Added support for Azure openAI and added API_AZURE_DEPLOYMENT environment variables to adapt to Azure openAI

dbgpt/app/base.py

@@ -105,36 +105,20 @@ def _migration_db_storage(param: "WebServerParameters"):
         from dbgpt.storage.metadata.db_manager import db
         from dbgpt.util._db_migration_utils import _ddl_init_and_upgrade
 
-        # Try to create all tables, when the dbtype is sqlite, it will auto create and upgrade system schema,
-        # Otherwise, you need to execute initialization scripts to create schemas.
-        CFG = Config()
-        if CFG.LOCAL_DB_TYPE == "sqlite":
-            try:
-                db.create_all()
-            except Exception as e:
-                logger.warning(
-                    f"Create all tables stored in this metadata error: {str(e)}"
-                )
-
-                _ddl_init_and_upgrade(
-                    default_meta_data_path, param.disable_alembic_upgrade
-                )
-        else:
-            warn_msg = """For safety considerations, MySQL Database not support DDL init and upgrade. "
-                "1.If you are use DB-GPT firstly, please manually execute the following command to initialize, 
-                `mysql -h127.0.0.1 -uroot -p{your_password} < ./assets/schema/dbgpt.sql` "
-                "2.If there are any changes to the table columns in the DB-GPT database, 
-                it is necessary to compare with the DB-GPT/assets/schema/dbgpt.sql file 
-                and manually make the columns changes in the MySQL database instance."""
-            logger.warning(warn_msg)
+        # try to create all tables
+        try:
+            db.create_all()
+        except Exception as e:
+            logger.warning(f"Create all tables stored in this metadata error: {str(e)}")
+        _ddl_init_and_upgrade(default_meta_data_path, param.disable_alembic_upgrade)
 
 
 def _initialize_db(
     try_to_create_db: Optional[bool] = False, system_app: Optional[SystemApp] = None
 ) -> str:
     """Initialize the database
 
-    Now just support sqlite and MySQL. If db type is sqlite, the db path is `pilot/meta_data/{db_name}.db`.
+    Now just support sqlite and mysql. If db type is sqlite, the db path is `pilot/meta_data/{db_name}.db`.
     """
     from urllib.parse import quote
     from urllib.parse import quote_plus as urlquote

dbgpt/model/utils/chatgpt_utils.py

@@ -37,6 +37,7 @@ class OpenAIParameters:
     api_base: Optional[str] = None
     api_key: Optional[str] = None
     api_version: Optional[str] = None
+    api_azure_deployment: Optional[str] = None
     full_url: Optional[str] = None
     proxies: Optional["ProxiesTypes"] = None
 
@@ -70,7 +71,7 @@ def _initialize_openai_v1(init_params: OpenAIParameters):
         os.getenv("AZURE_OPENAI_KEY") if api_type == "azure" else None,
     )
     api_version = api_version or os.getenv("OPENAI_API_VERSION")
-
+    api_azure_deployment = init_params.api_azure_deployment or os.getenv("API_AZURE_DEPLOYMENT")
     if not base_url and full_url:
         base_url = full_url.split("/chat/completions")[0]
 
@@ -84,6 +85,7 @@ def _initialize_openai_v1(init_params: OpenAIParameters):
     openai_params = {
         "api_key": api_key,
         "base_url": base_url,
+        "api_azure_deployment": api_azure_deployment
     }
     return openai_params, api_type, api_version
 
@@ -109,6 +111,8 @@ def _initialize_openai(params: OpenAIParameters):
     )
     api_version = params.api_version or os.getenv("OPENAI_API_VERSION")
 
+    api_azure_deployment = params.api_azure_deployment or os.getenv("API_AZURE_DEPLOYMENT")
+
     if not api_base and params.full_url:
         # Adapt previous proxy_server_url configuration
         api_base = params.full_url.split("/chat/completions")[0]
@@ -122,6 +126,8 @@ def _initialize_openai(params: OpenAIParameters):
         openai.api_version = api_version
     if params.proxies:
         openai.proxy = params.proxies
+    if params.api_azure_deployment:
+        openai.api_azure_deployment =api_azure_deployment
 
 
 def _build_openai_client(init_params: OpenAIParameters) -> Tuple[str, ClientType]:
@@ -134,6 +140,9 @@ def _build_openai_client(init_params: OpenAIParameters) -> Tuple[str, ClientType
         return api_type, AsyncAzureOpenAI(
             api_key=openai_params["api_key"],
             api_version=api_version,
+            #azure_deployment="siasmodel",
+            azure_deployment=openai_params["api_azure_deployment"],
+            #   model_name="gpt-35-turbo",
             azure_endpoint=openai_params["base_url"],
             http_client=httpx.AsyncClient(proxies=init_params.proxies),
         )

dbgpt/storage/vector_store/milvus_store.py

@@ -79,7 +79,7 @@ def __init__(self, vector_store_config: MilvusVectorConfig) -> None:
         self.port = milvus_vector_config.get("post") or os.getenv(
             "MILVUS_PORT", "19530"
         )
-        self.username = milvus_vector_config.get("user") or os.getenv("MILVUS_USERNAME")
+        self.username = milvus_vector_config.get("user") or os.getenv("MILVUS_USER")
         self.password = milvus_vector_config.get("password") or os.getenv(
             "MILVUS_PASSWORD"
         )
@@ -133,7 +133,7 @@ def __init__(self, vector_store_config: MilvusVectorConfig) -> None:
         connections.connect(
             host=self.uri or "127.0.0.1",
             port=self.port or "19530",
-            user=self.username,
+            username=self.username,
             password=self.password,
             alias="default",
         )

docs/docs/installation/sourcecode.md

@@ -354,50 +354,7 @@ Modify the `.env` file to use llama.cpp, and then you can start the service by r
 |          `llama_cpp_cache_capacity` |     None     |    Maximum model cache size. For example: 2000MiB, 2GiB                   | 
 |            `llama_cpp_prefer_cpu`   |     False     |    If a GPU is available, the GPU will be used first by default unless prefer_cpu=False is configured.              | 
 
-## Install DB-GPT Application Database
-<Tabs
-  defaultValue="sqlite"
-  values={[
-    {label: 'SQLite', value: 'sqlite'},
-    {label: 'MySQL', value: 'mysql'},
-  ]}>
-<TabItem value="sqlite" label="sqlite">
-
-:::tip NOTE
-
-You do not need to separately create the database tables related to the DB-GPT application in SQLite; 
-they will be created automatically for you by default.
-
-:::
-
-
- </TabItem>
-<TabItem value="mysql" label="MySQL">
-
-:::warning NOTE
-
-After version 0.4.7, we removed the automatic generation of MySQL database Schema for safety.
 
-:::
-
-1. Frist, execute MySQL script to create database and tables.
-
-```python
-$ mysql -h127.0.0.1 -uroot -p{your_password} < ./assets/schema/dbgpt.sql
-```
-
-2. Second, set DB-GPT MySQL database settings in `.env` file.
-
-```python
-LOCAL_DB_TYPE=mysql
-LOCAL_DB_USER= {your username}
-LOCAL_DB_PASSWORD={your_password}
-LOCAL_DB_HOST=127.0.0.1
-LOCAL_DB_PORT=3306
-```
-
- </TabItem>
-</Tabs>
 
 
 ## Test data (optional)