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f499f1ba59
* Using OpenAI API locally * Infinite prompt input and compression implementation (#332) * WIP on continuous prompt window summary * wip * Move chat out of VDB simplify chat interface normalize LLM model interface have compression abstraction Cleanup compressor TODO: Anthropic stuff * Implement compression for Anythropic Fix lancedb sources * cleanup vectorDBs and check that lance, chroma, and pinecone are returning valid metadata sources * Resolve Weaviate citation sources not working with schema * comment cleanup * disable import on hosted instances (#339) * disable import on hosted instances * Update UI on disabled import/export --------- Co-authored-by: timothycarambat <rambat1010@gmail.com> * Add support for gpt-4-turbo 128K model (#340) resolves #336 Add support for gpt-4-turbo 128K model * 315 show citations based on relevancy score (#316) * settings for similarity score threshold and prisma schema updated * prisma schema migration for adding similarityScore setting * WIP * Min score default change * added similarityThreshold checking for all vectordb providers * linting --------- Co-authored-by: shatfield4 <seanhatfield5@gmail.com> * rename localai to lmstudio * forgot files that were renamed * normalize model interface * add model and context window limits * update LMStudio tagline * Fully working LMStudio integration --------- Co-authored-by: Francisco Bischoff <984592+franzbischoff@users.noreply.github.com> Co-authored-by: Timothy Carambat <rambat1010@gmail.com> Co-authored-by: Sean Hatfield <seanhatfield5@gmail.com>
67 lines
2.2 KiB
Plaintext
67 lines
2.2 KiB
Plaintext
SERVER_PORT=3001
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CACHE_VECTORS="true"
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# JWT_SECRET="my-random-string-for-seeding" # Only needed if AUTH_TOKEN is set. 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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# LLM_PROVIDER='anthropic'
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# ANTHROPIC_API_KEY=sk-ant-xxxx
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# ANTHROPIC_MODEL_PREF='claude-2'
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# LLM_PROVIDER='lmstudio'
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# LMSTUDIO_BASE_PATH='http://your-server:1234/v1'
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# LMSTUDIO_MODEL_TOKEN_LIMIT=4096
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###########################################
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######## Embedding API SElECTION ##########
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###########################################
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# Only used if you are using an LLM that does not natively support embedding (openai or Azure)
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# EMBEDDING_ENGINE='openai'
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# OPEN_AI_KEY=sk-xxxx
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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://host.docker.internal:8000'
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# CHROMA_API_HEADER="X-Api-Key"
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# CHROMA_API_KEY="sk-123abc"
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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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# Enable all below if you are using vector database: Weaviate.
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# VECTOR_DB="weaviate"
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# WEAVIATE_ENDPOINT="http://localhost:8080"
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# WEAVIATE_API_KEY=
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# Enable all below if you are using vector database: Qdrant.
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# VECTOR_DB="qdrant"
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# QDRANT_ENDPOINT="http://localhost:6333"
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# QDRANT_API_KEY=
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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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# NO_DEBUG="true"
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STORAGE_DIR="/app/server/storage"
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UID='1000'
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GID='1000'
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