moved all functionality to api, improved performance

app.py

@@ -1,17 +1,25 @@
 import gradio as gr
-from openai import OpenAI, APIConnectionError, BadRequestError
 from gradio_client import Client
+from openai import OpenAI, APIConnectionError, BadRequestError
 import os
 from dotenv import load_dotenv
-# Load environment variables from .env file if it exists -- otherwise use hf secret
+
 if os.path.exists('.env'):
     load_dotenv()
-access_token =  os.getenv('PRIVATE_ACCESS_KEY') #both in hidden env & hf secrets.
-client = Client("neuronslabs/Text_modulator", hf_token=access_token)
-
-SYSTEM_PROMPT = """You are an advanced multilingual text transformation AI. Your role is to transform the provided text based on specific tasks, ensuring the core meaning remains intact. Each transformation should be distinct, creative, and suitable for the intended audience. Generate exactly 3 distinct variations of the transformed text, separated by '---'. Pay attention to language nuances, style, and context to enhance clarity and engagement."""
+access_token = os.getenv('PRIVATE_ACCESS_KEY')  # both in hidden env & hf secrets.
+# Initialize the client for the private space
+client = Client("neuronslabs/Text_modulator", hf_token = access_token)
 
 def validate_api_key(api_key):
+    """
+    Validate the provided OpenAI API key by attempting to list the available models.
+    
+    Args:
+        api_key (str): The OpenAI API key to validate.
+    
+    Returns:
+        bool: True if the API key is valid, False otherwise.
+    """
     try:
         openai_client = OpenAI(api_key=api_key)
         openai_client.models.list()
@@ -20,98 +28,62 @@ def validate_api_key(api_key):
         return False
 
 def check_api_key(api_key):
+    """
+    Check the validity of the provided OpenAI API key and return the connection status.
+    
+    Args:
+        api_key (str): The OpenAI API key to check.
+    
+    Returns:
+        str: "Connection successful" if the API key is valid, "Connection failed: Invalid API key" otherwise.
+    """
     if validate_api_key(api_key):
         return "Connection successful"
     else:
         return "Connection failed: Invalid API key"
 
-def generate_english_text(api_key, description, tone, channel, customizations, temperature):
-    openai_client = OpenAI(api_key=api_key)
-    customizations = [c.strip() for c in customizations] if customizations else []
-
-    messages = [
-        {"role": "system", "content": SYSTEM_PROMPT},
-        {"role": "user", "content": f"Task: Adjust the text to convey a '{tone}' tone. Ensure the message is clear and engaging. Provide 3 unique variations separated by '---'."},
-        {"role": "user", "content": f"Text: {description}"},
-    ]
-
-    if channel:
-        messages.append({"role": "user", "content": f"Channel: {channel}"})
-
-    if customizations:
-        messages.append({"role": "user", "content": f"Customizations: {', '.join(customizations)}"})
-
-    try:
-        response = openai_client.chat.completions.create(
-            model="gpt-3.5-turbo",
-            messages=messages,
-            temperature=temperature,
-            max_tokens=800
-        )
-        english_text = response.choices[0].message.content.strip()
-        options = english_text.split('---')
-
-        while len(options) < 3:
-            options.append("")
-
-        return [option.strip() for option in options]
-    except (APIConnectionError, BadRequestError) as e:
-        return [f"API request failed: {str(e)}", "", ""]
-
-def translate_text(api_key, english_text, translation, temperature):
-    if translation == "English":
-        options = english_text.split('---')
-        return [option.strip() for option in options]
-
-    openai_client = OpenAI(api_key=api_key)
-    messages = [
-        {"role": "system", "content": f"Translate the following text into {translation} while maintaining the original tone and context. Provide 3 unique variations, separated by '---'."},
-        {"role": "user", "content": english_text},
-    ]
-
+def nlp_interface(api_key, description, tone, channel, customizations, translation, temperature):
+    """
+    Main function to generate and translate text based on user input via the private space API.
+    
+    Args:
+        api_key (str): The OpenAI API key.
+        description (str): The text description to generate variations for.
+        tone (str): The desired tone for the generated text.
+        channel (str): The channel for which the text is being generated.
+        customizations (list): List of text customizations.
+        translation (str): The target language for translation.
+        temperature (float): The temperature value for the model.
+    
+    Returns:
+        tuple: Three text variations.
+    """
     try:
-        response = openai_client.chat.completions.create(
-            model="gpt-3.5-turbo",
-            messages=messages,
+        result = client.predict(
+            api_key=api_key,
+            description=description,
+            tone=tone,
+            channel=channel,
+            customizations=customizations,
+            translation=translation,
             temperature=temperature,
-            max_tokens=800
+            api_name="/nlp_interface"
         )
-        translated_text = response.choices[0].message.content.strip()
-        options = translated_text.split('---')
-
-        while len(options) < 3:
-            options.append("")
-
-        return [option.strip() for option in options]
-    except (APIConnectionError, BadRequestError) as e:
-        return [f"API request failed: {str(e)}", "", ""]
-
-def nlp_interface(api_key, description, tone, channel, customizations, translation, temperature):
-    english_options = generate_english_text(api_key, description, tone, channel, customizations, temperature)
-
-    if "API request failed" in english_options[0]:
-        return english_options
-
-    english_text = "---".join(english_options)
-    translated_options = translate_text(api_key, english_text, translation, temperature)
-
-    return translated_options
-
-def add_customization(customization, current_customizations):
-    result = client.predict(
-        customization=customization,
-        current_customizations=current_customizations,
-        api_name="/add_customization"
-    )
-    return result
+        return result[0], result[1], result[2]
+    except Exception as e:
+        return f"API request failed: {str(e)}", "", ""
 
-def connect(api_key):
-    status = check_api_key(api_key)
-    if "successful" in status:
-        return f"<div style='color: green; font-size: 20px;'>{status}</div>", gr.update(value="Submit", interactive=True), api_key
-    else:
-        return f"<div style='color: red;'>{status}</div>", gr.update(value="Please enter API Key", interactive=False), ""
+# JS codelet to force dark mode
+js_func = """
+function refresh() {
+    const url = new URL(window.location);
 
+    if (url.searchParams.get('__theme') !== 'dark') {
+        url.searchParams.set('__theme', 'dark');
+        window.location.href = url.href;
+    }
+}
+"""
 description = """
 <div style='text-align: center; font-size: 20px; font-weight: bold; margin-bottom: 20px;'>Welcome to the Promo Text Modulator Demo!</div>
 
@@ -124,56 +96,45 @@ description = """
 </div>
 """
 
-# JS codelet to force dark mode
-js_func = """
-function refresh() {
-    const url = new URL(window.location);
-
-    if (url.searchParams.get('__theme') !== 'dark') {
-        url.searchParams.set('__theme', 'dark');
-        window.location.href = url.href;
-    }
-}
-"""
-
 with gr.Blocks(js=js_func, css=".connection-status { text-align: center; margin-top: 20px; color: inherit; }") as demo:
     gr.Markdown(description)
 
     api_key_input = gr.Textbox(label="Your OpenAI API Key", type="password")
     connect_btn = gr.Button("Connect")
     connection_status = gr.HTML(visible=True, elem_classes=["connection-status"])
-    hidden_api_key = gr.State("")
 
     text_modulator = gr.Blocks()
 
     with text_modulator:
         with gr.Row():
             with gr.Column():
-                description_input = gr.Textbox(lines=3, label="Description")
+                
+                description_input = gr.Textbox(lines=3, label="Description and Details")
                 tone_input = gr.Dropdown(["Friendly and inviting", "Authoritative and confident", "Informative", "Enthusiastic and energetic", "Inspirational", "Exclusive and luxurious"], label="Tone", allow_custom_value=True)
                 channel_input = gr.Dropdown(["Facebook", "Instagram", "LinkedIn", "Twitter", "Viber", "Telegram", "Email"], label="Channel", allow_custom_value=True)
 
                 customizations_input = gr.Dropdown(
-                    ["Modernize", "Expand", "Add emojis", "Simplify language", "Improve writing", "Correct spelling"],
+                    ["Modernize", "Expand", "Add emojis", "Simplify language", "Improve writing", "Correct spelling", "Shorten"],
                     label="Text Customizations",
                     info="Select customization options",
                     show_label=True,
-                    multiselect=True  # Allow multiple selections
+                    multiselect=True,
+                    allow_custom_value=False
                 )
 
-                translation_input = gr.Dropdown(["English", "Moldovan", "Belarusian", "Albanian", "Russian", "Arabic", "Ukrainian", "French", "Kazakh", "Bosnian", "Armenian", "Serbian", "Tajik", "Azerbaijani", "Uzbek", "Romanian", "Spanish"], label="Translation", allow_custom_value=False)
+                translation_input = gr.Dropdown(["English", "Moldovan", "Belarusian", "Albanian", "Russian", "Arabic", "Ukrainian", "French", "Kazakh", "Bosnian", "Armenian", "Serbian", "Tajik", "Azerbaijani", "Uzbek", "Romanian", "Spanish"], label="Translation", allow_custom_value=True)
                 temperature_input = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label="Model Temperature", value=0.7)
 
                 submit_btn = gr.Button("Please enter API Key", interactive=False)
 
             with gr.Column():
-                output1 = gr.Textbox(label="Output 1")
-                output2 = gr.Textbox(label="Output 2")
-                output3 = gr.Textbox(label="Output 3")
+                output1 = gr.Textbox(label="Option 1")
+                output2 = gr.Textbox(label="Option 2")
+                output3 = gr.Textbox(label="Option 3")
 
                 submit_btn.click(
                     nlp_interface, 
-                    inputs=[hidden_api_key, description_input, tone_input, channel_input, customizations_input, translation_input, temperature_input],
+                    inputs=[api_key_input, description_input, tone_input, channel_input, customizations_input, translation_input, temperature_input],
                     outputs=[output1, output2, output3]
                 )
 
@@ -186,10 +147,17 @@ with gr.Blocks(js=js_func, css=".connection-status { text-align: center; margin-
             inputs=[description_input, tone_input, channel_input, customizations_input, translation_input]
         )
 
+    def connect(api_key):
+        status = check_api_key(api_key)
+        if "successful" in status:
+            return gr.update(value=f"<div style='color: green; font-size: 20px;'>{status}</div>", visible=True), gr.update(value="Submit", interactive=True)
+        else:
+            return gr.update(value=f"<div style='color: red;'>{status}</div>", visible=True), gr.update(value="Please enter API Key", interactive=False)
+
     connect_btn.click(
         fn=connect, 
         inputs=[api_key_input], 
-        outputs=[connection_status, submit_btn, hidden_api_key]
+        outputs=[connection_status, submit_btn]
     )
 
 demo.launch(share=True)