{"repo": "1thirteeng3/greenmoire", "files": {"integrations/anything-llm/server/.env.example": {"e98fa7294bf92bc8c01ae199cf74636874f94ca5": {"t": 1786068546.867348, "n": 16530, "h": "8f1d1f3dc51c4703", "c": "SERVER_PORT=3001\nJWT_SECRET=\"my-random-string-for-seeding\" # Please generate random string at least 12 chars long.\n# JWT_EXPIRY=\"30d\" # (optional) https://docs.anythingllm.com/configuration#custom-ttl-for-sessions\nSIG_KEY='passphrase' # Please generate random string at least 32 chars long.\nSIG_SALT='salt' # Please generate random string at least 32 chars long.\n\n###########################################\n######## LLM API SElECTION ################\n###########################################\n# LLM_PROVIDER='openai'\n# OPEN_AI_KEY=\n# OPEN_MODEL_PREF='gpt-4o'\n\n# LLM_PROVIDER='gemini'\n# GEMINI_API_KEY=\n# GEMINI_LLM_MODEL_PREF='gemini-2.0-flash-lite'\n\n# LLM_PROVIDER='azure'\n# AZURE_OPENAI_ENDPOINT=\n# AZURE_OPENAI_KEY=\n# AZURE_OPENAI_MODEL_PREF='my-gpt35-deployment' # This is the \"deployment\" on Azure you want to use. Not the base model.\n# 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\n\n# LLM_PROVIDER='anthropic'\n# ANTHROPIC_API_KEY=sk-ant-xxxx\n# ANTHROPIC_MODEL_PREF='claude-2'\n# ANTHROPIC_CACHE_CONTROL=\"5m\" # Enable prompt caching (5m=5min cache, 1h=1hour cache). Reduces costs and improves speed by caching system prompts.\n\n# LLM_PROVIDER='lmstudio'\n# LMSTUDIO_BASE_PATH='http://your-server:1234/v1'\n# LMSTUDIO_MODEL_PREF='Loaded from Chat UI' # this is a bug in LMStudio 0.2.17\n# LMSTUDIO_MODEL_TOKEN_LIMIT=4096\n# LMSTUDIO_AUTH_TOKEN='your-lmstudio-auth-token-here'\n\n# LLM_PROVIDER='localai'\n# LOCAL_AI_BASE_PATH='http://localhost:8080/v1'\n# LOCAL_AI_MODEL_PREF='luna-ai-llama2'\n# LOCAL_AI_MODEL_TOKEN_LIMIT=4096\n# LOCAL_AI_API_KEY=\"sk-123abc\"\n\n# LLM_PROVIDER='ollama'\n# OLLAMA_BASE_PATH='http://host.docker.internal:11434'\n# OLLAMA_MODEL_PREF='llama2'\n# OLLAMA_MODEL_TOKEN_LIMIT=4096\n# OLLAMA_AUTH_TOKEN='your-ollama-auth-token-here (optional, only for ollama running behind auth - Bearer token)'\n# OLLAMA_RESPONSE_TIMEOUT=7200000 (optional, max timeout in milliseconds for ollama response to conclude. Default is 5min before aborting)\n\n# LLM_PROVIDER='togetherai'\n# TOGETHER_AI_API_KEY='my-together-ai-key'\n# TOGETHER_AI_MODEL_PREF='mistralai/Mixtral-8x7B-Instruct-v0.1'\n\n# LLM_PROVIDER='fireworksai'\n# FIREWORKS_AI_LLM_API_KEY='my-fireworks-ai-key'\n# FIREWORKS_AI_LLM_MODEL_PREF='accounts/fireworks/models/llama-v3p1-8b-instruct'\n\n# LLM_PROVIDER='perplexity'\n# PERPLEXITY_API_KEY='my-perplexity-key'\n# PERPLEXITY_MODEL_PREF='codellama-34b-instruct'\n\n# LLM_PROVIDER='deepseek'\n# DEEPSEEK_API_KEY=YOUR_API_KEY\n# DEEPSEEK_MODEL_PREF='deepseek-chat'\n\n# LLM_PROVIDER='openrouter'\n# OPENROUTER_API_KEY='my-openrouter-key'\n# OPENROUTER_MODEL_PREF='openrouter/auto'\n\n# LLM_PROVIDER='mistral'\n# MISTRAL_API_KEY='example-mistral-ai-api-key'\n# MISTRAL_MODEL_PREF='mistral-tiny'\n\n# LLM_PROVIDER='huggingface'\n# HUGGING_FACE_LLM_ENDPOINT=https://uuid-here.us-east-1.aws.endpoints.huggingface.cloud\n# HUGGING_FACE_LLM_API_KEY=hf_xxxxxx\n# HUGGING_FACE_LLM_TOKEN_LIMIT=8000\n\n# LLM_PROVIDER='groq'\n# GROQ_API_KEY=gsk_abcxyz\n# GROQ_MODEL_PREF=llama3-8b-8192\n\n# LLM_PROVIDER='koboldcpp'\n# KOBOLD_CPP_BASE_PATH='http://127.0.0.1:5000/v1'\n# KOBOLD_CPP_MODEL_PREF='koboldcpp/codellama-7b-instruct.Q4_K_S'\n# KOBOLD_CPP_MODEL_TOKEN_LIMIT=4096\n# KOBOLD_CPP_MAX_TOKENS=2048\n\n# LLM_PROVIDER='textgenwebui'\n# TEXT_GEN_WEB_UI_BASE_PATH='http://127.0.0.1:5000/v1'\n# TEXT_GEN_WEB_UI_TOKEN_LIMIT=4096\n# TEXT_GEN_WEB_UI_API_KEY='sk-123abc'\n\n# LLM_PROVIDER='generic-openai'\n# GENERIC_OPEN_AI_BASE_PATH='http://proxy.url.openai.com/v1'\n# GENERIC_OPEN_AI_MODEL_PREF='gpt-3.5-turbo'\n# GENERIC_OPEN_AI_MODEL_TOKEN_LIMIT=4096\n# GENERIC_OPEN_AI_API_KEY=sk-123abc\n# GENERIC_OPEN_AI_CUSTOM_HEADERS=\"X-Custom-Auth:my-secret-key,X-Custom-Header:my-value\" (useful if using a proxy that requires authentication or other headers)\n\n# LLM_PROVIDER='litellm'\n# LITE_LLM_MODEL_PREF='gpt-3.5-turbo'\n# LITE_LLM_MODEL_TOKEN_LIMIT=4096\n# LITE_LLM_BASE_PATH='http://127.0.0.1:4000'\n# LITE_LLM_API_KEY='sk-123abc'\n\n# LLM_PROVIDER='novita'\n# NOVITA_LLM_API_KEY='your-novita-api-key-here' check on https://novita.ai/settings#key-management\n# NOVITA_LLM_MODEL_PREF='deepseek/deepseek-r1'\n\n# LLM_PROVIDER='cohere'\n# COHERE_API_KEY=\n# COHERE_MODEL_PREF='command-r'\n\n# LLM_PROVIDER='cometapi'\n# COMETAPI_LLM_API_KEY='your-cometapi-key-here' # Get one at https://api.cometapi.com/console/token\n# COMETAPI_LLM_MODEL_PREF='gpt-5-mini'\n# COMETAPI_LLM_TIMEOUT_MS=500 # Optional; stream idle timeout in ms (min 500ms)\n\n\n# LLM_PROVIDER='bedrock'\n# AWS_BEDROCK_LLM_ACCESS_KEY_ID=\n# AWS_BEDROCK_LLM_ACCESS_KEY=\n# AWS_BEDROCK_LLM_REGION=us-west-2\n# AWS_BEDROCK_LLM_MODEL_PREFERENCE=meta.llama3-1-8b-instruct-v1:0\n# AWS_BEDROCK_LLM_MODEL_TOKEN_LIMIT=8191\n# AWS_BEDROCK_LLM_CONNECTION_METHOD=iam\n# AWS_BEDROCK_LLM_MAX_OUTPUT_TOKENS=4096\n# AWS_BEDROCK_LLM_SESSION_TOKEN= # Only required if CONNECTION_METHOD is 'sessionToken'\n# or even use Short and Long Term API keys\n# AWS_BEDROCK_LLM_CONNECTION_METHOD=\"apiKey\"\n# AWS_BEDROCK_LLM_API_KEY=\n\n# LLM_PROVIDER='apipie'\n# APIPIE_LLM_API_KEY='sk-123abc'\n# APIPIE_LLM_MODEL_PREF='openrouter/llama-3.1-8b-instruct'\n\n# LLM_PROVIDER='xai'\n# XAI_LLM_API_KEY='xai-your-api-key-here'\n# XAI_LLM_MODEL_PREF='grok-beta'\n\n# LLM_PROVIDER='zai'\n# ZAI_API_KEY=\"your-zai-api-key-here\"\n# ZAI_MODEL_PREF=\"glm-4.5\"\n\n# LLM_PROVIDER='nvidia-nim'\n# NVIDIA_NIM_LLM_BASE_PATH='http://127.0.0.1:8000'\n# NVIDIA_NIM_LLM_MODEL_PREF='meta/llama-3.2-3b-instruct'\n\n# LLM_PROVIDER='ppio'\n# PPIO_API_KEY='your-ppio-api-key-here'\n# PPIO_MODEL_PREF='deepseek/deepseek-v3/community'\n\n# LLM_PROVIDER='moonshotai'\n# MOONSHOT_AI_API_KEY='your-moonshot-api-key-here'\n# MOONSHOT_AI_MODEL_PREF='moonshot-v1-32k'\n\n# LLM_PROVIDER='foundry'\n# FOUNDRY_BASE_PATH='http://127.0.0.1:55776'\n# FOUNDRY_MODEL_PREF='phi-3.5-mini'\n# FOUNDRY_MODEL_TOKEN_LIMIT=4096\n\n# LLM_PROVIDER='giteeai'\n# GITEE_AI_API_KEY=\n# GITEE_AI_MODEL_PREF=\n# GITEE_AI_MODEL_TOKEN_LIMIT=\n\n# LLM_PROVIDER='docker-model-runner'\n# DOCKER_MODEL_RUNNER_BASE_PATH='http://127.0.0.1:12434'\n# DOCKER_MODEL_RUNNER_LLM_MODEL_PREF='phi-3.5-mini'\n# DOCKER_MODEL_RUNNER_LLM_MODEL_TOKEN_LIMIT=4096\n\n# LLM_PROVIDER='privatemode'\n# PRIVATEMODE_LLM_BASE_PATH='http://127.0.0.1:8080'\n# PRIVATEMODE_LLM_MODEL_PREF='gemma-3-27b'\n\n# LLM_PROVIDER='sambanova'\n# SAMBANOVA_LLM_API_KEY='xxx-xxx-xxx'\n# SAMBANOVA_LLM_MODEL_PREF='gpt-oss-120b'\n\n###########################################\n######## Embedding API SElECTION ##########\n###########################################\n# This will be the assumed default embedding seleciton and model\n# EMBEDDING_ENGINE='native'\n# EMBEDDING_MODEL_PREF='Xenova/all-MiniLM-L6-v2'\n\n# Only used if you are using an LLM that does not natively support embedding (openai or Azure)\n# EMBEDDING_ENGINE='openai'\n# OPEN_AI_KEY=sk-xxxx\n# EMBEDDING_MODEL_PREF='text-embedding-ada-002'\n\n# EMBEDDING_ENGINE='azure'\n# AZURE_OPENAI_ENDPOINT=\n# AZURE_OPENAI_KEY=\n# 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\n\n# EMBEDDING_ENGINE='localai'\n# EMBEDDING_BASE_PATH='http://localhost:8080/v1'\n# EMBEDDING_MODEL_PREF='text-embedding-ada-002'\n# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=1000 # The max chunk size in chars a string to embed can be\n\n# EMBEDDING_ENGINE='ollama'\n# EMBEDDING_BASE_PATH='http://127.0.0.1:11434'\n# EMBEDDING_MODEL_PREF='nomic-embed-text:latest'\n# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192\n\n# EMBEDDING_ENGINE='lmstudio'\n# EMBEDDING_BASE_PATH='https://localhost:1234/v1'\n# EMBEDDING_MODEL_PREF='nomic-ai/nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.Q4_0.gguf'\n# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192\n\n# EMBEDDING_ENGINE='cohere'\n# COHERE_API_KEY=\n# EMBEDDING_MODEL_PREF='embed-english-v3.0'\n\n# EMBEDDING_ENGINE='voyageai'\n# VOYAGEAI_API_KEY=\n# EMBEDDING_MODEL_PREF='voyage-large-2-instruct'\n\n# EMBEDDING_ENGINE='litellm'\n# EMBEDDING_MODEL_PREF='text-embedding-ada-002'\n# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192\n# LITE_LLM_BASE_PATH='http://127.0.0.1:4000'\n# LITE_LLM_API_KEY='sk-123abc'\n\n# EMBEDDING_ENGINE='generic-openai'\n# EMBEDDING_MODEL_PREF='text-embedding-ada-002'\n# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192\n# EMBEDDING_BASE_PATH='http://127.0.0.1:4000'\n# GENERIC_OPEN_AI_EMBEDDING_API_KEY='sk-123abc'\n# GENERIC_OPEN_AI_EMBEDDING_MAX_CONCURRENT_CHUNKS=500\n# GENERIC_OPEN_AI_EMBEDDING_API_DELAY_MS=1000\n\n# EMBEDDING_ENGINE='gemini'\n# GEMINI_EMBEDDING_API_KEY=\n# EMBEDDING_MODEL_PREF='text-embedding-004'\n\n# EMBEDDING_ENGINE='openrouter'\n# EMBEDDING_MODEL_PREF='baai/bge-m3'\n# OPENROUTER_API_KEY=''\n\n# EMBEDDING_ENGINE='lemonade'\n# EMBEDDING_BASE_PATH='http://127.0.0.1:8000'\n# EMBEDDING_MODEL_PREF='Qwen3-embedder'\n# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192\n\n###########################################\n######## Vector Database Selection ########\n###########################################\n# Enable all below if you are using vector database: Chroma.\n# VECTOR_DB=\"chroma\"\n# CHROMA_ENDPOINT='http://localhost:8000'\n# CHROMA_API_HEADER=\"X-Api-Key\"\n# CHROMA_API_KEY=\"sk-123abc\"\n\n# Enable all below if you are using vector database: Chroma Cloud.\n# VECTOR_DB=\"chromacloud\"\n# CHROMACLOUD_API_KEY=\"ck-your-api-key\"\n# CHROMACLOUD_TENANT=\n# CHROMACLOUD_DATABASE=\n\n# Enable all below if you are using vector database: Pinecone.\n# VECTOR_DB=\"pinecone\"\n# PINECONE_API_KEY=\n# PINECONE_INDEX=\n\n# Enable all below if you are using vector database: Astra DB.\n# VECTOR_DB=\"astra\"\n# ASTRA_DB_APPLICATION_TOKEN=\n# ASTRA_DB_ENDPOINT=\n\n# Enable all below if you are using vector database: LanceDB.\nVECTOR_DB=\"lancedb\"\n\n# Enable all below if you are using vector database: PG Vector.\n# VECTOR_DB=\"pgvector\"\n# PGVECTOR_CONNECTION_STRING=\"postgresql://dbuser:dbuserpass@localhost:5432/yourdb\"\n# PGVECTOR_TABLE_NAME=\"anythingllm_vectors\" # optional, but can be defined\n\n# Enable all below if you are using vector database: Weaviate.\n# VECTOR_DB=\"weaviate\"\n# WEAVIATE_ENDPOINT=\"http://localhost:8080\"\n# WEAVIATE_API_KEY=\n\n# Enable all below if you are using vector database: Qdrant.\n# VECTOR_DB=\"qdrant\"\n# QDRANT_ENDPOINT=\"http://localhost:6333\"\n# QDRANT_API_KEY=\n\n# Enable all below if you are using vector database: Milvus.\n# VECTOR_DB=\"milvus\"\n# MILVUS_ADDRESS=\"http://localhost:19530\"\n# MILVUS_USERNAME=\n# MILVUS_PASSWORD=\n\n# Enable all below if you are using vector database: Zilliz Cloud.\n# VECTOR_DB=\"zilliz\"\n# ZILLIZ_ENDPOINT=\"https://sample.api.gcp-us-west1.zillizcloud.com\"\n# ZILLIZ_API_TOKEN=api-token-here\n\n###########################################\n######## Audio Model Selection ############\n###########################################\n# (default) use built-in whisper-small model.\nWHISPER_PROVIDER=\"local\"\n\n# use openai hosted whisper model.\n# WHISPER_PROVIDER=\"openai\"\n# OPEN_AI_KEY=sk-xxxxxxxx\n\n###########################################\n######## TTS/STT Model Selection ##########\n###########################################\nTTS_PROVIDER=\"native\"\n\n# TTS_PROVIDER=\"openai\"\n# TTS_OPEN_AI_KEY=sk-example\n# TTS_OPEN_AI_VOICE_MODEL=nova\n\n# TTS_PROVIDER=\"elevenlabs\"\n# TTS_ELEVEN_LABS_KEY=\n# TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel\n\n# TTS_PROVIDER=\"generic-openai\"\n# TTS_OPEN_AI_COMPATIBLE_KEY=sk-example\n# TTS_OPEN_AI_COMPATIBLE_MODEL=tts-1\n# TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL=nova\n# TTS_OPEN_AI_COMPATIBLE_ENDPOINT=\"https://api.openai.com/v1\"\n\n# CLOUD DEPLOYMENT VARIRABLES ONLY\n# AUTH_TOKEN=\"hunter2\" # This is the password to your application if remote hosting.\n# STORAGE_DIR= # absolute filesystem path with no trailing slash\n\n###########################################\n######## PASSWORD COMPLEXITY ##############\n###########################################\n# Enforce a password schema for your organization users.\n# Documentation on how to use https://github.com/kamronbatman/joi-password-complexity\n#PASSWORDMINCHAR=8\n#PASSWORDMAXCHAR=250\n#PASSWORDLOWERCASE=1\n#PASSWORDUPPERCASE=1\n#PASSWORDNUMERIC=1\n#PASSWORDSYMBOL=1\n#PASSWORDREQUIREMENTS=4\n\n###########################################\n######## ENABLE HTTPS SERVER ##############\n###########################################\n# By enabling this and providing the path/filename for the key and cert,\n# the server will use HTTPS instead of HTTP.\n#ENABLE_HTTPS=\"true\"\n#HTTPS_CERT_PATH=\"sslcert/cert.pem\"\n#HTTPS_KEY_PATH=\"sslcert/key.pem\"\n\n###########################################\n######## AGENT SERVICE KEYS ###############\n###########################################\n\n#------ SEARCH ENGINES -------\n#=============================\n#------ Google Search -------- https://programmablesearchengine.google.com/controlpanel/create\n# AGENT_GSE_KEY=\n# AGENT_GSE_CTX=\n\n#------ SerpApi ----------- https://serpapi.com/\n# AGENT_SERPAPI_API_KEY=\n# AGENT_SERPAPI_ENGINE=google\n\n#------ SearchApi.io ----------- https://www.searchapi.io/\n# AGENT_SEARCHAPI_API_KEY=\n# AGENT_SEARCHAPI_ENGINE=google\n\n#------ Serper.dev ----------- https://serper.dev/\n# AGENT_SERPER_DEV_KEY=\n\n#------ Bing Search ----------- https://portal.azure.com/\n# AGENT_BING_SEARCH_API_KEY=\n\n#------ Serply.io ----------- https://serply.io/\n# AGENT_SERPLY_API_KEY=\n\n#------ SearXNG ----------- https://github.com/searxng/searxng\n# AGENT_SEARXNG_API_URL=\n\n#------ Tavily ----------- https://www.tavily.com/\n# AGENT_TAVILY_API_KEY=\n\n#------ Exa Search ----------- https://www.exa.ai/\n# AGENT_EXA_API_KEY=\n\n#------ Perplexity Search ----------- [https://console.perplexity.ai](https://console.perplexity.ai)\n# AGENT_PERPLEXITY_API_KEY=\n\n###########################################\n######## Other Configurations ############\n###########################################\n\n# Disable viewing chat history from the UI and frontend APIs.\n# See https://docs.anythingllm.com/configuration#disable-view-chat-history for more information.\n# DISABLE_VIEW_CHAT_HISTORY=1\n\n# Enable simple SSO passthrough to pre-authenticate users from a third party service.\n# See https://docs.anythingllm.com/configuration#simple-sso-passthrough for more information.\n# SIMPLE_SSO_ENABLED=1\n# SIMPLE_SSO_NO_LOGIN=1\n# SIMPLE_SSO_NO_LOGIN_REDIRECT=https://your-custom-login-url.com (optional)\n\n# Allow scraping of any IP address in collector - must be string \"true\" to be enabled\n# See https://docs.anythingllm.com/configuration#local-ip-address-scraping for more information.\n# COLLECTOR_ALLOW_ANY_IP=\"true\"\n\n# Specify the target languages for when using OCR to parse images and PDFs.\n# This is a comma separated list of language codes as a string. Unsupported languages will be ignored.\n# Default is English. See https://tesseract-ocr.github.io/tessdoc/Data-Files-in-different-versions.html for a list of valid language codes.\n# TARGET_OCR_LANG=eng,deu,ita,spa,fra,por,rus,nld,tur,hun,pol,ita,spa,fra,por,rus,nld,tur,hun,pol\n\n# Runtime flags for built-in pupeeteer Chromium instance\n# This is only required on Linux machines running AnythingLLM via Docker\n# and do not want to use the --cap-add=SYS_ADMIN docker argument\n# ANYTHINGLLM_CHROMIUM_ARGS=\"--no-sandbox,--disable-setuid-sandbox\"\n\n# This enables HTTP request/response logging in development. Set value to a truthy string to enable, leave empty value or comment out to disable.\n# ENABLE_HTTP_LOGGER=\"\"\n# This enables timestamps for the HTTP Logger. Set value to a truthy string to enable, leave empty value or comment out to disable.\n# ENABLE_HTTP_LOGGER_TIMESTAMPS=\"\"\n\n# Disable Swagger API documentation endpoint.\n# Set to \"true\" to disable the /api/docs endpoint (recommended for production deployments).\n# DISABLE_SWAGGER_DOCS=\"true\"\n\n# Disable MCP cooldown timer for agent calls\n# this can lead to infinite recursive calls of the same function\n# for some model/provider combinations\n# MCP_NO_COOLDOWN=\"true\n\n# Allow native tool calling for specific providers.\n# This can VASTLY improve performance and speed of agent calls.\n# Check code for supported providers who can be enabled here via this flag\n# PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING=\"generic-openai,bedrock,localai,groq,litellm,openrouter\"\n\n# (optional) Maximum number of tools an agent can chain for a single response.\n# This prevents some lower-end models from infinite recursive tool calls.\n# AGENT_MAX_TOOL_CALLS=10\n\n# Enable agent tool reranking to reduce token usage by selecting only the most relevant tools\n# for each query. Uses the native embedding reranker to score tools against the user's prompt.\n# Set to \"true\" to enable. This can reduce token costs by 80% when you have\n# many tools/MCP servers enabled.\n# AGENT_SKILL_RERANKER_ENABLED=\"true\"\n# AGENT_SKILL_RERANKER_TOP_N=15 # (optional) Number of top tools to keep after reranking (default: 15)"}}}}