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Author SHA1 Message Date
Alexander Whitestone
c58093dccc WIP: Claude Code progress on #1285
Automated salvage commit — agent session ended (exit 124).
Work in progress, may need continuation.
2026-03-23 22:02:09 -04:00
55beaf241f [claude] Research summary: Kimi creative blueprint (#891) (#1286) 2026-03-24 01:46:28 +00:00
69498c9add [claude] Screenshot dump triage — 5 issues created (#1275) (#1287) 2026-03-24 01:46:22 +00:00
13 changed files with 429 additions and 28 deletions

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@@ -18,9 +18,17 @@ jobs:
- name: Lint (ruff via tox) - name: Lint (ruff via tox)
run: tox -e lint run: tox -e lint
test: typecheck:
runs-on: ubuntu-latest runs-on: ubuntu-latest
needs: lint needs: lint
steps:
- uses: actions/checkout@v4
- name: Type-check (mypy via tox)
run: tox -e typecheck
test:
runs-on: ubuntu-latest
needs: typecheck
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- name: Run tests (via tox) - name: Run tests (via tox)

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@@ -0,0 +1,89 @@
# Screenshot Dump Triage — Visual Inspiration & Research Leads
**Date:** March 24, 2026
**Source:** Issue #1275 — "Screenshot dump for triage #1"
**Analyst:** Claude (Sonnet 4.6)
---
## Screenshots Ingested
| File | Subject | Action |
|------|---------|--------|
| IMG_6187.jpeg | AirLLM / Apple Silicon local LLM requirements | → Issue #1284 |
| IMG_6125.jpeg | vLLM backend for agentic workloads | → Issue #1281 |
| IMG_6124.jpeg | DeerFlow autonomous research pipeline | → Issue #1283 |
| IMG_6123.jpeg | "Vibe Coder vs Normal Developer" meme | → Issue #1285 |
| IMG_6410.jpeg | SearXNG + Crawl4AI self-hosted search MCP | → Issue #1282 |
---
## Tickets Created
### #1281 — feat: add vLLM as alternative inference backend
**Source:** IMG_6125 (vLLM for agentic workloads)
vLLM's continuous batching makes it 310x more throughput-efficient than Ollama for multi-agent
request patterns. Implement `VllmBackend` in `infrastructure/llm_router/` as a selectable
backend (`TIMMY_LLM_BACKEND=vllm`) with graceful fallback to Ollama.
**Priority:** Medium — impactful for research pipeline performance once #972 is in use
---
### #1282 — feat: integrate SearXNG + Crawl4AI as self-hosted search backend
**Source:** IMG_6410 (luxiaolei/searxng-crawl4ai-mcp)
Self-hosted search via SearXNG + Crawl4AI removes the hard dependency on paid search APIs
(Brave, Tavily). Add both as Docker Compose services, implement `web_search()` and
`scrape_url()` tools in `timmy/tools/`, and register them with the research agent.
**Priority:** High — unblocks fully local/private operation of research agents
---
### #1283 — research: evaluate DeerFlow as autonomous research orchestration layer
**Source:** IMG_6124 (deer-flow Docker setup)
DeerFlow is ByteDance's open-source autonomous research pipeline framework. Before investing
further in Timmy's custom orchestrator (#972), evaluate whether DeerFlow's architecture offers
integration value or design patterns worth borrowing.
**Priority:** Medium — research first, implementation follows if go/no-go is positive
---
### #1284 — chore: document and validate AirLLM Apple Silicon requirements
**Source:** IMG_6187 (Mac-compatible LLM setup)
AirLLM graceful degradation is already implemented but undocumented. Add System Requirements
to README (M1/M2/M3/M4, 16 GB RAM min, 15 GB disk) and document `TIMMY_LLM_BACKEND` in
`.env.example`.
**Priority:** Low — documentation only, no code risk
---
### #1285 — chore: enforce "Normal Developer" discipline — tighten quality gates
**Source:** IMG_6123 (Vibe Coder vs Normal Developer meme)
Tighten the existing mypy/bandit/coverage gates: fix all mypy errors, raise coverage from 73%
to 80%, add a documented pre-push hook, and run `vulture` for dead code. The infrastructure
exists — it just needs enforcing.
**Priority:** Medium — technical debt prevention, pairs well with any green-field feature work
---
## Patterns Observed Across Screenshots
1. **Local-first is the north star.** All five images reinforce the same theme: private,
self-hosted, runs on your hardware. vLLM, SearXNG, AirLLM, DeerFlow — none require cloud.
Timmy is already aligned with this direction; these are tactical additions.
2. **Agentic performance bottlenecks are real.** Two of five images (vLLM, DeerFlow) focus
specifically on throughput and reliability for multi-agent loops. As the research pipeline
matures, inference speed and search reliability will become the main constraints.
3. **Discipline compounds.** The meme is a reminder that the quality gates we have (tox,
mypy, bandit, coverage) only pay off if they are enforced without exceptions.

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@@ -0,0 +1,290 @@
# Building Timmy: Technical Blueprint for Sovereign Creative AI
> **Source:** PDF attached to issue #891, "Building Timmy: a technical blueprint for sovereign
> creative AI" — generated by Kimi.ai, 16 pages, filed by Perplexity for Timmy's review.
> **Filed:** 2026-03-22 · **Reviewed:** 2026-03-23
---
## Executive Summary
The blueprint establishes that a sovereign creative AI capable of coding, composing music,
generating art, building worlds, publishing narratives, and managing its own economy is
**technically feasible today** — but only through orchestration of dozens of tools operating
at different maturity levels. The core insight: *the integration is the invention*. No single
component is new; the missing piece is a coherent identity operating across all domains
simultaneously with persistent memory, autonomous economics, and cross-domain creative
reactions.
Three non-negotiable architectural decisions:
1. **Human oversight for all public-facing content** — every successful creative AI has this;
every one that removed it failed.
2. **Legal entity before economic activity** — AI agents are not legal persons; establish
structure before wealth accumulates (Truth Terminal cautionary tale: $20M acquired before
a foundation was retroactively created).
3. **Hybrid memory: vector search + knowledge graph** — neither alone is sufficient for
multi-domain context breadth.
---
## Domain-by-Domain Assessment
### Software Development (immediately deployable)
| Component | Recommendation | Notes |
|-----------|----------------|-------|
| Primary agent | Claude Code (Opus 4.6, 77.2% SWE-bench) | Already in use |
| Self-hosted forge | Forgejo (MIT, 170200MB RAM) | Project uses Gitea/Forgejo now |
| CI/CD | GitHub Actions-compatible via `act_runner` | — |
| Tool-making | LATM pattern: frontier model creates tools, cheaper model applies them | New — see ADR opportunity |
| Open-source fallback | OpenHands (~65% SWE-bench, Docker sandboxed) | Backup to Claude Code |
| Self-improvement | Darwin Gödel Machine / SICA patterns | 36 month investment |
**Development estimate:** 23 weeks for Forgejo + Claude Code integration with automated
PR workflows; 12 months for self-improving tool-making pipeline.
**Cross-reference:** This project already runs Claude Code agents on Forgejo. The LATM
pattern (tool registry) and self-improvement loop are the actionable gaps.
---
### Music (14 weeks)
| Component | Recommendation | Notes |
|-----------|----------------|-------|
| Commercial vocals | Suno v5 API (~$0.03/song, $30/month Premier) | No official API; third-party: sunoapi.org, AIMLAPI, EvoLink |
| Local instrumental | MusicGen 1.5B (CC-BY-NC — monetization blocker) | On M2 Max: ~60s for 5s clip |
| Voice cloning | GPT-SoVITS v4 (MIT) | Works on Apple Silicon CPU, RTF 0.526 on M4 |
| Voice conversion | RVC (MIT, 510 min training audio) | — |
| Apple Silicon TTS | MLX-Audio: Kokoro 82M + Qwen3-TTS 0.6B | 45x faster via Metal |
| Publishing | Wavlake (90/10 split, Lightning micropayments) | Auto-syndicates to Fountain.fm |
| Nostr | NIP-94 (kind:1063) audio events → NIP-96 servers | — |
**Copyright reality:** US Copyright Office (Jan 2025) and US Court of Appeals (Mar 2025):
purely AI-generated music cannot be copyrighted and enters public domain. Wavlake's
Value4Value model works around this — fans pay for relationship, not exclusive rights.
**Avoid:** Udio (download disabled since Oct 2025, 2.4/5 Trustpilot).
---
### Visual Art (13 weeks)
| Component | Recommendation | Notes |
|-----------|----------------|-------|
| Local generation | ComfyUI API at `127.0.0.1:8188` (programmatic control via WebSocket) | MLX extension: 5070% faster |
| Speed | Draw Things (free, Mac App Store) | 3× faster than ComfyUI via Metal shaders |
| Quality frontier | Flux 2 (Nov 2025, 4MP, multi-reference) | SDXL needs 16GB+, Flux Dev 32GB+ |
| Character consistency | LoRA training (30 min, 1530 references) + Flux.1 Kontext | Solved problem |
| Face consistency | IP-Adapter + FaceID (ComfyUI-IP-Adapter-Plus) | Training-free |
| Comics | Jenova AI ($20/month, 200+ page consistency) or LlamaGen AI (free) | — |
| Publishing | Blossom protocol (SHA-256 addressed, kind:10063) + Nostr NIP-94 | — |
| Physical | Printful REST API (200+ products, automated fulfillment) | — |
---
### Writing / Narrative (14 weeks for pipeline; ongoing for quality)
| Component | Recommendation | Notes |
|-----------|----------------|-------|
| LLM | Claude Opus 4.5/4.6 (leads Mazur Writing Benchmark at 8.561) | Already in use |
| Context | 500K tokens (1M in beta) — entire novels fit | — |
| Architecture | Outline-first → RAG lore bible → chapter-by-chapter generation | Without outline: novels meander |
| Lore management | WorldAnvil Pro or custom LoreScribe (local RAG) | No tool achieves 100% consistency |
| Publishing (ebooks) | Pandoc → EPUB / KDP PDF | pandoc-novel template on GitHub |
| Publishing (print) | Lulu Press REST API (80% profit, global print network) | KDP: no official API, 3-book/day limit |
| Publishing (Nostr) | NIP-23 kind:30023 long-form events | Habla.news, YakiHonne, Stacker News |
| Podcasts | LLM script → TTS (ElevenLabs or local Kokoro/MLX-Audio) → feedgen RSS → Fountain.fm | Value4Value sats-per-minute |
**Key constraint:** AI-assisted (human directs, AI drafts) = 40% faster. Fully autonomous
without editing = "generic, soulless prose" and character drift by chapter 3 without explicit
memory.
---
### World Building / Games (2 weeks3 months depending on target)
| Component | Recommendation | Notes |
|-----------|----------------|-------|
| Algorithms | Wave Function Collapse, Perlin noise (FastNoiseLite in Godot 4), L-systems | All mature |
| Platform | Godot Engine + gd-agentic-skills (82+ skills, 26 genre blueprints) | Strong LLM/GDScript knowledge |
| Narrative design | Knowledge graph (world state) + LLM + quest template grammar | CHI 2023 validated |
| Quick win | Luanti/Minetest (Lua API, 2,800+ open mods for reference) | Immediately feasible |
| Medium effort | OpenMW content creation (omwaddon format engineering required) | 23 months |
| Future | Unity MCP (AI direct Unity Editor interaction) | Early-stage |
---
### Identity Architecture (2 months)
The blueprint formalizes the **SOUL.md standard** (GitHub: aaronjmars/soul.md):
| File | Purpose |
|------|---------|
| `SOUL.md` | Who you are — identity, worldview, opinions |
| `STYLE.md` | How you write — voice, syntax, patterns |
| `SKILL.md` | Operating modes |
| `MEMORY.md` | Session continuity |
**Critical decision — static vs self-modifying identity:**
- Static Core Truths (version-controlled, human-approved changes only) ✓
- Self-modifying Learned Preferences (logged with rollback, monitored by guardian) ✓
- **Warning:** OpenClaw's "Soul Evolution" creates a security attack surface — Zenity Labs
demonstrated a complete zero-click attack chain targeting SOUL.md files.
**Relevance to this repo:** Claude Code agents already use a `MEMORY.md` pattern in
this project. The SOUL.md stack is a natural extension.
---
### Memory Architecture (2 months)
Hybrid vector + knowledge graph is the recommendation:
| Component | Tool | Notes |
|-----------|------|-------|
| Vector + KG combined | Mem0 (mem0.ai) | 26% accuracy improvement over OpenAI memory, 91% lower p95 latency, 90% token savings |
| Vector store | Qdrant (Rust, open-source) | High-throughput with metadata filtering |
| Temporal KG | Neo4j + Graphiti (Zep AI) | P95 retrieval: 300ms, hybrid semantic + BM25 + graph |
| Backup/migration | AgentKeeper (95% critical fact recovery across model migrations) | — |
**Journal pattern (Stanford Generative Agents):** Agent writes about experiences, generates
high-level reflections 23x/day when importance scores exceed threshold. Ablation studies:
removing any component (observation, planning, reflection) significantly reduces behavioral
believability.
**Cross-reference:** The existing `brain/` package is the memory system. Qdrant and
Mem0 are the recommended upgrade targets.
---
### Multi-Agent Sub-System (36 months)
The blueprint describes a named sub-agent hierarchy:
| Agent | Role |
|-------|------|
| Oracle | Top-level planner / supervisor |
| Sentinel | Safety / moderation |
| Scout | Research / information gathering |
| Scribe | Writing / narrative |
| Ledger | Economic management |
| Weaver | Visual art generation |
| Composer | Music generation |
| Social | Platform publishing |
**Orchestration options:**
- **Agno** (already in use) — microsecond instantiation, 50× less memory than LangGraph
- **CrewAI Flows** — event-driven with fine-grained control
- **LangGraph** — DAG-based with stateful workflows and time-travel debugging
**Scheduling pattern (Stanford Generative Agents):** Top-down recursive daily → hourly →
5-minute planning. Event interrupts for reactive tasks. Re-planning triggers when accumulated
importance scores exceed threshold.
**Cross-reference:** The existing `spark/` package (event capture, advisory engine) aligns
with this architecture. `infrastructure/event_bus` is the choreography backbone.
---
### Economic Engine (14 weeks)
Lightning Labs released `lightning-agent-tools` (open-source) in February 2026:
- `lnget` — CLI HTTP client for L402 payments
- Remote signer architecture (private keys on separate machine from agent)
- Scoped macaroon credentials (pay-only, invoice-only, read-only roles)
- **Aperture** — converts any API to pay-per-use via L402 (HTTP 402)
| Option | Effort | Notes |
|--------|--------|-------|
| ln.bot | 1 week | "Bitcoin for AI Agents" — 3 commands create a wallet; CLI + MCP + REST |
| LND via gRPC | 23 weeks | Full programmatic node management for production |
| Coinbase Agentic Wallets | — | Fiat-adjacent; less aligned with sovereignty ethos |
**Revenue channels:** Wavlake (music, 90/10 Lightning), Nostr zaps (articles), Stacker News
(earn sats from engagement), Printful (physical goods), L402-gated API access (pay-per-use
services), Geyser.fund (Lightning crowdfunding, better initial runway than micropayments).
**Cross-reference:** The existing `lightning/` package in this repo is the foundation.
L402 paywall endpoints for Timmy's own services is the actionable gap.
---
## Pioneer Case Studies
| Agent | Active | Revenue | Key Lesson |
|-------|--------|---------|-----------|
| Botto | Since Oct 2021 | $5M+ (art auctions) | Community governance via DAO sustains engagement; "taste model" (humans guide, not direct) preserves autonomous authorship |
| Neuro-sama | Since Dec 2022 | $400K+/month (subscriptions) | 3+ years of iteration; errors became entertainment features; 24/7 capability is an insurmountable advantage |
| Truth Terminal | Since Jun 2024 | $20M accumulated | Memetic fitness > planned monetization; human gatekeeper approved tweets while selecting AI-intent responses; **establish legal entity first** |
| Holly+ | Since 2021 | Conceptual | DAO of stewards for voice governance; "identity play" as alternative to defensive IP |
| AI Sponge | 2023 | Banned | Unmoderated content → TOS violations + copyright |
| Nothing Forever | 2022present | 8 viewers | Unmoderated content → ban → audience collapse; novelty-only propositions fail |
**Universal pattern:** Human oversight + economic incentive alignment + multi-year personality
development + platform-native economics = success.
---
## Recommended Implementation Sequence
From the blueprint, mapped against Timmy's existing architecture:
### Phase 1: Immediate (weeks)
1. **Code sovereignty** — Forgejo + Claude Code automated PR workflows (already substantially done)
2. **Music pipeline** — Suno API → Wavlake/Nostr NIP-94 publishing
3. **Visual art pipeline** — ComfyUI API → Blossom/Nostr with LoRA character consistency
4. **Basic Lightning wallet** — ln.bot integration for receiving micropayments
5. **Long-form publishing** — Nostr NIP-23 + RSS feed generation
### Phase 2: Moderate effort (13 months)
6. **LATM tool registry** — frontier model creates Python utilities, caches them, lighter model applies
7. **Event-driven cross-domain reactions** — game event → blog + artwork + music (CrewAI/LangGraph)
8. **Podcast generation** — TTS + feedgen → Fountain.fm
9. **Self-improving pipeline** — agent creates, tests, caches own Python utilities
10. **Comic generation** — character-consistent panels with Jenova AI or local LoRA
### Phase 3: Significant investment (36 months)
11. **Full sub-agent hierarchy** — Oracle/Sentinel/Scout/Scribe/Ledger/Weaver with Agno
12. **SOUL.md identity system** — bounded evolution + guardian monitoring
13. **Hybrid memory upgrade** — Qdrant + Mem0/Graphiti replacing or extending `brain/`
14. **Procedural world generation** — Godot + AI-driven narrative (quests, NPCs, lore)
15. **Self-sustaining economic loop** — earned revenue covers compute costs
### Remains aspirational (12+ months)
- Fully autonomous novel-length fiction without editorial intervention
- YouTube monetization for AI-generated content (tightening platform policies)
- Copyright protection for AI-generated works (current US law denies this)
- True artistic identity evolution (genuine creative voice vs pattern remixing)
- Self-modifying architecture without regression or identity drift
---
## Gap Analysis: Blueprint vs Current Codebase
| Blueprint Capability | Current Status | Gap |
|---------------------|----------------|-----|
| Code sovereignty | Done (Claude Code + Forgejo) | LATM tool registry |
| Music generation | Not started | Suno API integration + Wavlake publishing |
| Visual art | Not started | ComfyUI API client + Blossom publishing |
| Writing/publishing | Not started | Nostr NIP-23 + Pandoc pipeline |
| World building | Bannerlord work (different scope) | Luanti mods as quick win |
| Identity (SOUL.md) | Partial (CLAUDE.md + MEMORY.md) | Full SOUL.md stack |
| Memory (hybrid) | `brain/` package (SQLite-based) | Qdrant + knowledge graph |
| Multi-agent | Agno in use | Named hierarchy + event choreography |
| Lightning payments | `lightning/` package | ln.bot wallet + L402 endpoints |
| Nostr identity | Referenced in roadmap, not built | NIP-05, NIP-89 capability cards |
| Legal entity | Unknown | **Must be resolved before economic activity** |
---
## ADR Candidates
Issues that warrant Architecture Decision Records based on this review:
1. **LATM tool registry pattern** — How Timmy creates, tests, and caches self-made tools
2. **Music generation strategy** — Suno (cloud, commercial quality) vs MusicGen (local, CC-BY-NC)
3. **Memory upgrade path** — When/how to migrate `brain/` from SQLite to Qdrant + KG
4. **SOUL.md adoption** — Extending existing CLAUDE.md/MEMORY.md to full SOUL.md stack
5. **Lightning L402 strategy** — Which services Timmy gates behind micropayments
6. **Sub-agent naming and contracts** — Formalizing Oracle/Sentinel/Scout/Scribe/Ledger/Weaver

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@@ -164,3 +164,7 @@ directory = "htmlcov"
[tool.coverage.xml] [tool.coverage.xml]
output = "coverage.xml" output = "coverage.xml"
[tool.mypy]
ignore_missing_imports = true
no_error_summary = true

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@@ -6,6 +6,8 @@ import sqlite3
from contextlib import closing from contextlib import closing
from pathlib import Path from pathlib import Path
from typing import Any
from fastapi import APIRouter, Request from fastapi import APIRouter, Request
from fastapi.responses import HTMLResponse, JSONResponse from fastapi.responses import HTMLResponse, JSONResponse
@@ -36,9 +38,9 @@ def _discover_databases() -> list[dict]:
return dbs return dbs
def _query_database(db_path: str) -> dict: def _query_database(db_path: str) -> dict[str, Any]:
"""Open a database read-only and return all tables with their rows.""" """Open a database read-only and return all tables with their rows."""
result = {"tables": {}, "error": None} result: dict[str, Any] = {"tables": {}, "error": None}
try: try:
with closing(sqlite3.connect(f"file:{db_path}?mode=ro", uri=True)) as conn: with closing(sqlite3.connect(f"file:{db_path}?mode=ro", uri=True)) as conn:
conn.row_factory = sqlite3.Row conn.row_factory = sqlite3.Row

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@@ -137,7 +137,7 @@ class HermesMonitor:
message=f"Check error: {r}", message=f"Check error: {r}",
) )
) )
else: elif isinstance(r, CheckResult):
checks.append(r) checks.append(r)
# Compute overall level # Compute overall level

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@@ -203,7 +203,7 @@ async def reload_config(
@router.get("/history") @router.get("/history")
async def get_history( async def get_history(
hours: int = 24, hours: int = 24,
store: Annotated[HealthHistoryStore, Depends(get_history_store)] = None, store: Annotated[HealthHistoryStore | None, Depends(get_history_store)] = None,
) -> list[dict[str, Any]]: ) -> list[dict[str, Any]]:
"""Get provider health history for the last N hours.""" """Get provider health history for the last N hours."""
if store is None: if store is None:

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@@ -744,19 +744,20 @@ class CascadeRouter:
self, self,
provider: Provider, provider: Provider,
messages: list[dict], messages: list[dict],
model: str, model: str | None,
temperature: float, temperature: float,
max_tokens: int | None, max_tokens: int | None,
content_type: ContentType = ContentType.TEXT, content_type: ContentType = ContentType.TEXT,
) -> dict: ) -> dict:
"""Try a single provider request.""" """Try a single provider request."""
start_time = time.time() start_time = time.time()
effective_model: str = model or provider.get_default_model() or ""
if provider.type == "ollama": if provider.type == "ollama":
result = await self._call_ollama( result = await self._call_ollama(
provider=provider, provider=provider,
messages=messages, messages=messages,
model=model or provider.get_default_model(), model=effective_model,
temperature=temperature, temperature=temperature,
max_tokens=max_tokens, max_tokens=max_tokens,
content_type=content_type, content_type=content_type,
@@ -765,7 +766,7 @@ class CascadeRouter:
result = await self._call_openai( result = await self._call_openai(
provider=provider, provider=provider,
messages=messages, messages=messages,
model=model or provider.get_default_model(), model=effective_model,
temperature=temperature, temperature=temperature,
max_tokens=max_tokens, max_tokens=max_tokens,
) )
@@ -773,7 +774,7 @@ class CascadeRouter:
result = await self._call_anthropic( result = await self._call_anthropic(
provider=provider, provider=provider,
messages=messages, messages=messages,
model=model or provider.get_default_model(), model=effective_model,
temperature=temperature, temperature=temperature,
max_tokens=max_tokens, max_tokens=max_tokens,
) )
@@ -781,7 +782,7 @@ class CascadeRouter:
result = await self._call_grok( result = await self._call_grok(
provider=provider, provider=provider,
messages=messages, messages=messages,
model=model or provider.get_default_model(), model=effective_model,
temperature=temperature, temperature=temperature,
max_tokens=max_tokens, max_tokens=max_tokens,
) )
@@ -789,7 +790,7 @@ class CascadeRouter:
result = await self._call_vllm_mlx( result = await self._call_vllm_mlx(
provider=provider, provider=provider,
messages=messages, messages=messages,
model=model or provider.get_default_model(), model=effective_model,
temperature=temperature, temperature=temperature,
max_tokens=max_tokens, max_tokens=max_tokens,
) )

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@@ -474,7 +474,7 @@ class DiscordVendor(ChatPlatform):
async def _run_client(self, token: str) -> None: async def _run_client(self, token: str) -> None:
"""Run the discord.py client (blocking call in a task).""" """Run the discord.py client (blocking call in a task)."""
try: try:
await self._client.start(token) await self._client.start(token) # type: ignore[union-attr]
except Exception as exc: except Exception as exc:
logger.error("Discord client error: %s", exc) logger.error("Discord client error: %s", exc)
self._state = PlatformState.ERROR self._state = PlatformState.ERROR
@@ -482,32 +482,32 @@ class DiscordVendor(ChatPlatform):
def _register_handlers(self) -> None: def _register_handlers(self) -> None:
"""Register Discord event handlers on the client.""" """Register Discord event handlers on the client."""
@self._client.event @self._client.event # type: ignore[union-attr]
async def on_ready(): async def on_ready():
self._guild_count = len(self._client.guilds) self._guild_count = len(self._client.guilds) # type: ignore[union-attr]
self._state = PlatformState.CONNECTED self._state = PlatformState.CONNECTED
logger.info( logger.info(
"Discord ready: %s in %d guild(s)", "Discord ready: %s in %d guild(s)",
self._client.user, self._client.user, # type: ignore[union-attr]
self._guild_count, self._guild_count,
) )
@self._client.event @self._client.event # type: ignore[union-attr]
async def on_message(message): async def on_message(message):
# Ignore our own messages # Ignore our own messages
if message.author == self._client.user: if message.author == self._client.user: # type: ignore[union-attr]
return return
# Only respond to mentions or DMs # Only respond to mentions or DMs
is_dm = not hasattr(message.channel, "guild") or message.channel.guild is None is_dm = not hasattr(message.channel, "guild") or message.channel.guild is None
is_mention = self._client.user in message.mentions is_mention = self._client.user in message.mentions # type: ignore[union-attr]
if not is_dm and not is_mention: if not is_dm and not is_mention:
return return
await self._handle_message(message) await self._handle_message(message)
@self._client.event @self._client.event # type: ignore[union-attr]
async def on_disconnect(): async def on_disconnect():
if self._state != PlatformState.DISCONNECTED: if self._state != PlatformState.DISCONNECTED:
self._state = PlatformState.CONNECTING self._state = PlatformState.CONNECTING
@@ -535,8 +535,8 @@ class DiscordVendor(ChatPlatform):
def _extract_content(self, message) -> str: def _extract_content(self, message) -> str:
"""Strip the bot mention and return clean message text.""" """Strip the bot mention and return clean message text."""
content = message.content content = message.content
if self._client.user: if self._client.user: # type: ignore[union-attr]
content = content.replace(f"<@{self._client.user.id}>", "").strip() content = content.replace(f"<@{self._client.user.id}>", "").strip() # type: ignore[union-attr]
return content return content
async def _invoke_agent(self, content: str, session_id: str, target): async def _invoke_agent(self, content: str, session_id: str, target):

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@@ -102,14 +102,14 @@ class TelegramBot:
self._token = tok self._token = tok
self._app = Application.builder().token(tok).build() self._app = Application.builder().token(tok).build()
self._app.add_handler(CommandHandler("start", self._cmd_start)) self._app.add_handler(CommandHandler("start", self._cmd_start)) # type: ignore[union-attr]
self._app.add_handler( self._app.add_handler( # type: ignore[union-attr]
MessageHandler(filters.TEXT & ~filters.COMMAND, self._handle_message) MessageHandler(filters.TEXT & ~filters.COMMAND, self._handle_message)
) )
await self._app.initialize() await self._app.initialize() # type: ignore[union-attr]
await self._app.start() await self._app.start() # type: ignore[union-attr]
await self._app.updater.start_polling(allowed_updates=Update.ALL_TYPES) await self._app.updater.start_polling(allowed_updates=Update.ALL_TYPES) # type: ignore[union-attr]
self._running = True self._running = True
logger.info("Telegram bot started.") logger.info("Telegram bot started.")

View File

@@ -245,6 +245,7 @@ class VoiceLoop:
def _transcribe(self, audio: np.ndarray) -> str: def _transcribe(self, audio: np.ndarray) -> str:
"""Transcribe audio using local Whisper model.""" """Transcribe audio using local Whisper model."""
self._load_whisper() self._load_whisper()
assert self._whisper_model is not None, "Whisper model failed to load"
sys.stdout.write(" 🧠 Transcribing...\r") sys.stdout.write(" 🧠 Transcribing...\r")
sys.stdout.flush() sys.stdout.flush()

10
tox.ini
View File

@@ -41,8 +41,10 @@ description = Static type checking with mypy
commands_pre = commands_pre =
deps = deps =
mypy>=1.0.0 mypy>=1.0.0
types-PyYAML
types-requests
commands = commands =
mypy src --ignore-missing-imports --no-error-summary mypy src
# ── Test Environments ──────────────────────────────────────────────────────── # ── Test Environments ────────────────────────────────────────────────────────
@@ -130,13 +132,17 @@ commands =
# ── Pre-push (mirrors CI exactly) ──────────────────────────────────────────── # ── Pre-push (mirrors CI exactly) ────────────────────────────────────────────
[testenv:pre-push] [testenv:pre-push]
description = Local gate — lint + full CI suite (same as Gitea Actions) description = Local gate — lint + typecheck + full CI suite (same as Gitea Actions)
deps = deps =
ruff>=0.8.0 ruff>=0.8.0
mypy>=1.0.0
types-PyYAML
types-requests
commands = commands =
ruff check src/ tests/ ruff check src/ tests/
ruff format --check src/ tests/ ruff format --check src/ tests/
bash -c 'files=$(grep -rl "<style" src/dashboard/templates/ --include="*.html" 2>/dev/null); if [ -n "$files" ]; then echo "ERROR: inline <style> blocks found — move CSS to static/css/mission-control.css:"; echo "$files"; exit 1; fi; echo "No inline CSS — OK"' bash -c 'files=$(grep -rl "<style" src/dashboard/templates/ --include="*.html" 2>/dev/null); if [ -n "$files" ]; then echo "ERROR: inline <style> blocks found — move CSS to static/css/mission-control.css:"; echo "$files"; exit 1; fi; echo "No inline CSS — OK"'
mypy src
mkdir -p reports mkdir -p reports
pytest tests/ \ pytest tests/ \
--cov=src \ --cov=src \