Update app.py

app.py

@@ -1,59 +1,142 @@
-
-import openai
 import os
-
-# Initialize the OpenAI client
 from openai import OpenAI
-# HF
+from datetime import datetime
+import gradio as gr
+import time
+
+# --- Constants ---
+DEFAULT_MODEL = "gpt-4.5-preview-2025-02-27"  # Assuming gpt-4o is a good default
+DEFAULT_TEMPERATURE = 1.0 # Match your example
+DEFAULT_TOP_P = 1.0       # Match your example
+DEFAULT_FREQ_PENALTY = 0  # Match your example
+DEFAULT_PRES_PENALTY = 0  # Match your example
+MAX_TOKENS = 2048       # Match your example
+MAX_HISTORY_LENGTH = 5
+
+# --- API Key and Client Initialization ---
+import openai
 API_KEY = os.getenv("OPENAI_API_KEY")
 client = OpenAI(api_key=API_KEY)
 
+# --- Helper Functions ---
+def get_openai_response(prompt, model=DEFAULT_MODEL, temperature=DEFAULT_TEMPERATURE, top_p=DEFAULT_TOP_P,
+                        frequency_penalty=DEFAULT_FREQ_PENALTY, presence_penalty=DEFAULT_PRES_PENALTY,
+                        max_tokens=MAX_TOKENS, system_prompt="", chat_history=None):
+    """Gets a response from the OpenAI API, handling errors and streaming."""
+    today_day = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    try:
+        messages = [{"role": "system", "content": f"You are GPT 4.5 the latest model from OpenAI, released Feb, 27th 2025 at 3 pm ET. Todays date is: {today_day} " + system_prompt}]
+        if chat_history:
+            for turn in chat_history:
+                messages.append({"role": "user", "content": turn[0]})
+                messages.append({"role": "assistant", "content": turn[1]})
+        messages.append({"role": "user", "content": prompt})
+
+        response = client.chat.completions.create(
+            model=model,
+            messages=messages,
+            temperature=temperature,
+            max_tokens=max_tokens, #Use the new name
+            top_p=top_p,
+            frequency_penalty=frequency_penalty,
+            presence_penalty=presence_penalty,
+            response_format={"type": "text"},  # As per your example
+            stream=True  # Enable streaming!
+        )
+
+        collected_messages = []
+        for chunk in response:
+            chunk_message = chunk.choices[0].delta.content
+            if chunk_message is not None:
+                collected_messages.append(chunk_message)
+            full_reply_content = ''.join(collected_messages)
+            yield full_reply_content
+
+    except openai.APIConnectionError as e:
+        return f"Error: Could not connect to OpenAI API: {e}"
+    except openai.RateLimitError as e:
+        return f"Error: Rate limit exceeded: {e}"
+    except openai.APIStatusError as e:
+        return f"Error: OpenAI API returned an error: {e}"
+    except Exception as e:
+        return f"An unexpected error occurred: {e}"
 
-from datetime import datetime
-# gpt function
-def chatgpt(prompt):
-    today_day = datetime.now().strftime("%Y-%m-%d %H:%M:%S")  # Get current date and time
-    response = openai.chat.completions.create(
-        model="gpt-4.5-preview-2025-02-27",  # Use an actual available model
-        messages=[
-            {"role": "system", "content": f"You are GPT 4.5 the latest model from OpenAI, released Feb, 27th 2025 at 3 pm ET. Todays date is: {today_day}"},
-            {"role": "user", "content": prompt}
-        ]
-    )
-    return response.choices[0].message.content
-#Gradio
-import gradio as gr
 
-# Function to handle chat interaction
-def respond(message, chat_history):
-    bot_message = chatgpt(message)  # Assuming chatgpt is defined elsewhere
-    chat_history.append((message, bot_message))
-    return "", chat_history
 
-# Create a Gradio Blocks interface
+def update_ui(message, chat_history, model, temperature, top_p, frequency_penalty, presence_penalty, system_prompt, history_length):
+    """Updates the Gradio UI; handles streaming response."""
+    bot_message_gen = get_openai_response(
+        prompt=message, model=model, temperature=temperature, top_p=top_p,
+        frequency_penalty=frequency_penalty, presence_penalty=presence_penalty,
+        system_prompt=system_prompt, chat_history=chat_history
+    )
+    chat_history.append((message, ""))
+    for bot_message in bot_message_gen:
+        chat_history[-1] = (chat_history[-1][0], bot_message)
+        visible_history = chat_history[-history_length:]
+        time.sleep(0.025) #Rate limiter
+        yield "", visible_history
+
+# --- Gradio Interface ---
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# Chat with GPT-4.5")
-    gr.Markdown("Ask anything to gpt-4.5-preview-2025-02-27 model. Made by: @diegocabezas01 [@diegocabezas01](https://x.com/diegocabezas01) on X (prev. Twitter)")
-    
-    chatbot = gr.Chatbot()
+    gr.Markdown("# Chat with GPT (Gradio)")
+    gr.Markdown("Made by: [@diegocabezas01](https://x.com/diegocabezas01) on X")
+    gr.Markdown("☕ [Support my work](https://buymeacoffee.com/diegocp01m)")
+
     with gr.Row():
-        msg = gr.Textbox(placeholder="Type your message here...", scale=4)
-        send = gr.Button("Send", scale=1)
-    clear = gr.Button("Clear")
-    
-    # Set up interactions
-    send.click(respond, [msg, chatbot], [msg, chatbot])
-    msg.submit(respond, [msg, chatbot], [msg, chatbot])  # Keeps Enter key functionality
+        with gr.Column(scale=4):
+            chatbot = gr.Chatbot(
+                show_label=False,
+                avatar_images=(
+                    "https://cdn-icons-png.flaticon.com/512/8428/8428718.png",  # User image URL
+                    "https://upload.wikimedia.org/wikipedia/commons/thumb/e/ef/ChatGPT-Logo.svg/640px-ChatGPT-Logo.svg.png"  # OpenAI image URL
+                ),
+                render_markdown=True,
+                height=500
+            )
+            msg = gr.Textbox(placeholder="Type your message here...", scale=4, show_label=False)
+
+            with gr.Accordion("Advanced Options", open=False):
+                model_select = gr.Dropdown(
+                    label="Model",
+                    choices=["gpt-4.5-preview-2025-02-27", "gpt-4o-mini-2024-07-18"],  # Update with your models
+                    value=DEFAULT_MODEL,
+                    interactive=True
+                )
+                temperature_slider = gr.Slider(label="Temperature", minimum=0.0, maximum=2.0, value=DEFAULT_TEMPERATURE, step=0.1, interactive=True)
+                top_p_slider = gr.Slider(label="Top P", minimum=0.0, maximum=1.0, value=DEFAULT_TOP_P, step=0.05, interactive=True)
+                frequency_penalty_slider = gr.Slider(label="Frequency Penalty", minimum=-2.0, maximum=2.0, value=DEFAULT_FREQ_PENALTY, step=0.1, interactive=True)
+                presence_penalty_slider = gr.Slider(label="Presence Penalty", minimum=-2.0, maximum=2.0, value=DEFAULT_PRES_PENALTY, step=0.1, interactive=True)
+                system_prompt_textbox = gr.Textbox(label="System Prompt", placeholder="Enter a custom system prompt...", lines=3, interactive=True)
+                history_length_slider = gr.Slider(label="Chat History Length", minimum=1, maximum=20, value=MAX_HISTORY_LENGTH, step=1, interactive=True)
+
+
+            with gr.Row():
+                send = gr.Button("Send")
+                clear = gr.Button("Clear")
+
+    # --- Event Handlers ---
+    send_event = send.click(
+        update_ui,
+        [msg, chatbot, model_select, temperature_slider, top_p_slider, frequency_penalty_slider, presence_penalty_slider, system_prompt_textbox, history_length_slider],
+        [msg, chatbot]
+    )
+    msg.submit(
+        update_ui,
+        [msg, chatbot, model_select, temperature_slider, top_p_slider, frequency_penalty_slider, presence_penalty_slider, system_prompt_textbox, history_length_slider],
+        [msg, chatbot]
+    )
     clear.click(lambda: None, None, chatbot, queue=False)
-    
-    # Add example prompts
+
     gr.Examples(
-        examples=["Tell me about quantum computing", 
-                 "Write a short poem about AI",
-                 "How can I improve my Python skills?"],
+        examples=["Tell me about quantum computing", "Write a short poem about AI", "How can I improve my Python skills?"],
         inputs=msg
     )
+    msg.focus()
 
-# Launch the app
+# --- Launch ---
 if __name__ == "__main__":
     demo.launch()
+
+
+