Switched to Flask app
Browse files- README.md +1 -1
- app.py +34 -61
- static/styles.css +0 -0
- templates/index.html +15 -0
- templates/results.html +19 -0
README.md
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@@ -3,7 +3,7 @@ title: Conceptt
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emoji: π
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colorFrom: green
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colorTo: red
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sdk:
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sdk_version: 1.43.2
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app_file: app.py
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pinned: false
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emoji: π
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colorFrom: green
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colorTo: red
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sdk: gradio
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sdk_version: 1.43.2
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app_file: app.py
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pinned: false
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app.py
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import
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import json
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from Vit_concept import run_inference, model
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from GP import genetic_programming
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input_output_pairs = []
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predicted_HLCs = []
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for sample in data.get("train", []): # or 'test'
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input_grid = sample["input"]
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output_grid = sample["output"]
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st.write("#### Input Grid:")
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st.text(input_grid)
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st.write("#### Output Grid:")
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st.text(output_grid)
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concept_label, _ = run_inference(model, input_grid, output_grid)
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st.write(f" Predicted Concept: `{concept_label}`")
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predicted_HLCs.append(concept_label)
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input_output_pairs.append((input_grid, output_grid))
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predicted_HLCs = list(set(predicted_HLCs))
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st.write("### Predicted High-Level Concepts:", predicted_HLCs)
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if st.button("Run Genetic Programming"):
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st.write("Running Genetic Programming... (this may take a few minutes)")
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best_program, generations = genetic_programming(
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input_output_pairs=input_output_pairs,
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population_size=300,
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generations=500,
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mutation_rate=0.2,
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crossover_rate=0.7,
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max_depth=3,
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predicted_HLCs=predicted_HLCs
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)
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st.success(" GP Completed!")
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st.write("### Best Program Found:")
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st.code(str(best_program))
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from flask import Flask, request, render_template, redirect, url_for
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import os
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import json
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from Vit_concept import run_inference, model
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from GP import genetic_programming
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app = Flask(__name__)
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UPLOAD_FOLDER = 'uploads'
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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@app.route('/')
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def index():
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return render_template('index.html')
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@app.route('/upload', methods=['POST'])
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def upload():
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if 'file' not in request.files:
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return "No file part"
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file = request.files['file']
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if file.filename == '':
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return "No selected file"
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filepath = os.path.join(UPLOAD_FOLDER, file.filename)
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file.save(filepath)
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with open(filepath, 'r') as f:
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data = json.load(f)
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input_output_pairs = []
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predicted_HLCs = []
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for sample in data.get("train", []):
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input_grid = sample["input"]
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output_grid = sample["output"]
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concept_label, _ = run_inference(model, input_grid, output_grid)
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predicted_HLCs.append(concept_label)
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input_output_pairs.append((input_grid, output_grid))
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predicted_HLCs = list(set(predicted_HLCs))
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best_program, generations = genetic_programming(
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input_output_pairs=input_output_pairs,
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population_size=300,
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generations=500,
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mutation_rate=0.2,
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crossover_rate=0.7,
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max_depth=3,
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predicted_HLCs=predicted_HLCs
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)
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return render_template("results.html", hlcs=predicted_HLCs, program=str(best_program))
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if __name__ == '__main__':
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app.run(host="0.0.0.0", port=7860)
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static/styles.css
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templates/index.html
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@@ -0,0 +1,15 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>ARC Task Solver</title>
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<link rel="stylesheet" href="/static/styles.css">
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</head>
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<body>
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<h1>Upload ARC Task File</h1>
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<form action="/upload" method="post" enctype="multipart/form-data">
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<input type="file" name="file" accept=".json" required>
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<button type="submit">Upload & Solve</button>
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</form>
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</body>
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</html>
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templates/results.html
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@@ -0,0 +1,19 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>Results</title>
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<link rel="stylesheet" href="/static/styles.css">
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</head>
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<body>
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<h1>Predicted Concepts</h1>
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<ul>
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{% for hlc in hlcs %}
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<li>{{ hlc }}</li>
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{% endfor %}
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</ul>
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<h2>Best Genetic Program</h2>
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<pre>{{ program }}</pre>
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</body>
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</html>
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