anything-llm/docker/.env.example
Francisco Bischoff f499f1ba59
Using OpenAI API locally (#335)
* 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

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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

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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

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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>
2023-11-09 12:33:21 -08:00

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SERVER_PORT=3001
CACHE_VECTORS="true"
# JWT_SECRET="my-random-string-for-seeding" # Only needed if AUTH_TOKEN is set. Please generate random string at least 12 chars long.
###########################################
######## LLM API SElECTION ################
###########################################
# LLM_PROVIDER='openai'
# OPEN_AI_KEY=
# OPEN_MODEL_PREF='gpt-3.5-turbo'
# LLM_PROVIDER='azure'
# AZURE_OPENAI_ENDPOINT=
# AZURE_OPENAI_KEY=
# OPEN_MODEL_PREF='my-gpt35-deployment' # This is the "deployment" on Azure you want to use. Not the base model.
# 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
# LLM_PROVIDER='anthropic'
# ANTHROPIC_API_KEY=sk-ant-xxxx
# ANTHROPIC_MODEL_PREF='claude-2'
# LLM_PROVIDER='lmstudio'
# LMSTUDIO_BASE_PATH='http://your-server:1234/v1'
# LMSTUDIO_MODEL_TOKEN_LIMIT=4096
###########################################
######## Embedding API SElECTION ##########
###########################################
# Only used if you are using an LLM that does not natively support embedding (openai or Azure)
# EMBEDDING_ENGINE='openai'
# OPEN_AI_KEY=sk-xxxx
###########################################
######## Vector Database Selection ########
###########################################
# Enable all below if you are using vector database: Chroma.
# VECTOR_DB="chroma"
# CHROMA_ENDPOINT='http://host.docker.internal:8000'
# CHROMA_API_HEADER="X-Api-Key"
# CHROMA_API_KEY="sk-123abc"
# Enable all below if you are using vector database: Pinecone.
# VECTOR_DB="pinecone"
# PINECONE_ENVIRONMENT=
# PINECONE_API_KEY=
# PINECONE_INDEX=
# Enable all below if you are using vector database: LanceDB.
VECTOR_DB="lancedb"
# Enable all below if you are using vector database: Weaviate.
# VECTOR_DB="weaviate"
# WEAVIATE_ENDPOINT="http://localhost:8080"
# WEAVIATE_API_KEY=
# Enable all below if you are using vector database: Qdrant.
# VECTOR_DB="qdrant"
# QDRANT_ENDPOINT="http://localhost:6333"
# QDRANT_API_KEY=
# CLOUD DEPLOYMENT VARIRABLES ONLY
# AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
# NO_DEBUG="true"
STORAGE_DIR="/app/server/storage"
UID='1000'
GID='1000'