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Merge pull request #22 from software-students-fall2023/KeiEditsTwo
Kei edits two
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,38 +1,64 @@ | ||
| from flask import Flask, render_template, request, jsonify | ||
| """ | ||
| app.py file that helps serve as the front end of our application | ||
| """ | ||
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| import os | ||
| import subprocess | ||
| from flask import Flask, render_template, request, jsonify | ||
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| app = Flask("project4") | ||
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| app = Flask('project4') | ||
| app.config["UPLOAD_FOLDER"] = "uploads" | ||
| os.makedirs(app.config["UPLOAD_FOLDER"], exist_ok=True) | ||
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| app.config['UPLOAD_FOLDER'] = 'uploads' | ||
| os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True) | ||
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| @app.route('/') | ||
| def RootPage(): | ||
| return render_template('root.html') | ||
| @app.route("/") | ||
| def root_page(): | ||
| """ | ||
| template to render root page | ||
| """ | ||
| return render_template("root.html") | ||
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| @app.route('/analyzeData', methods=['POST']) | ||
| def analyzeData(): | ||
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| @app.route("/analyzeData", methods=["POST"]) | ||
| def analyze_data(): | ||
| """ | ||
| Function to send genreated audio file to the machine learning client | ||
| """ | ||
| try: | ||
| if 'audio' not in request.files: | ||
| if "audio" not in request.files: | ||
| return jsonify({"status": "error", "message": "No audio file provided"}) | ||
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| audio_file = request.files['audio'] | ||
| audio_path = os.path.join(app.config['UPLOAD_FOLDER'], 'user_audio.wav') | ||
| audio_file = request.files["audio"] | ||
| audio_path = os.path.join(app.config["UPLOAD_FOLDER"], "user_audio.wav") | ||
| audio_file.save(audio_path) | ||
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| print("Audio file saved at:", audio_path) | ||
| result = subprocess.run(["C:\\Users\\Andrew - User\\AppData\\Local\\Microsoft\\WindowsApps\\python.exe", "E:\\4-containerized-app-exercise-rizzballs\\machine-learning-client\\machine_learning_client.py", audio_path], capture_output=True, text=True) | ||
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| print("Audio file saved at:", audio_path) | ||
| result = subprocess.run( | ||
| [ | ||
| "C:\\Users\\Andrew - User\\AppData\\Local\\Microsoft\\WindowsApps\\python.exe", | ||
| "E:\\4-containerized-app-exercise-rizzballs\\machine-learning-client\\machine_learning_client.py", # pylint: disable=line-too-long | ||
| audio_path, # pylint: disable=line-too-long disable=trailing-whitespace | ||
| ], | ||
| capture_output=True, | ||
| text=True, | ||
| check=True, | ||
| ) | ||
| if result.returncode == 0: | ||
| print("Process succeeded!") | ||
| else: | ||
| print("Process failed. Exit code:", result.returncode) | ||
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| return jsonify({"status": "success"}) | ||
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| except Exception as e: | ||
| return jsonify({"status": "error", "message": str(e)}) | ||
| except FileNotFoundError as e: | ||
| return jsonify({"status": "error", "message": f"File not found: {str(e)}"}) | ||
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| except subprocess.CalledProcessError as e: | ||
| return jsonify({"status": "error", "message": f"Subprocess failed: {str(e)}"}) | ||
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| if __name__ == "__main__": | ||
| PORT = os.getenv('PORT', 5000) | ||
| PORT = os.getenv("PORT", "5000") | ||
| app.run(debug=True, port=PORT) | ||
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|