refactor: Modify old package name pilot to dbgpt

.env.template

@@ -21,15 +21,15 @@ WEB_SERVER_PORT=7860
 #*******************************************************************#
 #**                         LLM MODELS                            **#
 #*******************************************************************#
-# LLM_MODEL, see /pilot/configs/model_config.LLM_MODEL_CONFIG
+# LLM_MODEL, see dbgpt/configs/model_config.LLM_MODEL_CONFIG
 LLM_MODEL=vicuna-13b-v1.5
 ## LLM model path, by default, DB-GPT will read the model path from LLM_MODEL_CONFIG based on the LLM_MODEL.
 ## Of course you can specify your model path according to LLM_MODEL_PATH
 ## In DB-GPT, the priority from high to low to read model path:
 ##    1. environment variable with key: {LLM_MODEL}_MODEL_PATH (Avoid multi-model conflicts)
 ##    2. environment variable with key: MODEL_PATH
 ##    3. environment variable with key: LLM_MODEL_PATH
-##    4. the config in /pilot/configs/model_config.LLM_MODEL_CONFIG
+##    4. the config in dbgpt/configs/model_config.LLM_MODEL_CONFIG
 # LLM_MODEL_PATH=/app/models/vicuna-13b-v1.5
 # LLM_PROMPT_TEMPLATE=vicuna_v1.1
 MODEL_SERVER=http://127.0.0.1:8000
@@ -47,7 +47,7 @@ QUANTIZE_8bit=True
 # PROXYLLM_BACKEND=
 
 ### You can configure parameters for a specific model with {model name}_{config key}=xxx
-### See /pilot/model/parameter.py
+### See dbgpt/model/parameter.py
 ## prompt template for current model
 # llama_cpp_prompt_template=vicuna_v1.1
 ## llama-2-70b must be 8
@@ -86,7 +86,7 @@ KNOWLEDGE_SEARCH_REWRITE=False
 # EMBEDDING_TOKENIZER=all-MiniLM-L6-v2
 # EMBEDDING_TOKEN_LIMIT=8191
 
-## Openai embedding model, See /pilot/model/parameter.py
+## Openai embedding model, See dbgpt/model/parameter.py
 # EMBEDDING_MODEL=proxy_openai
 # proxy_openai_proxy_server_url=https://api.openai.com/v1
 # proxy_openai_proxy_api_key={your-openai-sk}