Update app.py

app.py

@@ -10,12 +10,16 @@ groq_api_key = "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"
 groq_api_url = "https://api.groq.com/openai/v1/chat/completions"
 
 def qna(image, question, history):
+    if image is None:
+        return history + [(question, "Please upload an image first.")], history + [(question, "Please upload an image first.")]
+    
     try:
         inputs = processor(image, question, return_tensors="pt")
         out = model.generate(**inputs)
         short_answer = processor.decode(out[0], skip_special_tokens=True)
         
-        context = "\n".join([f"Q: {q}\nA: {a}" for q, a in history])
+        context = "\n".join([f"Q: {q}\nA: {a}" for q, a in history]) if history else "No previous context."
+        
         full_prompt = f"""Context of previous conversation:
 {context}
 
@@ -30,30 +34,35 @@ Please provide a detailed answer based on the image and previous context."""
         
         data = {
             "model": "llama3-8b-8192",
-            "messages": [{"role": "user", "content": full_prompt}]
+            "messages": [
+                {"role": "system", "content": "You are a helpful assistant that answers questions about images based on the provided context and BLIP model's initial analysis."},
+                {"role": "user", "content": full_prompt}
+            ]
         }
         
         response = requests.post(groq_api_url, headers=headers, json=data)
         
         if response.status_code == 200:
             detailed_answer = response.json()['choices'][0]['message']['content'].strip()
-            history.append((question, detailed_answer))
-            return history, history
+            new_history = history + [(question, detailed_answer)]
+            return new_history, new_history
         else:
             error_msg = f"Error {response.status_code}: {response.text}"
-            history.append((question, error_msg))
-            return history, history
+            return history + [(question, error_msg)], history + [(question, error_msg)]
             
     except Exception as e:
         error_msg = f"An error occurred: {str(e)}"
-        history.append((question, error_msg))
-        return history, history
+        return history + [(question, error_msg)], history + [(question, error_msg)]
 
 def clear_history():
     return [], []
 
+def init_history():
+    return [], []
+
 with gr.Blocks() as demo:
     gr.Markdown("# Interactive Image Chatbot")
+    gr.Markdown("Upload an image and ask questions about it. The chatbot will maintain context of the conversation.")
     
     with gr.Row():
         image_input = gr.Image(type="pil")
@@ -61,21 +70,37 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             chatbot = gr.Chatbot()
-            question = gr.Textbox(label="Ask a question about the image")
-            clear = gr.Button("Clear Conversation")
+            question = gr.Textbox(label="Ask a question about the image", placeholder="Type your question here...")
+            with gr.Row():
+                clear = gr.Button("Clear Conversation")
+                new_image = gr.Button("New Image")
     
     state = gr.State([])
     
+    # Handle question submission
     question.submit(
         qna,
         inputs=[image_input, question, state],
         outputs=[chatbot, state]
     )
     
+    # Handle image upload
+    image_input.change(
+        init_history,
+        outputs=[chatbot, state]
+    )
+    
+    # Clear conversation
     clear.click(
         clear_history,
         outputs=[chatbot, state]
     )
+    
+    # New image button
+    new_image.click(
+        clear_history,
+        outputs=[chatbot, state]
+    )
 
 if __name__ == "__main__":
     demo.launch()