id stringlengths 14 16 | text stringlengths 36 2.73k | source stringlengths 49 117 |
|---|---|---|
d3af39275c7b-1 | return values
[docs] def compress_documents(
self, documents: Sequence[Document], query: str
) -> Sequence[Document]:
"""Filter documents based on similarity of their embeddings to the query."""
stateful_documents = get_stateful_documents(documents)
embedded_documents = _get_embed... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/embeddings_filter.html |
109f1ead7d38-0 | Source code for langchain.retrievers.document_compressors.base
"""Interface for retrieved document compressors."""
from abc import ABC, abstractmethod
from typing import List, Sequence, Union
from pydantic import BaseModel
from langchain.schema import BaseDocumentTransformer, Document
class BaseDocumentCompressor(BaseM... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/base.html |
109f1ead7d38-1 | self, documents: Sequence[Document], query: str
) -> Sequence[Document]:
"""Compress retrieved documents given the query context."""
for _transformer in self.transformers:
if isinstance(_transformer, BaseDocumentCompressor):
documents = await _transformer.acompress_docume... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/base.html |
198471a5c9ae-0 | Source code for langchain.retrievers.document_compressors.chain_filter
"""Filter that uses an LLM to drop documents that aren't relevant to the query."""
from typing import Any, Callable, Dict, Optional, Sequence
from langchain import BasePromptTemplate, LLMChain, PromptTemplate
from langchain.base_language import Base... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/chain_filter.html |
198471a5c9ae-1 | include_doc = self.llm_chain.predict_and_parse(**_input)
if include_doc:
filtered_docs.append(doc)
return filtered_docs
[docs] async def acompress_documents(
self, documents: Sequence[Document], query: str
) -> Sequence[Document]:
"""Filter down documents."""
... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/chain_filter.html |
5ce3e16a2d9d-0 | Source code for langchain.retrievers.document_compressors.cohere_rerank
from __future__ import annotations
from typing import TYPE_CHECKING, Dict, Sequence
from pydantic import Extra, root_validator
from langchain.retrievers.document_compressors.base import BaseDocumentCompressor
from langchain.schema import Document
f... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/cohere_rerank.html |
5ce3e16a2d9d-1 | return []
doc_list = list(documents)
_docs = [d.page_content for d in doc_list]
results = self.client.rerank(
model=self.model, query=query, documents=_docs, top_n=self.top_n
)
final_results = []
for r in results:
doc = doc_list[r.index]
... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/cohere_rerank.html |
1174c1843903-0 | Source code for langchain.retrievers.document_compressors.chain_extract
"""DocumentFilter that uses an LLM chain to extract the relevant parts of documents."""
from __future__ import annotations
import asyncio
from typing import Any, Callable, Dict, Optional, Sequence
from langchain import LLMChain, PromptTemplate
from... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/chain_extract.html |
1174c1843903-1 | [docs] def compress_documents(
self, documents: Sequence[Document], query: str
) -> Sequence[Document]:
"""Compress page content of raw documents."""
compressed_docs = []
for doc in documents:
_input = self.get_input(query, doc)
output = self.llm_chain.pred... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/chain_extract.html |
1174c1843903-2 | _get_input = get_input if get_input is not None else default_get_input
llm_chain = LLMChain(llm=llm, prompt=_prompt, **(llm_chain_kwargs or {}))
return cls(llm_chain=llm_chain, get_input=_get_input)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/retrievers/document_compressors/chain_extract.html |
7fdcf1b946e8-0 | Source code for langchain.retrievers.self_query.base
"""Retriever that generates and executes structured queries over its own data source."""
from typing import Any, Dict, List, Optional, Type, cast
from pydantic import BaseModel, Field, root_validator
from langchain import LLMChain
from langchain.base_language import ... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/self_query/base.html |
7fdcf1b946e8-1 | vectorstore: VectorStore
"""The underlying vector store from which documents will be retrieved."""
llm_chain: LLMChain
"""The LLMChain for generating the vector store queries."""
search_type: str = "similarity"
"""The search type to perform on the vector store."""
search_kwargs: dict = Field(def... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/self_query/base.html |
7fdcf1b946e8-2 | if structured_query.limit is not None:
new_kwargs["k"] = structured_query.limit
search_kwargs = {**self.search_kwargs, **new_kwargs}
docs = self.vectorstore.search(new_query, self.search_type, **search_kwargs)
return docs
[docs] async def aget_relevant_documents(self, query: str) ... | https://python.langchain.com/en/latest/_modules/langchain/retrievers/self_query/base.html |
7fdcf1b946e8-3 | **kwargs,
)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/retrievers/self_query/base.html |
f7fac1d6b36c-0 | Source code for langchain.tools.base
"""Base implementation for tools or skills."""
from __future__ import annotations
import warnings
from abc import ABC, abstractmethod
from inspect import signature
from typing import Any, Awaitable, Callable, Dict, Optional, Tuple, Type, Union
from pydantic import (
BaseModel,
... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-1 | ...
args_schema: Type[BaseModel] = SchemaClass
..."""
raise SchemaAnnotationError(
f"Tool definition for {name} must include valid type annotations"
f" for argument 'args_schema' to behave as expected.\n"
f"Expected annotation of 'Type[... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-2 | model_name: str,
func: Callable,
) -> Type[BaseModel]:
"""Create a pydantic schema from a function's signature."""
validated = validate_arguments(func, config=_SchemaConfig) # type: ignore
inferred_model = validated.model # type: ignore
if "run_manager" in inferred_model.__fields__:
del in... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-3 | """Deprecated. Please use callbacks instead."""
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
arbitrary_types_allowed = True
@property
def is_single_input(self) -> bool:
"""Whether the tool only accepts a single input."""
keys = {k f... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-4 | values["callbacks"] = values.pop("callback_manager", None)
return values
@abstractmethod
def _run(
self,
*args: Any,
**kwargs: Any,
) -> Any:
"""Use the tool.
Add run_manager: Optional[CallbackManagerForToolRun] = None
to child implementations to enabl... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-5 | )
# TODO: maybe also pass through run_manager is _run supports kwargs
new_arg_supported = signature(self._run).parameters.get("run_manager")
run_manager = callback_manager.on_tool_start(
{"name": self.name, "description": self.description},
tool_input if isinstance(tool_i... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-6 | run_manager = await callback_manager.on_tool_start(
{"name": self.name, "description": self.description},
tool_input if isinstance(tool_input, str) else str(tool_input),
color=start_color,
**kwargs,
)
try:
# We then call the tool on the tool in... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-7 | return {"tool_input": {"type": "string"}}
def _to_args_and_kwargs(self, tool_input: Union[str, Dict]) -> Tuple[Tuple, Dict]:
"""Convert tool input to pydantic model."""
args, kwargs = super()._to_args_and_kwargs(tool_input)
# For backwards compatibility. The tool must be run with a single in... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-8 | **kwargs,
)
if new_argument_supported
else await self.coroutine(*args, **kwargs)
)
raise NotImplementedError("Tool does not support async")
# TODO: this is for backwards compatibility, remove in future
def __init__(
self, name: str, fun... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-9 | return self.args_schema.schema()["properties"]
def _run(
self,
*args: Any,
run_manager: Optional[CallbackManagerForToolRun] = None,
**kwargs: Any,
) -> Any:
"""Use the tool."""
new_argument_supported = signature(self.func).parameters.get("callbacks")
retur... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-10 | ) -> StructuredTool:
name = name or func.__name__
description = description or func.__doc__
assert (
description is not None
), "Function must have a docstring if description not provided."
# Description example:
# search_api(query: str) - Searches the API for... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-11 | # Searches the API for the query.
return
@tool("search", return_direct=True)
def search_api(query: str) -> str:
# Searches the API for the query.
return
"""
def _make_with_name(tool_name: str) -> Callable:
def _make_tool(func: Calla... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
f7fac1d6b36c-12 | # Example usage: @tool(return_direct=True)
def _partial(func: Callable[[str], str]) -> BaseTool:
return _make_with_name(func.__name__)(func)
return _partial
else:
raise ValueError("Too many arguments for tool decorator")
By Harrison Chase
© Copyright 2023, Harrison Cha... | https://python.langchain.com/en/latest/_modules/langchain/tools/base.html |
cc2cb5d2bed4-0 | Source code for langchain.tools.plugin
from __future__ import annotations
import json
from typing import Optional, Type
import requests
import yaml
from pydantic import BaseModel
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base impo... | https://python.langchain.com/en/latest/_modules/langchain/tools/plugin.html |
cc2cb5d2bed4-1 | plugin = AIPlugin.from_url(url)
description = (
f"Call this tool to get the OpenAPI spec (and usage guide) "
f"for interacting with the {plugin.name_for_human} API. "
f"You should only call this ONCE! What is the "
f"{plugin.name_for_human} API useful for? "
... | https://python.langchain.com/en/latest/_modules/langchain/tools/plugin.html |
4414a5007c31-0 | Source code for langchain.tools.ifttt
"""From https://github.com/SidU/teams-langchain-js/wiki/Connecting-IFTTT-Services.
# Creating a webhook
- Go to https://ifttt.com/create
# Configuring the "If This"
- Click on the "If This" button in the IFTTT interface.
- Search for "Webhooks" in the search bar.
- Choose the first... | https://python.langchain.com/en/latest/_modules/langchain/tools/ifttt.html |
4414a5007c31-1 | - To get your webhook URL go to https://ifttt.com/maker_webhooks/settings
- Copy the IFTTT key value from there. The URL is of the form
https://maker.ifttt.com/use/YOUR_IFTTT_KEY. Grab the YOUR_IFTTT_KEY value.
"""
from typing import Optional
import requests
from langchain.callbacks.manager import (
AsyncCallbackMa... | https://python.langchain.com/en/latest/_modules/langchain/tools/ifttt.html |
461f35cd67b5-0 | Source code for langchain.tools.wikipedia.tool
"""Tool for the Wikipedia API."""
from typing import Optional
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.utilities.wikipedia import WikipediaAPIWrap... | https://python.langchain.com/en/latest/_modules/langchain/tools/wikipedia/tool.html |
3c11ff521557-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/shell/tool.html |
3c11ff521557-1 | 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://python.langchain.com/en/latest/_modules/langchain/tools/shell/tool.html |
1b630b27b6df-0 | Source code for langchain.tools.zapier.tool
"""## Zapier Natural Language Actions API
\
Full docs here: https://nla.zapier.com/api/v1/docs
**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, Sales... | https://python.langchain.com/en/latest/_modules/langchain/tools/zapier/tool.html |
1b630b27b6df-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/demo/provid... | https://python.langchain.com/en/latest/_modules/langchain/tools/zapier/tool.html |
1b630b27b6df-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://python.langchain.com/en/latest/_modules/langchain/tools/zapier/tool.html |
1b630b27b6df-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://python.langchain.com/en/latest/_modules/langchain/tools/zapier/tool.html |
1b630b27b6df-4 | )
# other useful actions
[docs]class ZapierNLAListActions(BaseTool):
"""
Args:
None
"""
name = "Zapier NLA: List Actions"
description = BASE_ZAPIER_TOOL_PROMPT + (
"This tool returns a list of the user's exposed actions."
)
api_wrapper: ZapierNLAWrapper = Field(default_factor... | https://python.langchain.com/en/latest/_modules/langchain/tools/zapier/tool.html |
863f81a98a87-0 | Source code for langchain.tools.google_places.tool
"""Tool for the Google search API."""
from typing import Optional
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langcha... | https://python.langchain.com/en/latest/_modules/langchain/tools/google_places/tool.html |
06a4d7d92ffd-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://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
06a4d7d92ffd-1 | values, "azure_cogs_endpoint", "AZURE_COGS_ENDPOINT"
)
try:
import azure.ai.vision as sdk
values["vision_service"] = sdk.VisionServiceOptions(
endpoint=azure_cogs_endpoint, key=azure_cogs_key
)
values["analysis_options"] = sdk.ImageAnalysis... | https://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
06a4d7d92ffd-2 | if result.tags is not None:
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)
... | https://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
06a4d7d92ffd-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://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
fe0d7446fea4-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
fe0d7446fea4-1 | values, "azure_cogs_key", "AZURE_COGS_KEY"
)
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 AzureKeyC... | https://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
fe0d7446fea4-2 | with open(document_path, "rb") as document:
poller = self.doc_analysis_client.begin_analyze_document(
"prebuilt-document", document
)
elif document_src_type == "remote":
poller = self.doc_analysis_client.begin_analyze_document_from_url(
... | https://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
fe0d7446fea4-3 | run_manager: Optional[CallbackManagerForToolRun] = None,
) -> 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._... | https://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
6c926b6cfb39-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/speech2text.html |
6c926b6cfb39-1 | values, "azure_cogs_key", "AZURE_COGS_KEY"
)
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(
... | https://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/speech2text.html |
6c926b6cfb39-2 | try:
import azure.cognitiveservices.speech as speechsdk
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":
... | https://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/speech2text.html |
b4f7d3a1edb1-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
b4f7d3a1edb1-1 | )
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://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
b4f7d3a1edb1-2 | 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://python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
27d5be0c8cb2-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/read.html |
27d5be0c8cb2-1 | # TODO: Add aiofiles method
raise NotImplementedError
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/tools/file_management/read.html |
a26683cc34a0-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/file_search.html |
a26683cc34a0-1 | 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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/file_search.html |
fe6d423f5f3d-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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/list_dir.html |
fe6d423f5f3d-1 | raise NotImplementedError
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/tools/file_management/list_dir.html |
8e03746c2efc-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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/write.html |
8e03746c2efc-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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/write.html |
f7d76796fce1-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/copy.html |
f7d76796fce1-1 | 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
By Harrison C... | https://python.langchain.com/en/latest/_modules/langchain/tools/file_management/copy.html |
08010246c557-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/move.html |
08010246c557-1 | 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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/move.html |
8a9430181825-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/file_management/delete.html |
8a9430181825-1 | raise NotImplementedError
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/tools/file_management/delete.html |
4569e340b66d-0 | Source code for langchain.tools.playwright.navigate_back
from __future__ import annotations
from typing import Optional, Type
from pydantic import BaseModel
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.playwright.base import BaseBrow... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate_back.html |
4569e340b66d-1 | response = await page.go_back()
if response:
return (
f"Navigated back to the previous page with URL '{response.url}'."
f" Status code {response.status}"
)
else:
return "Unable to navigate back; no previous page in the history"
By Harri... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate_back.html |
977bb43d0c2a-0 | Source code for langchain.tools.playwright.navigate
from __future__ import annotations
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.playwright.base import BaseBr... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate.html |
977bb43d0c2a-1 | response = await page.goto(url)
status = response.status if response else "unknown"
return f"Navigating to {url} returned status code {status}"
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate.html |
3783a1a2f034-0 | Source code for langchain.tools.playwright.extract_hyperlinks
from __future__ import annotations
import json
from typing import TYPE_CHECKING, Any, Optional, Type
from pydantic import BaseModel, Field, root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToo... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_hyperlinks.html |
3783a1a2f034-1 | # Find all the anchor elements and extract their href attributes
anchors = soup.find_all("a")
if absolute_urls:
base_url = page.url
links = [urljoin(base_url, anchor.get("href", "")) for anchor in anchors]
else:
links = [anchor.get("href", "") for anchor in an... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_hyperlinks.html |
a9aea442cc7b-0 | Source code for langchain.tools.playwright.current_page
from __future__ import annotations
from typing import Optional, Type
from pydantic import BaseModel
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.playwright.base import BaseBrows... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/current_page.html |
bd3bd66536a0-0 | Source code for langchain.tools.playwright.click
from __future__ import annotations
from typing import Optional, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.playwright.base import BaseBrows... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/click.html |
bd3bd66536a0-1 | # Navigate to the desired webpage before using this tool
selector_effective = self._selector_effective(selector=selector)
from playwright.sync_api import TimeoutError as PlaywrightTimeoutError
try:
page.click(
selector_effective,
strict=self.playwright... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/click.html |
727634890b3a-0 | Source code for langchain.tools.playwright.extract_text
from __future__ import annotations
from typing import Optional, Type
from pydantic import BaseModel, root_validator
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.playwright.base ... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_text.html |
727634890b3a-1 | self, run_manager: Optional[AsyncCallbackManagerForToolRun] = None
) -> str:
"""Use the tool."""
if self.async_browser is None:
raise ValueError(f"Asynchronous browser not provided to {self.name}")
# Use Beautiful Soup since it's faster than looping through the elements
f... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_text.html |
6f3e6ebd7945-0 | Source code for langchain.tools.playwright.get_elements
from __future__ import annotations
import json
from typing import TYPE_CHECKING, List, Optional, Sequence, Type
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
fro... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
6f3e6ebd7945-1 | ) -> List[dict]:
"""Get elements matching the given CSS selector."""
elements = page.query_selector_all(selector)
results = []
for element in elements:
result = {}
for attribute in attributes:
if attribute == "innerText":
val: Optional[str] = element.inner_tex... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
6f3e6ebd7945-2 | raise ValueError(f"Asynchronous browser not provided to {self.name}")
page = await aget_current_page(self.async_browser)
# Navigate to the desired webpage before using this tool
results = await _aget_elements(page, selector, attributes)
return json.dumps(results, ensure_ascii=False)
By H... | https://python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
4932086af754-0 | 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://python.langchain.com/en/latest/_modules/langchain/tools/youtube/search.html |
4932086af754-1 | 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://python.langchain.com/en/latest/_modules/langchain/tools/youtube/search.html |
249a8376736c-0 | Source code for langchain.tools.openapi.utils.api_models
"""Pydantic models for parsing an OpenAPI spec."""
import logging
from enum import Enum
from typing import Any, Dict, List, Optional, Sequence, Tuple, Type, Union
from openapi_schema_pydantic import MediaType, Parameter, Reference, RequestBody, Schema
from pydant... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-1 | + f"Valid values are {[loc.value for loc in SUPPORTED_LOCATIONS]}"
)
SCHEMA_TYPE = Union[str, Type, tuple, None, Enum]
class APIPropertyBase(BaseModel):
"""Base model for an API property."""
# The name of the parameter is required and is case sensitive.
# If "in" is "path", the "name" field must correspond ... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-2 | type_ = schema.type
if not isinstance(type_, list):
return type_
else:
return tuple(type_)
@staticmethod
def _get_schema_type_for_enum(parameter: Parameter, schema: Schema) -> Enum:
"""Get the schema type when the parameter is an enum."""
param_name = f"{p... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-3 | schema_type = APIProperty._get_schema_type_for_enum(parameter, schema)
else:
# Directly use the primitive type
pass
else:
raise NotImplementedError(f"Unsupported type: {schema_type}")
return schema_type
@staticmethod
def _validate_location(... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-4 | location,
parameter.name,
)
cls._validate_content(parameter.content)
schema = cls._get_schema(parameter, spec)
schema_type = cls._get_schema_type(parameter, schema)
default_val = schema.default if schema is not None else None
return cls(
name=param... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-5 | cls.from_schema(
schema=prop_schema,
name=prop_name,
required=prop_name in required_props,
spec=spec,
references_used=references_used,
)
)
return schema.type, properties
@classmeth... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-6 | schema_type, properties = cls._process_object_schema(
schema, spec, references_used
)
elif schema_type == "array":
schema_type = cls._process_array_schema(schema, name, spec, references_used)
elif schema_type in PRIMITIVE_TYPES:
# Use the primitive typ... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-7 | f"Could not resolve schema for media type: {media_type_obj}"
)
api_request_body_properties = []
required_properties = schema.required or []
if schema.type == "object" and schema.properties:
for prop_name, prop_schema in schema.properties.items():
if isinst... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-8 | operation_id: str = Field(alias="operation_id")
"""The unique identifier of the operation."""
description: Optional[str] = Field(alias="description")
"""The description of the operation."""
base_url: str = Field(alias="base_url")
"""The base URL of the operation."""
path: str = Field(alias="path... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-9 | def from_openapi_url(
cls,
spec_url: str,
path: str,
method: str,
) -> "APIOperation":
"""Create an APIOperation from an OpenAPI URL."""
spec = OpenAPISpec.from_url(spec_url)
return cls.from_openapi_spec(spec, path, method)
[docs] @classmethod
def from_... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-10 | # parsing specs that are < v3
return "any"
elif isinstance(type_, str):
return {
"str": "string",
"integer": "number",
"float": "number",
"date-time": "string",
}.get(type_, type_)
elif isinstance(type_, ... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
249a8376736c-11 | if self.request_body:
formatted_request_body_props = self._format_nested_properties(
self.request_body.properties
)
params.append(formatted_request_body_props)
for prop in self.properties:
prop_name = prop.name
prop_type = self.ts_type_... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
2ae81e0b731f-0 | Source code for langchain.tools.openapi.utils.openapi_utils
"""Utility functions for parsing an OpenAPI spec."""
import copy
import json
import logging
import re
from enum import Enum
from pathlib import Path
from typing import Dict, List, Optional, Union
import requests
import yaml
from openapi_schema_pydantic import ... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/openapi_utils.html |
2ae81e0b731f-1 | return path_item
@property
def _components_strict(self) -> Components:
"""Get components or err."""
if self.components is None:
raise ValueError("No components found in spec. ")
return self.components
@property
def _parameters_strict(self) -> Dict[str, Union[Parameter... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/openapi_utils.html |
2ae81e0b731f-2 | parameter = self._get_referenced_parameter(ref)
while isinstance(parameter, Reference):
parameter = self._get_referenced_parameter(parameter)
return parameter
[docs] def get_referenced_schema(self, ref: Reference) -> Schema:
"""Get a schema (or nested reference) or err."""
... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/openapi_utils.html |
2ae81e0b731f-3 | """Alert if the spec is not supported."""
warning_message = (
" This may result in degraded performance."
+ " Convert your OpenAPI spec to 3.1.* spec"
+ " for better support."
)
swagger_version = obj.get("swagger")
openapi_version = obj.get("openapi")
... | https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/openapi_utils.html |
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