Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,34 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+from huggingface_hub import InferenceClient
+from PIL import Image
+import io
+
+# Streamlit UI setup
+st.set_page_config(page_title="Text-to-Image Generator", layout="centered")
+st.title("🖼️ Text to Image Generator")
+st.markdown("Enter a prompt and generate an image using the Flux model from Hugging Face.")
+
+# Input for the prompt
+prompt = st.text_input("Enter your prompt", "Astronaut riding a horse")
+
+# Generate button
+if st.button("Generate Image"):
+    with st.spinner("Generating... please wait"):
+        try:
+            # Initialize the Inference Client
+            client = InferenceClient(
+                provider="fal-ai",
+                api_key=st.secrets["TOGETHER_API_KEY"],  # Store your key in .streamlit/secrets.toml
+            )
+
+            # Generate image
+            image = client.text_to_image(
+                prompt,
+                model="black-forest-labs/FLUX.1-dev",
+            )
+
+            # Show image
+            st.image(image, caption=f"Generated Image for: {prompt}", use_column_width=True)
+
+        except Exception as e:
+            st.error(f"Error: {str(e)}")