AudioSummaryConverter
Generate concise summaries from audio recordings by transcribing speech and synthesizing key points. Supports meeting minutes, podcast summaries, and interview highlights with configurable length and format.
How It Works
Upload an audio file or provide a URL.
The audio is transcribed with speaker diarization.
Key topics, decisions, and action items are identified.
An LLM produces a structured summary from the transcript.
The summary is returned in your chosen format.
Code Examples
import os, requests
API = "https://api.mixpeek.com"
H = {"Authorization": f"Bearer {os.environ['MIXPEEK_API_KEY']}",
"X-Namespace": os.environ["NAMESPACE_ID"]}
# 1. a bucket, with a schema that declares the field you will send
bucket = requests.post(f"{API}/v1/buckets", headers=H, json={
"bucket_name": "audio-inputs",
"bucket_schema": {"properties": {"audio": {"type": "audio"}}},
}).json()
# 2. land the file as an object. the URL goes in data, on the blob
requests.post(f"{API}/v1/buckets/{bucket['bucket_id']}/objects", headers=H, json={
"key_prefix": "run-1",
"blobs": [{"property": "audio", "type": "audio",
"data": "https://example.com/call.mp3"}],
})
# 3. a collection over that bucket, running the extractor
collection = requests.post(f"{API}/v1/collections", headers=H, json={
"collection_name": "audio-to-summary",
"source": {"type": "bucket", "bucket_ids": [bucket["bucket_id"]]},
"feature_extractor": {"feature_extractor_name": "multimodal_extractor", "version": "v1"},
}).json()
# 4. run extraction over the bucket
requests.post(f"{API}/v1/buckets/{bucket['bucket_id']}/batches", headers=H, json={
"collection_ids": [collection["collection_id"]],
"auto_submit": True,
})
# 5. read the output
docs = requests.get(
f"{API}/v1/collections/{collection['collection_id']}/documents", headers=H
).json()
print(docs)Use Cases
Supported Input Formats
Quick Info
Run it over a library
Mixpeek runs this conversion as a pipeline over a whole library in your object storage, with the output landing as queryable documents. It is not a single-file converter.
Frequently Asked Questions
Related Converters
Video to Summary
Produce concise written summaries of video content by combining transcript analysis, scene understanding, and key moment detection. Summaries can be formatted as paragraphs, bullet points, or structured chapters.
Audio to Text
Transcribe audio files into text with high accuracy. Supports speaker diarization, punctuation restoration, timestamps, and over 50 languages. Handles podcasts, calls, meetings, and broadcast audio.
PDF to Text
Extract clean, structured text from PDF documents including scanned pages, multi-column layouts, headers/footers, and tables. Combines traditional parsing with OCR and layout analysis for maximum accuracy.
Ready to convert audio to summary?
Start using the Mixpeek Audio to Summary in minutes. Sign up for a free API key and follow the documentation to get started.