Update app.py

app.py

@@ -3,10 +3,10 @@ import requests
 import os
 
 # Fetch Hugging Face and Groq API keys from secrets
-Transalate_token = os.getenv('HUGGINGFACE_TOKEN')
-Image_Token = os.getenv('HUGGINGFACE_TOKEN')
-Content_Token = os.getenv('GROQ_API_KEY')
-Image_prompt_token = os.getenv('GROQ_API_KEY')
+Transalate_token = os.getenv('Translate')
+Image_Token = os.getenv('Image_generation')
+Content_Token = os.getenv('ContentGeneration')
+Image_prompt_token = os.getenv('Prompt_generation')
 
 # API Headers
 Translate = {"Authorization": f"Bearer {Transalate_token}"}
@@ -23,41 +23,45 @@ Image_Prompt = {
 # Translation Model API URL (Tamil to English)
 translation_url = "https://api-inference.huggingface.co/models/facebook/mbart-large-50-many-to-one-mmt"
 
-# Text-to-Image Model API URL
-image_generation_url = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
+# Text-to-Image Model API URLs
+image_generation_urls = {
+    "black-forest-labs/FLUX.1-schnell": "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell",
+    "CompVis/stable-diffusion-v1-4": "https://api-inference.huggingface.co/models/CompVis/stable-diffusion-v1-4",
+    "black-forest-labs/FLUX.1-dev": "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
+}
+
+# Default image generation model
+default_image_model = "black-forest-labs/FLUX.1-schnell"
+
+# Content generation models
+content_models = {
+    "llama-3.1-70b-versatile": "llama-3.1-70b-versatile",
+    "llama3-8b-8192": "llama3-8b-8192",
+    "gemma2-9b-it": "gemma2-9b-it",
+    "mixtral-8x7b-32768": "mixtral-8x7b-32768"
+}
 
-# Function to query Hugging Face translation model with try-except retry logic
+# Default content generation model
+default_content_model = "llama-3.1-70b-versatile"
+
+# Function to query Hugging Face translation model
 def translate_text(text):
     payload = {"inputs": text}
-    
-    # Try block to handle the first attempt
-    try:
-        response = requests.post(translation_url, headers=Translate, json=payload)
-        response.raise_for_status()  # Raise an error for bad status codes (non-200)
+    response = requests.post(translation_url, headers=Translate, json=payload)
+    if response.status_code == 200:
         result = response.json()
         translated_text = result[0]['generated_text']
         return translated_text
-
-    except requests.exceptions.RequestException as e:
-        st.warning(f"First attempt failed due to: {e}. Retrying...")
-
-        # Retry the request once if it fails
-        try:
-            response = requests.post(translation_url, headers=Translate, json=payload)
-            response.raise_for_status()  # Raise an error for bad status codes (non-200)
-            result = response.json()
-            translated_text = result[0]['generated_text']
-            return translated_text
-
-        except requests.exceptions.RequestException as e:
-            st.error(f"Second attempt failed: {e}")
-            return None
+    else:
+        st.error(f"Translation Error {response.status_code}: {response.text}")
+        st.write(f'Please try after sometime 😥😥😥')
+        return None
 
 # Function to query Groq content generation model
-def generate_content(english_text, max_tokens, temperature):
+def generate_content(english_text, max_tokens, temperature, model):
     url = "https://api.groq.com/openai/v1/chat/completions"
     payload = {
-        "model": "llama-3.1-70b-versatile",
+        "model": model,
         "messages": [
             {"role": "system", "content": "You are a creative and insightful writer."},
             {"role": "user", "content": f"Write educational content about {english_text} within {max_tokens} tokens."}
@@ -92,150 +96,103 @@ def generate_image_prompt(english_text):
         return None
 
 # Function to generate an image from the prompt
-def generate_image(image_prompt):
+def generate_image(image_prompt, model_url):
     data = {"inputs": image_prompt}
-    response = requests.post(image_generation_url, headers=Image_generation, json=data)
+    response = requests.post(model_url, headers=Image_generation, json=data)
     if response.status_code == 200:
         return response.content
     else:
         st.error(f"Image Generation Error {response.status_code}: {response.text}")
         return None
 
-# User Guide content
-def user_guide():
-    st.title("User Guide")
-    st.write("""
-    ### Welcome to FusionMind Multimodel ---> Your one stop solution for content creation.
-    
-    
-**How to use this app:**
-
-1. **Input Tamil Text**: 
-   - You can either select one of the suggested Tamil phrases or input your own text. The app primarily focuses on Tamil inputs, but it supports a wide range of other languages as well (see the list below).
-   
-2. **Generate Translations**: 
-   - Once you've input your text, the app will automatically translate it to English. The translation model is a **many-to-one model**, meaning it can take input from various languages and translate it into English.
-
-3. **Generate Educational Content**: 
-   - After translating the text into English, the app will generate **educational content** based on the translated input. You can adjust the creativity of the content generation using the temperature slider, and control the length of the output with the token limit setting.
-
-4. **Generate Images**: 
-   - In addition to generating content, the app can also generate an **image** related to the translated content. You don’t need to worry about creating complex image prompts—FusionMind includes an automatic **image prompt generator** that will convert your input into a well-defined image prompt, ensuring better image generation results.
-
----
-
-### Features:
-
-- **Multilingual Translation**: 
-   - FusionMind supports a **many-to-one translation model**, so you can input text in a wide variety of languages, not just Tamil. Below are the supported languages:
-   
-     - **Arabic (ar_AR)**, **Czech (cs_CZ)**, **German (de_DE)**, **English (en_XX)**, **Spanish (es_XX)**, **Estonian (et_EE)**, **Finnish (fi_FI)**, **French (fr_XX)**, **Gujarati (gu_IN)**, **Hindi (hi_IN)**, **Italian (it_IT)**, **Japanese (ja_XX)**, **Kazakh (kk_KZ)**, **Korean (ko_KR)**, **Lithuanian (lt_LT)**, **Latvian (lv_LV)**, **Burmese (my_MM)**, **Nepali (ne_NP)**, **Dutch (nl_XX)**, **Romanian (ro_RO)**, **Russian (ru_RU)**, **Sinhala (si_LK)**, **Turkish (tr_TR)**, **Vietnamese (vi_VN)**, **Chinese (zh_CN)**, **Afrikaans (af_ZA)**, **Azerbaijani (az_AZ)**, **Bengali (bn_IN)**, **Persian (fa_IR)**, **Hebrew (he_IL)**, **Croatian (hr_HR)**, **Indonesian (id_ID)**, **Georgian (ka_GE)**, **Khmer (km_KH)**, **Macedonian (mk_MK)**, **Malayalam (ml_IN)**, **Mongolian (mn_MN)**, **Marathi (mr_IN)**, **Polish (pl_PL)**, **Pashto (ps_AF)**, **Portuguese (pt_XX)**, **Swedish (sv_SE)**, **Swahili (sw_KE)**, **Tamil (ta_IN)**, **Telugu (te_IN)**, **Thai (th_TH)**, **Tagalog (tl_XX)**, **Ukrainian (uk_UA)**, **Urdu (ur_PK)**, **Xhosa (xh_ZA)**, **Galician (gl_ES)**, **Slovene (sl_SI)**.
-
-- **Temperature Adjustment**: 
-   - You can adjust the **temperature** of the content generation. A **higher temperature** makes the content more creative and varied, while a **lower temperature** generates more focused and deterministic responses.
-
-- **Token Limit**: 
-   - Set the **maximum number of tokens** for content generation. This allows you to control the length of the generated educational content.
-
-- **Automatic Retries**: 
-   - If a translation request fails due to any reason, the app is designed to **automatically retry**, ensuring a smooth experience.
-
-- **Auto-Generated Image Prompts**: 
-   - One of the unique features of FusionMind is the **auto-generated image prompts**. Even if you're not experienced in creating detailed prompts for image generation, the app will take care of this for you. It automatically converts the translated text or content into a well-defined prompt that produces more accurate and high-quality images.
-
----
-
-Enjoy the multimodal experience with **FusionMind** and explore its powerful translation, content generation, and image generation features!
-
-    """)
-
 # Main Streamlit app
 def main():
-    # Sidebar for navigation
-    st.sidebar.title("Navigation")
-    page = st.sidebar.radio("Go to", ["Home", "User Guide"])
-
-    # If user selects "User Guide" page
-    if page == "User Guide":
-        user_guide()
-    else:
-        # Custom CSS for background, borders, and other styling
-        st.markdown(
-            """
-            <style>
-            body {
-                background-image: url('https://wallpapercave.com/wp/wp4008910.jpg');
-                background-size: cover;
-            }
-            .reportview-container {
-                background: rgba(255, 255, 255, 0.85);
-                padding: 2rem;
-                border-radius: 10px;
-                box-shadow: 0px 0px 20px rgba(0, 0, 0, 0.1);
-            }
-            .result-container {
-                border: 2px solid #4CAF50;
-                padding: 20px;
-                border-radius: 10px;
-                margin-top: 20px;
-                animation: fadeIn 2s ease;
-            }
-            @keyframes fadeIn {
-                0% { opacity: 0; }
-                100% { opacity: 1; }
-            }
-            .stButton button {
-                background-color: #4CAF50;
-                color: white;
-                border-radius: 10px;
-                padding: 10px;
-            }
-            .stButton button:hover {
-                background-color: #45a049;
-                transform: scale(1.05);
-                transition: 0.2s ease-in-out;
-            }
-            </style>
-            """, unsafe_allow_html=True
-        )
-
-        st.title("🅰️ℹ️ FusionMind ➡️ Multimodal")
-
-        # Sidebar for temperature and token adjustment
-        st.sidebar.header("Settings")
-        temperature = st.sidebar.slider("Select Temperature", 0.1, 1.0, 0.7)
-        max_tokens = st.sidebar.slider("Max Tokens for Content Generation", 100, 400, 200)
-
-        # Suggested inputs
-        st.write("## Suggested Inputs")
-        suggestions = ["தரவு அறிவியல்", "புதிய திறன்களைக் கற்றுக்கொள்வது எப்படி", "ராக்கெட் எப்படி வேலை செய்கிறது"]
-        selected_suggestion = st.selectbox("Select a suggestion or enter your own:", [""] + suggestions)
-
-        # Input box for user
-        tamil_input = st.text_input("Enter Tamil text (or select a suggestion):", selected_suggestion)
-
-        if st.button("Generate"):
-            # Step 1: Translation (Tamil to English)
-            if tamil_input:
-                st.write("### Translated English Text:")
-                english_text = translate_text(tamil_input)
-                if english_text:
-                    st.success(english_text)
-
-                    # Step 2: Generate Educational Content
-                    st.write("### Generated Educational Content:")
-                    with st.spinner('Generating content...'):
-                        content_output = generate_content(english_text, max_tokens, temperature)
-                        if content_output:
-                            st.success(content_output)
-
-                    # Step 3: Generate Image from the prompt
-                    st.write("### Generated Image:")
-                    with st.spinner('Generating image...'):
-                        image_prompt = generate_image_prompt(english_text)
-                        image_data = generate_image(image_prompt)
-                        if image_data:
-                            st.image(image_data, caption="Generated Image")
+    # Custom CSS for background, borders, and other styling
+    st.markdown(
+        """
+        <style>
+        body {
+            background-image: url('https://wallpapercave.com/wp/wp4008910.jpg');
+            background-size: cover;
+        }
+        .reportview-container {
+            background: rgba(255, 255, 255, 0.85);
+            padding: 2rem;
+            border-radius: 10px;
+            box-shadow: 0px 0px 20px rgba(0, 0, 0, 0.1);
+        }
+        .result-container {
+            border: 2px solid #4CAF50;
+            padding: 20px;
+            border-radius: 10px;
+            margin-top: 20px;
+            animation: fadeIn 2s ease;
+        }
+        @keyframes fadeIn {
+            0% { opacity: 0; }
+            100% { opacity: 1; }
+        }
+        .stButton button {
+            background-color: #4CAF50;
+            color: white;
+            border-radius: 10px;
+            padding: 10px;
+        }
+        .stButton button:hover {
+            background-color: #45a049;
+            transform: scale(1.05);
+            transition: 0.2s ease-in-out;
+        }
+        </style>
+        """, unsafe_allow_html=True
+    )
+
+    st.title("🅰️ℹ️ FusionMind ➡️ Multimodal")
+
+    # Sidebar for temperature, token adjustment, and model selection
+    st.sidebar.header("Settings")
+    temperature = st.sidebar.slider("Select Temperature", 0.1, 1.0, 0.7)
+    max_tokens = st.sidebar.slider("Max Tokens for Content Generation", 100, 400, 200)
+    
+    # Content generation model selection
+    content_model = st.sidebar.selectbox("Select Content Generation Model", list(content_models.keys()), index=0)
+
+    # Image generation model selection
+    image_model = st.sidebar.selectbox("Select Image Generation Model", list(image_generation_urls.keys()), index=0)
+
+    # Reminder about model availability
+    st.sidebar.warning("Note: Based on availability, some models might not work. Please try another model if an error occurs.")
+
+    # Suggested inputs
+    st.write("## Suggested Inputs")
+    suggestions = ["தரவு அறிவியல்", "புதிய திறன்களைக் கற்றுக்கொள்வது எப்படி", "ராக்கெட் எப்படி வேலை செய்கிறது"]
+    selected_suggestion = st.selectbox("Select a suggestion or enter your own:", [""] + suggestions)
+
+    # Input box for user
+    tamil_input = st.text_input("Enter Tamil text (or select a suggestion):", selected_suggestion)
+
+    if st.button("Generate"):
+        # Step 1: Translation (Tamil to English)
+        if tamil_input:
+            st.write("### Translated English Text:")
+            english_text = translate_text(tamil_input)
+            if english_text:
+                st.success(english_text)
+
+                # Step 2: Generate Educational Content
+                st.write("### Generated Educational Content:")
+                with st.spinner('Generating content...'):
+                    content_output = generate_content(english_text, max_tokens, temperature, content_models[content_model])
+                    if content_output:
+                        st.success(content_output)
+
+                # Step 3: Generate Image from the prompt
+                st.write("### Generated Image:")
+                with st.spinner('Generating image...'):
+                    image_prompt = generate_image_prompt(english_text)
+                    image_data = generate_image(image_prompt, image_generation_urls[image_model])
+                    if image_data:
+                        st.image(image_data, caption="Generated Image")
 
 if __name__ == "__main__":
     main()