add llm API (#19)

* add llm API

* refine llm API

python/llm/cv_model.py

@@ -0,0 +1,66 @@
+from abc import ABC
+from openai import OpenAI
+import os
+import base64
+from io import BytesIO
+
+
+class Base(ABC):
+    def describe(self, image, max_tokens=300):
+        raise NotImplementedError("Please implement encode method!")
+
+    def image2base64(self, image):
+        if isinstance(image, BytesIO):
+            return base64.b64encode(image.getvalue()).decode("utf-8")
+        buffered = BytesIO()
+        try:
+            image.save(buffered, format="JPEG")
+        except Exception as e:
+            image.save(buffered, format="PNG")
+        return base64.b64encode(buffered.getvalue()).decode("utf-8")
+
+    def prompt(self, b64):
+        return [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": "请用中文详细描述一下图中的内容，比如时间，地点，人物，事情，人物心情等。",
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/jpeg;base64,{b64}"
+                        },
+                    },
+                ],
+            }
+        ]
+
+
+class GptV4(Base):
+    def __init__(self):
+        self.client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
+
+    def describe(self, image, max_tokens=300):
+        b64 = self.image2base64(image)
+
+        res = self.client.chat.completions.create(
+            model="gpt-4-vision-preview",
+            messages=self.prompt(b64),
+            max_tokens=max_tokens,
+        )
+        return res.choices[0].message.content.strip()
+
+
+class QWenCV(Base):
+    def describe(self, image, max_tokens=300):
+        from http import HTTPStatus
+        from dashscope import MultiModalConversation
+        # export DASHSCOPE_API_KEY=YOUR_DASHSCOPE_API_KEY
+        response = MultiModalConversation.call(model=MultiModalConversation.Models.qwen_vl_chat_v1,
+                                               messages=self.prompt(self.image2base64(image)))
+        if response.status_code == HTTPStatus.OK:
+            return response.output.choices[0]['message']['content']
+        return response.message