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Three private tiles published to the codeflash workspace: - codeflash-internal-rules: 6 eager rules (code-style, architecture, optimization-patterns, git-conventions, testing-rules, multi-language-handlers) - codeflash-internal-docs: 8 lazy doc pages (domain-types, optimization-pipeline, test-generation-pipeline, context-extraction, aiservice/cf-api endpoints, configuration-thresholds, llm-provider-abstraction) - codeflash-internal-skills: 4 on-demand skills (debug-optimization-failure, add-language-support, add-api-endpoint, debug-test-generation)
39 lines
1.7 KiB
Markdown
39 lines
1.7 KiB
Markdown
# Optimization Patterns
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## Router Dispatch
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- Shared routers in `core/shared/` dispatch by the `language` field on the request schema
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- Lazy imports inside the endpoint body to avoid circular dependencies:
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```python
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if data.language in ("javascript", "typescript"):
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from core.languages.js_ts.optimizer import optimize_javascript # noqa: PLC0415
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return await optimize_javascript(request, data)
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```
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- Default language is Python
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## Context Extraction
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- `BaseOptimizerContext` in `optimizer_context.py` handles prompt management and code extraction
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- Two context types: `SingleOptimizerContext` (single-file) and `MultiOptimizerContext` (multi-file)
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- `extract_code_and_explanation_from_llm_res()` parses LLM markdown response into code blocks
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- `parse_and_generate_candidate_schema()` converts extracted code to `OptimizeResponseItemSchema`
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## Model Distribution
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- `get_model_distribution()` in `optimizer_config.py` splits calls between OpenAI and Anthropic
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- Formula: `claude_calls = (total - 1) // 2`, `gpt_calls = total - claude_calls`
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- `MAX_OPTIMIZER_CALLS = 6`, `MAX_OPTIMIZER_LP_CALLS = 7`
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- Claude gets fewer calls as it's more expensive
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## Postprocessing
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- `postprocess.py` handles deduplication and validation of optimization candidates
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- Deduplication: normalize with `ast.parse()` + `ast.dump()`, skip duplicates with identical AST
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- Equality check: compare optimized code to original to skip no-ops
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- Uses `libcst` for all code transformations (preserves formatting)
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## Prompt Templates
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- Prompts stored as `.md` files alongside their modules
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- Rendered with Jinja2 (e.g., `build_prompt()` in testgen)
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- System and user prompts are constructed per-context type
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