Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,51 @@
-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])),
-    ))
+import requests
+import io
+from PIL import Image
+import os
+
+# Load Hugging Face token from environment
+hf_token = os.environ.get("hf_token")
+
+# API URLs for different models
+API_URL_KVI = "https://api-inference.huggingface.co/models/Kvikontent/kviImageR2.0"
+API_URL_MJ = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v6"
+API_URL_DALLE = "https://api-inference.huggingface.co/models/ehristoforu/dalle-3-xl"
+
+# Headers with Hugging Face token
+headers = {"Authorization": f"Bearer {hf_token}"}
+
+# Function to query Hugging Face API
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.content
+
+# Streamlit UI
+st.title("Text To Image models")
+st.write("Choose model and enter a prompt")
+
+model = st.selectbox(
+    "Choose model",
+    ("KVIImageR2.0", "Midjourney V6", "Dalle 3")
+)
+
+prompt = st.text_input("Enter prompt")
+
+# Generate Image
+if prompt:
+    if model == "KVIImageR2.0":
+        API_URL = API_URL_KVI
+    elif model == "Midjourney V6":
+        API_URL = API_URL_MJ
+    elif model == "Dalle 3":
+        API_URL = API_URL_DALLE
+
+    image_bytes = query({"inputs": prompt})
+
+    try:
+        image = Image.open(io.BytesIO(image_bytes))
+        st.image(image, caption="Generated Image")
+        st.info("Image generated successfully!")
+    except Exception as e:
+        st.error("Failed to generate image. Please try again.")
+        st.text(str(e))