Update app.py

app.py

@@ -1,35 +1,44 @@
 import gradio as gr
-from diffusers import StableDiffusionPipeline
-import torch
+import difflib
+import os
 
-# Load the stable diffusion model
-pipe = StableDiffusionPipeline.from_pretrained(
-    "CompVis/stable-diffusion-v1-4", 
-    revision="fp16", 
-    torch_dtype=torch.float16
-)
-pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+# A simple mapping of prompt keywords to image file names
+exercise_sets = {
+    "shoulder": "shoulder_mobility.png",
+    "neck": "neck_stretches.png",
+    "back": "back_mobility.png",
+    "full body": "full_body_mobility.png",
+    "warm up": "warmup_routine.png"
+}
 
-def generate_image(prompt):
-    image = pipe(prompt).images[0]
-    image.save("generated_exercise.png")  # Save image locally to return a downloadable version
-    return image, "generated_exercise.png"
+# Fuzzy matching prompt to known categories
+def match_prompt_to_exercise(prompt):
+    keywords = list(exercise_sets.keys())
+    closest = difflib.get_close_matches(prompt.lower(), keywords, n=1, cutoff=0.3)
+    if closest:
+        return exercise_sets[closest[0]]
+    else:
+        return None
 
-# Example prompts
-examples = [
-    ["Child to cobra pose yoga stretch"],
-    ["Cat to cow mobility exercise"],
-    ["Front scorpion leg raises"],
-    ["Wall-assisted hamstring stretch"]
-]
+# Main function
+def get_exercise_set(prompt):
+    matched_file = match_prompt_to_exercise(prompt)
+    if matched_file and os.path.exists(f"exercise_sets/{matched_file}"):
+        return f"exercise_sets/{matched_file}", f"exercise_sets/{matched_file}"
+    else:
+        return None, "Sorry, no matching set found. Try: 'shoulder', 'neck', 'warm up'"
 
-# Create a Gradio interface
+# Interface
 gr.Interface(
-    fn=generate_image,
-    inputs=gr.Textbox(lines=2, placeholder="Enter an exercise like 'child to cobra pose'"),
-    outputs=["image", gr.File(label="Download Image")],
-    title="AI Exercise Visual Generator",
-    description="Enter an exercise name. This tool will generate a visual representation using AI.",
-    examples=examples
+    fn=get_exercise_set,
+    inputs=gr.Textbox(label="Enter your goal (e.g., 'Shoulder mobility exercises')"),
+    outputs=[gr.Image(label="Generated Exercise Sheet"), gr.File(label="Download Image")],
+    title="🧘 AI Exercise Sheet Generator",
+    description="Type a goal like 'Neck stretches' or 'Warm-up routine' to get an illustrated exercise set.",
+    examples=[
+        ["Shoulder mobility exercises"],
+        ["Neck stretches"],
+        ["Warm-up before boxing"],
+        ["Full body mobility"]
+    ]
 ).launch()
-