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langchain/libs/community/langchain_community/tools/amadeus/closest_airport.py

51 lines
1.8 KiB
Python

community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
10 months ago
from typing import Optional, Type
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_community.chat_models import ChatOpenAI
from langchain_community.tools.amadeus.base import AmadeusBaseTool
class ClosestAirportSchema(BaseModel):
"""Schema for the AmadeusClosestAirport tool."""
location: str = Field(
description=(
" The location for which you would like to find the nearest airport "
" along with optional details such as country, state, region, or "
" province, allowing for easy processing and identification of "
" the closest airport. Examples of the format are the following:\n"
" Cali, Colombia\n "
" Lincoln, Nebraska, United States\n"
" New York, United States\n"
" Sydney, New South Wales, Australia\n"
" Rome, Lazio, Italy\n"
" Toronto, Ontario, Canada\n"
)
)
class AmadeusClosestAirport(AmadeusBaseTool):
"""Tool for finding the closest airport to a particular location."""
name: str = "closest_airport"
description: str = (
"Use this tool to find the closest airport to a particular location."
)
args_schema: Type[ClosestAirportSchema] = ClosestAirportSchema
def _run(
self,
location: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
content = (
f" What is the nearest airport to {location}? Please respond with the "
" airport's International Air Transport Association (IATA) Location "
' Identifier in the following JSON format. JSON: "iataCode": "IATA '
' Location Identifier" '
)
return ChatOpenAI(temperature=0).predict(content)