Update app.py

app.py

@@ -1,59 +1,257 @@
+Hugging Face's logo
+Hugging Face
+Models
+Datasets
+Spaces
+Community
+Docs
+Pricing
+
+
+
+Spaces:
+
+
+MoShow
+/
+deeptalkv1
+
+private
+
+App
+Files
+Community
+Settings
+deeptalkv1
+/
+app.py
+
+NihalGazi's picture
+NihalGazi
+Update app.py
+940ff5b
+verified
+25 days ago
+raw
+
+Copy download link
+history
+blame
+edit
+delete
+
+7.74 kB
+# app.py
 import gradio as gr
-from huggingface_hub import InferenceClient
+import requests
+import random
+import urllib.parse
+import tempfile
 import os
 
-# The token is securely pulled from the Hugging Face Space Secret named HUGGINGFACEHUB_API_TOKEN
-HF_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
-
-# Setup the inference client with your model and token
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta", token=HF_TOKEN)
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
-
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+NSFW_URL_TEMPLATE = os.getenv("NSFW_API_URL_TEMPLATE")
+TTS_URL_TEMPLATE = os.getenv("TTS_API_URL_TEMPLATE")
+
+
+if not NSFW_URL_TEMPLATE:
+    raise ValueError("Missing Secret: NSFW_API_URL_TEMPLATE is not set in Hugging Face Space secrets.")
+if not TTS_URL_TEMPLATE:
+    raise ValueError("Missing Secret: TTS_API_URL_TEMPLATE is not set in Hugging Face Space secrets.")
+# VOICES
+VOICES = [
+    "alloy", "echo", "fable", "onyx", "nova", "shimmer",  # Standard OpenAI Voices
+    "coral", "verse", "ballad", "ash", "sage", "amuch", "dan" # Some additional pre-trained
+]
+
+
+
+def check_nsfw(prompt: str) -> bool:
+    global NSFW_URL_TEMPLATE 
+    try:
+        encoded_prompt = urllib.parse.quote(prompt)
+        url = NSFW_URL_TEMPLATE.format(prompt=encoded_prompt)
+        print(f"DEBUG: Checking NSFW URL: {url.split('?')[0]}... (query params hidden)")
+
+        response = requests.get(url, timeout=20)
+        response.raise_for_status()
+
+        result = response.text.strip().upper()
+        print(f"DEBUG: NSFW Check Response: '{result}'")
+
+        if result == "YES":
+            return True
+        elif result == "NO":
+            return False
+        else:
+            print(f"Warning: Unexpected response from NSFW checker: {response.text}")
+            return True # unexpected responses = potentially NSFW
+
+    except requests.exceptions.RequestException as e:
+        print(f"Error during NSFW check: {e}")
+        raise gr.Error(f"Failed to check prompt safety.")
+    except Exception as e:
+        print(f"Unexpected error during NSFW check: {e}")
+        raise gr.Error(f"An unexpected error occurred during safety check. Please wait for a second and try again.")
+
+
+def generate_audio(prompt: str, voice: str, emotion: str, seed: int) -> bytes:
+   # Generates audio using the API from server
+    global TTS_URL_TEMPLATE 
+    try:
+        encoded_prompt = urllib.parse.quote(prompt)
+        encoded_emotion = urllib.parse.quote(emotion)
+
+        url = TTS_URL_TEMPLATE.format(
+            prompt=encoded_prompt,
+            emotion=encoded_emotion,
+            voice=voice,
+            seed=seed
+        )
+        print(f"DEBUG: Generating Audio URL: {url.split('?')[0]}... (query params hidden)")
+
+        response = requests.get(url, timeout=60)
+        response.raise_for_status()
+
+        content_type = response.headers.get('content-type', '').lower()
+        if 'audio' not in content_type:
+            print(f"Warning: Unexpected content type received: {content_type}")
+            print(f"Response Text: {response.text[:500]}")
+            raise gr.Error(f"API did not return audio.")
+
+        return response.content
+
+    except requests.exceptions.RequestException as e:
+        print(f"Error during audio generation: {e}")
+        error_details = ""
+        if hasattr(e, 'response') and e.response is not None:
+            error_details = e.response.text[:200]
+        raise gr.Error(f"Failed to generate audio. Please wait for a second and try again.")
+    except Exception as e:
+        print(f"Unexpected error during audio generation: {e}")
+        raise gr.Error(f"An unexpected error occurred during audio generation. Please wait for a second and try again.")
+
+
+
+def text_to_speech_app(prompt: str, voice: str, emotion: str, use_random_seed: bool, specific_seed: int):
+
+    print("\n\n\n"+prompt+"\n\n\n")
+    if not prompt:
+        raise gr.Error("Prompt cannot be empty.")
+    if not emotion:
+        emotion = "neutral"
+        print("Warning: No emotion provided, defaulting to 'neutral'.")
+    if not voice:
+         raise gr.Error("Please select a voice.")
+
+    seed = random.randint(0, 2**32 - 1) if use_random_seed else int(specific_seed)
+    print(f"Using Seed: {seed}")
+
+    # check NSFW
+    print("Checking prompt safety...")
+    try:
+        # is_nsfw = check_nsfw(prompt)
+        is_nsfw = False
+    except gr.Error as e:
+        return None, f"There was an error. Please wait for a second and try again."
+
+    if is_nsfw:
+        print("Prompt flagged as inappropriate.")
+        return None, "Error: The prompt was flagged as inappropriate and cannot be processed."
+
+    # if not nsfw
+    print("Prompt is safe. Generating audio...")
+    try:
+        audio_bytes = generate_audio(prompt, voice, emotion, seed)
+
+        # audio save to a temporary file
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio_file:
+            temp_audio_file.write(audio_bytes)
+            temp_file_path = temp_audio_file.name
+            print(f"Audio saved temporarily to: {temp_file_path}")
+
+        return temp_file_path, f"Audio generated successfully with voice '{voice}', emotion '{emotion}', and seed {seed}."
+
+    except gr.Error as e:
+         return None, str(e)
+    except Exception as e:
+        print(f"Unexpected error in main function: {e}")
+        return None, f"An unexpected error occurred: {e}"
+
+
+
+
+def toggle_seed_input(use_random_seed):
+    
+    return gr.update(visible=not use_random_seed, value=12345)
+
+with gr.Blocks() as app:
+    gr.Markdown("# Advanced OpenAI Text-To-Speech Unlimited")
+    gr.Markdown(
+        """Enter text, choose a voice and emotion, and generate audio. 
+        The text will be checked for appropriateness before generation. 
+        Use it as much as you want.
+        
+        
+        **Like & follow** for more AI projects:
+        
+        • Instagram: [@nihal_gazi_io](https://www.instagram.com/nihal_gazi_io/)  
+        • Discord: nihal_gazi_io"""
+    )
+
+    with gr.Row():
+        with gr.Column(scale=2):
+            prompt_input = gr.Textbox(label="Prompt", placeholder="Enter the text you want to convert to speech...")
+            emotion_input = gr.Textbox(label="Emotion Style", placeholder="e.g., happy, sad, excited, calm...")
+            voice_dropdown = gr.Dropdown(label="Voice", choices=VOICES, value="alloy")
+        with gr.Column(scale=1):
+            random_seed_checkbox = gr.Checkbox(label="Use Random Seed", value=True)
+            seed_input = gr.Number(label="Specific Seed", value=12345, visible=False, precision=0)
+
+    submit_button = gr.Button("Generate Audio", variant="primary")
+
+    with gr.Row():
+        audio_output = gr.Audio(label="Generated Audio", type="filepath")
+        status_output = gr.Textbox(label="Status")
+
+
+    random_seed_checkbox.change(
+        fn=toggle_seed_input,
+        inputs=[random_seed_checkbox],
+        outputs=[seed_input]
+    )
+
+    submit_button.click(
+        fn=text_to_speech_app,
+        inputs=[
+            prompt_input,
+            voice_dropdown,
+            emotion_input,
+            random_seed_checkbox,
+            seed_input
+        ],
+        outputs=[audio_output, status_output],
+        concurrency_limit=30
+    )
+
+
+    gr.Examples(
+        examples=[
+            ["Hello there! This is a test of the text-to-speech system.", "alloy", "neutral", False, 12345],
+            ["Surely *you* wouldn't want *that*. [laughs]", "shimmer", "sarcastic and mocking", True, 12345],
+            ["[sobbing] I am feeling... [sighs] a bit down today [cry]", "ballad", "sad and depressed, with stammering", True, 662437],
+            ["This technology is absolutely amazing!", "nova", "excited and joyful", True, 12345],
+        ],
+        inputs=[prompt_input, voice_dropdown, emotion_input, random_seed_checkbox, seed_input],
+        outputs=[audio_output, status_output],
+        fn=text_to_speech_app,
+        cache_examples=False, 
+    )
+
 
 if __name__ == "__main__":
-    demo.launch()
+    
+    if NSFW_URL_TEMPLATE and TTS_URL_TEMPLATE:
+        app.launch()
+    else:
+        print("ERROR: Cannot launch app. Required API URL secrets are missing.")
+