* feat: add Azure AI multi-provider support (TTS, STT, Embeddings, Realtime)
Enables Azure AI services across all model layers so users with Azure
credits can consolidate billing on a single provider.
- Voice (TTS): AzureSpeechTTSConfiguration via azure_speech provider
- Transcriber (STT): AzureSpeechSTTConfiguration via azure_speech provider
- Embedding: AzureOpenAIEmbeddingsConfiguration via azure provider
- Realtime: AzureRealtimeLLMConfiguration via azure_realtime provider
New files:
- api/services/pipecat/realtime/azure_realtime.py
- api/services/gen_ai/embedding/azure_openai_service.py
- api/tests/test_azure_speech_service_factory.py
The UI picks up all four providers automatically from the schema —
no frontend changes required.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: add validation for URL and params
---------
Co-authored-by: Vishal Dhateria <vishal@finela.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
* Add OpenAI-compatible API option in model configuration
Backend-only cherry-pick from 20617db37a.
* Potential fix for pull request finding
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
* fix: harden the base url settings in SaaS mode
---------
Co-authored-by: Chris Briddock <briddockchristopher@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
* feat: add MiniMax provider support (Chat + TTS)
- Add MiniMax LLM provider using OpenAI-compatible API
- Models: MiniMax-M2.7, MiniMax-M2.7-highspeed
- Default base URL: https://api.minimax.io/v1
- Uses MINIMAX_API_KEY for authentication
- Add MiniMax TTS provider using Pipecat's MiniMaxHttpTTSService
- Models: speech-2.8-hd (default), speech-2.8-turbo
- 6 built-in voices
- Requires group_id configuration
- Add unit tests for both providers
* fix(minimax): validator, temperature, session cleanup, reasoning filter
- check_validity.py: wire MiniMax into _validator_map and enforce
group_id at save time. Without this, saving a config with a valid
key was rejected.
- registry.py: surface temperature on the LLM config (gt=0; MiniMax
rejects 0) and base_url on the TTS config
- service_factory.py:
* Plumb temperature through create_llm_service
* Normalize TTS base_url to include /t2a_v2 — pipecat appends only
?GroupId=... to the URL.
* Use the new MiniMaxLLMService (from pipecat) to strip
<think>...</think> reasoning that MiniMax-M2.7 emits inline in
delta.content (otherwise it leaks straight to TTS).
* Use MiniMaxOwnedSessionTTSService so the per-instance aiohttp
session gets closed in cleanup() instead of leaking sockets/FDs.
- minimax_tts.py: small wrapper around MiniMaxHttpTTSService that owns
the session it was handed (pipecat's caller-owns-session API
conflicts with the ftory's per-instance pattern).
- pipecat submodule: bumps to a commit that adds MiniMaxLLMService — a
thin OpenAILLMService subclass with the streaming <think> filter
(mirrors NvidiaLLMService's pattern for NIM reasoning models).
- Tests updated/added for all of the above.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: octo-patch <octo-patch@github.com>
Co-authored-by: Sabiha Khan <sabihak89@gmail.com>