Update env.example
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1 changed files with 23 additions and 16 deletions
39
env.example
39
env.example
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@ -172,6 +172,8 @@ MAX_PARALLEL_INSERT=2
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### LLM Configuration
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### LLM Configuration
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### LLM_BINDING type: openai, ollama, lollms, azure_openai, aws_bedrock, gemini
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### LLM_BINDING type: openai, ollama, lollms, azure_openai, aws_bedrock, gemini
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### LLM_BINDING_HOST: host only for Ollama, endpoint for other LLM service
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### LLM_BINDING_HOST: host only for Ollama, endpoint for other LLM service
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### If LightRAG deployed in Docker:
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### uses host.docker.internal instead of localhost in LLM_BINDING_HOST
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###########################################################################
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###########################################################################
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### LLM request timeout setting for all llm (0 means no timeout for Ollma)
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### LLM request timeout setting for all llm (0 means no timeout for Ollma)
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# LLM_TIMEOUT=180
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# LLM_TIMEOUT=180
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@ -181,7 +183,7 @@ LLM_MODEL=gpt-4o
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LLM_BINDING_HOST=https://api.openai.com/v1
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LLM_BINDING_HOST=https://api.openai.com/v1
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LLM_BINDING_API_KEY=your_api_key
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LLM_BINDING_API_KEY=your_api_key
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### Optional for Azure
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### Env vars for Azure openai
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# AZURE_OPENAI_API_VERSION=2024-08-01-preview
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# AZURE_OPENAI_API_VERSION=2024-08-01-preview
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# AZURE_OPENAI_DEPLOYMENT=gpt-4o
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# AZURE_OPENAI_DEPLOYMENT=gpt-4o
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@ -196,22 +198,16 @@ LLM_BINDING_API_KEY=your_api_key
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# LLM_MODEL=gemini-flash-latest
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# LLM_MODEL=gemini-flash-latest
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# LLM_BINDING_API_KEY=your_gemini_api_key
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# LLM_BINDING_API_KEY=your_gemini_api_key
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# LLM_BINDING_HOST=https://generativelanguage.googleapis.com
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# LLM_BINDING_HOST=https://generativelanguage.googleapis.com
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GEMINI_LLM_THINKING_CONFIG='{"thinking_budget": 0, "include_thoughts": false}'
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### use the following command to see all support options for OpenAI, azure_openai or OpenRouter
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### lightrag-server --llm-binding gemini --help
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### Gemini Specific Parameters
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# GEMINI_LLM_MAX_OUTPUT_TOKENS=9000
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# GEMINI_LLM_MAX_OUTPUT_TOKENS=9000
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# GEMINI_LLM_TEMPERATURE=0.7
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# GEMINI_LLM_TEMPERATURE=0.7
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### Enable Thinking
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### OpenAI Compatible API Specific Parameters
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# GEMINI_LLM_THINKING_CONFIG='{"thinking_budget": -1, "include_thoughts": true}'
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### Increased temperature values may mitigate infinite inference loops in certain LLM, such as Qwen3-30B.
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### Disable Thinking
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# OPENAI_LLM_TEMPERATURE=0.9
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# GEMINI_LLM_THINKING_CONFIG='{"thinking_budget": 0, "include_thoughts": false}'
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### Set the max_tokens to mitigate endless output of some LLM (less than LLM_TIMEOUT * llm_output_tokens/second, i.e. 9000 = 180s * 50 tokens/s)
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### Typically, max_tokens does not include prompt content, though some models, such as Gemini Models, are exceptions
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### For vLLM/SGLang deployed models, or most of OpenAI compatible API provider
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# OPENAI_LLM_MAX_TOKENS=9000
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### For OpenAI o1-mini or newer modles
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OPENAI_LLM_MAX_COMPLETION_TOKENS=9000
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#### OpenAI's new API utilizes max_completion_tokens instead of max_tokens
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# OPENAI_LLM_MAX_COMPLETION_TOKENS=9000
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### use the following command to see all support options for OpenAI, azure_openai or OpenRouter
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### use the following command to see all support options for OpenAI, azure_openai or OpenRouter
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### lightrag-server --llm-binding openai --help
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### lightrag-server --llm-binding openai --help
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@ -222,8 +218,17 @@ OPENAI_LLM_MAX_COMPLETION_TOKENS=9000
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### Qwen3 Specific Parameters deploy by vLLM
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### Qwen3 Specific Parameters deploy by vLLM
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# OPENAI_LLM_EXTRA_BODY='{"chat_template_kwargs": {"enable_thinking": false}}'
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# OPENAI_LLM_EXTRA_BODY='{"chat_template_kwargs": {"enable_thinking": false}}'
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### OpenAI Compatible API Specific Parameters
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### Increased temperature values may mitigate infinite inference loops in certain LLM, such as Qwen3-30B.
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# OPENAI_LLM_TEMPERATURE=0.9
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### Set the max_tokens to mitigate endless output of some LLM (less than LLM_TIMEOUT * llm_output_tokens/second, i.e. 9000 = 180s * 50 tokens/s)
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### Typically, max_tokens does not include prompt content
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### For vLLM/SGLang deployed models, or most of OpenAI compatible API provider
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# OPENAI_LLM_MAX_TOKENS=9000
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### For OpenAI o1-mini or newer modles utilizes max_completion_tokens instead of max_tokens
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OPENAI_LLM_MAX_COMPLETION_TOKENS=9000
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### use the following command to see all support options for Ollama LLM
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### use the following command to see all support options for Ollama LLM
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### If LightRAG deployed in Docker uses host.docker.internal instead of localhost in LLM_BINDING_HOST
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### lightrag-server --llm-binding ollama --help
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### lightrag-server --llm-binding ollama --help
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### Ollama Server Specific Parameters
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### Ollama Server Specific Parameters
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### OLLAMA_LLM_NUM_CTX must be provided, and should at least larger than MAX_TOTAL_TOKENS + 2000
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### OLLAMA_LLM_NUM_CTX must be provided, and should at least larger than MAX_TOTAL_TOKENS + 2000
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@ -240,6 +245,8 @@ OLLAMA_LLM_NUM_CTX=32768
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### Embedding Configuration (Should not be changed after the first file processed)
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### Embedding Configuration (Should not be changed after the first file processed)
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### EMBEDDING_BINDING: ollama, openai, azure_openai, jina, lollms, aws_bedrock
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### EMBEDDING_BINDING: ollama, openai, azure_openai, jina, lollms, aws_bedrock
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### EMBEDDING_BINDING_HOST: host only for Ollama, endpoint for other Embedding service
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### EMBEDDING_BINDING_HOST: host only for Ollama, endpoint for other Embedding service
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### If LightRAG deployed in Docker:
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### uses host.docker.internal instead of localhost in EMBEDDING_BINDING_HOST
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#######################################################################################
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#######################################################################################
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# EMBEDDING_TIMEOUT=30
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# EMBEDDING_TIMEOUT=30
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