Update app.py

app.py

@@ -182,49 +182,39 @@ def process_text(user_name, text_input, selected_model, temp_values):
         st.markdown(f"{user_name} ({timestamp}): {text_input}")
     
     with st.chat_message("Assistant"):
-        try:
-            if selected_model == "GPT-4o":
-                completion = client.chat.completions.create(
-                    model=GPT4O_MODEL,
-                    messages=[
-                        {"role": "user", "content": m["message"]}
-                        for m in st.session_state.messages
-                    ],
-                    stream=True,
-                    temperature=temp_values
-                )
-                return_text = st.write_stream(completion)
-            else:
-                messages = [
-                    {"content": m["message"]}
+        if selected_model == "GPT-4o":
+            completion = client.chat.completions.create(
+                model=GPT4O_MODEL,
+                messages=[
+                    {"role": "user", "content": m["message"]}
                     for m in st.session_state.messages
-                ]
+                ],
+                stream=True,
+                temperature=temp_values
+            )
+            return_text = st.write_stream(completion)
+        else:
+            try:
                 stream = hf_client.chat.completions.create(
                     model=model_links[selected_model],
-                    messages=messages,
+                    messages=[
+                        {"role": m["role"], "content": m["content"]}
+                        for m in st.session_state.messages
+                    ],
                     temperature=temp_values,
                     stream=True,
                     max_tokens=3000,
                 )
                 return_text = st.write_stream(stream)
-        except openai.APIError as e:
-            return_text = f"OpenAI API Error: {str(e)}"
-            st.error(return_text)
-        except requests.exceptions.RequestException as e:
-            return_text = f"Network Error: {str(e)}"
-            st.error(return_text)
-        except Exception as e:
-            return_text = f"Unexpected Error: {str(e)}"
-            st.error(return_text)
+            except Exception as e:
+                return_text = f"Error: {str(e)}"
+                st.error(return_text)
         
-        if not return_text.startswith("Error:"):
-            st.markdown(f"Assistant ({timestamp}): {return_text}")
-            filename = generate_filename(text_input, "md")
-            create_file(filename, text_input, return_text, user_name, timestamp)
-            st.session_state.messages.append({"user": "Assistant", "message": return_text, "timestamp": timestamp})
-            save_data()
-    
-    return return_text
+        st.markdown(f"Assistant ({timestamp}): {return_text}")
+        filename = generate_filename(text_input, "md")
+        create_file(filename, text_input, return_text, user_name, timestamp)
+        st.session_state.messages.append({"user": "Assistant", "message": return_text, "timestamp": timestamp})
+        save_data()
 
 # Function to process image (using GPT-4o)
 def process_image(user_name, image_input, user_prompt):
@@ -276,7 +266,6 @@ def process_audio(user_name, audio_input, text_input):
             create_file(filename, text_input, transcription.text, user_name, timestamp)
             st.session_state.messages.append({"user": "Assistant", "message": transcription.text, "timestamp": timestamp})
             save_data()
-        return transcription.text
 
 # Function to process video (using GPT-4o)
 def process_video(user_name, video_input, user_prompt):
@@ -307,45 +296,6 @@ def process_video(user_name, video_input, user_prompt):
     save_data()
     return video_response
 
-# Callback function for text processing
-def process_text_callback(column_name):
-    text_input = st.session_state[f"{column_name}_text"]
-    selected_model = st.session_state[f"{column_name}_model"]
-    temp_values = st.session_state[f"{column_name}_temp"]
-    if text_input:
-        process_text(st.session_state.current_user['name'], text_input, selected_model, temp_values)
-        st.session_state[f"{column_name}_text"] = ""  # Clear the input after processing
-
-# Callback function for image processing
-def process_image_callback(column_name):
-    text_input = st.session_state[f"{column_name}_image_text"]
-    uploaded_files = st.session_state[f"{column_name}_image_upload"]
-    if text_input and uploaded_files:
-        for image_input in uploaded_files:
-            image_bytes = image_input.read()
-            process_image(st.session_state.current_user['name'], image_bytes, text_input)
-        st.session_state[f"{column_name}_image_text"] = ""  # Clear the input after processing
-        st.session_state[f"{column_name}_image_upload"] = None  # Clear the file uploader
-
-# Callback function for audio processing
-def process_audio_callback(column_name):
-    text_input = st.session_state[f"{column_name}_audio_text"]
-    uploaded_files = st.session_state[f"{column_name}_audio_upload"]
-    if uploaded_files:
-        for audio_input in uploaded_files:
-            process_audio(st.session_state.current_user['name'], audio_input, text_input)
-        st.session_state[f"{column_name}_audio_text"] = ""  # Clear the input after processing
-        st.session_state[f"{column_name}_audio_upload"] = None  # Clear the file uploader
-
-# Callback function for video processing
-def process_video_callback(column_name):
-    text_input = st.session_state[f"{column_name}_video_text"]
-    video_input = st.session_state[f"{column_name}_video_upload"]
-    if video_input and text_input:
-        process_video(st.session_state.current_user['name'], video_input, text_input)
-        st.session_state[f"{column_name}_video_text"] = ""  # Clear the input after processing
-        st.session_state[f"{column_name}_video_upload"] = None  # Clear the file uploader
-
 # Main function for each column
 def main_column(column_name):
     st.markdown(f"##### {column_name}")
@@ -355,20 +305,25 @@ def main_column(column_name):
     option = st.selectbox(f"Select an option for {column_name}", ("Text", "Image", "Audio", "Video"), key=f"{column_name}_option")
     
     if option == "Text":
-        st.text_input(f"Enter your text for {column_name}:", key=f"{column_name}_text")
-        st.button(f"Process Text for {column_name}", on_click=process_text_callback, args=(column_name,))
+        text_input = st.text_input(f"Enter your text for {column_name}:", key=f"{column_name}_text")
+        if text_input:
+            process_text(st.session_state.current_user['name'], text_input, selected_model, temp_values)
     elif option == "Image":
-        st.text_input(f"Enter text prompt to use with Image context for {column_name}:", key=f"{column_name}_image_text")
-        st.file_uploader(f"Upload images for {column_name}", type=["png", "jpg", "jpeg"], accept_multiple_files=True, key=f"{column_name}_image_upload")
-        st.button(f"Process Image for {column_name}", on_click=process_image_callback, args=(column_name,))
+        text_input = st.text_input(f"Enter text prompt to use with Image context for {column_name}:", key=f"{column_name}_image_text")
+        uploaded_files = st.file_uploader(f"Upload images for {column_name}", type=["png", "jpg", "jpeg"], accept_multiple_files=True, key=f"{column_name}_image_upload")
+        for image_input in uploaded_files:
+            image_bytes = image_input.read()
+            process_image(st.session_state.current_user['name'], image_bytes, text_input)
     elif option == "Audio":
-        st.text_input(f"Enter text prompt to use with Audio context for {column_name}:", key=f"{column_name}_audio_text")
-        st.file_uploader(f"Upload an audio file for {column_name}", type=["mp3", "wav"], accept_multiple_files=True, key=f"{column_name}_audio_upload")
-        st.button(f"Process Audio for {column_name}", on_click=process_audio_callback, args=(column_name,))
+        text_input = st.text_input(f"Enter text prompt to use with Audio context for {column_name}:", key=f"{column_name}_audio_text")
+        uploaded_files = st.file_uploader(f"Upload an audio file for {column_name}", type=["mp3", "wav"], accept_multiple_files=True, key=f"{column_name}_audio_upload")
+        for audio_input in uploaded_files:
+            process_audio(st.session_state.current_user['name'], audio_input, text_input)
     elif option == "Video":
-        st.file_uploader(f"Upload a video file for {column_name}", type=["mp4"], key=f"{column_name}_video_upload")
-        st.text_input(f"Enter text prompt to use with Video context for {column_name}:", key=f"{column_name}_video_text")
-        st.button(f"Process Video for {column_name}", on_click=process_video_callback, args=(column_name,))
+        video_input = st.file_uploader(f"Upload a video file for {column_name}", type=["mp4"], key=f"{column_name}_video_upload")
+        text_input = st.text_input(f"Enter text prompt to use with Video context for {column_name}:", key=f"{column_name}_video_text")
+        if video_input and text_input:
+            process_video(st.session_state.current_user['name'], video_input, text_input)
 
 # Main Streamlit app
 st.title("Personalized Real-Time Chat")
@@ -409,4 +364,5 @@ with col2:
 
 # Run the Streamlit app
 if __name__ == "__main__":
-    st.markdown("\n[by Aaron Wacker](https://huggingface.co/spaces/awacke1/ChatStreamlitMultiplayer).")
+    st.markdown("*by Aaron Wacker*")
+    st.markdown("\n[Aaron Wacker](https://huggingface.co/spaces/awacke1/).")