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refactor: Refactor storage and new serve template (#947)
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@@ -21,7 +21,7 @@ WEB_SERVER_PORT=7860
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#*******************************************************************#
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#** LLM MODELS **#
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#*******************************************************************#
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# LLM_MODEL, see /pilot/configs/model_config.LLM_MODEL_CONFIG
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# LLM_MODEL, see dbgpt/configs/model_config.LLM_MODEL_CONFIG
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LLM_MODEL=vicuna-13b-v1.5
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## LLM model path, by default, DB-GPT will read the model path from LLM_MODEL_CONFIG based on the LLM_MODEL.
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## Of course you can specify your model path according to LLM_MODEL_PATH
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@@ -29,7 +29,7 @@ LLM_MODEL=vicuna-13b-v1.5
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## 1. environment variable with key: {LLM_MODEL}_MODEL_PATH (Avoid multi-model conflicts)
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## 2. environment variable with key: MODEL_PATH
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## 3. environment variable with key: LLM_MODEL_PATH
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## 4. the config in /pilot/configs/model_config.LLM_MODEL_CONFIG
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## 4. the config in dbgpt/configs/model_config.LLM_MODEL_CONFIG
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# LLM_MODEL_PATH=/app/models/vicuna-13b-v1.5
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# LLM_PROMPT_TEMPLATE=vicuna_v1.1
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MODEL_SERVER=http://127.0.0.1:8000
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@@ -47,7 +47,7 @@ QUANTIZE_8bit=True
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# PROXYLLM_BACKEND=
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### You can configure parameters for a specific model with {model name}_{config key}=xxx
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### See /pilot/model/parameter.py
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### See dbgpt/model/parameter.py
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## prompt template for current model
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# llama_cpp_prompt_template=vicuna_v1.1
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## llama-2-70b must be 8
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@@ -86,7 +86,7 @@ KNOWLEDGE_SEARCH_REWRITE=False
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# EMBEDDING_TOKENIZER=all-MiniLM-L6-v2
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# EMBEDDING_TOKEN_LIMIT=8191
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## Openai embedding model, See /pilot/model/parameter.py
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## Openai embedding model, See dbgpt/model/parameter.py
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# EMBEDDING_MODEL=proxy_openai
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# proxy_openai_proxy_server_url=https://api.openai.com/v1
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# proxy_openai_proxy_api_key={your-openai-sk}
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