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31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
import os
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from decouple import config
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from langchain.chat_models import init_chat_model
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from langchain_google_vertexai import VertexAIEmbeddings
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from langchain_mongodb import MongoDBAtlasVectorSearch
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# Get the BASE_URL from the environment variables
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GOOGLE_API_KEY = config("GOOGLE_API_KEY", cast=str)
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WANDB_API_KEY = config("WANDB_API_KEY", cast=str)
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LANGSMITH_API_KEY = config("LANGSMITH_API_KEY", cast=str)
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LANGCHAIN_PROJECT = config("LANGCHAIN_PROJECT", cast=str)
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# Set environment variables
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os.environ["LANGCHAIN_TRACING"] = "true"
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os.environ["LANGCHAIN_ENDPOINT"] = "https://api.smith.langchain.com"
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os.environ["LANGCHAIN_PROJECT"] = LANGCHAIN_PROJECT
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os.environ["LANGCHAIN_API_KEY"] = LANGSMITH_API_KEY
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os.environ["GOOGLE_API_KEY"] = GOOGLE_API_KEY
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llm = init_chat_model("gemini-2.0-flash-001", model_provider="google_vertexai")
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embeddings = VertexAIEmbeddings(model="text-embedding-004")
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vector_store = MongoDBAtlasVectorSearch(
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embedding=embeddings,
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collection=MONGODB_COLLECTION,
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index_name=ATLAS_VECTOR_SEARCH_INDEX_NAME,
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relevance_score_fn="cosine",
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) |