create app.py

app.py

@@ -0,0 +1,98 @@
+# app.py - Microsoft Fara-7B Multi-Modal Demo
+import gradio as gr
+from transformers import AutoProcessor, AutoModelForVision2Seq
+import torch
+from PIL import Image
+import requests
+from io import BytesIO
+
+# 加载模型（首次加载约需 5–10 分钟）
+MODEL_NAME = "microsoft/Fara-7B"
+
+print("正在加载模型，请稍候...")
+
+processor = AutoProcessor.from_pretrained(MODEL_NAME, trust_remote_code=True)
+model = AutoModelForVision2Seq.from_pretrained(
+    MODEL_NAME,
+    trust_remote_code=True,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def chat_with_image(image: Image.Image, question: str, max_new_tokens: int = 200):
+    if image is None:
+        return "请上传一张图片。"
+    if not question.strip():
+        return "请输入问题。"
+    
+    try:
+        # 构造消息格式
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "image"},
+                    {"type": "text", "text": question}
+                ]
+            }
+        ]
+        
+        # 应用聊天模板
+        prompt = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+        
+        # 处理输入
+        inputs = processor(
+            text=prompt,
+            images=image,
+            return_tensors="pt"
+        ).to(model.device)
+
+        # 生成回答
+        with torch.no_grad():
+            outputs = model.generate(
+                **inputs,
+                max_new_tokens=max_new_tokens,
+                do_sample=False,
+                pad_token_id=processor.tokenizer.pad_token_id,
+                eos_token_id=processor.tokenizer.eos_token_id
+            )
+
+        response = processor.decode(outputs[0], skip_special_tokens=True)
+        
+        # 清理输出（只保留 Assistant 回答部分）
+        if "Assistant:" in response:
+            response = response.split("Assistant:")[-1].strip()
+        
+        return response
+
+    except Exception as e:
+        return f"处理出错: {str(e)}"
+
+# Gradio 界面
+with gr.Blocks(title="Fara-7B 多模态问答") as demo:
+    gr.Markdown("# 🖼️ Microsoft Fara-7B 图像问答系统\n上传图片并提问，AI 将为你解答！")
+    
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type="pil", label="上传图片")
+            question_input = gr.Textbox(label="你的问题", placeholder="例如：图中有什么动物？")
+            max_tokens = gr.Slider(50, 500, value=200, step=10, label="最大生成长度")
+            submit_btn = gr.Button("提交")
+        with gr.Column():
+            output = gr.Textbox(label="模型回答", lines=5)
+    
+    submit_btn.click(
+        fn=chat_with_image,
+        inputs=[image_input, question_input, max_tokens],
+        outputs=output
+    )
+    
+    gr.Examples(
+        examples=[
+            ["https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/candy.jpg", "What animal is on the candy?"],
+            ["https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/coco_sample.png", "Describe the scene in detail."]
+        ],
+        inputs=[image_input, question_input]
+    )
+
+demo.launch()