8a4a2e25db
Mirrors the LLM treatment from #368 for the OpenAI STT and OpenAI TTS providers. Users running OpenAI-compatible self-hosted services (vLLM, Speaches, llama.cpp, custom proxies) can now point Dograh at them via the OpenAI provider with `base_url`, instead of being forced onto the Speaches provider as a workaround. Changes: * `registry.py` — add `base_url` field (default `https://api.openai.com/v1`) to `OpenAISTTConfiguration` and `OpenAITTSService`, identical in shape to the existing `OpenAILLMService.base_url` from #368. * `service_factory.py` — in the OPENAI branches of `create_stt_service` and `create_tts_service`, lift `base_url` off the user config, run it through `_validate_runtime_service_url`, and forward it as a kwarg to `OpenAISTTService` / `OpenAITTSService` (both already accept it). Same pattern as the LLM branch. * `test_user_configured_service_url_security.py` — adds four runtime validation tests covering private-IP rejection and localhost rejection in SaaS mode for both STT and TTS. Existing OSS-mode permissiveness is unchanged (DEPLOYMENT_MODE=oss skips the validator, as before). No schema migration needed — Pydantic populates the default; existing configurations without `base_url` continue to talk to api.openai.com. `check_validity.py` requires no edits because the per-service validation loop already iterates `("base_url", "endpoint")` via `getattr`, and the `_check_openai_api_key` dispatcher already routes OPENAI providers through the base_url-aware code path (introduced in #368) for STT and TTS too. Tests pass locally: pytest api/tests/test_user_configured_service_url_security.py 23 passed in 4.80s (19 existing + 4 new) Co-authored-by: developer603 <developer603@users.noreply.github.com> |
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| .agents/skills | ||
| .devcontainer | ||
| .github | ||
| .vscode | ||
| api | ||
| config/coturn | ||
| deploy/templates | ||
| docs | ||
| evals | ||
| examples | ||
| nginx | ||
| pipecat@228324a146 | ||
| scripts | ||
| sdk | ||
| ui | ||
| .dockerignore | ||
| .gitignore | ||
| .gitmodules | ||
| .nvmrc | ||
| .python-version | ||
| .release-please-manifest.json | ||
| AGENTS.md | ||
| CHANGELOG.md | ||
| CLAUDE.md | ||
| CONTRIBUTING.md | ||
| docker-compose-local.yaml | ||
| docker-compose.yaml | ||
| LICENSE | ||
| PRIVATE_DEPLOYMENT_PLAN.md | ||
| README.md | ||
| README.zh-CN.md | ||
| release-please-config.json | ||
| remote_up.sh | ||
| SECURITY.md | ||
Dograh AI
The open-source, self-hostable alternative to Vapi & Retell — build production voice agents with a drag-and-drop workflow builder. From zero to a working bot in under 2 minutes.
📖 Docs · 📜 BSD 2-Clause · 🌐 中文
- 100% open source, self-hostable — no vendor lock-in, unlike Vapi or Retell
- Full control & transparency — every line of code is open, with flexible LLM / TTS / STT integration
- Maintained by YC alumni and exit founders, committed to keeping voice AI open
🎥 Featured
Featured by Better Stack — a hands-on look at Dograh
📺 Prefer a 2-minute product walkthrough? Click here.
⚖️ Dograh vs Vapi vs Retell
An honest comparison on the axes that matter most to teams evaluating voice AI platforms.
| Dograh | Vapi | Retell | |
|---|---|---|---|
| License | BSD 2-Clause (open source) | Proprietary | Proprietary |
| Self-hostable | ✅ Yes — one Docker command | ❌ SaaS only | ❌ SaaS only |
| Pricing | Free (self-host) · usage-based (cloud) | Per-minute SaaS | Per-minute SaaS |
| Bring your own LLM / STT / TTS | ✅ Any provider, or use Dograh's stack | Configurable within their integrations | Configurable within their integrations |
| Source-level customization | ✅ Every line is yours to modify | ❌ Closed source | ❌ Closed source |
| Data residency | Your infra, your rules | Their cloud | Their cloud |
| Vendor lock-in | None | Full | Full |
🚀 Get Started
Download and setup Dograh on your Local Machine
Note
We collect anonymous usage data to improve the product. You can opt out by setting the
ENABLE_TELEMETRYtofalsein the below command.
Note
If you wish to run the platform on a remote server instead, checkout our Documentation
curl -o docker-compose.yaml https://raw.githubusercontent.com/dograh-hq/dograh/main/docker-compose.yaml && REGISTRY=ghcr.io/dograh-hq ENABLE_TELEMETRY=true docker compose up --pull always
Note
First startup may take 2-3 minutes to download all images. Once running, open http://localhost:3010 to create your first AI voice assistant! For common issues and solutions, see 🔧 Troubleshooting.
🎙️ Your First Voice Bot
- Open http://localhost:3010 in your browser.
- Pick Inbound or Outbound, name your bot (e.g. Lead Qualification), and describe the use case in 5–10 words (e.g. Screen insurance form submissions for purchase intent).
- Click Web Call — you're talking to your bot.
🔑 No API keys needed. Dograh ships with auto-generated keys and its own LLM / TTS / STT stack. Connect your own keys for LLM, TTS, STT, or Telephony (e.g. Twilio, Vonage, Telnyx) anytime.
Features
Voice Capabilities
- Telephony: Built-in telephony integration like Twilio, Vonage, Vobiz, Cloudonix (easily add others), with support for transferring calls to human agents
- Languages: English support (expandable to other languages)
- Custom Models: Bring your own TTS/STT models
- Real-time Processing: Low-latency voice interactions
Developer Experience
- Zero Config Start: Auto-generated API keys for instant testing
- Python-Based: Built on Python for easy customization
- Docker-First: Containerized for consistent deployments
- Modular Architecture: Swap components as needed
Testing & Quality
- Test Mode: Try your agent end-to-end before publishing, with no production calls or data affected
- In-Dashboard Web Calls: Talk to your bot directly while building — no telephony setup required
- QA Node: A built-in workflow node that analyzes prompt quality across your other nodes
Deployment Options
Local Development
Refer Local Setup
Self-Hosted Deployment
For detailed deployment instructions including remote server setup with HTTPS, see our Docker Deployment Guide.
Cloud Version
Visit https://www.dograh.com for our managed cloud offering.
📚Documentation
You can go to https://docs.dograh.com for our documentation.
📦 SDKs
- Python SDK — pypi.org/project/dograh-sdk
- Node SDK — npmjs.com/package/@dograh/sdk
🤝Community & Support
👋 Coming from the Better Stack video? Drop your use case in our pinned GitHub Discussion — we read every reply and the founders personally onboard early adopters.
- Slack — the cornerstone of Dograh AI contributions. Connect with maintainers, discuss features before coding, get help with setup, and stay current on contribution sprints.
- GitHub Discussions — share use cases, ask questions, swap workflow recipes.
- GitHub Issues — report bugs or request features.
👉 Join us → Dograh Community Slack
🙌 Contributing
We love contributions! Dograh AI is 100% open source and we intend to keep it that way.
Getting Started
- Fork the repository
- Create your feature branch (git checkout -b feature/AmazingFeature)
- Commit your changes (git commit -m 'Add some AmazingFeature')
- Push to the branch (git push origin feature/AmazingFeature)
- Open a Pull Request
⭐ Star History
📄 License
Dograh AI is licensed under the BSD 2-Clause License- the same license as projects that were used in building Dograh AI, ensuring compatibility and freedom to use, modify, and distribute.
🏢 About
Built with ❤️ by Dograh (Zansat Technologies Private Limited) Founded by YC alumni and exit founders committed to keeping voice AI open and accessible to everyone.