Update app.py

app.py

@@ -78,61 +78,7 @@ def respond1(
 
             response += token
             yield response
-def respond0(multimodal_input,password):
-    if password==password1:
-        if multimodal_input["files"] == None:
-            content={"type": "text", "text": multimodal_input["text"]}
-            messages=[{"role":"system", "content":[{"type":"text", "text":"Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions:"+"You are a helpful assietant."}]}]
-            messages.append([{"role": "user", "content": content}])
-            response = ""
-
-            model_id = "HuggingFaceM4/idefics2-8b"
-
-            processor = AutoProcessor.from_pretrained(model_id)
-            model = AutoModelForVision2Seq.from_pretrained(
-                "HuggingFaceM4/idefics2-8b",
-                torch_dtype=torch.float16,    
-                quantization_config=quantization_config
-            ).to("cpu")            
-            prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
-            inputs = processor(text=prompt, images=[images], return_tensors="pt")
-            inputs = {k: v.to(model.device) for k, v in inputs.items()}
-            num_tokens = len(inputs["input_ids"][0])
-            with torch.inference_mode():
-                generated_ids = model.generate(**inputs, max_new_tokens=max_tokens,top_p=top_p, temperature=1.0,)
-
-            new_tokens = generated_ids[:, num_tokens:]
-            generated_text = processor.batch_decode(new_tokens, skip_special_tokens=True)[0]
-
-            token = generated_text
-            response+=token
-            yield response
 
-        else:
-            images = multimodal_input["files"]
-            content = [{"type": "image"} for _ in images]
-            content.append({"type": "text", "text": multimodal_input["text"]})
-            messages=[{"role":"system", "content":[{"type":"text", "text":"Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions:"+"You are a helpful assietant."}]}]
-            messages.append([{"role": "user", "content": content}])
-            response = ""
-
-            model_id = "HuggingFaceM4/idefics2-8b"
-
-            processor = AutoProcessor.from_pretrained(model_id)
-            model = AutoModelForVision2Seq.from_pretrained("HuggingFaceM4/idefics2-8b",torch_dtype=torch.float16,quantization_config=quantization_config).to("cpu")  
-            prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
-            inputs = processor(text=prompt, images=[images], return_tensors="pt")
-            inputs = {k: v.to(model.device) for k, v in inputs.items()}
-            num_tokens = len(inputs["input_ids"][0])
-            with torch.inference_mode():
-                generated_ids = model.generate(**inputs, max_new_tokens=max_tokens,top_p=top_p, temperature=1.0,)
-
-            new_tokens = generated_ids[:, num_tokens:]
-            generated_text = processor.batch_decode(new_tokens, skip_special_tokens=True)[0]
-
-            token = generated_text
-            response+=token
-            yield response
             
 
 
@@ -519,13 +465,7 @@ ae= gr.ChatInterface(
         
     ],
 )
-a7=gr.Interface(
-    respond0,
-    inputs=[gr.MultimodalTextbox(file_types=["image"], show_label=False), gr.Textbox()],
-    outputs="text",
-    title="IDEFICS2-8B DPO",
-    description="Try IDEFICS2-8B fine-tuned using direct preference optimization (DPO) in this demo. Learn more about vision language model DPO integration of TRL [here](https://huggingface.co/blog/dpo_vlm)."
-)
+
 aa=gr.ChatInterface(
     respond1,
     chatbot=chatbot3,
@@ -611,5 +551,5 @@ a8= gr.ChatInterface(
   
 if __name__ == "__main__":
     with gr.Blocks(theme="gstaff/xkcd") as ai:
-        gr.TabbedInterface([aa, ac, ab, ae, aaaa,demo2, a7,a8, a9], ["gpt4(Password needed)", "gpt4(only for programming)", "gpt4(only for medical questions)", "gpt4(only for food recommendations)", "gpt4(only for law questions)","image create", "multimodal", "gpt4(test)", "ai test"])
+        gr.TabbedInterface([aa, ac, ab, ae, aaaa,demo2,a8, a9], ["gpt4(Password needed)", "gpt4(only for programming)", "gpt4(only for medical questions)", "gpt4(only for food recommendations)", "gpt4(only for law questions)","image create", "gpt4(test)", "ai test"])
         ai.launch(share=True)