Refactor setup: new/update detection, split Python servers, add MCP server
- laptop_full_setup.sh now handles both fresh install and updates cleanly (detects existing install, --force flag to overwrite config files) - server.py: standalone RAG server with AST-aware code chunking (Python), pattern-split for JS/TS/Go, /ingest/repo and /webhook/gitea|github endpoints - mcp_server.py: new MCP server (port 8002/SSE) with Claude Code-equivalent tools: bash, file ops, ripgrep search, git ops, Gitea API, GitHub API, RAG repo ingest - docker-compose: adds mcp-server service, workspace volume, env_file for tokens - .env preserved on update (tokens never overwritten) - GPU: OLLAMA_NUM_GPU=999 auto-adapts to any VRAM size (no hard-coded 6GB) - ZIM downloads remain in kiwix_download.sh (separate, large files) https://claude.ai/code/session_012gDnantBmFTWZGCiKyjazx
This commit is contained in:
Claude
Regular → Executable
+339
-558
File diff suppressed because it is too large
Load Diff
+203
@@ -0,0 +1,203 @@
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#!/usr/bin/env python3
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"""
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MCP Server — Claude Code-equivalent tools for Open WebUI / Claude Code CLI.
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Tools: bash, file read/write/list, code search, git ops, Gitea API, repo ingest.
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Connects via SSE on port 8002 — add to Open WebUI Tools or ~/.claude/mcp.json
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"""
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import os, subprocess, textwrap
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from pathlib import Path
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import httpx
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from mcp.server.fastmcp import FastMCP
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WORKSPACE = Path(os.getenv("WORKSPACE_DIR", "/workspace"))
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REPOS_DIR = Path(os.getenv("REPOS_DIR", "/repos"))
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GITEA_URL = os.getenv("GITEA_URL", "http://gitea:3000")
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GITEA_TOKEN = os.getenv("GITEA_TOKEN", "")
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GITHUB_TOKEN= os.getenv("GITHUB_TOKEN","")
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RAG_URL = os.getenv("RAG_URL", "http://rag-server:8001")
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mcp = FastMCP("local-dev-tools")
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# ── bash ──────────────────────────────────────────────────────────────────────
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@mcp.tool()
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def bash(command: str, cwd: str = "") -> str:
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"""Run a shell command. Default cwd is /workspace."""
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work = Path(cwd) if cwd else WORKSPACE
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work.mkdir(parents=True, exist_ok=True)
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try:
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r = subprocess.run(command, shell=True, cwd=work, timeout=120,
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capture_output=True, text=True)
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out = r.stdout + (f"\n[stderr]\n{r.stderr}" if r.stderr else "")
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if r.returncode != 0:
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out += f"\n[exit {r.returncode}]"
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return out or "(no output)"
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except subprocess.TimeoutExpired:
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return "[timeout after 120s]"
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except Exception as e:
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return f"[error] {e}"
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# ── file ops ──────────────────────────────────────────────────────────────────
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@mcp.tool()
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def read_file(path: str) -> str:
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"""Read a file. Use absolute path or relative to /workspace."""
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p = Path(path) if Path(path).is_absolute() else WORKSPACE / path
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if not p.exists():
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return f"[not found] {p}"
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if p.stat().st_size > 500_000:
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return f"[too large — {p.stat().st_size//1024}KB]"
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return p.read_text(encoding="utf-8", errors="replace")
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@mcp.tool()
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def write_file(path: str, content: str) -> str:
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"""Write content to a file (creates parent dirs). Relative to /workspace."""
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p = Path(path) if Path(path).is_absolute() else WORKSPACE / path
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p.parent.mkdir(parents=True, exist_ok=True)
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p.write_text(content, encoding="utf-8")
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return f"Wrote {len(content)} chars to {p}"
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@mcp.tool()
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def list_files(path: str = "", pattern: str = "**/*") -> str:
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"""List files matching a glob pattern."""
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base = Path(path) if path else WORKSPACE
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if not base.exists():
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return f"[not found] {base}"
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files = sorted(str(f.relative_to(base)) for f in base.glob(pattern) if f.is_file())
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return "\n".join(files[:500]) or "(empty)"
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@mcp.tool()
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def search_code(query: str, path: str = "", glob: str = "",
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case_sensitive: bool = False) -> str:
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"""Search file contents with ripgrep. Returns file:line matches."""
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base = path or str(WORKSPACE)
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cmd = ["rg", "--line-number", "--no-heading"]
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if not case_sensitive:
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cmd.append("-i")
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if glob:
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cmd += ["-g", glob]
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cmd += [query, base]
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try:
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r = subprocess.run(cmd, capture_output=True, text=True, timeout=30)
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lines = r.stdout.strip().splitlines()
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if len(lines) > 200:
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lines = lines[:200] + [f"… ({len(r.stdout.splitlines())-200} more)"]
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return "\n".join(lines) or "(no matches)"
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except FileNotFoundError:
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# ripgrep not installed, fall back to grep
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r = subprocess.run(["grep", "-rn", query, base],
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capture_output=True, text=True, timeout=30)
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return r.stdout[:8000] or "(no matches)"
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except Exception as e:
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return f"[error] {e}"
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# ── git ───────────────────────────────────────────────────────────────────────
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def _git(args: list[str], repo: str = "") -> str:
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cwd = Path(repo) if repo else WORKSPACE
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r = subprocess.run(["git"] + args, cwd=cwd,
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capture_output=True, text=True, timeout=60)
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return (r.stdout + r.stderr).strip() or "(no output)"
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@mcp.tool()
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def git_status(repo: str = "") -> str:
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"""Show git status of a repo (default: /workspace)."""
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return _git(["status", "--short"], repo)
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@mcp.tool()
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def git_diff(repo: str = "", cached: bool = False) -> str:
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"""Show git diff (staged if cached=True)."""
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args = ["diff", "--stat", "--cached"] if cached else ["diff", "--stat"]
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return _git(args, repo) + "\n\n" + _git(
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["diff", "--cached"] if cached else ["diff"], repo)
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@mcp.tool()
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def git_log(repo: str = "", n: int = 10) -> str:
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"""Show last n git commits."""
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return _git(["log", f"-{n}", "--oneline", "--decorate"], repo)
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@mcp.tool()
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def git_commit(message: str, repo: str = "", add_all: bool = True) -> str:
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"""Stage all changes and create a commit."""
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if add_all:
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_git(["add", "-A"], repo)
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return _git(["commit", "-m", message], repo)
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@mcp.tool()
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def git_checkout(branch: str, repo: str = "", create: bool = False) -> str:
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"""Checkout a branch, optionally creating it."""
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args = ["checkout", "-b", branch] if create else ["checkout", branch]
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return _git(args, repo)
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# ── Gitea API ─────────────────────────────────────────────────────────────────
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def _gitea(method: str, path: str, body: dict = {}) -> dict:
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if not GITEA_TOKEN:
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return {"error": "GITEA_TOKEN not set in .env"}
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url = f"{GITEA_URL}/api/v1{path}"
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headers = {"Authorization": f"token {GITEA_TOKEN}",
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"Content-Type": "application/json"}
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r = httpx.request(method, url, json=body or None, headers=headers, timeout=30)
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try:
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return r.json()
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except Exception:
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return {"status": r.status_code, "text": r.text}
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@mcp.tool()
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def gitea_list_repos() -> str:
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"""List your Gitea repos."""
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repos = _gitea("GET", "/repos/search?limit=50")
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if "error" in repos:
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return repos["error"]
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return "\n".join(f"{r['full_name']} — {r.get('description','')}"
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for r in repos.get("data", []))
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@mcp.tool()
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def gitea_create_repo(name: str, private: bool = True, description: str = "") -> str:
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"""Create a new Gitea repository."""
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r = _gitea("POST", "/user/repos",
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{"name": name, "private": private, "description": description,
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"auto_init": True, "default_branch": "main"})
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return r.get("html_url") or str(r)
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@mcp.tool()
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def gitea_create_issue(repo: str, title: str, body: str = "") -> str:
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"""Create an issue on a Gitea repo (format: owner/repo)."""
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r = _gitea("POST", f"/repos/{repo}/issues", {"title": title, "body": body})
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return r.get("html_url") or str(r)
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# ── GitHub API ────────────────────────────────────────────────────────────────
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@mcp.tool()
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def github_api(method: str, endpoint: str, body: str = "") -> str:
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"""Call the GitHub REST API. endpoint e.g. /repos/owner/repo/issues"""
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if not GITHUB_TOKEN:
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return "GITHUB_TOKEN not set in .env"
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import json as _json
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headers = {"Authorization": f"Bearer {GITHUB_TOKEN}",
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"Accept": "application/vnd.github+json"}
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r = httpx.request(method.upper(), f"https://api.github.com{endpoint}",
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json=_json.loads(body) if body else None,
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headers=headers, timeout=30)
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try:
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return _json.dumps(r.json(), indent=2)
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except Exception:
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return r.text
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# ── RAG ingest ────────────────────────────────────────────────────────────────
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@mcp.tool()
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def ingest_repo(url: str, name: str = "", branch: str = "main") -> str:
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"""Clone a git repo and index it in the RAG code collection."""
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r = httpx.post(f"{RAG_URL}/ingest/repo",
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json={"url": url, "name": name, "branch": branch}, timeout=300)
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return r.text
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@mcp.tool()
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def rag_health() -> str:
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"""Check RAG server status and indexed document counts."""
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try:
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r = httpx.get(f"{RAG_URL}/health", timeout=10)
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return r.text
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except Exception as e:
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return f"RAG server unreachable: {e}"
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if __name__ == "__main__":
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import uvicorn
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app = mcp.get_asgi_app()
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uvicorn.run(app, host="0.0.0.0", port=8002)
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@@ -0,0 +1,281 @@
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#!/usr/bin/env python3
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"""
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RAG Server — code-aware chunking, multi-collection, repo ingest, webhooks.
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Collections: papers (PDFs/text), code (source files, AST-split for Python)
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"""
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import ast, fnmatch, hashlib, json, logging, os, re, subprocess, threading, time
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from pathlib import Path
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from typing import Any, Optional
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import chromadb
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import httpx
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from chromadb.utils.embedding_functions import OllamaEmbeddingFunction
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from fastapi import FastAPI, HTTPException, Request, BackgroundTasks
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel
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logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")
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log = logging.getLogger("rag")
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OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
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CHROMA_URL = os.getenv("CHROMA_URL", "http://chromadb:8000")
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EMBED_MODEL = os.getenv("EMBED_MODEL", "nomic-embed-text")
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CHAT_MODEL = os.getenv("CHAT_MODEL", "qwen2.5:14b")
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PAPERS_DIR = Path(os.getenv("PAPERS_DIR", "/papers"))
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REPOS_DIR = Path(os.getenv("REPOS_DIR", "/repos"))
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TOP_K = int(os.getenv("TOP_K", "6"))
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CODE_EXTS = {".py",".js",".ts",".tsx",".jsx",".go",".rs",".java",".c",".cpp",
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".h",".hpp",".cs",".rb",".sh",".yaml",".yml",".toml",".sql",".md"}
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SKIP_DIRS = {"node_modules",".git","__pycache__","dist","build",".venv",
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"venv","env",".next","vendor","target","bin","obj"}
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SKIP_FILES = {"package-lock.json","yarn.lock","pnpm-lock.yaml","Cargo.lock"}
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MAX_BYTES = 400_000
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app = FastAPI(title="RAG Server")
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app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])
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# ── ChromaDB ──────────────────────────────────────────────────────────────────
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def _embed_fn():
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return OllamaEmbeddingFunction(
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url=f"{OLLAMA_URL}/api/embeddings", model_name=EMBED_MODEL)
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def _chroma():
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host, port = CHROMA_URL.replace("http://","").split(":")
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return chromadb.HttpClient(host=host, port=int(port))
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def get_col(name: str):
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return _chroma().get_or_create_collection(name, embedding_function=_embed_fn())
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# ── chunkers ─────────────────────────────────────────────────────────────────
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def _doc_id(text: str, key: str) -> str:
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return hashlib.md5(f"{key}|{text[:200]}".encode()).hexdigest()
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def _sliding(text: str, size=1000, overlap=150) -> list[str]:
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chunks, i = [], 0
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while i < len(text):
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chunks.append(text[i:i+size])
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i += size - overlap
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return [c for c in chunks if c.strip()]
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def _chunk_python(src: str) -> list[tuple[str,str]]:
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try:
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tree = ast.parse(src)
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except SyntaxError:
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return []
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lines = src.splitlines()
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out = []
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for node in ast.iter_child_nodes(tree):
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if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef)):
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chunk = "\n".join(lines[node.lineno-1:node.end_lineno])
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out.append((node.name, chunk[:4000]))
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return out
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def _chunk_file(path: Path, src: str) -> list[tuple[str,str]]:
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if path.suffix == ".py":
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pairs = _chunk_python(src)
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if pairs:
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return pairs
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# function/class boundary split for JS/TS/Go/Rust etc.
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pat = re.compile(
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r'(?:^|\n)(?=(?:export\s+)?(?:async\s+)?(?:function|class|const\s+\w+\s*=\s*(?:async\s+)?\()'
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r'|^func |^type |^impl |^pub fn |^fn )',
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re.MULTILINE)
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parts = [p.strip() for p in pat.split(src) if p.strip()]
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if len(parts) > 1:
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return [(f"s{i}", p[:4000]) for i, p in enumerate(parts)]
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return [(f"c{i}", c) for i, c in enumerate(_sliding(src, 1200, 200))]
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# ── ingest helpers ────────────────────────────────────────────────────────────
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def ingest_file(col, fpath: Path, repo: str = ""):
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if fpath.stat().st_size > MAX_BYTES or fpath.name in SKIP_FILES:
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return
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if any(fnmatch.fnmatch(fpath.name, p) for p in ("*.min.js","*.min.css","*.map")):
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return
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try:
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src = fpath.read_text(encoding="utf-8", errors="ignore")
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except Exception:
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return
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if not src.strip():
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return
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rel = str(fpath)
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pairs = _chunk_file(fpath, src) if fpath.suffix in CODE_EXTS else \
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[(f"c{i}", c) for i, c in enumerate(_sliding(src))]
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ids, docs, metas = [], [], []
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for label, chunk in pairs:
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if not chunk.strip():
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continue
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ids.append(_doc_id(chunk, rel+label))
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docs.append(chunk)
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metas.append({"source": rel, "label": label, "repo": repo,
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"lang": fpath.suffix.lstrip(".")})
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if ids:
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col.upsert(ids=ids, documents=docs, metadatas=metas)
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def ingest_dir(col, directory: Path, repo: str = "") -> int:
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count = 0
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for f in directory.rglob("*"):
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if not f.is_file():
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continue
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if any(p in f.parts for p in SKIP_DIRS):
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continue
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ingest_file(col, f, repo)
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count += 1
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log.info("Indexed %d files from %s", count, directory)
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return count
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def ingest_pdfs(col) -> int:
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try:
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import pypdf
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except ImportError:
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log.warning("pypdf not installed — skipping PDFs")
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return 0
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n = 0
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for pdf in PAPERS_DIR.glob("*.pdf"):
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try:
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text = "\n".join(p.extract_text() or ""
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for p in pypdf.PdfReader(str(pdf)).pages)
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for i, chunk in enumerate(_sliding(text)):
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col.upsert(ids=[_doc_id(chunk, str(pdf)+str(i))],
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documents=[chunk],
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metadatas=[{"source": str(pdf), "label": f"p{i}",
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"repo": "", "lang": "pdf"}])
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n += 1
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except Exception as e:
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log.warning("PDF %s: %s", pdf.name, e)
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return n
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# ── startup ───────────────────────────────────────────────────────────────────
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def _startup_index():
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# wait for embed model
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for _ in range(40):
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try:
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r = httpx.get(f"{OLLAMA_URL}/api/tags", timeout=5)
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if any(EMBED_MODEL in m["name"] for m in r.json().get("models", [])):
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break
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except Exception:
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pass
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log.info("Waiting for embed model %s…", EMBED_MODEL)
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time.sleep(5)
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code_col = get_col("code")
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papers_col = get_col("papers")
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for d in REPOS_DIR.iterdir():
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if d.is_dir():
|
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ingest_dir(code_col, d, d.name)
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ingest_pdfs(papers_col)
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for f in PAPERS_DIR.glob("*.txt"):
|
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ingest_file(papers_col, f)
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||||
log.info("Startup index complete")
|
||||
|
||||
@app.on_event("startup")
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||||
async def on_startup():
|
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threading.Thread(target=_startup_index, daemon=True).start()
|
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|
||||
# ── endpoints ─────────────────────────────────────────────────────────────────
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||||
@app.get("/health")
|
||||
async def health():
|
||||
try:
|
||||
cc = _chroma()
|
||||
return {"status": "ok",
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"code": cc.get_collection("code", embedding_function=_embed_fn()).count(),
|
||||
"papers": cc.get_collection("papers", embedding_function=_embed_fn()).count(),
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||||
"embed": EMBED_MODEL, "chat": CHAT_MODEL}
|
||||
except Exception as e:
|
||||
return {"status": "error", "detail": str(e)}
|
||||
|
||||
class RepoRequest(BaseModel):
|
||||
url: str
|
||||
name: str = ""
|
||||
branch: str = "main"
|
||||
|
||||
@app.post("/ingest/repo")
|
||||
async def ingest_repo(req: RepoRequest):
|
||||
name = req.name or req.url.rstrip("/").split("/")[-1].removesuffix(".git")
|
||||
dest = REPOS_DIR / name
|
||||
try:
|
||||
if dest.exists():
|
||||
subprocess.run(["git","pull"], cwd=dest, check=True, timeout=120)
|
||||
else:
|
||||
subprocess.run(["git","clone","--depth=1","-b",req.branch,
|
||||
req.url, str(dest)], check=True, timeout=300)
|
||||
except subprocess.CalledProcessError as e:
|
||||
raise HTTPException(400, str(e))
|
||||
n = ingest_dir(get_col("code"), dest, name)
|
||||
return {"status": "ok", "repo": name, "files": n}
|
||||
|
||||
@app.post("/ingest/papers")
|
||||
async def trigger_papers(bg: BackgroundTasks):
|
||||
bg.add_task(ingest_pdfs, get_col("papers"))
|
||||
return {"status": "queued"}
|
||||
|
||||
async def _webhook(payload: dict):
|
||||
repo = payload.get("repository") or {}
|
||||
url = repo.get("clone_url") or repo.get("html_url","")
|
||||
name = repo.get("name","unknown")
|
||||
if not url:
|
||||
return {"status": "ignored"}
|
||||
dest = REPOS_DIR / name
|
||||
if dest.exists():
|
||||
subprocess.run(["git","pull"], cwd=dest, timeout=120)
|
||||
else:
|
||||
subprocess.run(["git","clone","--depth=1",url,str(dest)], timeout=300)
|
||||
n = ingest_dir(get_col("code"), dest, name)
|
||||
return {"status": "ok", "repo": name, "files": n}
|
||||
|
||||
@app.post("/webhook/gitea")
|
||||
async def webhook_gitea(r: Request): return await _webhook(await r.json())
|
||||
|
||||
@app.post("/webhook/github")
|
||||
async def webhook_github(r: Request): return await _webhook(await r.json())
|
||||
|
||||
# ── RAG chat ──────────────────────────────────────────────────────────────────
|
||||
class ChatRequest(BaseModel):
|
||||
model: str = CHAT_MODEL
|
||||
messages: list[dict[str,Any]]
|
||||
stream: bool = False
|
||||
collections: list[str] = ["code","papers"]
|
||||
|
||||
def _context(query: str, cols: list[str]) -> str:
|
||||
parts = []
|
||||
for cname in cols:
|
||||
try:
|
||||
col = get_col(cname)
|
||||
if col.count() == 0:
|
||||
continue
|
||||
res = col.query(query_texts=[query], n_results=min(TOP_K, col.count()))
|
||||
for doc, meta in zip(res["documents"][0], res["metadatas"][0]):
|
||||
parts.append(f"### {meta.get('source','')}:{meta.get('label','')}\n"
|
||||
f"```{meta.get('lang','')}\n{doc}\n```")
|
||||
except Exception as e:
|
||||
log.warning("col %s: %s", cname, e)
|
||||
return "\n\n".join(parts)
|
||||
|
||||
@app.post("/v1/chat/completions")
|
||||
async def chat(req: ChatRequest):
|
||||
query = next((m["content"] for m in reversed(req.messages)
|
||||
if m.get("role")=="user"), "")
|
||||
context = _context(query, req.collections)
|
||||
msgs = [{"role":"system","content":
|
||||
"You are a helpful coding assistant. Use the retrieved context below.\n\n"
|
||||
f"## Context\n{context}"}] + req.messages
|
||||
|
||||
payload = {"model": req.model, "messages": msgs, "stream": req.stream}
|
||||
|
||||
if req.stream:
|
||||
async def gen():
|
||||
async with httpx.AsyncClient(timeout=300) as client:
|
||||
async with client.stream("POST",
|
||||
f"{OLLAMA_URL}/v1/chat/completions", json=payload) as r:
|
||||
async for chunk in r.aiter_bytes():
|
||||
yield chunk
|
||||
return StreamingResponse(gen(), media_type="text/event-stream")
|
||||
|
||||
async with httpx.AsyncClient(timeout=300) as client:
|
||||
r = await client.post(f"{OLLAMA_URL}/v1/chat/completions", json=payload)
|
||||
return r.json()
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
uvicorn.run("server:app", host="0.0.0.0", port=8001, reload=False)
|
||||
Reference in New Issue
Block a user