deepgram/deepgram-python-sdk

Official Python SDK for Deepgram.

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Summary Information

Updated 14 minutes ago
Added to GitGenius on July 9th, 2026
Created on May 12th, 2021
Open Issues & Pull Requests: 37 (+0)
Number of forks: 140
Total Stargazers: 456 (+0)
Total Subscribers: 9 (+0)

Issue Activity (beta)

Open issues: 27
New in 7 days: 7
Closed in 7 days: 0
Avg open age: 38 days
Stale 30+ days: 16
Stale 90+ days: 7

Recent activity

Opened in 7 days: 7
Closed in 7 days: 0
Comments in 7 days: 1
Events in 7 days: 6

Top labels

  • bug (28)
  • documentation (11)
  • question (11)
  • enhancement (9)
  • low priority (8)
  • help wanted (3)
  • high priority (2)
  • improvement (2)

Repository Insights (GitGenius)

Median issue/PR response: 23.9 hours
Mean response time: 51.1 days
90th percentile: 140.0 days
Tracked items: 119

Most active contributors

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "bug" is answered fastest, typically in about 2 days, while "question" waits about 3 weeks. Only 10% of issues opened in the past year have been closed. Three people close 85% of everything that gets resolved.

Detailed Description

The Deepgram Python SDK is the official Python library for integrating Deepgram's speech recognition, text-to-speech, and language understanding APIs into applications. Built with Fern and requiring Python 3.10 or higher, the SDK provides developers with access to world-class speech and language AI models through a well-documented interface available at developers.deepgram.com. The library is distributed via PyPI under the MIT License and includes comprehensive migration guides for users upgrading from earlier versions, with documented paths from v2 through v7.

The SDK supports multiple core use cases across Deepgram's product suite. For speech recognition, it offers both Listen v1 and the newer Listen v2 with contextual turn detection for real-time transcription, alongside file and URL-based transcription capabilities. Text-to-speech functionality enables natural-sounding speech generation from text input. The SDK also provides text analysis features for sentiment detection, topic identification, and intent recognition through the Read API, plus voice agent capabilities for building conversational AI applications. Additional management features include project administration, API key handling, and usage analytics access.

The SDK provides both synchronous and asynchronous clients, allowing developers to choose between blocking and non-blocking operation patterns. Authentication is flexible, supporting both access token and API key methods with automatic environment variable discovery through DEEPGRAM_TOKEN and DEEPGRAM_API_KEY variables. Advanced features include raw HTTP response access, configurable timeouts and retries with exponential backoff, custom HTTP client support, and a pluggable transport system that allows developers to replace the built-in websockets implementation with custom transports for alternative protocols or specialized deployments. The SageMaker transport package demonstrates this extensibility, enabling Deepgram models to run on AWS SageMaker endpoints using HTTP/2 bidirectional streaming while maintaining the standard SDK interface.

Development activity shows strong engagement from the maintainer community. The repository shares contributors with microsoft/vscode, apollographql/apollo-client, and pipecat-ai/pipecat, suggesting integration points and ecosystem connections within the broader developer community.

The SDK is primarily generated from Deepgram's API specifications, though contributions are welcomed through the documented CONTRIBUTING guide. Development setup uses Poetry for dependency management, with separate installation paths for core dependencies and example code. The project maintains a community code of conduct and provides detailed exception handling for debugging, custom request configuration options, and comprehensive API reference documentation covering all available methods, parameters, and WebSocket connection types.

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