Integrates LLM Azure OpenAI (#1318)

### What problem does this PR solve?

feat: Integrates LLM Azure OpenAI #716 

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

### Other
It's just the back-end code, the front-end needs to provide the Azure
OpenAI model addition form.
   
#### Required parameters

- base_url
- api_key

---------

Co-authored-by: yonghui li <yonghui.li@bondex.com.cn>

api/db/init_data.py

     "logo": "",
     "tags": "LLM,TEXT EMBEDDING",
     "status": "1",
+},{
+    "name": "Azure-OpenAI",
+    "logo": "",
+    "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+    "status": "1",
 }
     # {
     #     "name": "文心一言",
             "max_tokens": 8192,
             "model_type": LLMType.EMBEDDING
         },
+        # ------------------------ Azure OpenAI -----------------------
+        #  Please ensure the llm_name is the same as the name in Azure
+        #  OpenAI deployment name (e.g., azure-gpt-4o). And the llm_name
+        #  must different from the OpenAI llm_name
+        #
+        #  Each model must be deployed in the Azure OpenAI service, otherwise,
+        #  you will receive an error message 'The API deployment for
+        #  this resource does not exist'
+        {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-gpt-4o",
+            "tags": "LLM,CHAT,128K",
+            "max_tokens": 128000,
+            "model_type": LLMType.CHAT.value + "," + LLMType.IMAGE2TEXT.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-gpt-35-turbo",
+            "tags": "LLM,CHAT,4K",
+            "max_tokens": 4096,
+            "model_type": LLMType.CHAT.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-gpt-35-turbo-16k",
+            "tags": "LLM,CHAT,16k",
+            "max_tokens": 16385,
+            "model_type": LLMType.CHAT.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-text-embedding-ada-002",
+            "tags": "TEXT EMBEDDING,8K",
+            "max_tokens": 8191,
+            "model_type": LLMType.EMBEDDING.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-text-embedding-3-small",
+            "tags": "TEXT EMBEDDING,8K",
+            "max_tokens": 8191,
+            "model_type": LLMType.EMBEDDING.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-text-embedding-3-large",
+            "tags": "TEXT EMBEDDING,8K",
+            "max_tokens": 8191,
+            "model_type": LLMType.EMBEDDING.value
+        },{
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-whisper-1",
+            "tags": "SPEECH2TEXT",
+            "max_tokens": 25 * 1024 * 1024,
+            "model_type": LLMType.SPEECH2TEXT.value
+         },
+        {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-gpt-4",
+            "tags": "LLM,CHAT,8K",
+            "max_tokens": 8191,
+            "model_type": LLMType.CHAT.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-gpt-4-turbo",
+            "tags": "LLM,CHAT,8K",
+            "max_tokens": 8191,
+            "model_type": LLMType.CHAT.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-gpt-4-32k",
+            "tags": "LLM,CHAT,32K",
+            "max_tokens": 32768,
+            "model_type": LLMType.CHAT.value
+        }, {
+            "fid": factory_infos[15]["name"],
+            "llm_name": "azure-gpt-4-vision-preview",
+            "tags": "LLM,CHAT,IMAGE2TEXT",
+            "max_tokens": 765,
+            "model_type": LLMType.IMAGE2TEXT.value
+        },
+
     ]
     for info in factory_infos:
         try:

api/settings.py

         "image2text_model": "gpt-4-vision-preview",
         "asr_model": "whisper-1",
     },
+    "Azure-OpenAI": {
+        "chat_model": "azure-gpt-35-turbo",
+        "embedding_model": "azure-text-embedding-ada-002",
+        "image2text_model": "azure-gpt-4-vision-preview",
+        "asr_model": "azure-whisper-1",
+    },
     "ZHIPU-AI": {
         "chat_model": "glm-3-turbo",
         "embedding_model": "embedding-2",

rag/llm/__init__.py

 EmbeddingModel = {
     "Ollama": OllamaEmbed,
     "OpenAI": OpenAIEmbed,
+    "Azure-OpenAI": AzureEmbed,
     "Xinference": XinferenceEmbed,
     "Tongyi-Qianwen": QWenEmbed,
     "ZHIPU-AI": ZhipuEmbed,
 
 CvModel = {
     "OpenAI": GptV4,
+    "Azure-OpenAI": AzureGptV4,
     "Ollama": OllamaCV,
     "Xinference": XinferenceCV,
     "Tongyi-Qianwen": QWenCV,
 
 ChatModel = {
     "OpenAI": GptTurbo,
+    "Azure-OpenAI": AzureChat,
     "ZHIPU-AI": ZhipuChat,
     "Tongyi-Qianwen": QWenChat,
     "Ollama": OllamaChat,

rag/llm/chat_model.py

 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+from openai.lib.azure import AzureOpenAI
 from zhipuai import ZhipuAI
 from dashscope import Generation
 from abc import ABC
         if not base_url: base_url="https://api.deepseek.com/v1"
         super().__init__(key, model_name, base_url)
 
+class AzureChat(Base):
+    def __init__(self, key, model_name, **kwargs):
+        self.client = AzureOpenAI(api_key=key, azure_endpoint=kwargs["base_url"], api_version="2024-02-01")
+        self.model_name = model_name
+
 
 class BaiChuanChat(Base):
     def __init__(self, key, model_name="Baichuan3-Turbo", base_url="https://api.baichuan-ai.com/v1"):

rag/llm/cv_model.py

 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+from openai.lib.azure import AzureOpenAI
 from zhipuai import ZhipuAI
 import io
 from abc import ABC
         )
         return res.choices[0].message.content.strip(), res.usage.total_tokens
 
+class AzureGptV4(Base):
+    def __init__(self, key, model_name, lang="Chinese", **kwargs):
+        self.client = AzureOpenAI(api_key=key, azure_endpoint=kwargs["base_url"], api_version="2024-02-01")
+        self.model_name = model_name
+        self.lang = lang
+
+    def describe(self, image, max_tokens=300):
+        b64 = self.image2base64(image)
+        prompt = self.prompt(b64)
+        for i in range(len(prompt)):
+            for c in prompt[i]["content"]:
+                if "text" in c: c["type"] = "text"
+
+        res = self.client.chat.completions.create(
+            model=self.model_name,
+            messages=prompt,
+            max_tokens=max_tokens,
+        )
+        return res.choices[0].message.content.strip(), res.usage.total_tokens
 
 class QWenCV(Base):
     def __init__(self, key, model_name="qwen-vl-chat-v1", lang="Chinese", **kwargs):

rag/llm/embedding_model.py

 import  threading
 import requests
 from huggingface_hub import snapshot_download
+from openai.lib.azure import AzureOpenAI
 from zhipuai import ZhipuAI
 import os
 from abc import ABC
         return np.array(res.data[0].embedding), res.usage.total_tokens
 
 
+class AzureEmbed(Base):
+    def __init__(self, key, model_name, **kwargs):
+        self.client = AzureOpenAI(api_key=key, azure_endpoint=kwargs["base_url"], api_version="2024-02-01")
+        self.model_name = model_name
+
 class BaiChuanEmbed(OpenAIEmbed):
     def __init__(self, key,
                  model_name='Baichuan-Text-Embedding',