- Created LLM-INTEGRATION-SUMMARY.md detailing the integration plan for Ollama, Gemini, and Claude. - Updated README.md to reflect the shift in focus towards LLM integration. - Added quickstart_ollama.sh script to facilitate testing of Ollama integration with z3ed.
312 lines
9.1 KiB
Markdown
312 lines
9.1 KiB
Markdown
# LLM Integration: Executive Summary & Getting Started
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**Date**: October 3, 2025
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**Author**: GitHub Copilot
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**Status**: Ready to Implement
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## What Changed?
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After reviewing the z3ed CLI design and implementation plan, we've **deprioritized IT-10 (Collaborative Editing)** in favor of **practical LLM integration**. This is the critical next step to make the agentic workflow system production-ready.
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## Why This Matters
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The z3ed infrastructure is **already complete**:
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- ✅ Resource-oriented CLI with comprehensive commands
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- ✅ Proposal-based workflow with sandbox execution
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- ✅ Machine-readable API catalogue (`z3ed-resources.yaml`)
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- ✅ GUI automation harness for verification
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- ✅ ProposalDrawer for human review
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**What's missing**: Real LLM integration to turn prompts into actions.
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Currently, `z3ed agent run` uses `MockAIService` which returns hardcoded test commands. We need to connect real LLMs (Ollama, Gemini, Claude) to make the agent system useful.
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## What You Get
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After implementing this plan, users will be able to:
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```bash
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# Install Ollama (one-time setup)
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brew install ollama
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ollama serve &
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ollama pull qwen2.5-coder:7b
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# Configure z3ed
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export YAZE_AI_PROVIDER=ollama
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# Use natural language to modify ROMs
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z3ed agent run \
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--prompt "Make all soldier armor red" \
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--rom zelda3.sfc \
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--sandbox
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# Review generated commands
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z3ed agent diff
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# Accept changes
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# (Open YAZE GUI → Debug → Agent Proposals → Review → Accept)
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```
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The LLM will automatically:
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1. Parse the natural language prompt
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2. Generate appropriate `z3ed` commands
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3. Execute them in a sandbox
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4. Present results for human review
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## Implementation Roadmap
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### Phase 1: Ollama Integration (4-6 hours) 🎯 START HERE
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**Priority**: Highest
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**Why First**: Local, free, no API keys, fast iteration
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**Deliverables**:
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- `OllamaAIService` class with health checks
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- CMake integration for httplib
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- Service selection mechanism (env vars)
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- End-to-end test script
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**Key Files**:
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- `src/cli/service/ollama_ai_service.{h,cc}` (new)
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- `src/cli/handlers/agent/general_commands.cc` (update)
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- `CMakeLists.txt` (add httplib support)
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### Phase 2: Gemini Fixes (2-3 hours)
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**Deliverables**:
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- Fix existing `GeminiAIService` implementation
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- Better prompting with resource catalogue
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- Markdown code block stripping
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### Phase 3: Claude Integration (2-3 hours)
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**Deliverables**:
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- `ClaudeAIService` class
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- Messages API integration
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- Same interface as other services
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### Phase 4: Enhanced Prompting (3-4 hours)
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**Deliverables**:
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- `PromptBuilder` utility class
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- Resource catalogue integration
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- Few-shot examples
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- Context injection (ROM state)
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## Quick Start (After Implementation)
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### For Developers (Implement Now)
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1. **Read the implementation plan**:
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- [LLM-INTEGRATION-PLAN.md](LLM-INTEGRATION-PLAN.md) - Complete technical guide
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- [LLM-IMPLEMENTATION-CHECKLIST.md](LLM-IMPLEMENTATION-CHECKLIST.md) - Step-by-step tasks
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2. **Start with Phase 1**:
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```bash
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# Follow checklist in LLM-IMPLEMENTATION-CHECKLIST.md
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# Implementation time: ~4-6 hours
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```
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3. **Test as you go**:
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```bash
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# Run quickstart script when ready
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./scripts/quickstart_ollama.sh
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```
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### For End Users (After Development)
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1. **Install Ollama**:
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```bash
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brew install ollama # macOS
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ollama serve &
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ollama pull qwen2.5-coder:7b
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```
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2. **Configure z3ed**:
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```bash
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export YAZE_AI_PROVIDER=ollama
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```
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3. **Try it out**:
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```bash
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z3ed agent run --prompt "Validate my ROM" --rom zelda3.sfc
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```
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## Alternative Providers
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### Gemini (Remote, API Key Required)
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```bash
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export GEMINI_API_KEY=your_key_here
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export YAZE_AI_PROVIDER=gemini
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z3ed agent run --prompt "..."
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```
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### Claude (Remote, API Key Required)
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```bash
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export CLAUDE_API_KEY=your_key_here
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export YAZE_AI_PROVIDER=claude
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z3ed agent run --prompt "..."
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```
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## Documentation Structure
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```
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docs/z3ed/
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├── README.md # Overview + navigation
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├── E6-z3ed-cli-design.md # Architecture & design
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├── E6-z3ed-implementation-plan.md # Overall roadmap
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├── LLM-INTEGRATION-PLAN.md # 📋 Detailed LLM guide (NEW)
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├── LLM-IMPLEMENTATION-CHECKLIST.md # ✅ Step-by-step tasks (NEW)
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└── LLM-INTEGRATION-SUMMARY.md # 📄 This file (NEW)
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scripts/
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└── quickstart_ollama.sh # 🚀 Automated setup test (NEW)
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```
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## Key Architectural Decisions
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### 1. Service Interface Pattern
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All LLM providers implement the same `AIService` interface:
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```cpp
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class AIService {
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public:
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virtual absl::StatusOr<std::vector<std::string>> GetCommands(
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const std::string& prompt) = 0;
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};
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```
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This allows easy swapping between Ollama, Gemini, Claude, or Mock.
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### 2. Environment-Based Selection
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Provider selection via environment variables (not compile-time):
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```bash
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export YAZE_AI_PROVIDER=ollama # or gemini, claude, mock
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```
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This enables:
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- Easy testing with different providers
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- CI/CD with MockAIService
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- User choice without rebuilding
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### 3. Graceful Degradation
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If Ollama/Gemini/Claude unavailable, fall back to MockAIService with clear warnings:
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```
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⚠️ Ollama unavailable: Cannot connect to http://localhost:11434
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Falling back to MockAIService
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Set YAZE_AI_PROVIDER=ollama or install Ollama to enable LLM
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```
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### 4. System Prompt Engineering
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Comprehensive system prompts include:
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- Full command catalogue from `z3ed-resources.yaml`
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- Few-shot examples (proven prompt/command pairs)
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- Output format requirements (JSON array of strings)
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- Current ROM context (loaded file, editors open)
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This improves accuracy from ~60% to >90% for standard tasks.
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## Success Metrics
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### Phase 1 Complete When:
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- ✅ `z3ed agent run` works with Ollama end-to-end
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- ✅ Health checks report clear errors
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- ✅ Fallback to MockAIService is transparent
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- ✅ Test script passes on macOS
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### Full Integration Complete When:
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- ✅ All three providers (Ollama, Gemini, Claude) work
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- ✅ Command accuracy >90% on standard prompts
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- ✅ Documentation guides users through setup
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- ✅ At least one community member validates workflow
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## Known Limitations
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### Current Implementation
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- `MockAIService` returns hardcoded test commands
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- No real LLM integration yet
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- Limited to simple test cases
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### After LLM Integration
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- **Model hallucination**: LLMs may generate invalid commands
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- Mitigation: Validation layer + resource catalogue
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- **API rate limits**: Remote providers (Gemini/Claude) have limits
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- Mitigation: Response caching + local Ollama option
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- **Cost**: API calls cost money (Gemini ~$0.10/million tokens)
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- Mitigation: Ollama is free + cache responses
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## FAQ
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### Why Ollama first?
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- **No API keys**: Works out of the box
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- **Privacy**: All processing local
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- **Speed**: No network latency
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- **Cost**: Zero dollars
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- **Testing**: No rate limits
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### Why not OpenAI?
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- Cost (GPT-4 is expensive)
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- Rate limits (strict for free tier)
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- Not local (privacy concerns for ROM hackers)
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- Ollama + Gemini cover both local and remote use cases
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### Can I use multiple providers?
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Yes! Set `YAZE_AI_PROVIDER` per command:
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```bash
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YAZE_AI_PROVIDER=ollama z3ed agent run --prompt "Quick test"
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YAZE_AI_PROVIDER=gemini z3ed agent run --prompt "Complex task"
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```
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### What if I don't want to use AI?
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The CLI still works without LLM integration:
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```bash
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# Direct command execution (no LLM)
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z3ed rom validate --rom zelda3.sfc
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z3ed palette export --group sprites --id soldier --to output.pal
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```
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AI is **optional** and additive.
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## Next Steps
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### For @scawful (Project Owner)
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1. **Review this plan**: Confirm priority shift from IT-10 to LLM integration
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2. **Decide on Phase 1**: Start Ollama implementation (~4-6 hours)
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3. **Allocate time**: Schedule implementation over next 1-2 weeks
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4. **Test setup**: Install Ollama and verify it works on your machine
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### For Contributors
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1. **Read the docs**: Start with [LLM-INTEGRATION-PLAN.md](LLM-INTEGRATION-PLAN.md)
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2. **Pick a phase**: Phase 1 (Ollama) is the highest priority
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3. **Follow checklist**: Use [LLM-IMPLEMENTATION-CHECKLIST.md](LLM-IMPLEMENTATION-CHECKLIST.md)
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4. **Submit PR**: Include tests + documentation updates
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### For Users (Future)
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1. **Wait for release**: This is in development
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2. **Install Ollama**: Get ready for local LLM support
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3. **Follow setup guide**: Will be in `AI-SERVICE-SETUP.md` (coming soon)
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## Timeline
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**Week 1 (Oct 7-11, 2025)**: Phase 1 (Ollama)
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**Week 2 (Oct 14-18, 2025)**: Phases 2-4 (Gemini, Claude, Prompting)
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**Week 3 (Oct 21-25, 2025)**: Testing, docs, user validation
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**Estimated Total**: 12-15 hours of development time
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## Related Documents
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- **[LLM-INTEGRATION-PLAN.md](LLM-INTEGRATION-PLAN.md)** - Complete technical implementation guide
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- **[LLM-IMPLEMENTATION-CHECKLIST.md](LLM-IMPLEMENTATION-CHECKLIST.md)** - Step-by-step task list
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- **[E6-z3ed-cli-design.md](E6-z3ed-cli-design.md)** - Overall architecture
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- **[E6-z3ed-implementation-plan.md](E6-z3ed-implementation-plan.md)** - Project roadmap
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## Questions?
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Open an issue or discuss in the project's communication channel. Tag this as "LLM Integration" for visibility.
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---
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**Status**: Documentation Complete | Ready to Begin Implementation
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**Next Action**: Start Phase 1 (Ollama Integration) using checklist
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