Update app.py

app.py

@@ -48,13 +48,23 @@ def get_movie_info(movie_title):
             # Convert poster_path to a complete image URL
             # image_url = f"https://image.tmdb.org/t/p/w500{poster_path}" if poster_path else ""
 
-            return f"Title: {title}, Year: {year}, Genre: {genre}\nFind more info here: {tmdb_link}"
+            return {
+                "title": title,
+                "year": year,
+                "genre": genre,
+                "tmdb_link": tmdb_link,
+            }
 
         else:
-            return "Movie not found", ""
+            return {"error": "Movie not found"}
 
     except Exception as e:
-        return f"Error: {e}", ""
+        return {"error": f"Error: {e}"}
+
+def process_image(movie_info):
+    # Process the image, return image_url
+    # For now, let's just return a placeholder
+    return "https://via.placeholder.com/150"
 
 def generate_response(prompt):
     input_text_template = (
@@ -67,8 +77,17 @@ def generate_response(prompt):
     # Call the get_movie_info function to enrich the response
     movie_info = get_movie_info(prompt)
 
+    if "error" in movie_info:
+        return f"Error: {movie_info['error']}", None
+
+    # Process the image separately
+    image_url = process_image(movie_info)
+
     # Concatenate the movie info with the input template
-    input_text_template += f" Movie Info: {movie_info}"
+    input_text_template += (
+        f" Movie Info: Title: {movie_info['title']}, Year: {movie_info['year']}, "
+        f"Genre: {movie_info['genre']}\nFind more info here: {movie_info['tmdb_link']}"
+    )
 
     model_inputs = tokenizer(input_text_template, return_tensors="pt").to(device)
 
@@ -84,19 +103,19 @@ def generate_response(prompt):
 
     generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
     
-    # Display image directly in the chat
-    # image_component = gr.Image(image_url)
-    
-    return f"Movie Info:\n{movie_info}\n\nGenerated Response:\n{generated_text}\n"
+    return f"Movie Info:\n{movie_info['title']}, {movie_info['year']}, {movie_info['genre']}\n\n" \
+           f"Generated Response:\n{generated_text}", image_url
 
 # Define chat function for gr.ChatInterface
 def chat_function(message, history):
-    response = generate_response(message)
-    history.append([message, response])
-    return response
+    response_text, response_image = generate_response(message)
+    history.append([message, response_text])
+    history.append([message, response_image])  # Separate history for image
+    return response_text, response_image
 
 # Create Gradio Chat Interface
 chat_interface = gr.ChatInterface(chat_function)
 chat_interface.launch(share=True)  # Added share=True to create a public link
 
 
+