Commit Graph

7 Commits

Author SHA1 Message Date
Alexander Payne
f95c9606f1 fix: Timmy startup crashes and clean initialization
- Remove show_tool_calls kwarg (not in Agno 2.5.3), which crashed Agent.__init__
- Guard memory_search against top_k=None from model, return formatted string
- Skip Telegram/Discord startup silently when no token configured
- Replace placeholder MEMORY.md with proper structured hot memory document

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 09:11:48 -05:00
Alexander Payne
26e1691099 Fix Timmy coherence: persistent session, model-aware tools, response sanitization
Timmy was exhibiting severe incoherence (no memory between messages, tool call
leakage, chain-of-thought narration, random tool invocations) due to creating
a brand new agent per HTTP request and giving a 3B model (llama3.2) a 73-line
system prompt with complex tool-calling instructions it couldn't follow.

Key changes:
- Add session.py singleton with stable session_id for conversation continuity
- Add _model_supports_tools() to strip tools from small models (< 7B)
- Add two-tier prompts: lite (12 lines) for small models, full for capable ones
- Add response sanitizer to strip leaked JSON tool calls and CoT narration
- Set show_tool_calls=False to prevent raw tool JSON in output
- Wire ConversationManager for user name extraction
- Deprecate orphaned memory_layers.py (unused 4-layer system)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-25 19:18:08 -05:00
Alexander Payne
7838df19b0 Implement three-tier memory architecture (Hot/Vault/Handoff)
This commit replaces the previous memory_layers.py with a proper three-tier
memory system as specified by the user:

## Tier 1 — Hot Memory (MEMORY.md)
- Single flat file always loaded into system context
- Contains: current status, standing rules, agent roster, key decisions
- ~300 lines max, pruned monthly
- Managed by HotMemory class

## Tier 2 — Structured Vault (memory/)
- Directory with three namespaces:
  • self/ — identity.md, user_profile.md, methodology.md
  • notes/ — session logs, AARs, research
  • aar/ — post-task retrospectives
- Markdown format, Obsidian-compatible
- Append-only, date-stamped
- Managed by VaultMemory class

## Handoff Protocol
- last-session-handoff.md written at session end
- Contains: summary, key decisions, open items, next steps
- Auto-loaded at next session start
- Maintains continuity across resets

## Implementation

### New Files:
- src/timmy/memory_system.py — Core memory system
- MEMORY.md — Hot memory template
- memory/self/*.md — Identity, user profile, methodology

### Modified:
- src/timmy/agent.py — Integrated with memory system
  - create_timmy() injects memory context
  - TimmyWithMemory class with automatic fact extraction
- tests/test_agent.py — Updated for memory context

## Key Principles
- Hot memory = small and curated
- Vault = append-only, never delete
- Handoffs = continuity mechanism
- Flat files = human-readable, portable

## Usage

All 973 tests pass.
2026-02-25 18:17:43 -05:00
Alexander Payne
625806daf5 Fine-tune Timmy's conversational AI with memory layers
## Enhanced System Prompt
- Detailed tool usage guidelines with explicit examples
- Clear DO and DON'T examples for tool selection
- Memory system documentation
- Conversation flow guidelines
- Context awareness instructions

## Memory Layer System (NEW)
Implemented 3-layer memory architecture:

1. WORKING MEMORY (src/timmy/memory_layers.py)
   - Immediate context (last 20 messages)
   - Topic tracking
   - Tool call tracking
   - Fast, ephemeral

2. SHORT-TERM MEMORY (Agno SQLite)
   - Recent conversations (100)
   - Persists across restarts
   - Managed by Agno Agent

3. LONG-TERM MEMORY (src/timmy/memory_layers.py)
   - Facts about user (name, preferences)
   - SQLite storage in data/memory/
   - Auto-extraction from conversations
   - User profile generation

## Memory Manager (NEW)
- Central coordinator for all memory layers
- Context injection into prompts
- Fact extraction and storage
- Session management

## TimmyWithMemory Class (NEW)
- Wrapper around Agno Agent with explicit memory
- Auto-injects user context from LTM
- Tracks exchanges across all layers
- Simple chat() interface

## Agent Configuration
- Increased num_history_runs: 10 -> 20
- Better conversational context retention

## Tests
- All 973 tests pass
- Fixed test expectations for new config
- Fixed module path in test_scary_paths.py

## Files Added/Modified
- src/timmy/prompts.py - Enhanced with memory and tool guidance
- src/timmy/agent.py - Added TimmyWithMemory class
- src/timmy/memory_layers.py - NEW memory system
- src/timmy/conversation.py - NEW conversation manager
- tests/ - Updated for new config
2026-02-25 18:07:44 -05:00
Alexander Payne
29292cfb84 feat: single-command Docker startup, fix UI bugs, add Selenium tests
- Add `make up` / `make up DEV=1` for one-command Docker startup with
  optional hot-reload via docker-compose.dev.yml overlay
- Add `timmy up --dev` / `timmy down` CLI commands
- Fix cross-platform font resolution in creative assembler (7 test failures)
- Fix Ollama host URL not passed to Agno model (container connectivity)
- Fix task panel route shadowing by reordering literal routes before
  parameterized routes in swarm.py
- Fix chat input not clearing after send (hx-on::after-request)
- Fix chat scroll overflow (CSS min-height: 0 on flex children)
- Add Selenium UI smoke tests (17 tests, gated behind SELENIUM_UI=1)
- Install fonts-dejavu-core in Dockerfile for container font support
- Remove obsolete docker-compose version key
- Bump CSS cache-bust to v4

833 unit tests pass, 15 Selenium tests pass (2 skipped).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-25 07:20:56 -05:00
Claude
19af4ae540 feat: integrate AirLLM as optional high-performance backend
Adds the `bigbrain` optional dependency group (airllm>=2.9.0) and a
complete second inference path that runs 8B / 70B / 405B Llama models
locally via layer-by-layer loading — no GPU required, no cloud, fully
sovereign.

Key changes:
- src/timmy/backends.py   — TimmyAirLLMAgent (same print_response interface
                            as Agno Agent); auto-selects AirLLMMLX on Apple
                            Silicon, AutoModel (PyTorch) everywhere else
- src/timmy/agent.py      — _resolve_backend() routing with explicit override,
                            env-config, and 'auto' Apple-Silicon detection
- src/timmy/cli.py        — --backend / --model-size flags on all commands
- src/config.py           — timmy_model_backend + airllm_model_size settings
- src/timmy/prompts.py    — mentions AirLLM "even bigger brains, still fully
                            sovereign"
- pyproject.toml          — bigbrain optional dep; wheel includes updated
- .env.example            — TIMMY_MODEL_BACKEND + AIRLLM_MODEL_SIZE docs
- tests/conftest.py       — stubs 'airllm' module so tests run without GPU
- tests/test_backends.py  — 13 new tests covering helpers + TimmyAirLLMAgent
- tests/test_agent.py     — 7 new tests for backend routing
- README.md               — Big Brain section with one-line install
- activate_self_tdd.sh    — bootstrap script (venv + install + tests +
                            watchdog + dashboard); --big-brain flag

All 61 tests pass. Self-TDD watchdog unaffected.

https://claude.ai/code/session_01DMjQ5qMZ8iHeyix1j3GS7c
2026-02-21 16:53:16 +00:00
Claude
5e7d805245 feat: scaffold Timmy Time Mission Control (v1.0.0 Genesis)
- src/timmy/ — Agno agent wrapper (llama3.2 via Ollama, SQLite memory, TIMMY_SYSTEM_PROMPT)
- src/dashboard/ — FastAPI + HTMX + Jinja2 Mission Control UI
  - /health + /health/status (Ollama ping, HTMX 30s poll)
  - /agents list + /agents/timmy/chat (HTMX form submission)
- static/style.css — dark terminal mission-control aesthetic
- tests/ — 27 pytest tests (prompts, agent config, dashboard routes); no Ollama required
- pyproject.toml — hatchling build, pytest configured with pythonpath=src

https://claude.ai/code/session_01M4L3R98N5fgXFZRvV8X9b6
2026-02-19 19:05:01 +00:00