi.get_table_names()) | https://api.python.langchain.com/en/stable/_modules/langchain/tools/powerbi/tool.html |
73a23553967d-0 | Source code for langchain.tools.spark_sql.tool
# flake8: noqa
"""Tools for interacting with Spark SQL."""
from typing import Any, Dict, Optional
from pydantic import BaseModel, Extra, Field, root_validator
from langchain.base_language import BaseLanguageModel
from langchain.callbacks.manager import (
AsyncCallbackM... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/spark_sql/tool.html |
73a23553967d-1 | return self.db.run_no_throw(query)
async def _arun(
self,
query: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
raise NotImplementedError("QuerySqlDbTool does not support async")
[docs]class InfoSparkSQLTool(BaseSparkSQLTool, BaseTool):
"""Tool f... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/spark_sql/tool.html |
73a23553967d-2 | ) -> str:
"""Get the schema for a specific table."""
return ", ".join(self.db.get_usable_table_names())
async def _arun(
self,
tool_input: str = "",
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
raise NotImplementedError("ListTablesSqlDbT... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/spark_sql/tool.html |
73a23553967d-3 | return values
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the LLM to check the query."""
return self.llm_chain.predict(query=query)
async def _arun(
self,
query: str,
run_manager: Option... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/spark_sql/tool.html |
668b5f6ae291-0 | Source code for langchain.tools.google_places.tool
"""Tool for the Google search API."""
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from l... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/google_places/tool.html |
cc98a75937bb-0 | Source code for langchain.tools.azure_cognitive_services.image_analysis
from __future__ import annotations
import logging
from typing import Any, Dict, Optional
from pydantic import root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langcha... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
cc98a75937bb-1 | )
try:
import azure.ai.vision as sdk
values["vision_service"] = sdk.VisionServiceOptions(
endpoint=azure_cogs_endpoint, key=azure_cogs_key
)
values["analysis_options"] = sdk.ImageAnalysisOptions()
values["analysis_options"].features = (... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
cc98a75937bb-2 | res_dict["tags"] = [tag.name for tag in result.tags]
if result.text is not None:
res_dict["text"] = [line.content for line in result.text.lines]
else:
error_details = sdk.ImageAnalysisErrorDetails.from_result(result)
raise RuntimeError(
f"Image... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
cc98a75937bb-3 | if not image_analysis_result:
return "No good image analysis result was found"
return self._format_image_analysis_result(image_analysis_result)
except Exception as e:
raise RuntimeError(f"Error while running AzureCogsImageAnalysisTool: {e}")
async def _arun(
s... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
c0557ad0a7d6-0 | Source code for langchain.tools.azure_cognitive_services.text2speech
from __future__ import annotations
import logging
import tempfile
from typing import Any, Dict, Optional
from pydantic import root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
c0557ad0a7d6-1 | )
try:
import azure.cognitiveservices.speech as speechsdk
values["speech_config"] = speechsdk.SpeechConfig(
subscription=azure_cogs_key, region=azure_cogs_region
)
except ImportError:
raise ImportError(
"azure-cognitiveservi... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
c0557ad0a7d6-2 | def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
try:
speech_file = self._text2speech(query, self.speech_language)
return speech_file
except Exception as e:
raise Run... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
4b65dd6c7e83-0 | Source code for langchain.tools.azure_cognitive_services.form_recognizer
from __future__ import annotations
import logging
from typing import Any, Dict, List, Optional
from pydantic import root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from ... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
4b65dd6c7e83-1 | )
azure_cogs_endpoint = get_from_dict_or_env(
values, "azure_cogs_endpoint", "AZURE_COGS_ENDPOINT"
)
try:
from azure.ai.formrecognizer import DocumentAnalysisClient
from azure.core.credentials import AzureKeyCredential
values["doc_analysis_client"]... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
4b65dd6c7e83-2 | "prebuilt-document", document
)
elif document_src_type == "remote":
poller = self.doc_analysis_client.begin_analyze_document_from_url(
"prebuilt-document", document_path
)
else:
raise ValueError(f"Invalid document path: {document_path}"... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
4b65dd6c7e83-3 | ) -> str:
"""Use the tool."""
try:
document_analysis_result = self._document_analysis(query)
if not document_analysis_result:
return "No good document analysis result was found"
return self._format_document_analysis_result(document_analysis_result)
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
aa2d04290bfa-0 | Source code for langchain.tools.azure_cognitive_services.speech2text
from __future__ import annotations
import logging
import time
from typing import Any, Dict, Optional
from pydantic import root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
fro... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/speech2text.html |
aa2d04290bfa-1 | )
azure_cogs_region = get_from_dict_or_env(
values, "azure_cogs_region", "AZURE_COGS_REGION"
)
try:
import azure.cognitiveservices.speech as speechsdk
values["speech_config"] = speechsdk.SpeechConfig(
subscription=azure_cogs_key, region=azure_c... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/speech2text.html |
aa2d04290bfa-2 | except ImportError:
pass
audio_src_type = detect_file_src_type(audio_path)
if audio_src_type == "local":
audio_config = speechsdk.AudioConfig(filename=audio_path)
elif audio_src_type == "remote":
tmp_audio_path = download_audio_from_url(audio_path)
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/azure_cognitive_services/speech2text.html |
466acbf49ca7-0 | Source code for langchain.tools.sleep.tool
"""Tool for agent to sleep."""
from asyncio import sleep as asleep
from time import sleep
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/sleep/tool.html |
93221d9a6d04-0 | Source code for langchain.tools.jira.tool
"""
This tool allows agents to interact with the atlassian-python-api library
and operate on a Jira instance. For more information on the
atlassian-python-api library, see https://atlassian-python-api.readthedocs.io/jira.html
To use this tool, you must first set as environment ... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/jira/tool.html |
93221d9a6d04-1 | """Use the Atlassian Jira API to run an operation."""
return self.api_wrapper.run(self.mode, instructions)
async def _arun(
self,
_: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Use the Atlassian Jira API to run an operation."""
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/jira/tool.html |
ce08c637bfe4-0 | Source code for langchain.tools.youtube.search
"""
Adapted from https://github.com/venuv/langchain_yt_tools
CustomYTSearchTool searches YouTube videos related to a person
and returns a specified number of video URLs.
Input to this tool should be a comma separated list,
- the first part contains a person name
- and th... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/youtube/search.html |
ce08c637bfe4-1 | num_results = int(values[1])
else:
num_results = 2
return self._search(person, num_results)
async def _arun(
self,
query: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Use the tool asynchronously."""
raise NotI... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/youtube/search.html |
2e530b41d256-0 | Source code for langchain.tools.vectorstore.tool
"""Tools for interacting with vectorstores."""
import json
from typing import Any, Dict, Optional
from pydantic import BaseModel, Field
from langchain.base_language import BaseLanguageModel
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/vectorstore/tool.html |
2e530b41d256-1 | def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
chain = RetrievalQA.from_chain_type(
self.llm, retriever=self.vectorstore.as_retriever()
)
return chain.run(query)
async def _aru... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/vectorstore/tool.html |
2e530b41d256-2 | self.llm, retriever=self.vectorstore.as_retriever()
)
return json.dumps(chain({chain.question_key: query}, return_only_outputs=True))
async def _arun(
self,
query: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Use the tool asynchr... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/vectorstore/tool.html |
d091c4059e27-0 | Source code for langchain.tools.google_search.tool
"""Tool for the Google search API."""
from typing import Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.utilities.google_search import Goog... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/google_search/tool.html |
d091c4059e27-1 | api_wrapper: GoogleSearchAPIWrapper
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
return str(self.api_wrapper.results(query, self.num_results))
async def _arun(
self,
query: str,
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/google_search/tool.html |
804813befe0b-0 | Source code for langchain.tools.wolfram_alpha.tool
"""Tool for the Wolfram Alpha API."""
from typing import Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.utilities.wolfram_alpha import Wolf... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/wolfram_alpha/tool.html |
7a2747ca06cb-0 | Source code for langchain.tools.human.tool
"""Tool for asking human input."""
from typing import Callable, Optional
from pydantic import Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
def _print_func(text: st... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/human/tool.html |
3fe715576f65-0 | Source code for langchain.tools.shell.tool
import asyncio
import platform
import warnings
from typing import List, Optional, Type, Union
from pydantic import BaseModel, Field, root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.too... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/shell/tool.html |
3fe715576f65-1 | name: str = "terminal"
"""Name of tool."""
description: str = f"Run shell commands on this {_get_platform()} machine."
"""Description of tool."""
args_schema: Type[BaseModel] = ShellInput
"""Schema for input arguments."""
def _run(
self,
commands: Union[str, List[str]],
r... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/shell/tool.html |
d45b403c20c7-0 | Source code for langchain.tools.gmail.send_message
"""Send Gmail messages."""
import base64
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from typing import Any, Dict, List, Optional, Union
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCal... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/send_message.html |
d45b403c20c7-1 | """Create a message for an email."""
mime_message = MIMEMultipart()
mime_message.attach(MIMEText(message, "html"))
mime_message["To"] = ", ".join(to if isinstance(to, list) else [to])
mime_message["Subject"] = subject
if cc is not None:
mime_message["Cc"] = ", ".join(... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/send_message.html |
d45b403c20c7-2 | to: Union[str, List[str]],
subject: str,
cc: Optional[Union[str, List[str]]] = None,
bcc: Optional[Union[str, List[str]]] = None,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Run the tool asynchronously."""
raise NotImplementedError(f"The... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/send_message.html |
6e57b486130b-0 | Source code for langchain.tools.gmail.get_message
import base64
import email
from typing import Dict, Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.gmail.base import GmailBaseTool
f... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/get_message.html |
6e57b486130b-1 | "snippet": message_data["snippet"],
"body": body,
"subject": subject,
"sender": sender,
}
async def _arun(
self,
message_id: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> Dict:
"""Run the tool."""
raise... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/get_message.html |
73ebb8fc7245-0 | Source code for langchain.tools.gmail.search
import base64
import email
from enum import Enum
from typing import Any, Dict, List, Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.gmail... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/search.html |
73ebb8fc7245-1 | name: str = "search_gmail"
description: str = (
"Use this tool to search for email messages or threads."
" The input must be a valid Gmail query."
" The output is a JSON list of the requested resource."
)
args_schema: Type[SearchArgsSchema] = SearchArgsSchema
def _parse_threads(s... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/search.html |
73ebb8fc7245-2 | body = clean_email_body(message_body)
results.append(
{
"id": message["id"],
"threadId": message_data["threadId"],
"snippet": message_data["snippet"],
"body": body,
"subject": subject,
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/search.html |
bbb3fe78de05-0 | Source code for langchain.tools.gmail.create_draft
import base64
from email.message import EmailMessage
from typing import List, Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.gmail.... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/create_draft.html |
bbb3fe78de05-1 | draft_message["Subject"] = subject
if cc is not None:
draft_message["Cc"] = ", ".join(cc)
if bcc is not None:
draft_message["Bcc"] = ", ".join(bcc)
encoded_message = base64.urlsafe_b64encode(draft_message.as_bytes()).decode()
return {"message": {"raw": encoded_mes... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/create_draft.html |
f1df414ffb5d-0 | Source code for langchain.tools.gmail.get_thread
from typing import Dict, Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.gmail.base import GmailBaseTool
class GetThreadSchema(BaseMod... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/get_thread.html |
f1df414ffb5d-1 | )
return thread_data
async def _arun(
self,
thread_id: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> Dict:
"""Run the tool."""
raise NotImplementedError | https://api.python.langchain.com/en/stable/_modules/langchain/tools/gmail/get_thread.html |
d7149ef3b4e0-0 | Source code for langchain.tools.file_management.move
import shutil
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.tools.file_ma... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/move.html |
d7149ef3b4e0-1 | shutil.move(str(source_path_), destination_path_)
return f"File moved successfully from {source_path} to {destination_path}."
except Exception as e:
return "Error: " + str(e)
async def _arun(
self,
source_path: str,
destination_path: str,
run_manager: ... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/move.html |
120793147a7f-0 | Source code for langchain.tools.file_management.file_search
import fnmatch
import os
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langc... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/file_search.html |
120793147a7f-1 | matches.append(relative_path)
if matches:
return "\n".join(matches)
else:
return f"No files found for pattern {pattern} in directory {dir_path}"
except Exception as e:
return "Error: " + str(e)
async def _arun(
self,
dir_pat... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/file_search.html |
478e58e1ebd6-0 | Source code for langchain.tools.file_management.copy
import shutil
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.tools.file_ma... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/copy.html |
478e58e1ebd6-1 | except Exception as e:
return "Error: " + str(e)
async def _arun(
self,
source_path: str,
destination_path: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
# TODO: Add aiofiles method
raise NotImplementedError | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/copy.html |
dc594cbfc59e-0 | Source code for langchain.tools.file_management.list_dir
import os
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.tools.file_ma... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/list_dir.html |
0e7b7d3dd8a2-0 | Source code for langchain.tools.file_management.delete
import os
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.tools.file_mana... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/delete.html |
b680e4aa1ebb-0 | Source code for langchain.tools.file_management.read
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.tools.file_management.utils... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/read.html |
02b48bca2b68-0 | Source code for langchain.tools.file_management.write
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.tools.file_management.util... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/write.html |
02b48bca2b68-1 | except Exception as e:
return "Error: " + str(e)
async def _arun(
self,
file_path: str,
text: str,
append: bool = False,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
# TODO: Add aiofiles method
raise NotImplementedErr... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/file_management/write.html |
a47e723ed941-0 | Source code for langchain.tools.zapier.tool
"""## Zapier Natural Language Actions API
\
Full docs here: https://nla.zapier.com/start/
**Zapier Natural Language Actions** gives you access to the 5k+ apps, 20k+ actions
on Zapier's platform through a natural language API interface.
NLA supports apps like Gmail, Salesforce... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/zapier/tool.html |
a47e723ed941-1 | 2. Use LLMChain to generate a draft reply to (1)
3. Use NLA to send the draft reply (2) to someone in Slack via direct message
In code, below:
```python
import os
# get from https://platform.openai.com/
os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY", "")
# get from https://nla.zapier.com/docs/authen... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/zapier/tool.html |
a47e723ed941-2 | agent = initialize_agent(
toolkit.get_tools(),
llm,
agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
verbose=True
)
agent.run(("Summarize the last email I received regarding Silicon Valley Bank. "
"Send the summary to the #test-zapier channel in slack."))
```
"""
from typing import Any, Dict, Optional
f... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/zapier/tool.html |
a47e723ed941-3 | name = ""
description = ""
@root_validator
def set_name_description(cls, values: Dict[str, Any]) -> Dict[str, Any]:
zapier_description = values["zapier_description"]
params_schema = values["params_schema"]
if "instructions" in params_schema:
del params_schema["instruction... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/zapier/tool.html |
a47e723ed941-4 | )
ZapierNLARunAction.__doc__ = (
ZapierNLAWrapper.run.__doc__ + ZapierNLARunAction.__doc__ # type: ignore
)
# other useful actions
[docs]class ZapierNLAListActions(BaseTool):
"""
Args:
None
"""
name = "ZapierNLA_list_actions"
description = BASE_ZAPIER_TOOL_PROMPT + (
"This tool ... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/zapier/tool.html |
2ccd0b9b1e8c-0 | Source code for langchain.tools.json.tool
# flake8: noqa
"""Tools for working with JSON specs."""
from __future__ import annotations
import json
import re
from pathlib import Path
from typing import Dict, List, Optional, Union
from pydantic import BaseModel
from langchain.callbacks.manager import (
AsyncCallbackMan... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/json/tool.html |
2ccd0b9b1e8c-1 | val = self.dict_
for i in items:
if i:
val = val[i]
if not isinstance(val, dict):
raise ValueError(
f"Value at path `{text}` is not a dict, get the value directly."
)
return str(list(val.keys()))
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/json/tool.html |
2ccd0b9b1e8c-2 | def _run(
self,
tool_input: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
return self.spec.keys(tool_input)
async def _arun(
self,
tool_input: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/json/tool.html |
3d1ff054da00-0 | Source code for langchain.tools.google_serper.tool
"""Tool for the Serper.dev Google Search API."""
from typing import Optional
from pydantic.fields import Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from ... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/google_serper/tool.html |
3d1ff054da00-1 | )
api_wrapper: GoogleSerperAPIWrapper = Field(default_factory=GoogleSerperAPIWrapper)
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
return str(self.api_wrapper.results(query))
async def _arun(
... | https://api.python.langchain.com/en/stable/_modules/langchain/tools/google_serper/tool.html |
9801e4f15094-0 | Source code for langchain.prompts.few_shot
"""Prompt template that contains few shot examples."""
from typing import Any, Dict, List, Optional
from pydantic import Extra, root_validator
from langchain.prompts.base import (
DEFAULT_FORMATTER_MAPPING,
StringPromptTemplate,
check_valid_template,
)
from langcha... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/few_shot.html |
9801e4f15094-1 | def check_examples_and_selector(cls, values: Dict) -> Dict:
"""Check that one and only one of examples/example_selector are provided."""
examples = values.get("examples", None)
example_selector = values.get("example_selector", None)
if examples and example_selector:
raise Val... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/few_shot.html |
9801e4f15094-2 | .. code-block:: python
prompt.format(variable1="foo")
"""
kwargs = self._merge_partial_and_user_variables(**kwargs)
# Get the examples to use.
examples = self._get_examples(**kwargs)
examples = [
{k: e[k] for k in self.example_prompt.input_variables} for e... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/few_shot.html |
52b6b813e75a-0 | Source code for langchain.prompts.loading
"""Load prompts from disk."""
import importlib
import json
import logging
from pathlib import Path
from typing import Union
import yaml
from langchain.output_parsers.regex import RegexParser
from langchain.prompts.base import BasePromptTemplate
from langchain.prompts.few_shot i... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/loading.html |
52b6b813e75a-1 | # Load the template.
if template_path.suffix == ".txt":
with open(template_path) as f:
template = f.read()
else:
raise ValueError
# Set the template variable to the extracted variable.
config[var_name] = template
return config
def _load_example... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/loading.html |
52b6b813e75a-2 | """Load the few shot prompt from the config."""
# Load the suffix and prefix templates.
config = _load_template("suffix", config)
config = _load_template("prefix", config)
# Load the example prompt.
if "example_prompt_path" in config:
if "example_prompt" in config:
raise ValueErr... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/loading.html |
52b6b813e75a-3 | 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.suffix == ".yaml":
with open(file_path, "r") as f:
config = yaml.safe_load(f)
... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/loading.html |
3598e739834c-0 | Source code for langchain.prompts.few_shot_with_templates
"""Prompt template that contains few shot examples."""
from typing import Any, Dict, List, Optional
from pydantic import Extra, root_validator
from langchain.prompts.base import DEFAULT_FORMATTER_MAPPING, StringPromptTemplate
from langchain.prompts.example_selec... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/few_shot_with_templates.html |
3598e739834c-1 | examples = values.get("examples", None)
example_selector = values.get("example_selector", None)
if examples and example_selector:
raise ValueError(
"Only one of 'examples' and 'example_selector' should be provided"
)
if examples is None and example_selecto... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/few_shot_with_templates.html |
3598e739834c-2 | Args:
kwargs: Any arguments to be passed to the prompt template.
Returns:
A formatted string.
Example:
.. code-block:: python
prompt.format(variable1="foo")
"""
kwargs = self._merge_partial_and_user_variables(**kwargs)
# Get the example... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/few_shot_with_templates.html |
3598e739834c-3 | """Return a dictionary of the prompt."""
if self.example_selector:
raise ValueError("Saving an example selector is not currently supported")
return super().dict(**kwargs) | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/few_shot_with_templates.html |
a3868e6ba3b0-0 | Source code for langchain.prompts.prompt
"""Prompt schema definition."""
from __future__ import annotations
from pathlib import Path
from string import Formatter
from typing import Any, Dict, List, Union
from pydantic import root_validator
from langchain.prompts.base import (
DEFAULT_FORMATTER_MAPPING,
StringPr... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/prompt.html |
a3868e6ba3b0-1 | """
kwargs = self._merge_partial_and_user_variables(**kwargs)
return DEFAULT_FORMATTER_MAPPING[self.template_format](self.template, **kwargs)
@root_validator()
def template_is_valid(cls, values: Dict) -> Dict:
"""Check that template and input variables are consistent."""
if value... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/prompt.html |
a3868e6ba3b0-2 | [docs] @classmethod
def from_file(
cls, template_file: Union[str, Path], input_variables: List[str], **kwargs: Any
) -> PromptTemplate:
"""Load a prompt from a file.
Args:
template_file: The path to the file containing the prompt template.
input_variables: A li... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/prompt.html |
5df8c2d18d3e-0 | Source code for langchain.prompts.pipeline
from typing import Any, Dict, List, Tuple
from pydantic import root_validator
from langchain.prompts.base import BasePromptTemplate
from langchain.prompts.chat import BaseChatPromptTemplate
from langchain.schema import PromptValue
def _get_inputs(inputs: dict, input_variables:... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/pipeline.html |
5df8c2d18d3e-1 | if isinstance(prompt, BaseChatPromptTemplate):
kwargs[k] = prompt.format_messages(**_inputs)
else:
kwargs[k] = prompt.format(**_inputs)
_inputs = _get_inputs(kwargs, self.final_prompt.input_variables)
return self.final_prompt.format_prompt(**_inputs)
[docs] ... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/pipeline.html |
3c3578e9c2ac-0 | Source code for langchain.prompts.chat
"""Chat prompt template."""
from __future__ import annotations
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Callable, List, Sequence, Tuple, Type, TypeVar, Union
from pydantic import Field, root_validator
from langchain.load.serializable imp... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/chat.html |
3c3578e9c2ac-1 | f" got {value}"
)
return value
@property
def input_variables(self) -> List[str]:
"""Input variables for this prompt template."""
return [self.variable_name]
MessagePromptTemplateT = TypeVar(
"MessagePromptTemplateT", bound="BaseStringMessagePromptTemplate"
)
class Bas... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/chat.html |
3c3578e9c2ac-2 | text = self.prompt.format(**kwargs)
return ChatMessage(
content=text, role=self.role, additional_kwargs=self.additional_kwargs
)
[docs]class HumanMessagePromptTemplate(BaseStringMessagePromptTemplate):
[docs] def format(self, **kwargs: Any) -> BaseMessage:
text = self.prompt.forma... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/chat.html |
3c3578e9c2ac-3 | """Format kwargs into a list of messages."""
[docs]class ChatPromptTemplate(BaseChatPromptTemplate, ABC):
input_variables: List[str]
messages: List[Union[BaseMessagePromptTemplate, BaseMessage]]
@root_validator(pre=True)
def validate_input_variables(cls, values: dict) -> dict:
messages = values[... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/chat.html |
3c3578e9c2ac-4 | [docs] @classmethod
def from_strings(
cls, string_messages: List[Tuple[Type[BaseMessagePromptTemplate], str]]
) -> ChatPromptTemplate:
messages = [
role(prompt=PromptTemplate.from_template(template))
for role, template in string_messages
]
return cls.fr... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/chat.html |
3c3578e9c2ac-5 | def _prompt_type(self) -> str:
return "chat"
[docs] def save(self, file_path: Union[Path, str]) -> None:
raise NotImplementedError | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/chat.html |
a60ce9173993-0 | Source code for langchain.prompts.base
"""BasePrompt schema definition."""
from __future__ import annotations
import json
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, List, Mapping, Optional, Set, Union
import yaml
from pydantic import Field, root_validator
from l... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/base.html |
a60ce9173993-1 | if error_message:
raise KeyError(error_message.strip())
def _get_jinja2_variables_from_template(template: str) -> Set[str]:
try:
from jinja2 import Environment, meta
except ImportError:
raise ImportError(
"jinja2 not installed, which is needed to use the jinja2_formatter. "
... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/base.html |
a60ce9173993-2 | """Return prompt as string."""
return self.text
def to_messages(self) -> List[BaseMessage]:
"""Return prompt as messages."""
return [HumanMessage(content=self.text)]
[docs]class BasePromptTemplate(Serializable, ABC):
"""Base class for all prompt templates, returning a prompt."""
inpu... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/base.html |
a60ce9173993-3 | f"Found overlapping input and partial variables: {overall}"
)
return values
[docs] def partial(self, **kwargs: Union[str, Callable[[], str]]) -> BasePromptTemplate:
"""Return a partial of the prompt template."""
prompt_dict = self.__dict__.copy()
prompt_dict["input_variabl... | https://api.python.langchain.com/en/stable/_modules/langchain/prompts/base.html |
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