erowid-bot/app
Jeff Emmett 08be7716f9 Aggressively optimize Ollama CPU inference speed
- Warm up both models on startup with keep_alive=24h (no cold starts)
- Use 16 threads for inference (server has 20 cores)
- Reduce context window to 1024 tokens, max output to 256
- Persistent httpx client for embedding calls (skip TCP handshake)
- Trim RAG chunks to 300 chars, history to 4 messages
- Shorter system prompt and context wrapper

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-17 01:12:04 -07:00
..
scraper Initial commit: Erowid conversational bot 2026-02-17 01:19:49 +00:00
static Initial commit: Erowid conversational bot 2026-02-17 01:19:49 +00:00
__init__.py Initial commit: Erowid conversational bot 2026-02-17 01:19:49 +00:00
config.py Speed up bot: use llama3.2:1b, reduce context, limit tokens 2026-02-16 19:44:04 -07:00
database.py Initial commit: Erowid conversational bot 2026-02-17 01:19:49 +00:00
embeddings.py Aggressively optimize Ollama CPU inference speed 2026-02-17 01:12:04 -07:00
llm.py Aggressively optimize Ollama CPU inference speed 2026-02-17 01:12:04 -07:00
main.py Aggressively optimize Ollama CPU inference speed 2026-02-17 01:12:04 -07:00
models.py Initial commit: Erowid conversational bot 2026-02-17 01:19:49 +00:00
rag.py Aggressively optimize Ollama CPU inference speed 2026-02-17 01:12:04 -07:00