mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
ed58eeb9c5
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
51 lines
1.8 KiB
Python
51 lines
1.8 KiB
Python
from typing import Optional, Type
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from langchain_core.callbacks import CallbackManagerForToolRun
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from langchain_core.pydantic_v1 import BaseModel, Field
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from langchain_community.chat_models import ChatOpenAI
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from langchain_community.tools.amadeus.base import AmadeusBaseTool
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class ClosestAirportSchema(BaseModel):
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"""Schema for the AmadeusClosestAirport tool."""
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location: str = Field(
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description=(
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" The location for which you would like to find the nearest airport "
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" along with optional details such as country, state, region, or "
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" province, allowing for easy processing and identification of "
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" the closest airport. Examples of the format are the following:\n"
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" Cali, Colombia\n "
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" Lincoln, Nebraska, United States\n"
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" New York, United States\n"
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" Sydney, New South Wales, Australia\n"
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" Rome, Lazio, Italy\n"
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" Toronto, Ontario, Canada\n"
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)
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)
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class AmadeusClosestAirport(AmadeusBaseTool):
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"""Tool for finding the closest airport to a particular location."""
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name: str = "closest_airport"
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description: str = (
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"Use this tool to find the closest airport to a particular location."
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)
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args_schema: Type[ClosestAirportSchema] = ClosestAirportSchema
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def _run(
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self,
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location: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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content = (
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f" What is the nearest airport to {location}? Please respond with the "
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" airport's International Air Transport Association (IATA) Location "
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' Identifier in the following JSON format. JSON: "iataCode": "IATA '
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' Location Identifier" '
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)
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return ChatOpenAI(temperature=0).predict(content)
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