Drag and drop
Browse files- app.py +33 -1
- requirements.txt +1 -1
- templates/index.html +71 -2
app.py
CHANGED
@@ -12,13 +12,23 @@ import os, time, sys
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from datetime import datetime as dt
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from datetime import timedelta
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from datetime import timezone
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app = Flask(__name__)
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# Initialize Qdrant Client and other required settings
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qdrant_api_key = os.environ.get("qdrant_api_key")
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qdrant_url = os.environ.get("qdrant_url")
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client = QdrantClient(url=qdrant_url, port=443, api_key=qdrant_api_key, prefer_grpc=False)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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@@ -70,7 +80,7 @@ def search():
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else: results = client.search(collection_name=collection_name, query_vector=(qvector, sq), with_payload=True, limit=100)
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print('SEARCH TIME: ', time.time() - timh)
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-
print(results[0].payload['text'].split('\n'))
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try:
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results = [{"text": x.payload['text'], "date": str(int(x.payload['date'])), "id": x.id} for x in results] # Implement your Qdrant search here
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return jsonify(results)
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@@ -84,5 +94,27 @@ def delete_joke():
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client.delete(collection_name="jks", points_selector=models.PointIdsList(points=[int(joke_id)],),)
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return jsonify({"deleted": True})
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if __name__ == "__main__":
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app.run(host="0.0.0.0", debug=True, port=7860)
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from datetime import datetime as dt
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from datetime import timedelta
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from datetime import timezone
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from faster_whisper import WhisperModel
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import io
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app = Flask(__name__)
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# Faster Whisper setup
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# model_size = 'small'
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beamsize = 2
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wmodel = WhisperModel("guillaumekln/faster-whisper-small", device="cpu", compute_type="int8")
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# Initialize Qdrant Client and other required settings
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qdrant_api_key = os.environ.get("qdrant_api_key")
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qdrant_url = os.environ.get("qdrant_url")
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qdrant_api_key = "WaGH94-bo_CzlxTNHFjBAGPvWRhbsWEKUKbMz6YQtYt4oTD1ZXTvwg"
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qdrant_url = "https://c9bee7c7-2bf3-4e1b-8838-2f6f23372ab5.us-east-1-0.aws.cloud.qdrant.io"
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client = QdrantClient(url=qdrant_url, port=443, api_key=qdrant_api_key, prefer_grpc=False)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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else: results = client.search(collection_name=collection_name, query_vector=(qvector, sq), with_payload=True, limit=100)
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print('SEARCH TIME: ', time.time() - timh)
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# print(results[0].payload['text'].split('\n'))
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try:
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results = [{"text": x.payload['text'], "date": str(int(x.payload['date'])), "id": x.id} for x in results] # Implement your Qdrant search here
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return jsonify(results)
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client.delete(collection_name="jks", points_selector=models.PointIdsList(points=[int(joke_id)],),)
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return jsonify({"deleted": True})
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@app.route("/whisper_transcribe", methods=["POST"])
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def whisper_transcribe():
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if 'audio' not in request.files: return jsonify({'error': 'No file provided'}), 400
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audio_file = request.files['audio']
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allowed_extensions = {'mp3', 'wav', 'ogg', 'm4v'}
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if not (audio_file and audio_file.filename.lower().split('.')[-1] in allowed_extensions): return jsonify({'error': 'Invalid file format'}), 400
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print('Transcribing audio')
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audio_bytes = audio_file.read()
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audio_file = io.BytesIO(audio_bytes)
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segments, info = wmodel.transcribe(audio_file, beam_size=beamsize) # beamsize is 2.
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text = ''
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starttime = time.time()
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for segment in segments:
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text += segment.text
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print('Time to transcribe:', time.time() - starttime, 'seconds')
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return jsonify({'transcription': text})
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if __name__ == "__main__":
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app.run(host="0.0.0.0", debug=True, port=7860)
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requirements.txt
CHANGED
@@ -2,4 +2,4 @@ transformers
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torch
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qdrant-client
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flask
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-
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torch
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qdrant-client
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flask
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faster-whisper
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templates/index.html
CHANGED
@@ -30,7 +30,7 @@
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border: none;
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padding: 10px 20px;
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cursor: pointer;
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margin-left: 10px;
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}
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#results {
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@@ -51,6 +51,17 @@
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cursor: pointer;
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margin: 0 10px;
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}
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</style>
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</head>
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<body>
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@@ -60,6 +71,11 @@
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<button id="search">Search</button>
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</div>
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<div id="results"></div>
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<script>
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$(document).ready(function () {
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@@ -67,6 +83,7 @@
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var query = $("#query").val();
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$.post("/search", { query: query }, function (data) {
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var results = $("#results");
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results.empty();
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@@ -96,14 +113,66 @@
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});
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}
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$("#search").on("click", function () {
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performSearch();
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});
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$("#query").on("keydown", function (event) {
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if (event.key === "Enter") {
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event.preventDefault();
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performSearch();
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}
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});
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});
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border: none;
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padding: 10px 20px;
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cursor: pointer;
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margin-left: 10px;
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}
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#results {
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cursor: pointer;
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margin: 0 10px;
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}
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#drag-drop-container {
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border: 2px dashed #4c72af;
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padding: 20px;
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text-align: center;
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cursor: pointer;
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}
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.deleted-text {
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color: red;
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}
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</style>
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</head>
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<body>
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<button id="search">Search</button>
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</div>
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<div id="results"></div>
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<!-- Drag and drop area -->
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<div id="drag-drop-container">
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Drag & Drop Audio File (mp3, wav, ogg, m4v) Here
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</div>
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<script>
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$(document).ready(function () {
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var query = $("#query").val();
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$.post("/search", { query: query }, function (data) {
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// Handle search results
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var results = $("#results");
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results.empty();
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});
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}
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function displayTranscriptionResult(transcription) {
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// Display the transcription result
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var results = $("#results");
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results.empty();
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results.append("<div class='result'>" + "<p>" + transcription + "</p>" + "</div>");
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// Hide the "Transcribing..." message
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$("#drag-drop-container").text("Drag & Drop Audio File (mp3, wav, ogg, m4v) Here");
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$("#drag-drop-container").css("border-color", "#4c72af");
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}
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$("#search").on("click", function () {
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performSearch();
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$("#drag-drop-container").css("display", "none"); // Hide drag & drop area
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});
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$("#query").on("keydown", function (event) {
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if (event.key === "Enter") {
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event.preventDefault();
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performSearch();
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$("#drag-drop-container").css("display", "none"); // Hide drag & drop area
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}
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});
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// Drag and drop functionality
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$("#drag-drop-container").on("dragover", function (e) {
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e.preventDefault();
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$(this).css("border", "2px dashed #ff0000");
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});
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$("#drag-drop-container").on("dragleave", function (e) {
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e.preventDefault();
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$(this).css("border", "2px dashed #4c72af");
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});
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$("#drag-drop-container").on("drop", function (e) {
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e.preventDefault();
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$(this).css("border", "2px dashed #4c72af");
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var files = e.originalEvent.dataTransfer.files;
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if (files.length > 0) {
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// Display "Transcribing..." message
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$("#drag-drop-container").text("Transcribing the audio file...");
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$("#drag-drop-container").css("border-color", "#ccc");
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// Assume there's only one file for simplicity
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var file = files[0];
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var formData = new FormData();
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formData.append("audio", file);
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$.ajax({
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url: "/whisper_transcribe",
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type: "POST",
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data: formData,
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processData: false,
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contentType: false,
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success: function (data) {
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// Handle transcription result
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displayTranscriptionResult(data.transcription);
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},
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});
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}
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});
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});
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