id stringlengths 14 16 | text stringlengths 4 1.28k | source stringlengths 54 121 |
|---|---|---|
210b10c26422-4 | )
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 asynchronously."""
raise NotImplementedError("VectorStoreQA... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/vectorstore/tool.html |
289a2a83c2bf-0 | Source code for langchain.tools.pubmed.tool
"""Tool for the Pubmed API."""
from typing import Optional
from pydantic import Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.utilities.pupmed impor... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/pubmed/tool.html |
289a2a83c2bf-1 | )
api_wrapper: PubMedAPIWrapper = Field(default_factory=PubMedAPIWrapper)
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the Arxiv tool."""
return self.api_wrapper.run(query)
async def _arun(
self,
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/pubmed/tool.html |
c7d3716a6ba0-0 | 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/latest/_modules/langchain/tools/google_search/tool.html |
c7d3716a6ba0-1 | ) -> str:
"""Use the tool."""
return self.api_wrapper.run(query)
async def _arun(
self,
query: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Use the tool asynchronously."""
raise NotImplementedError("GoogleSearchRun does n... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/google_search/tool.html |
c7d3716a6ba0-2 | 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/latest/_modules/langchain/tools/google_search/tool.html |
40978ca4af5d-0 | Source code for langchain.tools.searx_search.tool
"""Tool for the SearxNG search API."""
from typing import Optional
from pydantic import Extra
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool, Field
from langchain.u... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/searx_search/tool.html |
40978ca4af5d-1 | def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
return self.wrapper.run(query, **self.kwargs)
async def _arun(
self,
query: str,
run_manager: Optional[AsyncCallbackManagerForToolRun... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/searx_search/tool.html |
40978ca4af5d-2 | "Input should be a search query. Output is a JSON array of the query results"
)
wrapper: SearxSearchWrapper
num_results: int = 4
kwargs: dict = Field(default_factory=dict)
class Config:
"""Pydantic config."""
extra = Extra.allow
def _run(
self,
query: str,
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/searx_search/tool.html |
40978ca4af5d-3 | return (
await self.wrapper.aresults(query, self.num_results, **self.kwargs)
).__str__() | https://api.python.langchain.com/en/latest/_modules/langchain/tools/searx_search/tool.html |
bef1f9041caf-0 | Source code for langchain.tools.requests.tool
# flake8: noqa
"""Tools for making requests to an API endpoint."""
import json
from typing import Any, Dict, Optional
from pydantic import BaseModel
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-1 | """Tool for making a GET request to an API endpoint."""
name = "requests_get"
description = "A portal to the internet. Use this when you need to get specific content from a website. Input should be a url (i.e. https://www.google.com). The output will be the text response of the GET request."
def _run(
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-2 | [docs]class RequestsPostTool(BaseRequestsTool, BaseTool):
"""Tool for making a POST request to an API endpoint."""
name = "requests_post"
description = """Use this when you want to POST to a website.
Input should be a json string with two keys: "url" and "data".
The value of "url" should be a string... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-3 | data = _parse_input(text)
return self.requests_wrapper.post(_clean_url(data["url"]), data["data"])
except Exception as e:
return repr(e)
async def _arun(
self,
text: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Ru... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-4 | Input should be a json string with two keys: "url" and "data".
The value of "url" should be a string, and the value of "data" should be a dictionary of
key-value pairs you want to PATCH to the url.
Be careful to always use double quotes for strings in the json string
The output will be the text respons... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-5 | self,
text: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Run the tool asynchronously."""
try:
data = _parse_input(text)
return await self.requests_wrapper.apatch(
_clean_url(data["url"]), data["data"]
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-6 | key-value pairs you want to PUT to the url.
Be careful to always use double quotes for strings in the json string.
The output will be the text response of the PUT request.
"""
def _run(
self, text: str, run_manager: Optional[CallbackManagerForToolRun] = None
) -> str:
"""Run the tool... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-7 | data = _parse_input(text)
return await self.requests_wrapper.aput(
_clean_url(data["url"]), data["data"]
)
except Exception as e:
return repr(e)
[docs]class RequestsDeleteTool(BaseRequestsTool, BaseTool):
"""Tool for making a DELETE request to an API endpo... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
bef1f9041caf-8 | self,
url: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Run the tool asynchronously."""
return await self.requests_wrapper.adelete(_clean_url(url)) | https://api.python.langchain.com/en/latest/_modules/langchain/tools/requests/tool.html |
fdb9e3a5cfce-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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_text.html |
fdb9e3a5cfce-1 | except ImportError:
raise ValueError(
"The 'beautifulsoup4' package is required to use this tool."
" Please install it with 'pip install beautifulsoup4'."
)
return values
def _run(self, run_manager: Optional[CallbackManagerForToolRun] = None) -> str:
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_text.html |
fdb9e3a5cfce-2 | async def _arun(
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 throu... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_text.html |
07dfeffb7d3b-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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate_back.html |
07dfeffb7d3b-1 | """Use the tool."""
if self.sync_browser is None:
raise ValueError(f"Synchronous browser not provided to {self.name}")
page = get_current_page(self.sync_browser)
response = page.go_back()
if response:
return (
f"Navigated back to the previous page ... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate_back.html |
07dfeffb7d3b-2 | 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" | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate_back.html |
a2e30f1366e6-0 | 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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_hyperlinks.html |
a2e30f1366e6-1 | description: str = "Extract all hyperlinks on the current webpage"
args_schema: Type[BaseModel] = ExtractHyperlinksToolInput
@root_validator
def check_bs_import(cls, values: dict) -> dict:
"""Check that the arguments are valid."""
try:
from bs4 import BeautifulSoup # noqa: F401
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_hyperlinks.html |
a2e30f1366e6-2 | # 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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_hyperlinks.html |
a2e30f1366e6-3 | html_content = page.content()
return self.scrape_page(page, html_content, absolute_urls)
async def _arun(
self,
absolute_urls: bool = False,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Use the tool asynchronously."""
if self.async_br... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/extract_hyperlinks.html |
3e2fe96c6495-0 | 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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/click.html |
3e2fe96c6495-1 | """Whether to consider only visible elements."""
playwright_strict: bool = False
"""Whether to employ Playwright's strict mode when clicking on elements."""
playwright_timeout: float = 1_000
"""Timeout (in ms) for Playwright to wait for element to be ready."""
def _selector_effective(self, selector:... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/click.html |
3e2fe96c6495-2 | selector_effective = self._selector_effective(selector=selector)
from playwright.sync_api import TimeoutError as PlaywrightTimeoutError
try:
page.click(
selector_effective,
strict=self.playwright_strict,
timeout=self.playwright_timeout,
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/click.html |
3e2fe96c6495-3 | selector_effective = self._selector_effective(selector=selector)
from playwright.async_api import TimeoutError as PlaywrightTimeoutError
try:
await page.click(
selector_effective,
strict=self.playwright_strict,
timeout=self.playwright_timeout,
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/click.html |
778ee6de228f-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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate.html |
778ee6de228f-1 | self,
url: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
if self.sync_browser is None:
raise ValueError(f"Synchronous browser not provided to {self.name}")
page = get_current_page(self.sync_browser)
response = ... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate.html |
778ee6de228f-2 | response = await page.goto(url)
status = response.status if response else "unknown"
return f"Navigating to {url} returned status code {status}" | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/navigate.html |
0d9f1c0ec6b8-0 | 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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
0d9f1c0ec6b8-1 | attributes: List[str] = Field(
default_factory=lambda: ["innerText"],
description="Set of attributes to retrieve for each element",
)
async def _aget_elements(
page: AsyncPage, selector: str, attributes: Sequence[str]
) -> List[dict]:
"""Get elements matching the given CSS selector."""
e... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
0d9f1c0ec6b8-2 | return results
def _get_elements(
page: SyncPage, selector: str, attributes: Sequence[str]
) -> 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:
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
0d9f1c0ec6b8-3 | )
args_schema: Type[BaseModel] = GetElementsToolInput
def _run(
self,
selector: str,
attributes: Sequence[str] = ["innerText"],
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
if self.sync_browser is None:
rai... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
0d9f1c0ec6b8-4 | ) -> str:
"""Use the tool."""
if self.async_browser is None:
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_element... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/get_elements.html |
439ce4ed22c0-0 | 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://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/current_page.html |
439ce4ed22c0-1 | page = get_current_page(self.sync_browser)
return str(page.url)
async def _arun(
self,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
if self.async_browser is None:
raise ValueError(f"Asynchronous browser not provid... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/playwright/current_page.html |
f8fe23585a8b-0 | Source code for langchain.tools.ddg_search.tool
"""Tool for the DuckDuckGo search API."""
import warnings
from typing import Any, Optional
from pydantic import Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
f... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/ddg_search/tool.html |
f8fe23585a8b-1 | default_factory=DuckDuckGoSearchAPIWrapper
)
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
return self.api_wrapper.run(query)
async def _arun(
self,
query: str,
run_manage... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/ddg_search/tool.html |
f8fe23585a8b-2 | "Useful for when you need to answer questions about current events. "
"Input should be a search query. Output is a JSON array of the query results"
)
num_results: int = 4
api_wrapper: DuckDuckGoSearchAPIWrapper = Field(
default_factory=DuckDuckGoSearchAPIWrapper
)
def _run(
s... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/ddg_search/tool.html |
f8fe23585a8b-3 | """Use the tool asynchronously."""
raise NotImplementedError("DuckDuckGoSearchResults does not support async")
def DuckDuckGoSearchTool(*args: Any, **kwargs: Any) -> DuckDuckGoSearchRun:
"""
Deprecated. Use DuckDuckGoSearchRun instead.
Args:
*args:
**kwargs:
Returns:
Duck... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/ddg_search/tool.html |
e27c4736326d-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/latest/_modules/langchain/tools/brave_search/tool.html |
e27c4736326d-1 | ) -> BraveSearch:
wrapper = BraveSearchWrapper(api_key=api_key, search_kwargs=search_kwargs or {})
return cls(search_wrapper=wrapper, **kwargs)
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/brave_search/tool.html |
71392965bbfe-0 | Source code for langchain.tools.scenexplain.tool
"""Tool for the SceneXplain API."""
from typing import Optional
from pydantic import BaseModel, Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.tools.base import BaseTool
from langchain.u... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/scenexplain/tool.html |
71392965bbfe-1 | "the output will be a text description that covers every detail of the image."
)
api_wrapper: SceneXplainAPIWrapper = Field(default_factory=SceneXplainAPIWrapper)
def _run(
self, query: str, run_manager: Optional[CallbackManagerForToolRun] = None
) -> str:
"""Use the tool."""
ret... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/scenexplain/tool.html |
20db56ba472f-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://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-1 | # for more info.
class APIPropertyLocation(Enum):
"""The location of the property."""
QUERY = "query"
PATH = "path"
HEADER = "header"
COOKIE = "cookie" # Not yet supported
@classmethod
def from_str(cls, location: str) -> "APIPropertyLocation":
"""Parse an APIPropertyLocation."""
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-2 | " for parameter {name}. "
+ 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... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-3 | """The name of the property."""
required: bool = Field(alias="required")
"""Whether the property is required."""
type: SCHEMA_TYPE = Field(alias="type")
"""The type of the property.
Either a primitive type, a component/parameter type,
or an array or 'object' (dict) of the above."""
defa... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-4 | @staticmethod
def _cast_schema_list_type(schema: Schema) -> Optional[Union[str, Tuple[str, ...]]]:
type_ = schema.type
if not isinstance(type_, list):
return type_
else:
return tuple(type_)
@staticmethod
def _get_schema_type_for_enum(parameter: Parameter, sche... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-5 | elif isinstance(items, Reference):
ref_name = items.ref.split("/")[-1]
schema_type = ref_name # TODO: Add ref definitions to make his valid
else:
raise ValueError(f"Unsupported array items: {items}")
if isinstance(schema_type, str):
# TODO: recurse
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-6 | raise NotImplementedError("Objects not yet supported")
elif schema_type in PRIMITIVE_TYPES:
if schema.enum:
schema_type = APIProperty._get_schema_type_for_enum(parameter, schema)
else:
# Directly use the primitive type
pass
else:
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-7 | )
@staticmethod
def _get_schema(parameter: Parameter, spec: OpenAPISpec) -> Optional[Schema]:
schema = parameter.param_schema
if isinstance(schema, Reference):
schema = spec.get_referenced_schema(schema)
elif schema is None:
return None
elif not isinstance... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-8 | cls._validate_location(
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
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-9 | references_used: List[str] = Field(alias="references_used")
"""The references used by the property."""
@classmethod
def _process_object_schema(
cls, schema: Schema, spec: OpenAPISpec, references_used: List[str]
) -> Tuple[Union[str, List[str], None], List["APIRequestBodyProperty"]]:
prop... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-10 | else:
continue
properties.append(
cls.from_schema(
schema=prop_schema,
name=prop_name,
required=prop_name in required_props,
spec=spec,
references_used=references_used,
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-11 | else:
pass
if isinstance(items, Schema):
array_type = cls.from_schema(
schema=items,
name=f"{name}Item",
required=True, # TODO: Add required
spec=spec,
references_used=referen... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-12 | if schema_type == "object" and schema.properties:
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 schem... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-13 | )
class APIRequestBody(BaseModel):
"""A model for a request body."""
description: Optional[str] = Field(alias="description")
"""The description of the request body."""
properties: List[APIRequestBodyProperty] = Field(alias="properties")
# E.g., application/json - we only support JSON at the moment.
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-14 | schema = spec.get_referenced_schema(schema)
if schema is None:
raise ValueError(
f"Could not resolve schema for media type: {media_type_obj}"
)
api_request_body_properties = []
required_properties = schema.required or []
if schema.type == "object" ... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-15 | type=schema.type,
default=schema.default,
description=schema.description,
properties=[],
references_used=references_used,
)
)
return api_request_body_properties
@classmethod
def from_request_body(... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-16 | )
[docs]class APIOperation(BaseModel):
"""A model for a single API operation."""
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(ali... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-17 | # """The properties of the operation."""
# components: Dict[str, BaseModel] = Field(alias="components")
request_body: Optional[APIRequestBody] = Field(alias="request_body")
"""The request body of the operation."""
@staticmethod
def _get_properties_from_parameters(
parameters: List[Parameter]... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-18 | INVALID_LOCATION_TEMPL.format(
location=param.param_in, name=param.name
)
+ " Ignoring optional parameter"
)
pass
return properties
[docs] @classmethod
def from_openapi_url(
cls,
spec_url: str,... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-19 | parameters = spec.get_parameters_for_operation(operation)
properties = cls._get_properties_from_parameters(parameters, spec)
operation_id = OpenAPISpec.get_cleaned_operation_id(operation, path, method)
request_body = spec.get_request_body_for_operation(operation)
api_request_body = (
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-20 | )
[docs] @staticmethod
def ts_type_from_python(type_: SCHEMA_TYPE) -> str:
if type_ is None:
# TODO: Handle Nones better. These often result when
# parsing specs that are < v3
return "any"
elif isinstance(type_, str):
return {
"str":... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-21 | def _format_nested_properties(
self, properties: List[APIRequestBodyProperty], indent: int = 2
) -> str:
"""Format nested properties."""
formatted_props = []
for prop in properties:
prop_name = prop.name
prop_type = self.ts_type_from_python(prop.type)
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-22 | [docs] def to_typescript(self) -> str:
"""Get typescript string representation of the operation."""
operation_name = self.operation_id
params = []
if self.request_body:
formatted_request_body_props = self._format_nested_properties(
self.request_body.propert... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
20db56ba472f-23 | typescript_definition = f"""
{description_str}
type {operation_name} = (_: {{
{formatted_params}
}}) => any;
"""
return typescript_definition.strip()
@property
def query_params(self) -> List[str]:
return [
property.name
for property in self.properties
if prope... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/api_models.html |
2bcdf9404bc0-0 | 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/latest/_modules/langchain/tools/google_serper/tool.html |
2bcdf9404bc0-1 | self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
return str(self.api_wrapper.run(query))
async def _arun(
self,
query: str,
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
) -> str:
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/google_serper/tool.html |
2bcdf9404bc0-2 | "Input should be a search query. Output is a JSON object of the query results"
)
api_wrapper: GoogleSerperAPIWrapper = Field(default_factory=GoogleSerperAPIWrapper)
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the t... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/google_serper/tool.html |
db08b9eb4c1a-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/latest/_modules/langchain/tools/jira/tool.html |
db08b9eb4c1a-1 | agent = initialize_agent(
toolkit.get_tools(),
llm,
agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
verbose=True
)
```
"""
from typing import Optional
from pydantic import Field
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun,
)
from langchain.too... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/jira/tool.html |
db08b9eb4c1a-2 | 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."""
raise NotImplementedError("JiraAction does not support async") | https://api.python.langchain.com/en/latest/_modules/langchain/tools/jira/tool.html |
b191e8bccacd-0 | Source code for langchain.tools.steamship_image_generation.tool
"""This tool allows agents to generate images using Steamship.
Steamship offers access to different third party image generation APIs
using a single API key.
Today the following models are supported:
- Dall-E
- Stable Diffusion
To use this tool, you must f... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html |
b191e8bccacd-1 | class ModelName(str, Enum):
"""Supported Image Models for generation."""
DALL_E = "dall-e"
STABLE_DIFFUSION = "stable-diffusion"
SUPPORTED_IMAGE_SIZES = {
ModelName.DALL_E: ("256x256", "512x512", "1024x1024"),
ModelName.STABLE_DIFFUSION: ("512x512", "768x768"),
}
[docs]class SteamshipImageGeneration... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html |
b191e8bccacd-2 | description = (
"Useful for when you need to generate an image."
"Input: A detailed text-2-image prompt describing an image"
"Output: the UUID of a generated image"
)
@root_validator(pre=True)
def validate_size(cls, values: Dict) -> Dict:
if "size" in values:
size... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html |
b191e8bccacd-3 | values, "steamship_api_key", "STEAMSHIP_API_KEY"
)
try:
from steamship import Steamship
except ImportError:
raise ImportError(
"steamship is not installed. "
"Please install it with `pip install steamship`"
)
steamship =... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html |
b191e8bccacd-4 | plugin_handle=self.model_name.value, config={"n": 1, "size": self.size}
)
task = image_generator.generate(text=query, append_output_to_file=True)
task.wait()
blocks = task.output.blocks
if len(blocks) > 0:
if self.return_urls:
return make_image_public(... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html |
93b10fe08a85-0 | 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/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
93b10fe08a85-1 | azure_cogs_region: str = "" #: :meta private:
speech_language: str = "en-US" #: :meta private:
speech_config: Any #: :meta private:
name = "azure_cognitive_services_text2speech"
description = (
"A wrapper around Azure Cognitive Services Text2Speech. "
"Useful for when you need to conv... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
93b10fe08a85-2 | )
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/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
93b10fe08a85-3 | )
result = speech_synthesizer.speak_text(text)
if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
stream = speechsdk.AudioDataStream(result)
with tempfile.NamedTemporaryFile(
mode="wb", suffix=".wav", delete=False
) as f:
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
93b10fe08a85-4 | 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/latest/_modules/langchain/tools/azure_cognitive_services/text2speech.html |
b495fd22399d-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/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
b495fd22399d-1 | https://learn.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/quickstarts/get-started-sdks-rest-api?view=form-recog-3.0.0&pivots=programming-language-python
"""
azure_cogs_key: str = "" #: :meta private:
azure_cogs_endpoint: str = "" #: :meta private:
doc_analysis_client: Any #: :meta p... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
b495fd22399d-2 | """Validate that api key and endpoint exists in environment."""
azure_cogs_key = get_from_dict_or_env(
values, "azure_cogs_key", "AZURE_COGS_KEY"
)
azure_cogs_endpoint = get_from_dict_or_env(
values, "azure_cogs_endpoint", "AZURE_COGS_ENDPOINT"
)
try:
... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
b495fd22399d-3 | )
return values
def _parse_tables(self, tables: List[Any]) -> List[Any]:
result = []
for table in tables:
rc, cc = table.row_count, table.column_count
_table = [["" for _ in range(cc)] for _ in range(rc)]
for cell in table.cells:
_table[cel... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
b495fd22399d-4 | document_src_type = detect_file_src_type(document_path)
if document_src_type == "local":
with open(document_path, "rb") as document:
poller = self.doc_analysis_client.begin_analyze_document(
"prebuilt-document", document
)
elif document_src... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
b495fd22399d-5 | res_dict["key_value_pairs"] = self._parse_kv_pairs(result.key_value_pairs)
return res_dict
def _format_document_analysis_result(self, document_analysis_result: Dict) -> str:
formatted_result = []
if "content" in document_analysis_result:
formatted_result.append(
f... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
b495fd22399d-6 | )
return "\n".join(formatted_result)
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
try:
document_analysis_result = self._document_analysis(query)
if not document_analysis_... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/form_recognizer.html |
3872b4afaaf5-0 | 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/latest/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
3872b4afaaf5-1 | azure_cogs_endpoint: str = "" #: :meta private:
vision_service: Any #: :meta private:
analysis_options: Any #: :meta private:
name = "azure_cognitive_services_image_analysis"
description = (
"A wrapper around Azure Cognitive Services Image Analysis. "
"Useful for when you need to anal... | https://api.python.langchain.com/en/latest/_modules/langchain/tools/azure_cognitive_services/image_analysis.html |
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