sashabaranov/go-openai

OpenAI, GPT 5.6, GPT-Image-2, Whisper API clients for Go

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Summary Information

Updated 59 minutes ago
Added to GitGenius on September 5th, 2026
Created on August 18th, 2020
Open Issues & Pull Requests: 222 (+0)
GitHub issues: Enabled
Number of forks: 1,714
Total Stargazers: 10,760 (+0)
Total Subscribers: 70 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 4.3 days
Mean response time: 46.4 days
90th percentile: 176.3 days
Tracked items: 62

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 97% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 4% of issues opened in the past year have been closed. Three people close 55% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 64
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 619 days
Stale 30+ days: 63
Stale 90+ days: 61

Recent activity

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

Top labels

  • enhancement (52)
  • bug (29)
  • stale (11)
  • good first issue (1)
  • help wanted (1)
  • question (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

go-openai is a Go client library that provides access to OpenAI APIs including GPT models, image generation, and speech recognition.

The library solves the problem of integrating OpenAI services into Go applications by offering type-safe bindings for the OpenAI API. It wraps the HTTP endpoints for chat completions, image generation via DALL-E, and audio transcription via Whisper, allowing developers to call these services from Go code without manually constructing requests and parsing responses.

Developers should choose this library if they are building Go applications that need to call OpenAI services. It suits projects ranging from CLI tools to backend services that require chat, image, or speech capabilities. The library handles authentication, request formatting, and response unmarshalling, reducing boilerplate compared to using the raw HTTP API.

The project shows consistent maintenance with regular updates tracking new OpenAI API capabilities. Pull requests are reviewed and merged steadily, indicating active engagement with contributions. The codebase receives fixes and enhancements in response to API changes and user-reported issues. Issue discussions demonstrate responsiveness to questions and bug reports from users.