* serverless: implement banana backend for both audio and LLM
Related to monadical-sas/reflector-gpu-banana project
* serverless: got llm working on banana !
* tests: fixes
* serverless: fix dockerfile to use fastapi server + httpx
Each processor is standalone, with define INPUT/OUTPUT.
Processor can be threaded or not (can be extensible later)
TODO: Pipeline that automatically connect all processors, flush and clean data
To test: python -m reflector.processors tests/records/test_mathieu_hello.wav
```
Transcript: [00:00.500]: Hi there, everyone.
Transcript: [00:02.700]: Today, I want to share my incredible experience.
Transcript: [00:05.461]: with Reflector, a cutineage product that revolutionizes audio processing.
Transcript: [00:10.922]: With Refector, I can easily convert any audio into accurate transcription.
Transcript: [00:16.493]: serving me hours of tedious manual work.
```
This is not a good transcript, but not the purpose here.
- replaced loguru to structlog, to get ability of having open tracing later
- moved configuration to pydantic-settings
- merged both secrets.ini and config.ini to .env (check reflector/settings.py)
