Update app.py

app.py

@@ -8,6 +8,117 @@ GROQ_API_KEY = os.getenv('GROQ_API_KEY')
 
 # API Headers
 headers_hf = {"Authorization": f"Bearer {HUGGINGFACE_TOKEN}"}
-…
+headers_groq = {
+    "Authorization": f"Bearer {GROQ_API_KEY}",
+    "Content-Type": "application/json"
+}
+
+# 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"
+
+# Function to query Hugging Face translation model
+def translate_text(text):
+    payload = {"inputs": text}
+    response = requests.post(translation_url, headers=headers_hf, json=payload)
+    if response.status_code == 200:
+        result = response.json()
+        translated_text = result[0]['generated_text']
+        return translated_text
+    else:
+        st.error(f"Translation Error {response.status_code}: {response.text}")
+        return None
+
+# Function to query Groq content generation model
+def generate_content(english_text, max_tokens, temperature):
+    url = "https://api.groq.com/openai/v1/chat/completions"
+    payload = {
+        "model": "llama-3.1-70b-versatile",
+        "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."}
+        ],
+        "max_tokens": max_tokens,
+        "temperature": temperature
+    }
+    response = requests.post(url, json=payload, headers=headers_groq)
+    if response.status_code == 200:
+        result = response.json()
+        return result['choices'][0]['message']['content']
+    else:
+        st.error(f"Content Generation Error: {response.status_code}")
+        return None
+
+# Function to generate image prompt
+def generate_image_prompt(english_text):
+    payload = {
+        "model": "mixtral-8x7b-32768",
+        "messages": [
+            {"role": "system", "content": "You are a professional Text to image prompt generator."},
+            {"role": "user", "content": f"Create a text to image generation prompt about {english_text} within 30 tokens."}
+        ],
+        "max_tokens": 30
+    }
+    response = requests.post("https://api.groq.com/openai/v1/chat/completions", json=payload, headers=headers_groq)
+    if response.status_code == 200:
+        result = response.json()
+        return result['choices'][0]['message']['content']
+    else:
+        st.error(f"Prompt Generation Error: {response.status_code}")
+        return None
+
+# Function to generate an image from the prompt
+def generate_image(image_prompt):
+    data = {"inputs": image_prompt}
+    response = requests.post(image_generation_url, headers=headers_hf, json=data)
+    if response.status_code == 200:
+        return response.content
+    else:
+        st.error(f"Image Generation Error {response.status_code}: {response.text}")
+        return None
+
+# Main Streamlit app
+def main():
+    st.title("Multimodal Generator")
+
+    # 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, 300, 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")
+
 if __name__ == "__main__":
     main()
+