Create version1.txt

version1.txt

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+import gradio as gr
+import openai
+import fitz  # PyMuPDF for PDF processing
+import base64
+import io
+
+# Variable to store API key
+api_key = ""
+
+# Function to update API key
+def set_api_key(key):
+    global api_key
+    api_key = key
+    return "API Key Set Successfully!"
+
+# Function to interact with OpenAI API
+def query_openai(messages, temperature, top_p, max_output_tokens):
+    if not api_key:
+        return "Please enter your OpenAI API key first."
+
+    try:
+        openai.api_key = api_key  # Set API key dynamically
+
+        # Ensure numeric values for OpenAI parameters
+        temperature = float(temperature) if temperature else 1.0
+        top_p = float(top_p) if top_p else 1.0
+        max_output_tokens = int(max_output_tokens) if max_output_tokens else 2048
+
+        response = openai.ChatCompletion.create(
+            model="gpt-4.5-preview",
+            messages=messages,
+            temperature=temperature,
+            top_p=top_p,
+            max_tokens=max_output_tokens
+        )
+        return response["choices"][0]["message"]["content"]
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Function to process image URL input
+def image_url_chat(image_url, text_query, temperature, top_p, max_output_tokens):
+    if not image_url or not text_query:
+        return "Please provide an image URL and a query."
+
+    messages = [
+        {"role": "user", "content": [
+            {"type": "image_url", "image_url": {"url": image_url}},  # Corrected format
+            {"type": "text", "text": text_query}
+        ]},
+    ]
+    return query_openai(messages, temperature, top_p, max_output_tokens)
+
+# Function to process text input
+def text_chat(text_query, temperature, top_p, max_output_tokens):
+    if not text_query:
+        return "Please enter a query."
+
+    messages = [{"role": "user", "content": [{"type": "text", "text": text_query}]}]
+    return query_openai(messages, temperature, top_p, max_output_tokens)
+
+# Function to process uploaded image input
+def image_chat(image_file, text_query, temperature, top_p, max_output_tokens):
+    if image_file is None or not text_query:
+        return "Please upload an image and provide a query."
+
+    # Encode image as base64
+    with open(image_file, "rb") as img:
+        base64_image = base64.b64encode(img.read()).decode("utf-8")
+
+    image_data = f"data:image/jpeg;base64,{base64_image}"
+
+    messages = [
+        {"role": "user", "content": [
+            {"type": "image_url", "image_url": {"url": image_data}},  # Fixed format
+            {"type": "text", "text": text_query}
+        ]},
+    ]
+    return query_openai(messages, temperature, top_p, max_output_tokens)
+
+# Function to process uploaded PDF input
+def pdf_chat(pdf_file, text_query, temperature, top_p, max_output_tokens):
+    if pdf_file is None or not text_query:
+        return "Please upload a PDF and provide a query."
+
+    try:
+        # Extract text from all pages of the PDF
+        doc = fitz.open(pdf_file.name)
+        text = "\n".join([page.get_text("text") for page in doc])  # Extract text from all pages
+
+        # If no text found, return an error
+        if not text.strip():
+            return "No text found in the PDF."
+
+        # Create the query message with the extracted text and the user's query
+        messages = [
+            {"role": "user", "content": [
+                {"type": "text", "text": text},  # The extracted text from the PDF
+                {"type": "text", "text": text_query}
+            ]},
+        ]
+        return query_openai(messages, temperature, top_p, max_output_tokens)
+    
+    except Exception as e:
+        return f"Error processing the PDF: {str(e)}"
+
+# Function to transcribe audio to text using OpenAI Whisper API
+def transcribe_audio(audio_binary, openai_api_key):
+    if not openai_api_key:
+        return "Error: No API key provided."
+    
+    openai.api_key = openai_api_key
+    
+    try:
+        # Use the correct transcription API call
+        audio_file_obj = io.BytesIO(audio_binary)
+        audio_file_obj.name = 'audio.wav'  # Set a name for the file object (as OpenAI expects it)
+
+        # Transcribe the audio to text using OpenAI's whisper model
+        audio_file_transcription = openai.Audio.transcribe(file=audio_file_obj, model="whisper-1")
+        return audio_file_transcription.text
+    except Exception as e:
+        return f"Error transcribing audio: {str(e)}"
+
+# Function to clear the chat (Fix: Returns the correct number of outputs)
+def clear_chat():
+    return "", "", "", "", "", "", "", None, "", None, "", 1.0, 1.0, 2048
+
+# Gradio UI Layout
+with gr.Blocks() as demo:
+    gr.Markdown("## GPT-4.5 Preview Chatbot")
+
+    # Accordion for explaining hyperparameters
+    with gr.Accordion("Hyperparameters", open=False):
+        gr.Markdown("""
+        ### Temperature: 
+        Controls the randomness of the model's output. A lower temperature makes the model more deterministic, while a higher temperature makes it more creative and varied.
+        ### Top-P (Nucleus Sampling): 
+        Controls the cumulative probability distribution from which the model picks the next word. A lower value makes the model more focused and deterministic, while a higher value increases randomness.
+        ### Max Output Tokens: 
+        Limits the number of tokens (words or subwords) the model can generate in its response. You can use this to control the length of the response.
+        """)
+
+    gr.HTML("""
+    <style>
+        #api_key_button {
+            margin-top: 27px; /* Add margin-top to the button */
+            background: linear-gradient(135deg, #4a00e0 0%, #8e2de2 100%); /* Purple gradient */
+        }
+        #api_key_button:hover {
+            background: linear-gradient(135deg, #5b10f1 0%, #9f3ef3 100%); /* Slightly lighter */
+        }
+        #clear_chat_button {
+            background: linear-gradient(135deg, #e53e3e 0%, #f56565 100%); /* Red gradient */
+        }
+        #clear_chat_button:hover {
+            background: linear-gradient(135deg, #c53030 0%, #e53e3e 100%); /* Slightly darker red gradient on hover */
+        }
+        #ask_button {
+            background: linear-gradient(135deg, #fbd38d 0%, #f6e05e 100%); /* Yellow gradient */
+        }
+        #ask_button:hover {
+            background: linear-gradient(135deg, #ecc94b 0%, #fbd38d 100%); /* Slightly darker yellow gradient on hover */
+        }
+    </style>
+    """)
+    
+    # API Key Input
+    with gr.Row():
+        api_key_input = gr.Textbox(label="Enter OpenAI API Key", type="password")
+        api_key_button = gr.Button("Set API Key", elem_id="api_key_button")
+        api_key_output = gr.Textbox(label="API Key Status", interactive=False)
+
+    with gr.Row():
+        temperature = gr.Slider(0, 2, value=1.0, step=0.1, label="Temperature")
+        top_p = gr.Slider(0, 1, value=1.0, step=0.1, label="Top-P")
+        max_output_tokens = gr.Slider(0, 16384, value=2048, step=512, label="Max Output Tokens")  # Changed default to 2048
+    
+    with gr.Tabs():
+        with gr.Tab("Image URL Chat"):
+            image_url = gr.Textbox(label="Enter Image URL")
+            image_query = gr.Textbox(label="Ask about the Image")
+            image_url_output = gr.Textbox(label="Response", interactive=False)
+            image_url_button = gr.Button("Ask",elem_id="ask_button")
+        
+        with gr.Tab("Text Chat"):
+            text_query = gr.Textbox(label="Enter your query")
+            text_output = gr.Textbox(label="Response", interactive=False)
+            text_button = gr.Button("Ask",elem_id="ask_button")
+        
+        with gr.Tab("Image Chat"):
+            image_upload = gr.File(label="Upload an Image", type="filepath")
+            image_text_query = gr.Textbox(label="Ask about the uploaded image")
+            image_output = gr.Textbox(label="Response", interactive=False)
+            image_button = gr.Button("Ask",elem_id="ask_button")
+        
+        with gr.Tab("PDF Chat"):
+            pdf_upload = gr.File(label="Upload a PDF", type="filepath")
+            pdf_text_query = gr.Textbox(label="Ask about the uploaded PDF")
+            pdf_output = gr.Textbox(label="Response", interactive=False)
+            pdf_button = gr.Button("Ask",elem_id="ask_button")
+
+        with gr.Tab("Voice Chat"):
+            audio_upload = gr.File(label="Upload an Audio File", type="binary")
+            audio_query = gr.Textbox(label="Ask about the transcription")
+            audio_output = gr.Textbox(label="Response", interactive=False)
+            audio_button = gr.Button("Ask",elem_id="ask_button")
+
+    # Clear chat button
+    clear_button = gr.Button("Clear Chat",elem_id="clear_chat_button")
+
+    # Button Click Actions
+    api_key_button.click(set_api_key, inputs=[api_key_input], outputs=[api_key_output])
+    image_url_button.click(image_url_chat, [image_url, image_query, temperature, top_p, max_output_tokens], image_url_output)
+    text_button.click(text_chat, [text_query, temperature, top_p, max_output_tokens], text_output)
+    image_button.click(image_chat, [image_upload, image_text_query, temperature, top_p, max_output_tokens], image_output)
+    pdf_button.click(pdf_chat, [pdf_upload, pdf_text_query, temperature, top_p, max_output_tokens], pdf_output)
+    
+    # For Voice Chat
+    audio_button.click(
+        lambda audio_binary, query, temperature, top_p, max_output_tokens: query_openai(
+            [{"role": "user", "content": [{"type": "text", "text": transcribe_audio(audio_binary, api_key)}, {"type": "text", "text": query}]}],
+            temperature, top_p, max_output_tokens
+        ), [audio_upload, audio_query, temperature, top_p, max_output_tokens], audio_output
+    )
+
+    # Fix: Clear button resets all necessary fields correctly
+    clear_button.click(
+        clear_chat,
+        outputs=[
+            image_url, image_query, image_url_output, 
+            text_query, text_output, 
+            image_text_query, image_output, 
+            pdf_upload, pdf_text_query, pdf_output, 
+            temperature, top_p, max_output_tokens
+        ]
+    )
+
+# Launch Gradio App
+if __name__ == "__main__":
+    demo.launch()