Santhosh54321/Test_model
0
1import streamlit as st2import requests3import os4import time # Import time module for implementing delay5 6# Fetch Hugging Face and Groq API keys from secrets7Transalate_token = os.getenv('HUGGINGFACE_TOKEN')8Image_Token = os.getenv('HUGGINGFACE_TOKEN')9Content_Token = os.getenv('GROQ_API_KEY')10Image_prompt_token = os.getenv('GROQ_API_KEY')11 12# API Headers13Translate = {"Authorization": f"Bearer {Transalate_token}"}14Image_generation = {"Authorization": f"Bearer {Image_Token}"}15Content_generation = {16 "Authorization": f"Bearer {Content_Token}",17 "Content-Type": "application/json"18}19Image_Prompt = {20 "Authorization": f"Bearer {Image_prompt_token}",21 "Content-Type": "application/json"22}23 24# Translation Model API URL (Tamil to English)25translation_url = "https://api-inference.huggingface.co/models/facebook/mbart-large-50-many-to-one-mmt"26 27# Text-to-Image Model API URLs28image_generation_urls = {29 "black-forest-labs/FLUX.1-schnell": "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell",30 "CompVis/stable-diffusion-v1-4": "https://api-inference.huggingface.co/models/CompVis/stable-diffusion-v1-4",31 "black-forest-labs/FLUX.1-dev": "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"32}33 34# Default image generation model35default_image_model = "black-forest-labs/FLUX.1-schnell"36 37# Content generation models38content_models = {39 "llama-3.1-70b-versatile": "llama-3.1-70b-versatile",40 "llama3-8b-8192": "llama3-8b-8192",41 "gemma2-9b-it": "gemma2-9b-it",42 "mixtral-8x7b-32768": "mixtral-8x7b-32768"43}44 45# Default content generation model46default_content_model = "llama-3.1-70b-versatile"47 48# Function to query Hugging Face translation model with retry mechanism49def translate_text(text):50 payload = {"inputs": text}51 max_retries = 3 # Maximum number of retry attempts52 delay = 2 # Delay between retries in seconds53 54 for attempt in range(max_retries):55 response = requests.post(translation_url, headers=Translate, json=payload)56 if response.status_code == 200:57 result = response.json()58 translated_text = result[0]['generated_text']59 return translated_text60 else:61 st.warning(f"Translation failed (Attempt {attempt+1}/{max_retries}) - Retrying in {delay} seconds...")62 time.sleep(delay) # Wait for 2 seconds before retrying63 64 # If all retries fail, show an error65 st.error(f"Translation failed after {max_retries} attempts. Please reload the page and try again later.")66 return None67 68# Function to query Groq content generation model69def generate_content(english_text, max_tokens, temperature, model):70 url = "https://api.groq.com/openai/v1/chat/completions"71 payload = {72 "model": model,73 "messages": [74 {"role": "system", "content": "You are a creative and insightful writer."},75 {"role": "user", "content": f"Write educational content about {english_text} within {max_tokens} tokens."}76 ],77 "max_tokens": max_tokens,78 "temperature": temperature79 }80 response = requests.post(url, json=payload, headers=Content_generation)81 if response.status_code == 200:82 result = response.json()83 return result['choices'][0]['message']['content']84 else:85 st.error(f"Content Generation Error: {response.status_code}")86 return None87 88# Function to generate image prompt89def generate_image_prompt(english_text):90 payload = {91 "model": "mixtral-8x7b-32768",92 "messages": [93 {"role": "system", "content": "You are a professional Text to image prompt generator."},94 {"role": "user", "content": f"Create a text to image generation prompt about {english_text} within 30 tokens."}95 ],96 "max_tokens": 3097 }98 response = requests.post("https://api.groq.com/openai/v1/chat/completions", json=payload, headers=Image_Prompt)99 if response.status_code == 200:100 result = response.json()101 return result['choices'][0]['message']['content']102 else:103 st.error(f"Prompt Generation Error: {response.status_code}")104 return None105 106# Function to generate an image from the prompt107def generate_image(image_prompt, model_url):108 data = {"inputs": image_prompt}109 response = requests.post(model_url, headers=Image_generation, json=data)110 if response.status_code == 200:111 return response.content112 else:113 st.error(f"Image Generation Error {response.status_code}: {response.text}")114 return None115 116# User Guide Section117def show_user_guide():118 st.title("FusionMind User Guide")119 st.write("""120 ### Welcome to the FusionMind User Guide!121 122 ### How to use this app:123 ... (omitted for brevity)124 """)125 126# Main Streamlit app127def main():128 # Sidebar Menu129 st.sidebar.title("FusionMind Options")130 page = st.sidebar.radio("Select a page:", ["Main App", "User Guide"])131 132 if page == "User Guide":133 show_user_guide()134 return135 136 # Custom CSS for background, borders, and other styling137 st.markdown(138 """139 <style>140 body {141 background-image: url('https://wallpapercave.com/wp/wp4008910.jpg');142 background-size: cover;143 }144 .reportview-container {145 background: rgba(255, 255, 255, 0.85);146 padding: 2rem;147 border-radius: 10px;148 box-shadow: 0px 0px 20px rgba(0, 0, 0, 0.1);149 }150 .result-container {151 border: 2px solid #4CAF50;152 padding: 20px;153 border-radius: 10px;154 margin-top: 20px;155 animation: fadeIn 2s ease;156 }157 @keyframes fadeIn {158 0% { opacity: 0; }159 100% { opacity: 1; }160 }161 .stButton button {162 background-color: #4CAF50;163 color: white;164 border-radius: 10px;165 padding: 10px;166 }167 .stButton button:hover {168 background-color: #45a049;169 transform: scale(1.05);170 transition: 0.2s ease-in-out;171 }172 </style>173 """, unsafe_allow_html=True174 )175 176 st.title("🅰️ℹ️ FusionMind ➡️ Multimodal")177 178 # Sidebar for temperature, token adjustment, and model selection179 st.sidebar.header("Settings")180 temperature = st.sidebar.slider("Select Temperature", 0.1, 1.0, 0.7)181 max_tokens = st.sidebar.slider("Max Tokens for Content Generation", 100, 400, 200)182 183 # Content generation model selection184 content_model = st.sidebar.selectbox("Select Content Generation Model", list(content_models.keys()), index=0)185 186 # Image generation model selection187 image_model = st.sidebar.selectbox("Select Image Generation Model", list(image_generation_urls.keys()), index=0)188 189 # Reminder about model availability190 st.sidebar.warning("Note: Based on availability, some models might not work. Please try another model if an error occurs.By default the perfect model is selected try with it and then experiment with different models")191 192 # Suggested inputs193 st.write("## Suggested Inputs")194 suggestions = ["தரவு அறிவியல்", "உளவியல்", "ராக்கெட் எப்படி வேலை செய்கிறது"]195 selected_suggestion = st.selectbox("Select a suggestion or enter your own:", [""] + suggestions)196 197 # Input box for user198 tamil_input = st.text_input("Enter Tamil text (or select a suggestion):", selected_suggestion)199 200 if st.button("Generate"):201 # Step 1: Translation (Tamil to English)202 if tamil_input:203 st.write("### Translated English Text:")204 english_text = translate_text(tamil_input)205 if english_text:206 st.write(english_text)207 208 # Step 2: Content Generation209 st.write("### Educational Content Generated:")210 content = generate_content(english_text, max_tokens, temperature, content_models[content_model])211 if content:212 st.write(content)213 214 # Step 3: Generate Image Prompt215 st.write("### Image Prompt:")216 image_prompt = generate_image_prompt(english_text)217 if image_prompt:218 st.write(image_prompt)219 220 # Step 4: Image Generation221 st.write("### Generated Image:")222 image = generate_image(image_prompt, image_generation_urls[image_model])223 if image:224 st.image(image)225 else:226 st.error("Please enter or select Tamil text.")227 228if __name__ == "__main__":229 main()230