Update app.py

app.py

@@ -1,7 +1,7 @@
-from huggingfaceinferenceclient import HuggingFaceInferenceClient
-from outpaintprocessor import DynamicImageOutpainter
-from aivideopipeline import AIImageVideoPipeline
-from mmig import MultiModelImageGenerator
+#from huggingfaceinferenceclient import HuggingFaceInferenceClient
+#from outpaintprocessor import DynamicImageOutpainter
+#from aivideopipeline import AIImageVideoPipeline
+#from mmig import MultiModelImageGenerator
 
 
 import os
@@ -12,9 +12,19 @@ from huggingface_hub import InferenceClient
 from IPython.display import Audio, display
 import gradio as gr
 
+read_token = os.getenv('HF_READ')
+write_token = os.getenv('HF_WRITE')
+#chatmodel
+chatmodel="mistralai/Mistral-Nemo-Instruct-2407"
 # Whisper for Speech-to-Text
 WHISPER_API_URL = "https://api-inference.huggingface.co/models/distil-whisper/distil-large-v2"
-WHISPER_HEADERS = {"Authorization": "Bearer hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
+WHISPER_HEADERS = {"Authorization": "Bearer " + read_token}
+# Bark for Text-to-Speech
+BARK_API_URL = "https://api-inference.huggingface.co/models/suno/bark"
+BARK_HEADERS = {"Authorization": "Bearer "+read_token}
+# Flux for Image Generation
+FLUX_API_URL = "https://api-inference.huggingface.co/models/enhanceaiteam/Flux-uncensored"
+FLUX_HEADERS = {"Authorization": "Bearer "+read_token}
 
 def speech_to_text(filename):
     with open(filename, "rb") as f:
@@ -27,13 +37,13 @@ def speech_to_text(filename):
         return None
 
 # Chatbot Logic with Hugging Face InferenceClient
-client = InferenceClient(api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
+client = InferenceClient(api_key=read_token)
 
 def chatbot_logic(input_text):
     messages = [{"role": "user", "content": input_text}]
     try:
         completion = client.chat.completions.create(
-            model="mistralai/Mistral-Nemo-Instruct-2407", 
+            model=chatmodel, 
             messages=messages, 
             max_tokens=500
         )
@@ -42,9 +52,6 @@ def chatbot_logic(input_text):
         print(f"Error: {e}")
         return None
 
-# Bark for Text-to-Speech
-BARK_API_URL = "https://api-inference.huggingface.co/models/suno/bark"
-BARK_HEADERS = {"Authorization": "Bearer hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
 
 def text_to_speech(text):
     payload = {"inputs": text}
@@ -55,10 +62,6 @@ def text_to_speech(text):
         print(f"Error: {response.status_code} - {response.text}")
         return None
 
-# Flux for Image Generation
-FLUX_API_URL = "https://api-inference.huggingface.co/models/enhanceaiteam/Flux-uncensored"
-FLUX_HEADERS = {"Authorization": "Bearer hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
-
 def generate_image(prompt):
     data = {"inputs": prompt}
     response = requests.post(FLUX_API_URL, headers=FLUX_HEADERS, json=data)