Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import requests
 import base64
+import json
 import os
 
 # --- UI Constants ---
@@ -42,7 +43,10 @@ def openai_responses_api(api_key, messages, previous_response_id=None):
     if r.status_code == 200:
         return r.json()
     else:
-        raise Exception(r.json().get("error", {}).get("message", "Unknown error"))
+        try:
+            return {"error": r.json().get("error", {}).get("message", "Unknown error")}
+        except Exception:
+            return {"error": "Unknown error"}
 
 def encode_image_to_base64(image):
     """Encode uploaded image to base64 string."""
@@ -72,32 +76,34 @@ def chat_fn(user_message, chat_history, image, state):
     api_key = state.get("api_key")
     if not api_key:
         return chat_history, state, gr.update(visible=True), "Please enter your OpenAI API key."
+    if not user_message and image is None:
+        return chat_history, state, gr.update(visible=False), ""
     # Prepare messages for API
-    messages = []
-    for turn in chat_history:
-        messages.append({"role": turn["role"], "content": turn["content"]})
+    messages = chat_history.copy()
     # Add current user message
     if image is not None:
-        # Image attached: send as multimodal input
         base64_img = encode_image_to_base64(image)
         content = [
             {"type": "input_text", "text": user_message or "Please describe this image."},
             {"type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_img}"}
         ]
         messages.append({"role": "user", "content": content})
-        chat_history.append({"role": "user", "content": f"{user_message}\n[Image attached]"})
+        display_user = (user_message or "") + "\n[Image attached]"
     else:
         messages.append({"role": "user", "content": user_message})
-        chat_history.append({"role": "user", "content": user_message})
+        display_user = user_message
     # Call OpenAI Responses API
-    try:
-        response = openai_responses_api(api_key, messages)
-        output_text = response.get("output_text", "")
-        chat_history.append({"role": "assistant", "content": output_text})
-        state["previous_response_id"] = response.get("id")
-        return chat_history, state, gr.update(visible=False), ""
-    except Exception as e:
-        return chat_history, state, gr.update(visible=True), f"API error: {str(e)}"
+    response = openai_responses_api(api_key, messages, state.get("previous_response_id"))
+    if "error" in response:
+        return chat_history, state, gr.update(visible=True), f"API error: {response['error']}"
+    output_text = response.get("output_text", "")
+    state["previous_response_id"] = response.get("id")
+    # Update chat history for display
+    chat_history = chat_history + [
+        {"role": "user", "content": display_user},
+        {"role": "assistant", "content": output_text}
+    ]
+    return chat_history, state, gr.update(visible=False), ""
 
 def image_analysis_fn(image, state):
     """Analyze uploaded image using OpenAI Responses API."""
@@ -116,17 +122,17 @@ def image_analysis_fn(image, state):
             ]
         }
     ]
-    try:
-        response = openai_responses_api(api_key, messages)
-        return response.get("output_text", ""), gr.update(visible=False), ""
-    except Exception as e:
-        return f"API error: {str(e)}", gr.update(visible=True), f"API error: {str(e)}"
+    response = openai_responses_api(api_key, messages)
+    if "error" in response:
+        return f"API error: {response['error']}", gr.update(visible=True), f"API error: {response['error']}"
+    return response.get("output_text", ""), gr.update(visible=False), ""
 
 def export_chat(chat_history):
     """Export chat history as JSON."""
-    import json
     chat_json = chat_history
-    return gr.File.update(value=("chat_history.json", json.dumps(chat_json, indent=2)), visible=True)
+    with open("chat_history.json", "w", encoding="utf-8") as f:
+        json.dump(chat_json, f, indent=2, ensure_ascii=False)
+    return "chat_history.json"
 
 def show_iframe(space_url):
     """Show iframe code for embedding."""
@@ -167,17 +173,37 @@ with gr.Blocks(theme=gr.themes.Soft(), css=".footer {text-align: center; font-si
                 iframe_btn = gr.Button("Get iframe code")
                 iframe_code = gr.Textbox(label="Embed code", interactive=False, visible=False)
             # Chat logic
-            send_btn.click(chat_fn, [user_input, chatbot, image_input, state], [chatbot, state, chat_error, api_key_error])
-            user_input.submit(chat_fn, [user_input, chatbot, image_input, state], [chatbot, state, chat_error, api_key_error])
-            export_btn.click(export_chat, chatbot, export_file)
-            iframe_btn.click(show_iframe, gr.Textbox(value="https://huggingface.co/spaces/your-space-name", visible=False), iframe_code)
+            send_btn.click(
+                chat_fn,
+                [user_input, chatbot, image_input, state],
+                [chatbot, state, chat_error, api_key_error]
+            )
+            user_input.submit(
+                chat_fn,
+                [user_input, chatbot, image_input, state],
+                [chatbot, state, chat_error, api_key_error]
+            )
+            export_btn.click(
+                export_chat,
+                chatbot,
+                export_file
+            )
+            iframe_btn.click(
+                show_iframe,
+                gr.Textbox(value="https://huggingface.co/spaces/your-space-name", visible=False),
+                iframe_code
+            )
         # --- Image Analysis Tab ---
         with gr.Tab("🖼️ Image Analysis"):
             image_upload = gr.Image(type="filepath", label="Upload image")
             analyze_btn = gr.Button("Analyze")
             image_result = gr.Textbox(label="Analysis result", lines=4)
             image_error = gr.Markdown("", visible=False)
-            analyze_btn.click(image_analysis_fn, [image_upload, state], [image_result, api_key_error, image_error])
+            analyze_btn.click(
+                image_analysis_fn,
+                [image_upload, state],
+                [image_result, api_key_error, image_error]
+            )
 
     # --- Footer ---
     gr.Markdown(f"<div class='footer'>{FOOTER}</div>")