parcadei/fastedit

ملف parcadei

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# FastEdit AST-aware code editing powered by a fine-tuned 1.7B model. Diffs, SEARCH/REPLACE, and apply_patch all force the agent to repeat back old code to say *where* the edit goes. FastEdit uses tree-sitter to find the target by name — the agent writes only the change plus a line or two of context. ### Agent output token savings | Model | Edit tool tokens | FastEdit tokens | Saved | Reduction | |-------|-----------------|-----------------|-------|-----------| | GPT-5.4 | 3,404 | 1,557 | 1,847 | **54.3%** | | Opus 4.6 | 4,286 | 2,291 | 1,995 | **46.5%** | | Opus 4.7 | 4,771 | 2,645 | 2,126 | **44.6%** | | Grok 4.20 | 2,946 | 1,661 | 1,285 | **43.6%** | ## The problem Every AI code editor today makes the model output old code to locate edits. Whether it's unified diffs, SEARCH/REPLACE blocks, or `apply_patch` — the model has to repeat back the lines it wants to change: ``` # Claude Code / Codex — model outputs old AND new code @@ -1,4 +1,6 @@ def process(data): - result = transform(data) - return result + try: + result = transform(data) + return result + except Error as e: + return {"error": str(e)} ``` You're paying double: the model writes every old line (to say "find this") plus every new line (to say "put this"). On a 50-line function where you change 3 lines, that's 50 lines of output just for location, plus 3 lines of actual edit. **~94% of output tokens are wasted on telling the model where to put the code.** ## How FastEdit works FastEdit eliminates location tokens entirely. Instead of making the model repeat old code, it uses two things: 1. **AST awareness** — tree-sitter parses the file and finds the target function/class by name. No need to output old lines for location. 2. **A fine-tuned 1.7B SLM** — when the edit is complex, a small merge model takes the original chunk (~35 lines) + edit snippet and produces the merged result. ```python # FastEdit — model writes ONLY the change fastedit edit api.py --replace process --snippet ' try: #... except Error as e: return {"error": str(e)} ' ``` `--replace process` uses tree-sitter to find the function and auto-preserves its signature. `#...` (short form) tells the system to preserve untouched lines. The model never outputs old code — zero tokens spent on location, zero tokens spent on the signature. ## The three edit modes | Mode | What happens | Tokens | Speed | |------|-------------|--------|-------| | `--after symbol` | Text insertion after the named symbol | 0 | Instant | | `--replace symbol` (deterministic) | Context anchors splice new lines in | 0 | Instant | | `--replace symbol` (model) | 1.7B SLM merges snippet into ~35-line chunk | ~40 | <1s | The system tries deterministic text-matching first. It classifies each snippet line as "context" (matches the original) or "new" (the edit), then splices new lines between the matched anchors. This handles **74% of real edits** with zero model calls. When deterministic matching can't resolve the edit (indent structure changes, full rewrites, <2 matching lines), the 1.7B model takes over. It only ever sees a ~35-line function — never the whole file — so it's fast and accurate. ## Install **Prerequisite:** [tldr](https://github.com/parcadei/tldr-code) must be on PATH (used for AST analysis). ### Recommended — `uv tool` (handles the venv for you) ```bash # Apple Silicon (local 1.7B model via MLX) + MCP server: uv tool install 'fastedits[mlx,mcp]' # GPU servers (vLLM backend) + MCP server: uv tool install 'fastedits[vllm,mcp]' # Generic (external OpenAI-compatible server) + MCP server: uv tool install 'fastedits[mcp]' # Download the 1.7B merge model (~3 GB, one-time): fastedit pull --model mlx-8bit # Apple Silicon fastedit pull --model bf16 # Linux / GPU ``` The CLI lands at `~/.local/bin/fastedit`. Upgrade later with: ```bash uv tool upgrade fastedits ``` If it says "Nothing to upgrade" right after a fresh release lands on PyPI, uv's 10-minute package-index cache is stale. Clear it and retry: ```bash uv cache clean fastedits && uv tool upgrade fastedits ``` Or force a clean reinstall: ```bash uv tool install --reinstall 'fastedits[mlx,mcp]' ``` Drop the `mcp` extra if you only want the CLI. Drop `mlx` / `vllm` if you only want to point at an external LLM server. ### Alternatives ```bash # pipx (same idea, different tool): pipx install 'fastedits[mlx,mcp]' && fastedit pull --model mlx-8bit # Plain venv: python3 -m venv ~/.venvs/fastedit source ~/.venvs/fastedit/bin/activate pip install 'fastedits[mlx,mcp]' fastedit pull --model mlx-8bit ``` Avoid `pip install fastedits` into a Homebrew / distro-managed Python — it will fail with `error: externally-managed-environment` (PEP 668). ### Pointing at an external LLM server ```bash FASTEDIT_BACKEND=llm FASTEDIT_LLM_API_BASE=http://localhost:1234/v1 fastedit edit ... ``` Works with LM Studio, llama.cpp, Ollama (via OpenAI-compatible endpoint), vLLM, TGI, any OpenAI-API-compatible server. ## CLI ```bash # View file structure (functions, classes, line ranges) fastedit read src/app.py # Edit a function (AST-scoped merge) # replace= auto-preserves the signature; #... marks the rest of the body. fastedit edit src/app.py --replace handle_request --snippet ' validate(data) #... logger.info("done") ' # Insert new code after a symbol (0 tokens) fastedit edit src/app.py --after handle_request --snippet ' def health_check(): return {"status": "ok"} ' # Batch edits to one file fastedit batch-edit src/app.py --edits '[ {"snippet": "import redis", "after": "import json"}, {"snippet": "def cache_get(key): ...", "after": "connect"} ]' # Delete, move, rename (all instant, no model) fastedit delete src/app.py deprecated_handler # refuses if cross-file callers exist fastedit delete src/app.py deprecated_handler --force # override the safety check fastedit move src/app.py helper_func --after main fastedit rename src/app.py old_name new_name # AST-verified, skips strings/comments fastedit rename src/app.py old_name new_name --dry-run # Cross-file rename — walk a directory, skip vendor/build dirs fastedit rename-all src/ old_name new_name fastedit rename-all src/ old_name new_name --dry-run fastedit rename-all src/ old_name new_name --only function # narrow to a definition kind # Cross-file move — relocate a symbol and rewrite importers automatically fastedit move-to-file foo src/a.py src/b.py --dry-run fastedit move-to-file foo src/a.py src/b.py # Undo last edit / show diff fastedit undo src/app.py fastedit diff src/app.py ``` ## MCP server FastEdit runs as an MCP server for AI agents (Claude Code, Cursor, etc.). If you installed with the `mcp` extra above, the server binary is already on PATH as `fastedit-mcp`. ### One-liner setup ```bash fastedit mcp-install # writes ~/.claude.json (user scope) fastedit mcp-install --scope project # writes ./.mcp.json (project scope) ``` Idempotent — safe to re-run. Backs up existing config before modifying. ### Manual setup Or add the entry to `~/.claude.json` / project `.mcp.json` by hand: ```json { "mcpServers": { "fastedit": { "command": "fastedit-mcp", "type": "stdio" } } } ``` No hardcoded python paths, no `-m` invocation. Works wherever `fastedit` is on PATH. 12 tools: `fast_edit`, `fast_batch_edit`, `fast_multi_edit`, `fast_read`, `fast_search`, `fast_diff`, `fast_delete`, `fast_move`, `fast_move_to_file`, `fast_rename`, `fast_rename_all`, `fast_undo` ### Diagnosing issues ```bash fastedit doctor ``` Checks binaries, Python version, backend extras, model cache state, MCP config sanity, and tldr. Run this first when anything breaks. ### Auto-redirect Edit → fast_edit (optional) A PreToolUse hook intercepts Claude's built-in `Edit` tool and redirects to `fast_edit`. Zero tokens wasted — Edit never executes. Works on Mac, Linux, and Windows (PowerShell too). Add to `.claude/settings.json` or your project `.claude.json`: ```json { "hooks": { "PreToolUse": [ { "matcher": "Edit", "hooks": [{"type": "command", "command": "fastedit-hook"}] } ] } } ``` `fastedit-hook` is installed automatically with `uv tool install fastedits` — no paths, no `python3` vs `python` issues. ## The model FastEdit includes a fine-tuned 1.7B parameter model (Qwen2.5-Coder-1.5B architecture) trained specifically for code merging. It takes an original code chunk + edit snippet and produces the merged result. Most edits never reach the model: - `--after` is pure text insertion (0 tokens, instant) - `--replace` tries deterministic text matching first (0 tokens, instant) - Only when the snippet has complex structural changes does the 1.7B model activate The model is scoped to ~35-line chunks via AST, so it runs in <1s on Apple Silicon (MLX) or GPU (vLLM). ## Accuracy Tested across 22 structurally distinct edit patterns (73 cases): | Path | Accuracy | Tokens | Latency | |------|----------|--------|---------| | Deterministic (74% of edits) | 100% | 0 | <1ms | | Model (26% of edits) | 92% | ~40 | ~500ms | | **Combined (production)** | **~98%** | **~10 avg** | **~130ms avg** | The deterministic path handles the easy majority perfectly and for free. The model handles the complex minority. The AST scoping prevents the failure modes that plague whole-file approaches (ordering errors, content loss). Per-language model accuracy (156-example benchmark): | Language | Accuracy | |----------|----------| | Python, Java, Kotlin, C, PHP | 92% | | JavaScript, TypeScript, Rust, Swift | 85% | | Go, C++, Ruby | 77% | ## How it compares | | FastEdit | Claude Code / Codex | Aider SEARCH/REPLACE | |--|---------|-------------------|---------------------| | **How it locates the edit** | AST — names the symbol | Model outputs old lines | Model outputs SEARCH block | | **Tokens for location** | 0 | ~50% of output | ~50% of output | | **What the model sees** | ~35-line chunk | Entire file context | Entire file context | | **Failure mode** | Symbol not found (immediate, clear error) | Can't find old lines (silent misapply) | Can't find SEARCH block | | **Languages** | 13 | Any | Any | ## Supported languages Python, JavaScript, TypeScript, Rust, Go, Java, C, C++, Ruby, Swift, Kotlin, C#, PHP ## Environment variables | Variable | Default | Description | |----------|---------|-------------| | `FASTEDIT_MODEL_PATH` | `~/.cache/fastedit/models/...` | Path to model | | `FASTEDIT_BACKEND` | `mlx` | Backend: `mlx` or `llm` | | `FASTEDIT_LLM_API_BASE` | `http://127.0.0.1:8000/v1` | LLM server URL (any OpenAI-compatible) | | `FASTEDIT_LLM_MODEL` | `fastedit` | Model name to send in API requests | | `FASTEDIT_LLM_API_KEY` | `not-needed` | API key (if server requires one) | ## License MIT

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Install + configure FastEdit — AST-scoped code edits via 1.7B model

لغة النص الأصلي: الإنجليزية

2026-04-23

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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/parcadei/fastedit.