aws-deepgram-sagemaker

Automation scripts for testing Deepgram services running on Amazon SageMaker as an "Endpoint" resource.

Speech-to-Text (STT)

JavaScript

See js-stt/README.md for setup and usage. Built on the AWS SDK HTTP/2 bidirectional streaming client (@aws-sdk/client-sagemaker-runtime-http2); configuration (region, endpoint name, input file, query string) is edited inline at the top of each script.

Scripts:

• stt.file.ts — streams a WAV file to a bidirectional streaming endpoint, chunking the file with keepalives
• stt.microphone.ts — captures live microphone input and streams it to a bidirectional streaming endpoint
• stress-stt.ts — fires N parallel stt.file.ts invocations and reports success/failure counts and timing

Python

See python-stt/README.md for full setup and usage.

Scripts:

• stt_microphone_stress.py — streams live microphone audio; supports multiple simultaneous connections
• stt_wav_stress.py stream — streams a WAV file at real-time pace; repeatable load testing without a microphone
• stt_wav_stress.py batch — posts WAV files via HTTP with configurable concurrency; reports latency and throughput
• stt_wav_async.py — transcribes a WAV file (up to 1 GiB) via the SageMaker InvokeEndpointAsync API with S3 input/output; suits long-form audio beyond the synchronous invoke limit, with configurable concurrency and a latency/throughput summary

End-to-end correctness gates (python-stt/e2e/) — wrap the stress scripts and score each connection's transcript against a known reference (spacewalk.wav) via Word Error Rate; intended as the promotion gate before an endpoint goes live:

• e2e/e2e_test_streaming.py — drives stt_wav_stress.py stream through ~10 scenarios (basic short/long-form, sustained + ramped concurrency, the major feature flags, an adversarial WebSocket-close path) and checks each connection's combined final transcript by WER
• e2e/e2e_test_batch.py — --mode sync (25 s sample via invoke_endpoint, ≤ 25 MB) or --mode async (~15 min / ~76 MB via invoke_endpoint_async + S3, incl. summarize); validates every returned transcript by WER

Java

See java/README.md for an index of Java projects.

• java/stt/aws-sdk — WAV streaming load test built directly on AWS SDK v2 HTTP/2 bidi streaming
• java/stt/deepgram-sdk — same load test, via the Deepgram Java SDK + SageMaker transport

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Text-to-Speech (TTS)

JavaScript

TBD

Python

See python-tts/README.md for full setup and usage.

Scripts:

• tts_stress.py — streams text phrases to multiple simultaneous bidirectional connections; plays audio from one selectable connection

End-to-end correctness gates (python-tts/e2e/) — validate the synthesized audio itself (non-empty, correct container/codec, non-silent, requested sample rate, speed→duration), so no second transcription endpoint is required:

• e2e/e2e_test_batch.py — synchronous invoke_endpoint against /v1/speak; carries the full parameter matrix (model/encoding/sample_rate/bit_rate/container/speed, inline IPA override, 2000-char limit)
• e2e/e2e_test_streaming.py — websocket /v1/speak; the streaming-only behaviors (Speak→audio, Flush→Flushed, sustained concurrency, streaming encodings, voice/speed)

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Flux (Conversational STT)

Python

See python-flux/README.md for full setup and usage.

Scripts:

• flux_stress.py file — streams a WAV file to multiple Flux connections at real-time pace
• flux_stress.py microphone — streams live microphone audio to multiple Flux connections
• flux_stress.py list-endpoints — lists available SageMaker endpoints in the target region

End-to-end correctness gate (python-flux/e2e/) — Flux is streaming-only (/v2/listen), so a single driver covers it:

• e2e/e2e_test_streaming.py — drives flux_stress.py file through basic / concurrency / connection-param / multilingual / in-band-control / negative scenarios, scoring each connection's combined EndOfTurn transcript against the reference by WER