Kevin Carter 36ae76143f Phase 3B: Implement pluggable LLM client for summary generation
- Create llm_client.py with 5 provider implementations (Anthropic, OpenAI, Ollama, OpenRouter, Google)
- Add build_prompt() helper to construct system/user prompts from templates
- Wire up POST /transcribe/sessions/{id}/summaries endpoint to call LLM client
- Return generated content + token counts (input_tokens, output_tokens)
- API keys passed per-request, never stored or logged
- Uses prompt templates from prompts.py based on summary_type
2026-05-20 22:20:19 +00:00
2025-11-14 14:47:19 +00:00
2026-02-23 20:58:35 +00:00
2025-11-19 20:02:34 +00:00
2025-11-19 20:02:34 +00:00
2025-11-19 20:02:34 +00:00
2025-11-19 20:02:34 +00:00
2026-02-23 20:58:35 +00:00
2025-11-19 20:02:34 +00:00
2025-07-11 13:52:19 +00:00
2025-11-14 14:47:19 +00:00
2025-11-14 14:47:19 +00:00
2025-11-14 14:47:19 +00:00
2025-11-14 14:47:19 +00:00
2025-11-14 14:47:19 +00:00
2025-11-14 14:47:19 +00:00
Description
FastAPI + Python 3.12 backend for Classroom Copilot — auth, document processing, transcription sessions, LLM integration, Supabase-backed
62 MiB
Languages
Python 98.9%
Shell 0.8%
Jupyter Notebook 0.3%