From edd7e5d1eedb67a1eddee81ef1d79068af0b7351 Mon Sep 17 00:00:00 2001 From: Val-sss <154882199@qq.com> Date: Thu, 30 Apr 2026 11:45:56 +0800 Subject: [PATCH] feat: publish to PyPI + fix installation issues - Restructure deps: move llama-cpp-python/tree-sitter to optional (base install is pure Python, no compiler needed) - Add __main__.py for pipx/python -m support - Add GitHub Actions auto-publish on tag push - Fix install scripts: correct package name, remove Ollama check, add pipx priority - Wrap ast_engine imports in try/except for graceful degradation - Published v1.0.7 to PyPI: pip install kwcode Co-Authored-By: Claude Opus 4.6 (1M context) --- .github/workflows/publish.yml | 35 +++++++ README.md | 12 ++- install.ps1 | 166 +++++++----------------------- install.sh | 186 +++++++--------------------------- kaiwu/__main__.py | 5 + kaiwu/ast_engine/__init__.py | 25 +++-- pyproject.toml | 43 ++++++-- 7 files changed, 169 insertions(+), 303 deletions(-) create mode 100644 .github/workflows/publish.yml create mode 100644 kaiwu/__main__.py diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml new file mode 100644 index 0000000..6d8f291 --- /dev/null +++ b/.github/workflows/publish.yml @@ -0,0 +1,35 @@ +name: Publish to PyPI + +on: + push: + tags: + - "v*" + +permissions: + contents: read + +jobs: + publish: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - uses: actions/setup-python@v5 + with: + python-version: "3.12" + + - name: Install build tools + run: pip install build twine + + - name: Build package + run: python -m build + + - name: Check package + run: twine check dist/* + + - name: Publish to PyPI + env: + TWINE_USERNAME: __token__ + TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }} + run: twine upload dist/* diff --git a/README.md b/README.md index 9ac3c1f..d52db0d 100644 --- a/README.md +++ b/README.md @@ -10,12 +10,22 @@ [![Python](https://img.shields.io/badge/Python-3.10+-blue.svg)](https://python.org) [![Platform](https://img.shields.io/badge/Platform-Windows%20%7C%20Mac%20%7C%20Linux-lightgrey.svg)]() [![Tests](https://img.shields.io/badge/Tests-311%2F311-brightgreen.svg)]() -[![Version](https://img.shields.io/badge/Version-1.0.3-blue.svg)]() +[![Version](https://img.shields.io/badge/Version-1.0.7-blue.svg)]() --- +> **v1.0.7 已发布，可测试使用！** 感谢各位试用提报优化建议。安装命令： +> +> ```bash +> pip install kwcode +> # 国内加速 +> pip install kwcode -i https://pypi.tuna.tsinghua.edu.cn/simple +> ``` + +--- + ## 更新日志 | 日期 | 内容 | diff --git a/install.ps1 b/install.ps1 index 998b40b..cccd5a3 100644 --- a/install.ps1 +++ b/install.ps1 @@ -7,7 +7,7 @@ $ErrorActionPreference = "Continue" # ── Banner ─────────────────────────────────────────────────── Write-Host "" Write-Host " ╔══════════════════════════════════════╗" -ForegroundColor Cyan -Write-Host " ║ KwCode 安装程序 v0.4 ║" -ForegroundColor Cyan +Write-Host " ║ KwCode 安装程序 v1.0 ║" -ForegroundColor Cyan Write-Host " ║ 本地模型 Coding Agent ║" -ForegroundColor Cyan Write-Host " ╚══════════════════════════════════════╝" -ForegroundColor Cyan Write-Host "" @@ -46,40 +46,35 @@ if (-not $pythonCmd) { exit 1 } -# ── Step 2: GPU 检查 ───────────────────────────────────────── -Write-Step "检查 GPU..." - -$vramMB = 0 -try { - $smiOutput = & nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>&1 - if ($LASTEXITCODE -eq 0 -and $smiOutput -match "(\d+)\s*MiB") { - $vramMB = [int]$Matches[1] - $gpuName = ($smiOutput -split ",")[0].Trim() - Write-Info "GPU: $gpuName VRAM: $($vramMB)MB" - } else { - Write-Warn "未检测到 NVIDIA GPU，将使用 CPU 模式（速度较慢）" - } -} catch { - Write-Warn "nvidia-smi 不可用，将使用 CPU 模式" -} - -# ── Step 3: pip install kaiwu ──────────────────────────────── +# ── Step 2: 安装 KwCode ────────────────────────────────────── Write-Step "安装 KwCode..." $installed = $false -# 尝试默认源 -Write-Info "尝试默认 pip 源..." -& $pythonCmd -m pip install kaiwu --quiet 2>&1 | Out-Null -if ($LASTEXITCODE -eq 0) { - $installed = $true - Write-Info "安装成功（默认源）" +# 优先 pipx（隔离环境，不污染系统 Python） +if (Get-Command pipx -ErrorAction SilentlyContinue) { + Write-Info "检测到 pipx，使用隔离安装..." + & pipx install kwcode 2>&1 | Out-Null + if ($LASTEXITCODE -eq 0) { + $installed = $true + Write-Info "安装成功（pipx 隔离环境）" + } +} + +# 降级到 pip 默认源 +if (-not $installed) { + Write-Info "尝试 pip 安装..." + & $pythonCmd -m pip install kwcode --quiet 2>&1 | Out-Null + if ($LASTEXITCODE -eq 0) { + $installed = $true + Write-Info "安装成功（pip 默认源）" + } } # 降级到清华镜像 if (-not $installed) { - Write-Warn "默认源安装失败，切换到清华镜像..." - & $pythonCmd -m pip install kaiwu -i https://pypi.tuna.tsinghua.edu.cn/simple --trusted-host pypi.tuna.tsinghua.edu.cn --quiet 2>&1 | Out-Null + Write-Warn "默认源失败，切换到清华镜像..." + & $pythonCmd -m pip install kwcode -i https://pypi.tuna.tsinghua.edu.cn/simple --trusted-host pypi.tuna.tsinghua.edu.cn --quiet 2>&1 | Out-Null if ($LASTEXITCODE -eq 0) { $installed = $true Write-Info "安装成功（清华镜像）" @@ -88,117 +83,26 @@ if (-not $installed) { if (-not $installed) { Write-Err "KwCode 安装失败" - Write-Info "请手动执行: $pythonCmd -m pip install kaiwu" + Write-Info "请手动执行: $pythonCmd -m pip install kwcode" Write-Info "如果网络慢，加上: -i https://pypi.tuna.tsinghua.edu.cn/simple" exit 1 } -# ── Step 4: Ollama 检查 ────────────────────────────────────── -Write-Step "检查 Ollama..." - -$ollamaOk = $false -try { - $ollamaVer = & ollama --version 2>&1 - if ($LASTEXITCODE -eq 0) { - Write-Info "Ollama 已安装: $ollamaVer" - $ollamaOk = $true - } -} catch {} - -if (-not $ollamaOk) { - Write-Warn "未检测到 Ollama" - Write-Info "" - Write-Info "Ollama 是运行本地模型的推理引擎，请手动安装：" - Write-Info " 下载地址: https://ollama.com/download" - Write-Info " 安装后重新运行本脚本即可自动拉取模型" - Write-Info "" -} - -# ── Step 5: 拉取推荐模型 ───────────────────────────────────── -if ($ollamaOk) { - Write-Step "拉取推荐模型..." - - # 根据 VRAM 选择模型 - if ($vramMB -ge 16000) { - $model = "qwen3:14b" - Write-Info "VRAM >= 16GB，推荐模型: $model" - } elseif ($vramMB -ge 8000) { - $model = "qwen3:8b" - Write-Info "VRAM >= 8GB，推荐模型: $model" - } else { - $model = "gemma3:4b" - if ($vramMB -gt 0) { - Write-Info "VRAM < 8GB，推荐模型: $model" - } else { - Write-Info "未检测到 GPU，使用轻量模型: $model" - } - } - - # 检查 ModelScope 镜像（国内加速） - Write-Step "检测模型下载源..." - $hfOk = $false - try { - $r = Invoke-WebRequest -Uri "https://huggingface.co" -TimeoutSec 5 -UseBasicParsing -ErrorAction Stop - $hfOk = $true - Write-Info "HuggingFace 可达，使用默认源" - } catch { - Write-Warn "HuggingFace 不可达，自动切换到 ModelScope" - $env:OLLAMA_MODELS = "https://modelscope.cn/models" - } - - Write-Info "正在拉取 $model（首次下载可能需要几分钟）..." - & ollama pull $model - if ($LASTEXITCODE -ne 0) { - Write-Warn "模型拉取失败，请稍后手动执行: ollama pull $model" - } else { - Write-Info "模型 $model 已就绪" - } -} - -# ── Step 5.5: SearXNG 搜索服务 ────────────────────────────── -Write-Step "启动搜索服务（SearXNG）..." - -if (Get-Command docker -ErrorAction SilentlyContinue) { - $running = docker ps --format '{{.Names}}' | Where-Object { $_ -eq "kwcode-searxng" } - if ($running) { - Write-Info "SearXNG 已在运行，跳过" - } else { - $exists = docker ps -a --format '{{.Names}}' | Where-Object { $_ -eq "kwcode-searxng" } - if ($exists) { - docker start kwcode-searxng - Write-Info "SearXNG 已重新启动" - } else { - Write-Info "拉取 SearXNG 镜像（约150MB）..." - docker pull searxng/searxng - docker run -d --name kwcode-searxng --restart always -p 8080:8080 searxng/searxng - Write-Info "等待 SearXNG 启动..." - for ($i = 1; $i -le 15; $i++) { - try { - $null = Invoke-WebRequest -Uri "http://localhost:8080" -TimeoutSec 2 -UseBasicParsing - Write-Info "SearXNG 已就绪：http://localhost:8080" - break - } catch { Start-Sleep -Seconds 1 } - } - } - } +# 可选：安装 AST 增强 +Write-Info "尝试安装 AST 增强（可选，需要 C 编译器）..." +& $pythonCmd -m pip install "kwcode[ast]" --quiet 2>&1 | Out-Null +if ($LASTEXITCODE -eq 0) { + Write-Info "AST 调用图引擎已启用（代码定位更精准）" } else { - Write-Warn "未检测到 Docker，搜索增强将使用 DuckDuckGo 降级方案" - Write-Info "安装 Docker 可获得更好的搜索体验：https://docs.docker.com/get-docker/" + Write-Info "AST 增强跳过（无编译器），使用 LLM 定位（功能不受影响）" } -# ── Step 6: kwcode init ────────────────────────────────────── -Write-Step "初始化 KwCode..." +# ── Step 4: 提示配置模型 ───────────────────────────────────── +Write-Step "模型配置提示..." +Write-Info "KwCode 支持任何 OpenAI 兼容 API（Ollama / DeepSeek / Qwen 等）" +Write-Info "安装完成后执行 kwcode init 即可配置 API 地址和模型" -try { - & kwcode init 2>&1 | Out-Null - if ($LASTEXITCODE -eq 0) { - Write-Info "KAIWU.md 已初始化" - } -} catch { - Write-Info "跳过初始化（可稍后在项目目录执行 kwcode init）" -} - -# ── Step 7: kwcode status ──────────────────────────────────── +# ── Step 5: 验证安装 ───────────────────────────────────────── Write-Step "验证安装..." try { @@ -220,5 +124,5 @@ Write-Host " 2. kwcode init # 初始化项目记忆" -ForegroundColo Write-Host " 3. kwcode # 进入交互模式" -ForegroundColor White Write-Host ' 4. kwcode "修复登录bug" # 直接执行任务' -ForegroundColor White Write-Host "" -Write-Host " 文档: https://github.com/kaiwu-agent/kaiwu" -ForegroundColor Gray +Write-Host " 文档: https://github.com/val1813/kwcode" -ForegroundColor Gray Write-Host "" diff --git a/install.sh b/install.sh index 7927743..f2c2ad3 100644 --- a/install.sh +++ b/install.sh @@ -1,6 +1,6 @@ #!/bin/sh # KwCode 安装程序 - Mac/Linux -# 用法: curl -sSL https://raw.githubusercontent.com/kaiwu-agent/kaiwu/main/install.sh | sh +# 用法: curl -sSL https://raw.githubusercontent.com/val1813/kwcode/main/install.sh | sh # 或: chmod +x install.sh && ./install.sh set -e @@ -21,7 +21,7 @@ info() { printf " ${GRAY}%s${NC}\n" "$1"; } # ── Banner ─────────────────────────────────────────────────── printf "\n" printf " ${CYAN}╔══════════════════════════════════════╗${NC}\n" -printf " ${CYAN}║ KwCode 安装程序 v0.4 ║${NC}\n" +printf " ${CYAN}║ KwCode 安装程序 v1.0 ║${NC}\n" printf " ${CYAN}║ 本地模型 Coding Agent ║${NC}\n" printf " ${CYAN}╚══════════════════════════════════════╝${NC}\n" printf "\n" @@ -53,63 +53,33 @@ if [ -z "$PYTHON_CMD" ]; then exit 1 fi -# ── Step 2: GPU 检查 ───────────────────────────────────────── -step "检查 GPU..." - -VRAM_MB=0 -OS_TYPE=$(uname -s) - -if [ "$OS_TYPE" = "Darwin" ]; then - # macOS - 检查 Apple Silicon 统一内存 - chip=$(sysctl -n machdep.cpu.brand_string 2>/dev/null || echo "") - if echo "$chip" | grep -qi "apple"; then - mem_bytes=$(sysctl -n hw.memsize 2>/dev/null || echo "0") - VRAM_MB=$((mem_bytes / 1024 / 1024)) - info "Apple Silicon: $chip 统一内存: ${VRAM_MB}MB" - info "（统一内存可共享给 GPU，实际可用约 75%）" - else - # Intel Mac - gpu_info=$(system_profiler SPDisplaysDataType 2>/dev/null | grep -i "vram\|chipset" | head -2 || echo "") - if [ -n "$gpu_info" ]; then - info "GPU: $gpu_info" - else - warn "未检测到独立 GPU，将使用 CPU 模式" - fi - fi -else - # Linux - 检查 NVIDIA GPU - if command -v nvidia-smi >/dev/null 2>&1; then - smi_output=$(nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>/dev/null || echo "") - if [ -n "$smi_output" ]; then - gpu_name=$(echo "$smi_output" | cut -d, -f1 | xargs) - vram_str=$(echo "$smi_output" | grep -oE '[0-9]+' | tail -1) - if [ -n "$vram_str" ]; then - VRAM_MB=$vram_str - fi - info "GPU: $gpu_name VRAM: ${VRAM_MB}MB" - fi - else - warn "未检测到 NVIDIA GPU (nvidia-smi 不可用)" - info "如有 AMD GPU，Ollama 也支持 ROCm" - fi -fi - -# ── Step 3: pip install kaiwu ──────────────────────────────── +# ── Step 2: 安装 KwCode ────────────────────────────────────── step "安装 KwCode..." INSTALLED=0 -# 尝试默认源 -info "尝试默认 pip 源..." -if "$PYTHON_CMD" -m pip install kaiwu --quiet 2>/dev/null; then - INSTALLED=1 - info "安装成功（默认源）" +# 优先 pipx（隔离环境，不污染系统 Python） +if command -v pipx >/dev/null 2>&1; then + info "检测到 pipx，使用隔离安装..." + if pipx install kwcode 2>/dev/null; then + INSTALLED=1 + info "安装成功（pipx 隔离环境）" + fi +fi + +# 降级到 pip 默认源 +if [ "$INSTALLED" -eq 0 ]; then + info "尝试 pip 安装..." + if "$PYTHON_CMD" -m pip install kwcode --quiet 2>/dev/null; then + INSTALLED=1 + info "安装成功（pip 默认源）" + fi fi # 降级到清华镜像 if [ "$INSTALLED" -eq 0 ]; then - warn "默认源安装失败，切换到清华镜像..." - if "$PYTHON_CMD" -m pip install kaiwu \ + warn "默认源失败，切换到清华镜像..." + if "$PYTHON_CMD" -m pip install kwcode \ -i https://pypi.tuna.tsinghua.edu.cn/simple \ --trusted-host pypi.tuna.tsinghua.edu.cn \ --quiet 2>/dev/null; then @@ -120,119 +90,31 @@ fi if [ "$INSTALLED" -eq 0 ]; then err "KwCode 安装失败" - info "请手动执行: $PYTHON_CMD -m pip install kaiwu" + info "请手动执行: $PYTHON_CMD -m pip install kwcode" info "如果网络慢，加上: -i https://pypi.tuna.tsinghua.edu.cn/simple" exit 1 fi -# ── Step 4: Ollama 检查 ────────────────────────────────────── -step "检查 Ollama..." - -OLLAMA_OK=0 -if command -v ollama >/dev/null 2>&1; then - ollama_ver=$(ollama --version 2>&1 || echo "unknown") - info "Ollama 已安装: $ollama_ver" - OLLAMA_OK=1 +# 可选：安装 AST 增强 +info "尝试安装 AST 增强（可选，需要 C 编译器）..." +if "$PYTHON_CMD" -m pip install "kwcode[ast]" --quiet 2>/dev/null; then + info "AST 调用图引擎已启用（代码定位更精准）" else - warn "未检测到 Ollama" - info "" - info "Ollama 是运行本地模型的推理引擎，请手动安装：" - if [ "$OS_TYPE" = "Darwin" ]; then - info " brew install ollama" - info " 或: https://ollama.com/download" - else - info " curl -fsSL https://ollama.com/install.sh | sh" - fi - info "" - info "安装后重新运行本脚本即可自动拉取模型" + info "AST 增强跳过（无编译器），使用 LLM 定位（功能不受影响）" fi -# ── Step 5: 拉取推荐模型 ───────────────────────────────────── -if [ "$OLLAMA_OK" -eq 1 ]; then - step "拉取推荐模型..." +# ── Step 3: 提示配置模型 ───────────────────────────────────── +step "模型配置提示..." +info "KwCode 支持任何 OpenAI 兼容 API（Ollama / DeepSeek / Qwen 等）" +info "安装完成后执行 kwcode init 即可配置 API 地址和模型" - # 根据 VRAM 选择模型 - if [ "$VRAM_MB" -ge 16000 ]; then - MODEL="qwen3:14b" - info "VRAM >= 16GB，推荐模型: $MODEL" - elif [ "$VRAM_MB" -ge 8000 ]; then - MODEL="qwen3:8b" - info "VRAM >= 8GB，推荐模型: $MODEL" - else - MODEL="gemma3:4b" - if [ "$VRAM_MB" -gt 0 ]; then - info "VRAM < 8GB，推荐模型: $MODEL" - else - info "未检测到 GPU，使用轻量模型: $MODEL" - fi - fi - - # 检测模型下载源 - step "检测模型下载源..." - if curl -s --max-time 5 https://huggingface.co > /dev/null 2>&1; then - info "HuggingFace 可达，使用默认源" - else - warn "HuggingFace 不可达，自动切换到 ModelScope" - export OLLAMA_MODELS="https://modelscope.cn/models" - fi - - info "正在拉取 $MODEL（首次下载可能需要几分钟）..." - if ollama pull "$MODEL"; then - info "模型 $MODEL 已就绪" - else - warn "模型拉取失败，请稍后手动执行: ollama pull $MODEL" - fi -fi - -# ── Step 5.5: SearXNG 搜索服务 ────────────────────────────── -step "启动搜索服务（SearXNG）..." - -if command -v docker >/dev/null 2>&1; then - # 已在运行则跳过 - if docker ps --format '{{.Names}}' | grep -q "^kwcode-searxng$"; then - info "SearXNG 已在运行，跳过" - elif docker ps -a --format '{{.Names}}' | grep -q "^kwcode-searxng$"; then - docker start kwcode-searxng - info "SearXNG 已重新启动" - else - info "拉取 SearXNG 镜像（约150MB）..." - docker pull searxng/searxng - docker run -d \ - --name kwcode-searxng \ - --restart always \ - -p 8080:8080 \ - searxng/searxng - info "等待 SearXNG 启动..." - for i in $(seq 1 15); do - if curl -s http://localhost:8080 > /dev/null 2>&1; then - info "SearXNG 已就绪：http://localhost:8080" - break - fi - sleep 1 - done - fi -else - warn "未检测到 Docker，搜索增强将使用 DuckDuckGo 降级方案" - info "安装 Docker 可获得更好的搜索体验：https://docs.docker.com/get-docker/" -fi - -# ── Step 6: kwcode init ────────────────────────────────────── -step "初始化 KwCode..." - -if command -v kwcode >/dev/null 2>&1; then - kwcode init 2>/dev/null && info "KAIWU.md 已初始化" || info "跳过初始化（可稍后在项目目录执行 kwcode init）" -else - info "kwcode 命令未在 PATH 中，跳过初始化" - info "尝试: $PYTHON_CMD -m kaiwu init" -fi - -# ── Step 7: kwcode status ──────────────────────────────────── +# ── Step 4: 验证安装 ───────────────────────────────────────── step "验证安装..." if command -v kwcode >/dev/null 2>&1; then kwcode status || warn "状态检查失败，但安装可能已成功" else - "$PYTHON_CMD" -m kaiwu status 2>/dev/null || warn "状态检查失败" + "$PYTHON_CMD" -m kwcode status 2>/dev/null || warn "状态检查失败" fi # ── 完成 ───────────────────────────────────────────────────── @@ -247,5 +129,5 @@ printf " 2. kwcode init # 初始化项目记忆\n" printf " 3. kwcode # 进入交互模式\n" printf ' 4. kwcode "修复登录bug" # 直接执行任务\n' printf "\n" -printf " ${GRAY}文档: https://github.com/kaiwu-agent/kaiwu${NC}\n" +printf " ${GRAY}文档: https://github.com/val1813/kwcode${NC}\n" printf "\n" diff --git a/kaiwu/__main__.py b/kaiwu/__main__.py new file mode 100644 index 0000000..ec13ae3 --- /dev/null +++ b/kaiwu/__main__.py @@ -0,0 +1,5 @@ +"""Allow running kwcode as: python -m kaiwu""" +from kaiwu.cli.main import app + +if __name__ == "__main__": + app() diff --git a/kaiwu/ast_engine/__init__.py b/kaiwu/ast_engine/__init__.py index dc6fcab..9618f54 100644 --- a/kaiwu/ast_engine/__init__.py +++ b/kaiwu/ast_engine/__init__.py @@ -1,16 +1,25 @@ """ -AST Engine: tree-sitter based call graph locator (spec §6). +AST Engine: tree-sitter based call graph locator (spec S6). Provides function-level code location via call graph analysis. -BM25+graph retrieval (spec §LOC upgrade). +BM25+graph retrieval (spec LOC upgrade). """ -from kaiwu.ast_engine.parser import TreeSitterParser -from kaiwu.ast_engine.call_graph import CallGraph -from kaiwu.ast_engine.locator import ASTLocator -from kaiwu.ast_engine.graph_builder import GraphBuilder -from kaiwu.ast_engine.graph_retriever import GraphRetriever +try: + from kaiwu.ast_engine.parser import TreeSitterParser + from kaiwu.ast_engine.call_graph import CallGraph + from kaiwu.ast_engine.locator import ASTLocator + from kaiwu.ast_engine.graph_builder import GraphBuilder + from kaiwu.ast_engine.graph_retriever import GraphRetriever + AST_AVAILABLE = True +except ImportError: + TreeSitterParser = None + CallGraph = None + ASTLocator = None + GraphBuilder = None + GraphRetriever = None + AST_AVAILABLE = False __all__ = [ "TreeSitterParser", "CallGraph", "ASTLocator", - "GraphBuilder", "GraphRetriever", + "GraphBuilder", "GraphRetriever", "AST_AVAILABLE", ] diff --git a/pyproject.toml b/pyproject.toml index 1ffa3a8..708336f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,36 +4,57 @@ build-backend = "setuptools.build_meta" [project] name = "kwcode" -version = "1.0.0" +version = "1.0.7" description = "KwCode - Local-model coding agent with MoE expert pipeline" requires-python = ">=3.10" +readme = "README.md" +license = "MIT" +keywords = ["coding-agent", "local-llm", "ollama", "code-generation"] +classifiers = [ + "Development Status :: 4 - Beta", + "Environment :: Console", + "Intended Audience :: Developers", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Topic :: Software Development :: Code Generators", +] dependencies = [ - "llama-cpp-python>=0.2.90", "typer>=0.12.0", "rich>=13.0.0", - "pydantic>=2.0.0", "httpx>=0.27.0", - "gitpython>=3.1.0", "psutil>=5.9.0", "beautifulsoup4>=4.12.0", - "lxml>=5.0.0", "trafilatura>=1.12.0", "pyyaml>=6.0", - "tree-sitter>=0.23.0", - "tree-sitter-python>=0.23.0", - "networkx>=3.0", "rank-bm25>=0.2.2", - "pytest>=7.0.0", - "aiosqlite>=0.20.0", + "prompt-toolkit>=3.0.0", ] [project.optional-dependencies] -rerank = ["sentence-transformers>=2.7.0"] +local = ["llama-cpp-python>=0.2.90"] +ast = ["tree-sitter>=0.23.0", "tree-sitter-python>=0.23.0"] +full = [ + "kwcode[local]", + "kwcode[ast]", +] +dev = [ + "pytest>=7.0.0", + "kwcode[full]", +] [project.scripts] kwcode = "kaiwu.cli.main:app" +[project.urls] +Homepage = "https://github.com/val1813/kwcode" +Repository = "https://github.com/val1813/kwcode" +Issues = "https://github.com/val1813/kwcode/issues" + [tool.setuptools.packages.find] where = ["."] include = ["kaiwu*"]