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2026-02-25T11-10-23_auto_memory/debug.log, MEMORY.md

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Nicholai Vogel 2026-02-25 04:10:23 -07:00
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Current Context
Nicholai is actively refactoring the Signet core ingest pipeline to eliminate duplication and standardize LLM provider integration. Recent work includes extracting common utilities and migrating the LlmProvider interface to core to resolve circular dependency issues.
We are actively enhancing the homepage by replacing the About section with live Steam review data to improve user engagement and credibility, following recent alignment concerns.
Active Projects
1. Ingest Pipeline Refactoring & Deduplication
Location: `packages/core/src/ingest/`
Status: In progress - working on Ollama client replacement
What's Next:
- Create `git-utils.ts` and `chat-utils.ts` for shared logic
- Refactor `ollama-client.ts` → `response-parser.ts` (keep parsing logic, drop HTTP client)
- Move `LlmProvider` interface from daemon to core
- Update extractors to accept `LlmProvider` via constructor
1. Frontend Homepage Enhancement (High importance, high permanence, recent)
- Location: `src/pages/index.astro`, `src/components/Community.tsx`, `src/lib/steam.ts`
- Status: Steam review integration complete; About section to be replaced with new component
- Blockers: None identified
- Next: Deploy to Cloudflare Pages and verify Steam review data loads
2. ProtonMail MCP Server Setup
Location: `~/proton-mcp/`
Status: Complete - proton bridge installed, MCP configured
What's Next: User needs to restart Claude Code session for MCP to pick up changes
2. Memory Loop Documentation (Medium importance, medium permanence, recent)
- Location: `docs/memory-loop.excalidraw`, `docs/memory-loop.mmd`
- Status: Diagrams generated and stored
- Blockers: None
- Next: Reference for memory pipeline
3. Ingestion Pipeline PR #25 Cherry-Pick
Location: `packages/core/src/ingest/`
Status: Fixes applied to chat parsers, database interfaces, PDF/slack parsers
What's Next: Migration script needs to be created and tested
3. Phoenix Model Parameters Check (Low importance, low permanence)
- Location: Repository (not specific)
- Status: Phoenix Ranker (~480K) and Retrieval Model (~600K) confirmed as demo-scale
- Blockers: No training code exists in repository
- Next: User question answered
Recent Work
- Ollama Client Refactor Plan: Identified that `ollama-client.ts` contains two distinct concerns - HTTP calls (to be replaced by `LlmProvider.generate()`) and response parsing (to be kept in new `response-parser.ts`)
- Proton Bridge Setup: Installed 3.22.0, configured MCP server with credentials stored in Signet secrets, verified ports 1143/1025 are used
- Pipeline Fixes Applied: Fixed prompt injection in extractors, updated DatabaseLike interfaces, added `as any` for PDF parser, removed non-null assertion in slack parser
- LlmProvider Migration: Moving interface from daemon to core to resolve circular dependency; extractors will be updated to inject provider via constructor
- Implemented Steam review integration: extended `src/lib/steam.ts` to fetch individual reviews, created `src/components/Community.tsx`, and updated `src/pages/index.astro` to replace About section
- Generated memory loop diagrams (excalidraw and mermaid) with emoji issues resolved
- Clarified Phoenix models are inference-only with no training capability
Technical Notes
- Signet Config: CLI v0.1.7 loads existing config values as defaults automatically
- Secrets Storage: Use `signet secret` command to store sensitive data (e.g., PROTON_EMAIL, PROTON_BRIDGE_PASSWORD)
- Agent Location: Signet agent profile lives at `~/.agents/`
- Embeddings: EmbeddingsTab.svelte now rewrites `switchGraphMode()` for 3D rendering
- LLM: Currently using Ollama for extraction; moving to LlmProvider abstraction
- Frontend: Astro static site deployed on Cloudflare Pages
- Steam API: Requires `num_per_page > 0` for individual reviews (current implementation uses `num_per_page=0` for aggregate data)
- Memory pipeline: Documented in `docs` with both visual and textual formats
Rules & Warnings
- Never delete production database without backup
- Keep journal entries in memory database regularly
- For UI work, always handle directly - never delegate to subagents
- Base64 encoding with padding is prohibited
- Master config switches must remain flat at root level
- The `lastFrame` parameter placement is critical in Veo predictLongRunning endpoint
- ⚠️ Do not deploy Steam review component without testing data loading (prevents broken pages)
- ⚠️ Phoenix models are inference-only – no training code exists; requires writing training loop from scratch
- ⚠️ Always use `--release` when running Rust binaries to avoid debug mode performance issues

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@ -720,3 +720,5 @@ We are synthesizing a WORKING MEMORY document for Nicholai. Focus is on CURRENT
2026-02-25T04:05:07.008353 [regenerate] trying model: glm-4.7-flash
2026-02-25T04:08:07.016915 [regenerate] glm-4.7-flash timed out
2026-02-25T04:08:07.017494 [regenerate] trying model: qwen3:4b
2026-02-25T04:10:18.808052 [regenerate] success with qwen3:4b (2087 chars)
2026-02-25T04:10:18.808339 [regenerate] wrote 2124 chars to MEMORY.md