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https://github.com/Mintplex-Labs/anything-llm.git
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732d07829f
* Added improved password complexity checking capability. * Move password complexity checker as User.util dynamically import required libraries depending on code execution flow lint * Ensure persistence of password requirements on restarts via env-dump Copy example schema to docker env as well --------- Co-authored-by: timothycarambat <rambat1010@gmail.com>
95 lines
3.2 KiB
Plaintext
95 lines
3.2 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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# LLM_PROVIDER='localai'
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# LOCAL_AI_BASE_PATH='http://host.docker.internal:8080/v1'
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# LOCAL_AI_MODEL_PREF='luna-ai-llama2'
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# LOCAL_AI_MODEL_TOKEN_LIMIT=4096
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# LOCAL_AI_API_KEY="sk-123abc"
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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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# EMBEDDING_ENGINE='azure'
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# AZURE_OPENAI_ENDPOINT=
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# AZURE_OPENAI_KEY=
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# EMBEDDING_MODEL_PREF='my-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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# EMBEDDING_ENGINE='localai'
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# EMBEDDING_BASE_PATH='https://localhost:8080/v1'
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# EMBEDDING_MODEL_PREF='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://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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###########################################
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######## PASSWORD COMPLEXITY ##############
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###########################################
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# Enforce a password schema for your organization users.
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# Documentation on how to use https://github.com/kamronbatman/joi-password-complexity
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# Default is only 8 char minimum
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# PASSWORDMINCHAR=8
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# PASSWORDMAXCHAR=250
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# PASSWORDLOWERCASE=1
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# PASSWORDUPPERCASE=1
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# PASSWORDNUMERIC=1
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# PASSWORDSYMBOL=1
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# PASSWORDREQUIREMENTS=4 |