Mortdecai
4b9c537dda
Fills the gap between existing chat-agent (Simon) and pipeline (AI_Visualizer) patterns. Covers openclaw/open code/pi/hermes first-party agents from the HF launch blog, honest positioning vs qwen3-coder:30b, CLI-agent-specific gotchas (safety filter on security code, long-JSON weakness, no code exec), and a concrete homelab bakeoff plan pointed at CT 166 openclaw2 → CT 105 Ollama on pve197. Key research finding: Google published LiveCodeBench + Codeforces but NOT SWE-bench or Aider polyglot. The "autonomous agents" claim is plausible but unproven for multi-file repo-scale coding specifically.
28 lines
2.5 KiB
Markdown
28 lines
2.5 KiB
Markdown
# gemma4-research
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Research corpus and implementation guidance for Google Gemma 4, based on production use in Seth's homelab.
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## Files
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| File | What | When to Read |
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| `SYNTHESIS.md` | **Start here.** Opinionated guide — how to build with Gemma 4 | Before any new Gemma 4 implementation |
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| `GOTCHAS.md` | Known issues and workarounds, severity-ranked | When debugging Gemma 4 issues or starting a new project |
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| `IMPLEMENTATIONS.md` | Patterns from Simon and AI_Visualizer | When designing a new Gemma 4 integration |
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| `CORPUS_architecture.md` | Model architecture details (layers, attention, PLE, MoE) | When you need to understand WHY Gemma 4 behaves a certain way |
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| `CORPUS_ollama_variants.md` | Available models, sizes, VRAM, Ollama settings | When choosing a model variant or configuring Ollama |
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| `CORPUS_capabilities.md` | Modalities (vision, audio, video, tools), what it can/can't do | When scoping what Gemma 4 can handle |
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| `CORPUS_benchmarks.md` | Full benchmark table vs Gemma 3, arena scores, agentic scores | When comparing Gemma 4 to alternatives |
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| `CORPUS_tool_calling_format.md` | Native token format + JSON API format for function calling | When implementing tool calling |
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| `CORPUS_cli_coding_agent.md` | Positioning Gemma 4 for CLI coding agent use (openclaw / open code / pi / hermes / aider style). Honest take on what Google did and didn't measure, head-to-head with `qwen3-coder:30b`, homelab setup pointer | When scoping a CLI coding agent or deciding Gemma 4 vs Qwen3-Coder |
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| `tooling/` | **Canonical upstream tooling** — real scripts, notebooks, model cards, and configs pulled from Google / HF / framework maintainers (147 files). Subdirs: `google-official/`, `huggingface/`, `inference-frameworks/`, `gemma-family/`, `fine-tuning/`. See `tooling/README.md` for index and findings that update the older `CORPUS_*` docs | When you need authoritative source material — model cards, chat templates, fine-tuning recipes, serving commands for vLLM / llama.cpp / MLX, or to scope a specialized sibling (ShieldGemma, EmbeddingGemma, etc.) |
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## Source Projects
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- **Simon** (`~/bin/FreibergFamily/simon/`) — Multi-turn chat agent with 6 tools, genealogy historian
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- **AI Visualizer** (`~/bin/AI_Visualizer/`) — Music video generator, 4-stage Gemma pipeline + vision
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## Key Insight
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Gemma 4 is ultra-compliant and highly capable but doesn't know who it is. It needs explicit system prompts, not hand-holding. Due to fast local inference, sequential tool calls beat long JSON requests.
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