37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
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import os
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from flask import Flask, request, jsonify
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from openai import OpenAI
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app = Flask(__name__)
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client = OpenAI() # reads OPENAI_API_KEY from env
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def transcribe_with_timestamps(local_path: str):
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# Use whisper-1 for verbose_json + timestamp_granularities (segment/word)
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# timestamp_granularities requires response_format="verbose_json" :contentReference[oaicite:1]{index=1}
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with open(local_path, "rb") as f:
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tr = client.audio.transcriptions.create(
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model="whisper-1",
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file=f,
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response_format="verbose_json",
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timestamp_granularities=["segment"],
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)
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segments = []
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for seg in tr.segments:
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segments.append({
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"start_ms": int(seg["start"] * 1000),
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"end_ms": int(seg["end"] * 1000),
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"text": seg["text"].strip(),
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})
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return segments
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@app.post("/upload-audio")
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def upload_audio():
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file = request.files["file"]
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local_path = f"/tmp/{file.filename}"
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file.save(local_path)
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segments = transcribe_with_timestamps(local_path)
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# TODO: insert `segments` into transcript_segments table
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return jsonify({"segments": segments})
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