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* Remove LangchainJS for chat support chaining Implement runtime LLM selection Implement AzureOpenAI Support for LLM + Emebedding WIP on frontend Update env to reflect the new fields * Remove LangchainJS for chat support chaining Implement runtime LLM selection Implement AzureOpenAI Support for LLM + Emebedding WIP on frontend Update env to reflect the new fields * Replace keys with LLM Selection in settings modal Enforce checks for new ENVs depending on LLM selection
37 lines
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1.3 KiB
Text
37 lines
No EOL
1.3 KiB
Text
SERVER_PORT=3001
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CACHE_VECTORS="true"
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JWT_SECRET="my-random-string-for-seeding" # Please generate random string at least 12 chars long.
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###########################################
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######## LLM API SElECTION ################
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###########################################
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LLM_PROVIDER='openai'
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# OPEN_AI_KEY=
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OPEN_MODEL_PREF='gpt-3.5-turbo'
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# LLM_PROVIDER='azure'
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# AZURE_OPENAI_ENDPOINT=
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# AZURE_OPENAI_KEY=
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# OPEN_MODEL_PREF='my-gpt35-deployment' # This is the "deployment" on Azure you want to use. Not the base model.
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# EMBEDDING_MODEL_PREF='embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002
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###########################################
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######## Vector Database Selection ########
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###########################################
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# Enable all below if you are using vector database: Chroma.
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# VECTOR_DB="chroma"
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# CHROMA_ENDPOINT='http://localhost:8000'
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# Enable all below if you are using vector database: Pinecone.
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VECTOR_DB="pinecone"
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PINECONE_ENVIRONMENT=
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PINECONE_API_KEY=
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PINECONE_INDEX=
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# Enable all below if you are using vector database: LanceDB.
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# VECTOR_DB="lancedb"
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# CLOUD DEPLOYMENT VARIRABLES ONLY
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# AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
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# STORAGE_DIR= # absolute filesystem path with no trailing slash
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# NO_DEBUG="true" |