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def _create_json_content(self, command: str) -> dict[str, Any]: """Create the json content for the request.""" return { "queries": [{"query": rf"{command}"}], "impersonatedUserName": self.impersonated_user_name, "serializerSettings": {"includeNulls": True}, } ...
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) -> str: """Converts a JSON object to a markdown table.""" output_md = "" headers = json_contents[0].keys() for header in headers: header.replace("[", ".").replace("]", "") if table_name: header.replace(f"{table_name}.", "") output_md += f"| {header} " output_md ...
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Source code for langchain.utilities.serpapi """Chain that calls SerpAPI. Heavily borrowed from https://github.com/ofirpress/self-ask """ import os import sys from typing import Any, Dict, Optional, Tuple import aiohttp from pydantic import BaseModel, Extra, Field, root_validator from langchain.utils import get_from_dic...
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aiosession: Optional[aiohttp.ClientSession] = None class Config: """Configuration for this pydantic object.""" extra = Extra.forbid arbitrary_types_allowed = True @root_validator() def validate_environment(cls, values: Dict) -> Dict: """Validate that api key and python packag...
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"""Use aiohttp to run query through SerpAPI and return the results async.""" def construct_url_and_params() -> Tuple[str, Dict[str, str]]: params = self.get_params(query) params["source"] = "python" if self.serpapi_api_key: params["serp_api_key"] = self.serpap...
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toret = res["answer_box"]["snippet"] elif ( "answer_box" in res.keys() and "snippet_highlighted_words" in res["answer_box"].keys() ): toret = res["answer_box"]["snippet_highlighted_words"][0] elif ( "sports_results" in res.keys() and "g...
https://python.langchain.com/en/latest/_modules/langchain/utilities/serpapi.html
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Source code for langchain.utilities.bing_search """Util that calls Bing Search. In order to set this up, follow instructions at: https://levelup.gitconnected.com/api-tutorial-how-to-use-bing-web-search-api-in-python-4165d5592a7e """ from typing import Dict, List import requests from pydantic import BaseModel, Extra, ro...
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bing_subscription_key = get_from_dict_or_env( values, "bing_subscription_key", "BING_SUBSCRIPTION_KEY" ) values["bing_subscription_key"] = bing_subscription_key bing_search_url = get_from_dict_or_env( values, "bing_search_url", "BING_SEARCH_URL", ...
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"snippet": result["snippet"], "title": result["name"], "link": result["url"], } metadata_results.append(metadata_result) return metadata_results By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 28, 2023.
https://python.langchain.com/en/latest/_modules/langchain/utilities/bing_search.html
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Source code for langchain.utilities.bash """Wrapper around subprocess to run commands.""" from __future__ import annotations import platform import re import subprocess from typing import TYPE_CHECKING, List, Union from uuid import uuid4 if TYPE_CHECKING: import pexpect def _lazy_import_pexpect() -> pexpect: ""...
https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html
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# Set the custom prompt process.sendline("PS1=" + prompt) process.expect_exact(prompt, timeout=10) return process [docs] def run(self, commands: Union[str, List[str]]) -> str: """Run commands and return final output.""" if isinstance(commands, str): commands = [com...
https://python.langchain.com/en/latest/_modules/langchain/utilities/bash.html
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self.process.expect(self.prompt, timeout=10) self.process.sendline("") try: self.process.expect([self.prompt, pexpect.EOF], timeout=10) except pexpect.TIMEOUT: return f"Timeout error while executing command {command}" if self.process.after == pexpect.EOF: ...
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Source code for langchain.utilities.wikipedia """Util that calls Wikipedia.""" import logging from typing import Any, Dict, List, Optional from pydantic import BaseModel, Extra, root_validator from langchain.schema import Document logger = logging.getLogger(__name__) WIKIPEDIA_MAX_QUERY_LENGTH = 300 [docs]class Wikiped...
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summaries = [] for page_title in page_titles[: self.top_k_results]: if wiki_page := self._fetch_page(page_title): if summary := self._formatted_page_summary(page_title, wiki_page): summaries.append(summary) if not summaries: return "No good Wik...
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except ( self.wiki_client.exceptions.PageError, self.wiki_client.exceptions.DisambiguationError, ): return None [docs] def load(self, query: str) -> List[Document]: """ Run Wikipedia search and get the article text plus the meta information. See ...
https://python.langchain.com/en/latest/_modules/langchain/utilities/wikipedia.html
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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...
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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? " ...
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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...
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- 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
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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, ...
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... 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[...
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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...
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"""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...
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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...
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) # 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...
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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...
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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...
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**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...
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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...
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) -> 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...
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# 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...
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# 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...
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Source code for langchain.tools.metaphor_search.tool """Tool for the Metaphor search API.""" from typing import Dict, List, Optional, Union from langchain.callbacks.manager import ( AsyncCallbackManagerForToolRun, CallbackManagerForToolRun, ) from langchain.tools.base import BaseTool from langchain.utilities.me...
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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...
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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...
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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...
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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...
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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...
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) # 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...
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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....
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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...
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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...
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) return thread_data async def _arun( self, thread_id: str, run_manager: Optional[AsyncCallbackManagerForToolRun] = None, ) -> Dict: """Run the tool.""" raise NotImplementedError By Harrison Chase © Copyright 2023, Harrison Chase. Last updated ...
https://python.langchain.com/en/latest/_modules/langchain/tools/gmail/get_thread.html
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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 from pydantic import BaseModel, Field from langchain.callbacks.manager import ( AsyncCallbackMa...
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mime_message["To"] = ", ".join(to) mime_message["Subject"] = subject if cc is not None: mime_message["Cc"] = ", ".join(cc) if bcc is not None: mime_message["Bcc"] = ", ".join(bcc) encoded_message = base64.urlsafe_b64encode(mime_message.as_bytes()).decode() ...
https://python.langchain.com/en/latest/_modules/langchain/tools/gmail/send_message.html
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By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 28, 2023.
https://python.langchain.com/en/latest/_modules/langchain/tools/gmail/send_message.html
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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...
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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...
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body = clean_email_body(message_body) results.append( { "id": message["id"], "threadId": message_data["threadId"], "snippet": message_data["snippet"], "body": body, "subject": subject, ...
https://python.langchain.com/en/latest/_modules/langchain/tools/gmail/search.html
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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...
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"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://python.langchain.com/en/latest/_modules/langchain/tools/gmail/get_message.html
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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...
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description = ( "A wrapper around Duck Duck Go Search. " "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( ...
https://python.langchain.com/en/latest/_modules/langchain/tools/ddg_search/tool.html
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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...
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+ 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 ...
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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...
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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(...
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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...
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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...
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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...
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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...
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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...
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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_...
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# 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_, ...
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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
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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
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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...
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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.""" ...
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"""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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def from_spec_dict(cls, spec_dict: dict) -> "OpenAPISpec": """Get an OpenAPI spec from a dict.""" return cls.parse_obj(spec_dict) [docs] @classmethod def from_text(cls, text: str) -> "OpenAPISpec": """Get an OpenAPI spec from a text.""" try: spec_dict = json.loads(text...
https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/openapi_utils.html
2e3d1af696f2-5
if isinstance(operation, Operation): results.append(method.value) return results [docs] def get_operation(self, path: str, method: str) -> Operation: """Get the operation object for a given path and HTTP method.""" path_item = self._get_path_strict(path) operation_obj ...
https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/openapi_utils.html
2e3d1af696f2-6
By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 28, 2023.
https://python.langchain.com/en/latest/_modules/langchain/tools/openapi/utils/openapi_utils.html
3c4c51d9b99a-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://python.langchain.com/en/latest/_modules/langchain/tools/wolfram_alpha/tool.html
778c94e21c9b-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
778c94e21c9b-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
d01bf4e1885c-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
d01bf4e1885c-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
85e77bfafde0-0
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://python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html
85e77bfafde0-1
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://python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html
85e77bfafde0-2
) 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(self.steamship, blocks[0]) else: return blocks[0].id...
https://python.langchain.com/en/latest/_modules/langchain/tools/steamship_image_generation/tool.html
e17eae577e41-0
Source code for langchain.tools.powerbi.tool """Tools for interacting with a Power BI dataset.""" from typing import Any, Dict, Optional, Tuple from pydantic import Field, validator from langchain.callbacks.manager import ( AsyncCallbackManagerForToolRun, CallbackManagerForToolRun, ) from langchain.chains.llm i...
https://python.langchain.com/en/latest/_modules/langchain/tools/powerbi/tool.html
e17eae577e41-1
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", "examples", ]: raise ValueError( "LLM...
https://python.langchain.com/en/latest/_modules/langchain/tools/powerbi/tool.html
e17eae577e41-2
return self.session_cache[tool_input] if query == "I cannot answer this": self.session_cache[tool_input] = query return self.session_cache[tool_input] pbi_result = self.powerbi.run(command=query) result, error = self._parse_output(pbi_result) iterations = kwargs.g...
https://python.langchain.com/en/latest/_modules/langchain/tools/powerbi/tool.html
e17eae577e41-3
self.session_cache[tool_input] = query return self.session_cache[tool_input] pbi_result = await self.powerbi.arun(command=query) result, error = self._parse_output(pbi_result) iterations = kwargs.get("iterations", 0) if error and iterations < self.max_iterations: ...
https://python.langchain.com/en/latest/_modules/langchain/tools/powerbi/tool.html
e17eae577e41-4
Be sure that the tables actually exist by calling list_tables_powerbi first! 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( ...
https://python.langchain.com/en/latest/_modules/langchain/tools/powerbi/tool.html
e17eae577e41-5
self, tool_input: Optional[str] = None, run_manager: Optional[AsyncCallbackManagerForToolRun] = None, ) -> str: """Get the names of the tables.""" return ", ".join(self.powerbi.get_table_names()) By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on ...
https://python.langchain.com/en/latest/_modules/langchain/tools/powerbi/tool.html
5806d1bac02c-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
dde67394cd48-0
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
dde67394cd48-1
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
64a210af5233-0
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
64a210af5233-1
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
7c6e2fc0cda3-0
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
7c6e2fc0cda3-1
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
9b4b2d7d2b43-0
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
9b4b2d7d2b43-1
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
139afa5fe22f-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
139afa5fe22f-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
d9f77821baec-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
d9f77821baec-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
27feea1168f0-0
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