Update app.py

app.py

@@ -6,41 +6,86 @@ import matplotlib.pyplot as plt
 import numpy as np
 from io import BytesIO
 
-# Styles
-st.markdown(
-    """
-    <link href="https://fonts.googleapis.com/css2?family=Roboto:wght@300&display=swap" rel="stylesheet">
-    <style>
-    body {
-        font-family: 'Roboto', sans-serif;
-    }
-    .sidebar .sidebar-content {
-        background-color: #f0f0f5; /* Light gray */
-    }
-    .stButton > button {
-        background-color: #4CAF50; /* Green */
-        color: white;
-        border: none;
-        padding: 10px 20px;
-        font-size: 16px;
-        margin: 4px 2px;
-        cursor: pointer;
-    }
-    .stTextArea > textarea {
-        border-radius: 10px;
-        border: 2px solid #4CAF50; /* Green */
-        padding: 10px;
-        font-size: 16px;
-    }
-    .stImage {
-        border: 2px solid #4CAF50; /* Green */
-        border-radius: 10px;
+# Hugging Face API URLs and token
+TRANSLATE_API_URL = "https://api-inference.huggingface.co/models/facebook/mbart-large-50-many-to-one-mmt"
+IMAGE_API_URL = "https://api-inference.huggingface.co/models/CompVis/stable-diffusion-v1-4"
+HUGGINGFACE_TOKEN = "YOUR_HUGGINGFACE_TOKEN"  # Replace with your actual token
+headers = {"Authorization": f"Bearer {HUGGINGFACE_TOKEN}"}
+
+# Function to translate Tamil to English
+def translate_tamil_to_english(text):
+    payload = {"inputs": text}
+    response = requests.post(TRANSLATE_API_URL, headers=headers, json=payload)
+    if response.status_code == 200:
+        result = response.json()
+        return result[0]['generated_text']
+    else:
+        return f"Error {response.status_code}: {response.text}"
+
+# Function to generate an image from a prompt
+def generate_image(prompt):
+    data = {"inputs": prompt}
+    response = requests.post(IMAGE_API_URL, headers=headers, json=data)
+    if response.status_code == 200:
+        image = Image.open(BytesIO(response.content))
+        return image
+    else:
+        return f"Error {response.status_code}: {response.text}"
+
+# Function to generate text using Groq
+def generate_text(prompt, max_tokens, temperature):
+    messages = [{"role": "user", "content": prompt}]
+    payload = {
+        "model": "mixtral-8x7b-32768",
+        "messages": messages,
+        "max_tokens": max_tokens,
+        "temperature": temperature,
     }
-    </style>
-    """,
-    unsafe_allow_html=True,
-)
+    response = requests.post("https://api.groq.com/openai/v1/chat/completions", headers={"Authorization": "Bearer YOUR_GROQ_TOKEN"}, json=payload)
+    if response.status_code == 200:
+        result = response.json()
+        return result["choices"][0]["message"]["content"]
+    else:
+        return f"Error {response.status_code}: {response.text}"
 
-# Rest of your app code
+# Process input data
+def process_input(tamil_text, max_tokens, temperature):
+    english_text = translate_tamil_to_english(tamil_text)
+    image = generate_image(english_text)
+    generated_story = generate_text(english_text, max_tokens, temperature)
+    return english_text, image, generated_story
+
+# Streamlit UI
 st.markdown("<h1 style='text-align: center;'>Tamil to English Translation and Story Generation App</h1>", unsafe_allow_html=True)
-# Sidebar, input fields, and functionality continue as before...
+
+st.sidebar.header("Settings")
+tamil_text_input = st.sidebar.text_area("Enter Tamil Text")
+max_tokens_input = st.sidebar.slider("Max Tokens", min_value=50, max_value=200, value=100, step=10)
+temperature_input = st.sidebar.slider("Temperature", min_value=0.0, max_value=1.0, value=0.7, step=0.1)
+
+if st.sidebar.button("Submit"):
+    english_text, image, generated_story = process_input(tamil_text_input, max_tokens_input, temperature_input)
+
+    st.subheader("Translated English Text")
+    st.write(english_text)
+
+    st.subheader("Generated Image")
+    if isinstance(image, Image.Image):
+        plt.imshow(np.array(image))
+        plt.axis('off')
+        st.pyplot(plt)
+    else:
+        st.error(image)
+
+    st.subheader("Generated Story")
+    st.write(generated_story)
+
+# Guide section
+if st.sidebar.button("How to Use"):
+    st.sidebar.write("""
+    ### How to Use This App
+    1. **Enter Tamil Text**: Type or paste the Tamil text you want to translate.
+    2. **Adjust Settings**: Use the sliders to set the maximum tokens for text generation and the temperature for creativity.
+    3. **Submit**: Click the Submit button to generate translations, images, and stories.
+    4. **View Results**: Check the translated text, generated image, and story in the main area.
+    """)