a230a44f5c
* Added exa-search case to the search provider switch in web-browsing.js * Added ExaSearchOptions component for API key input * update * Patch missing image crashing UI Fix issue where ENV key did not exist or was saved on click Update copy for provider Add Docs for ENV keys for manual placements update systemssettings for returning key saved to UI --------- Co-authored-by: timothycarambat <rambat1010@gmail.com>
354 lines
12 KiB
Plaintext
354 lines
12 KiB
Plaintext
SERVER_PORT=3001
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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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# SIG_KEY='passphrase' # Please generate random string at least 32 chars long.
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# SIG_SALT='salt' # Please generate random string at least 32 chars long.
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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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# JWT_EXPIRY="30d" # (optional) https://docs.anythingllm.com/configuration#custom-ttl-for-sessions
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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-4o'
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# LLM_PROVIDER='gemini'
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# GEMINI_API_KEY=
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# GEMINI_LLM_MODEL_PREF='gemini-2.0-flash-lite'
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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_PREF='Loaded from Chat UI' # this is a bug in LMStudio 0.2.17
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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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# LLM_PROVIDER='ollama'
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# OLLAMA_BASE_PATH='http://host.docker.internal:11434'
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# OLLAMA_MODEL_PREF='llama2'
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# OLLAMA_MODEL_TOKEN_LIMIT=4096
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# OLLAMA_AUTH_TOKEN='your-ollama-auth-token-here (optional, only for ollama running behind auth - Bearer token)'
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# LLM_PROVIDER='togetherai'
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# TOGETHER_AI_API_KEY='my-together-ai-key'
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# TOGETHER_AI_MODEL_PREF='mistralai/Mixtral-8x7B-Instruct-v0.1'
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# LLM_PROVIDER='mistral'
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# MISTRAL_API_KEY='example-mistral-ai-api-key'
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# MISTRAL_MODEL_PREF='mistral-tiny'
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# LLM_PROVIDER='perplexity'
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# PERPLEXITY_API_KEY='my-perplexity-key'
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# PERPLEXITY_MODEL_PREF='codellama-34b-instruct'
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# LLM_PROVIDER='openrouter'
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# OPENROUTER_API_KEY='my-openrouter-key'
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# OPENROUTER_MODEL_PREF='openrouter/auto'
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# LLM_PROVIDER='huggingface'
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# HUGGING_FACE_LLM_ENDPOINT=https://uuid-here.us-east-1.aws.endpoints.huggingface.cloud
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# HUGGING_FACE_LLM_API_KEY=hf_xxxxxx
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# HUGGING_FACE_LLM_TOKEN_LIMIT=8000
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# LLM_PROVIDER='groq'
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# GROQ_API_KEY=gsk_abcxyz
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# GROQ_MODEL_PREF=llama3-8b-8192
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# LLM_PROVIDER='koboldcpp'
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# KOBOLD_CPP_BASE_PATH='http://127.0.0.1:5000/v1'
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# KOBOLD_CPP_MODEL_PREF='koboldcpp/codellama-7b-instruct.Q4_K_S'
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# KOBOLD_CPP_MODEL_TOKEN_LIMIT=4096
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# LLM_PROVIDER='textgenwebui'
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# TEXT_GEN_WEB_UI_BASE_PATH='http://127.0.0.1:5000/v1'
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# TEXT_GEN_WEB_UI_TOKEN_LIMIT=4096
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# TEXT_GEN_WEB_UI_API_KEY='sk-123abc'
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# LLM_PROVIDER='generic-openai'
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# GENERIC_OPEN_AI_BASE_PATH='http://proxy.url.openai.com/v1'
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# GENERIC_OPEN_AI_MODEL_PREF='gpt-3.5-turbo'
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# GENERIC_OPEN_AI_MODEL_TOKEN_LIMIT=4096
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# GENERIC_OPEN_AI_API_KEY=sk-123abc
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# LLM_PROVIDER='litellm'
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# LITE_LLM_MODEL_PREF='gpt-3.5-turbo'
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# LITE_LLM_MODEL_TOKEN_LIMIT=4096
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# LITE_LLM_BASE_PATH='http://127.0.0.1:4000'
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# LITE_LLM_API_KEY='sk-123abc'
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# LLM_PROVIDER='novita'
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# NOVITA_LLM_API_KEY='your-novita-api-key-here' check on https://novita.ai/settings/key-management
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# NOVITA_LLM_MODEL_PREF='deepseek/deepseek-r1'
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# LLM_PROVIDER='cohere'
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# COHERE_API_KEY=
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# COHERE_MODEL_PREF='command-r'
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# LLM_PROVIDER='bedrock'
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# AWS_BEDROCK_LLM_ACCESS_KEY_ID=
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# AWS_BEDROCK_LLM_ACCESS_KEY=
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# AWS_BEDROCK_LLM_REGION=us-west-2
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# AWS_BEDROCK_LLM_MODEL_PREFERENCE=meta.llama3-1-8b-instruct-v1:0
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# AWS_BEDROCK_LLM_MODEL_TOKEN_LIMIT=8191
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# AWS_BEDROCK_LLM_CONNECTION_METHOD=iam
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# AWS_BEDROCK_LLM_MAX_OUTPUT_TOKENS=4096
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# AWS_BEDROCK_LLM_SESSION_TOKEN= # Only required if CONNECTION_METHOD is 'sessionToken'
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# LLM_PROVIDER='fireworksai'
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# FIREWORKS_AI_LLM_API_KEY='my-fireworks-ai-key'
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# FIREWORKS_AI_LLM_MODEL_PREF='accounts/fireworks/models/llama-v3p1-8b-instruct'
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# LLM_PROVIDER='apipie'
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# APIPIE_LLM_API_KEY='sk-123abc'
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# APIPIE_LLM_MODEL_PREF='openrouter/llama-3.1-8b-instruct'
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# LLM_PROVIDER='xai'
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# XAI_LLM_API_KEY='xai-your-api-key-here'
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# XAI_LLM_MODEL_PREF='grok-beta'
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# LLM_PROVIDER='nvidia-nim'
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# NVIDIA_NIM_LLM_BASE_PATH='http://127.0.0.1:8000'
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# NVIDIA_NIM_LLM_MODEL_PREF='meta/llama-3.2-3b-instruct'
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# LLM_PROVIDER='deepseek'
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# DEEPSEEK_API_KEY='your-deepseek-api-key-here'
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# DEEPSEEK_MODEL_PREF='deepseek-chat'
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# LLM_PROVIDER='ppio'
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# PPIO_API_KEY='your-ppio-api-key-here'
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# PPIO_MODEL_PREF=deepseek/deepseek-v3/community
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# LLM_PROVIDER='moonshotai'
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# MOONSHOT_AI_API_KEY='your-moonshot-api-key-here'
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# MOONSHOT_AI_MODEL_PREF='moonshot-v1-32k'
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###########################################
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######## Embedding API SElECTION ##########
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###########################################
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# This will be the assumed default embedding seleciton and model
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# EMBEDDING_ENGINE='native'
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# EMBEDDING_MODEL_PREF='Xenova/all-MiniLM-L6-v2'
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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_MODEL_PREF='text-embedding-ada-002'
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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='http://localhost:8080/v1'
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# EMBEDDING_MODEL_PREF='text-embedding-ada-002'
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# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=1000 # The max chunk size in chars a string to embed can be
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# EMBEDDING_ENGINE='ollama'
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# EMBEDDING_BASE_PATH='http://host.docker.internal:11434'
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# EMBEDDING_MODEL_PREF='nomic-embed-text:latest'
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# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192
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# EMBEDDING_ENGINE='lmstudio'
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# EMBEDDING_BASE_PATH='https://host.docker.internal:1234/v1'
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# EMBEDDING_MODEL_PREF='nomic-ai/nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.Q4_0.gguf'
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# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192
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# EMBEDDING_ENGINE='cohere'
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# COHERE_API_KEY=
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# EMBEDDING_MODEL_PREF='embed-english-v3.0'
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# EMBEDDING_ENGINE='voyageai'
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# VOYAGEAI_API_KEY=
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# EMBEDDING_MODEL_PREF='voyage-large-2-instruct'
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# EMBEDDING_ENGINE='litellm'
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# EMBEDDING_MODEL_PREF='text-embedding-ada-002'
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# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192
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# LITE_LLM_BASE_PATH='http://127.0.0.1:4000'
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# LITE_LLM_API_KEY='sk-123abc'
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# EMBEDDING_ENGINE='generic-openai'
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# EMBEDDING_MODEL_PREF='text-embedding-ada-002'
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# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192
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# EMBEDDING_BASE_PATH='http://127.0.0.1:4000'
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# GENERIC_OPEN_AI_EMBEDDING_API_KEY='sk-123abc'
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# GENERIC_OPEN_AI_EMBEDDING_MAX_CONCURRENT_CHUNKS=500
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# EMBEDDING_ENGINE='gemini'
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# GEMINI_EMBEDDING_API_KEY=
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# EMBEDDING_MODEL_PREF='text-embedding-004'
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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: 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="pgvector"
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# PGVECTOR_CONNECTION_STRING="postgresql://dbuser:dbuserpass@localhost:5432/yourdb"
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# PGVECTOR_TABLE_NAME="anythingllm_vectors" # optional, but can be defined
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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_API_KEY=
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# PINECONE_INDEX=
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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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# Enable all below if you are using vector database: Milvus.
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# VECTOR_DB="milvus"
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# MILVUS_ADDRESS="http://localhost:19530"
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# MILVUS_USERNAME=
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# MILVUS_PASSWORD=
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# Enable all below if you are using vector database: Zilliz Cloud.
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# VECTOR_DB="zilliz"
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# ZILLIZ_ENDPOINT="https://sample.api.gcp-us-west1.zillizcloud.com"
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# ZILLIZ_API_TOKEN=api-token-here
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# Enable all below if you are using vector database: Astra DB.
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# VECTOR_DB="astra"
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# ASTRA_DB_APPLICATION_TOKEN=
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# ASTRA_DB_ENDPOINT=
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###########################################
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######## Audio Model Selection ############
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###########################################
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# (default) use built-in whisper-small model.
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# WHISPER_PROVIDER="local"
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# use openai hosted whisper model.
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# WHISPER_PROVIDER="openai"
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# OPEN_AI_KEY=sk-xxxxxxxx
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###########################################
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######## TTS/STT Model Selection ##########
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###########################################
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# TTS_PROVIDER="native"
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# TTS_PROVIDER="openai"
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# TTS_OPEN_AI_KEY=sk-example
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# TTS_OPEN_AI_VOICE_MODEL=nova
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# TTS_PROVIDER="generic-openai"
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# TTS_OPEN_AI_COMPATIBLE_KEY=sk-example
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# TTS_OPEN_AI_COMPATIBLE_MODEL=tts-1
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# TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL=nova
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# TTS_OPEN_AI_COMPATIBLE_ENDPOINT="https://api.openai.com/v1"
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# TTS_PROVIDER="elevenlabs"
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# TTS_ELEVEN_LABS_KEY=
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# TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel
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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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# DISABLE_TELEMETRY="false"
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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
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###########################################
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######## ENABLE HTTPS SERVER ##############
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###########################################
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# By enabling this and providing the path/filename for the key and cert,
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# the server will use HTTPS instead of HTTP.
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#ENABLE_HTTPS="true"
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#HTTPS_CERT_PATH="sslcert/cert.pem"
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#HTTPS_KEY_PATH="sslcert/key.pem"
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###########################################
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######## AGENT SERVICE KEYS ###############
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###########################################
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#------ SEARCH ENGINES -------
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#=============================
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#------ Google Search -------- https://programmablesearchengine.google.com/controlpanel/create
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# AGENT_GSE_KEY=
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# AGENT_GSE_CTX=
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#------ SearchApi.io ----------- https://www.searchapi.io/
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# AGENT_SEARCHAPI_API_KEY=
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# AGENT_SEARCHAPI_ENGINE=google
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#------ Serper.dev ----------- https://serper.dev/
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# AGENT_SERPER_DEV_KEY=
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#------ Bing Search ----------- https://portal.azure.com/
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# AGENT_BING_SEARCH_API_KEY=
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#------ Serply.io ----------- https://serply.io/
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# AGENT_SERPLY_API_KEY=
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#------ SearXNG ----------- https://github.com/searxng/searxng
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# AGENT_SEARXNG_API_URL=
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#------ Tavily ----------- https://www.tavily.com/
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# AGENT_TAVILY_API_KEY=
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#------ Exa Search ----------- https://www.exa.ai/
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# AGENT_EXA_API_KEY=
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###########################################
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######## Other Configurations ############
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###########################################
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# Disable viewing chat history from the UI and frontend APIs.
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# See https://docs.anythingllm.com/configuration#disable-view-chat-history for more information.
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# DISABLE_VIEW_CHAT_HISTORY=1
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# Enable simple SSO passthrough to pre-authenticate users from a third party service.
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# See https://docs.anythingllm.com/configuration#simple-sso-passthrough for more information.
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# SIMPLE_SSO_ENABLED=1
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# SIMPLE_SSO_NO_LOGIN=1
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# Allow scraping of any IP address in collector - must be string "true" to be enabled
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# See https://docs.anythingllm.com/configuration#local-ip-address-scraping for more information.
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# COLLECTOR_ALLOW_ANY_IP="true"
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# Specify the target languages for when using OCR to parse images and PDFs.
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# This is a comma separated list of language codes as a string. Unsupported languages will be ignored.
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# Default is English. See https://tesseract-ocr.github.io/tessdoc/Data-Files-in-different-versions.html for a list of valid language codes.
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# TARGET_OCR_LANG=eng,deu,ita,spa,fra,por,rus,nld,tur,hun,pol,ita,spa,fra,por,rus,nld,tur,hun,pol |