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>

rag/llm/__init__.py

@@ -22,6 +22,7 @@ from .rerank_model import *
 EmbeddingModel = {
     "Ollama": OllamaEmbed,
     "OpenAI": OpenAIEmbed,
+    "Azure-OpenAI": AzureEmbed,
     "Xinference": XinferenceEmbed,
     "Tongyi-Qianwen": QWenEmbed,
     "ZHIPU-AI": ZhipuEmbed,
@@ -36,6 +37,7 @@ EmbeddingModel = {
 
 CvModel = {
     "OpenAI": GptV4,
+    "Azure-OpenAI": AzureGptV4,
     "Ollama": OllamaCV,
     "Xinference": XinferenceCV,
     "Tongyi-Qianwen": QWenCV,
@@ -46,6 +48,7 @@ CvModel = {
 
 ChatModel = {
     "OpenAI": GptTurbo,
+    "Azure-OpenAI": AzureChat,
     "ZHIPU-AI": ZhipuChat,
     "Tongyi-Qianwen": QWenChat,
     "Ollama": OllamaChat,

rag/llm/chat_model.py

@@ -13,6 +13,7 @@
 #  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
@@ -94,6 +95,11 @@ class DeepSeekChat(Base):
         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

@@ -13,6 +13,7 @@
 #  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
@@ -87,6 +88,25 @@ class GptV4(Base):
         )
         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

@@ -18,6 +18,7 @@ from typing import Optional
 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
@@ -110,6 +111,11 @@ class OpenAIEmbed(Base):
         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',