Update index.html

index.html

@@ -1,48 +1,17 @@
-<script>
-  const HF_TOKEN = "YOUR_HUGGING_FACE_TOKEN"; // Replace with your token
-
-  async function generateImage() {
-    const prompt = document.getElementById("prompt").value;
-    const imageContainer = document.getElementById("image");
-    
-    if (!prompt) {
-      imageContainer.innerHTML = "Please enter a prompt.";
-      return;
-    }
-
-    imageContainer.innerHTML = "Generating...";
-
-    try {
-      // Generate a RANDOM SEED (0 to 1,000,000)
-      const randomSeed = Math.floor(Math.random() * 1000000);
-
-      // Add parameters for randomness
-      const response = await fetch(
-        "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5",
-        {
-          method: "POST",
-          headers: {
-            "Authorization": `Bearer ${HF_TOKEN}`,
-            "Content-Type": "application/json",
-          },
-          body: JSON.stringify({
-            inputs: prompt,
-            parameters: {
-              seed: randomSeed,       // Random seed for variation
-              guidance_scale: 7.5,   // Controls creativity (7-15)
-              num_inference_steps: 50 // More steps = more details (20-100)
-            }
-          }),
-        }
-      );
-
-      if (!response.ok) throw new Error("API error: " + response.status);
-
-      const imageBlob = await response.blob();
-      const imageUrl = URL.createObjectURL(imageBlob);
-      imageContainer.innerHTML = `<img src="${imageUrl}" style="max-width:100%;">`;
-    } catch (error) {
-      imageContainer.innerHTML = "Error: " + error.message;
-    }
-  }
-</script>
+import streamlit as st
+from diffusers import StableDiffusionPipeline
+import torch
+
+# Load the model
+model_id = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionPipeline.from_pretrained(model_id)
+pipe = pipe.to("cuda")  # Runs on Hugging Face's GPU servers
+
+# Streamlit UI
+st.title("Free AI Image Generator")
+prompt = st.text_input("Describe your image...")
+
+if prompt:
+    with st.spinner("Generating..."):
+        image = pipe(prompt).images[0]
+        st.image(image, caption=prompt, use_column_width=True)