56 lines
1.6 KiB
Markdown
56 lines
1.6 KiB
Markdown
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# opencode Configuration
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This file configures opencode for working with the DataPRO codebase.
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## Model Configuration
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Configured to use vast.ai hosted GLM-5-FP8 model with 131k context window.
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## MCP Servers
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### vastai-ctl
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Control vast.ai GPU instances (start, stop, status).
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### retrieval
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Semantic search over code and enrichment documentation.
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- `vector_search(query)` - Find relevant code by meaning
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- `get_module_summary(path)` - Get AI-generated module docs
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- `list_enriched_modules()` - List all enriched modules
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## AI-Generated Artifacts
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This codebase has pre-computed AI artifacts for efficient assistance:
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| Location | Purpose |
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|----------|---------|
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| `GLM5Analysis/Architecture.md` | System architecture overview |
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| `GLM5Analysis/PatternLibrary/` | Reusable code patterns |
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| `GLM5Analysis/PromptTemplates/` | Task-specific guides |
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| `GLM5Analysis/TestScaffolds/` | Test templates |
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| `enriched-qwen3-coder-next/` | Module-level documentation |
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**Always check `GLM5Analysis/` before starting a task.**
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## Workflow
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1. Check `GLM5Analysis/Architecture.md` for system context
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2. Check `GLM5Analysis/PromptTemplates/` for task-specific guidance
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3. Use `vector_search()` to find relevant code
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4. Use `get_module_summary()` for detailed module docs
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5. Follow patterns from `GLM5Analysis/PatternLibrary/`
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## Build Commands
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```bash
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# Build solution (requires Windows/Visual Studio)
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msbuild DataPRO/DataPRO.sln /p:Configuration=Debug
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# Run tests
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# Tests are NUnit-based in DataPRO/UnitTest/
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```
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## Important Files
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- `GIT Migration.md` - Plan for SVN to Git migration
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- `AGENTS.md` - Instructions for AI assistants
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