From 8a1ac05f1e89fdd19480c8033163ec468edc9d14 Mon Sep 17 00:00:00 2001 From: Claude Date: Fri, 20 Mar 2026 15:14:10 +0000 Subject: [PATCH] Add single self-contained local-ai-setup.sh MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Merges all components into one script — no separate server files needed. Embeds server.py (RAG) and mcp_server.py (MCP) as inline heredocs. - Auto-detects VRAM and sets models + context window accordingly: 6GB → 7B models, 8k ctx 8GB+ → 14B chat + 7B code, 16k ctx 16GB → 14B models, 32k ctx (V100/A100 friendly) - New install or update (detects existing compose) - --force flag to overwrite config files - --no-pull to skip model download prompt - Adds fetch_url tool to MCP server - Optional DeepSeek-R1:14b pull for reasoning tasks https://claude.ai/code/session_012gDnantBmFTWZGCiKyjazx --- local-ai-setup.sh | 837 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 837 insertions(+) create mode 100755 local-ai-setup.sh diff --git a/local-ai-setup.sh b/local-ai-setup.sh new file mode 100755 index 0000000..7c61c9f --- /dev/null +++ b/local-ai-setup.sh @@ -0,0 +1,837 @@ +#!/usr/bin/env bash +# Local AI Stack — single script, new install or update +# Usage: ./local-ai-setup.sh [--force] [--no-pull] +set -euo pipefail + +RED='\033[0;31m'; GREEN='\033[0;32m'; YELLOW='\033[1;33m' +CYAN='\033[0;36m'; BOLD='\033[1m'; NC='\033[0m' +info() { echo -e "${CYAN}[..]${NC} $*"; } +ok() { echo -e "${GREEN}[OK]${NC} $*"; } +warn() { echo -e "${YELLOW}[!!]${NC} $*"; } +section() { echo -e "\n${BOLD}━━━ $* ━━━${NC}"; } + +FORCE=false; NO_PULL=false +for a in "$@"; do [[ "$a" == "--force" ]] && FORCE=true; [[ "$a" == "--no-pull" ]] && NO_PULL=true; done + +BASE="$HOME/docker/ai-stack" +LOCAL_IP=$(ip route get 1.1.1.1 2>/dev/null | grep -oP 'src \K\S+' || hostname -I | awk '{print $1}') +[[ -z "$LOCAL_IP" ]] && read -rp "Enter LAN IP: " LOCAL_IP + +IS_UPDATE=false; [[ -f "$BASE/docker-compose.yml" ]] && IS_UPDATE=true + +# ── detect VRAM and set models accordingly ──────────────────────────────────── +VRAM_GB=$(nvidia-smi --query-gpu=memory.total --format=csv,noheader,nounits 2>/dev/null \ + | head -1 | awk '{printf "%d", $1/1024}' 2>/dev/null || echo "0") + +if [[ "$VRAM_GB" -ge 14 ]]; then + CHAT_MODEL="qwen2.5:14b"; CODE_MODEL="qwen2.5-coder:14b" + CTX=32768; TIER="16GB — 14B models + 32k context" +elif [[ "$VRAM_GB" -ge 8 ]]; then + CHAT_MODEL="qwen2.5:14b"; CODE_MODEL="qwen2.5-coder:7b" + CTX=16384; TIER="8-16GB — 14B chat, 7B code, 16k context" +elif [[ "$VRAM_GB" -ge 4 ]]; then + CHAT_MODEL="qwen2.5:7b"; CODE_MODEL="qwen2.5-coder:7b" + CTX=8192; TIER="6GB — 7B models, 8k context" +else + CHAT_MODEL="qwen2.5:7b"; CODE_MODEL="qwen2.5-coder:7b" + CTX=4096; TIER="CPU-only — 7B models, 4k context" +fi +EMBED_MODEL="nomic-embed-text" + +section "Local AI Stack — $($IS_UPDATE && echo UPDATE || echo NEW INSTALL)" +info "Base : $BASE" +info "IP : $LOCAL_IP" +info "GPU : ${VRAM_GB}GB VRAM → $TIER" + +write_if_new() { + local dest="$1"; local body; body=$(cat) + if [[ ! -f "$dest" ]] || $FORCE; then + printf '%s\n' "$body" > "$dest"; ok "Wrote $(basename "$dest")" + else + info "Kept $(basename "$dest") (--force to overwrite)" + fi +} + +# ── prereqs (new install only) ──────────────────────────────────────────────── +if ! $IS_UPDATE; then + section "Prerequisites" + if ! command -v docker &>/dev/null; then + info "Installing Docker..." + curl -fsSL https://get.docker.com | sh + sudo usermod -aG docker "$USER" + warn "Run: newgrp docker (or log out/in)" + else + ok "Docker: $(docker --version | cut -d' ' -f3)" + fi + + if command -v nvidia-smi &>/dev/null && ! dpkg -l 2>/dev/null | grep -q nvidia-container-toolkit; then + info "Installing NVIDIA Container Toolkit..." + dist=$(. /etc/os-release && echo "$ID$VERSION_ID") + curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \ + | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg + curl -fsSL "https://nvidia.github.io/libnvidia-container/$dist/libnvidia-container.list" \ + | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \ + | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list + sudo apt-get update -qq && sudo apt-get install -y nvidia-container-toolkit + sudo nvidia-ctk runtime configure --runtime=docker && sudo systemctl restart docker + ok "NVIDIA Container Toolkit installed" + fi + command -v rg &>/dev/null || sudo apt-get install -y ripgrep +fi + +# ── directories ─────────────────────────────────────────────────────────────── +section "Directories" +for d in papers repos workspace index searxng invokeai-data invokeai-outputs kiwix gitea portainer-data logs; do + mkdir -p "$BASE/$d" +done +ok "Ready under $BASE" + +# ============================================================================= +section "Writing server.py (RAG)" +# ============================================================================= +write_if_new "$BASE/server.py" << 'PY' +import ast, fnmatch, hashlib, json, logging, os, re, subprocess, threading, time +from pathlib import Path +from typing import Any +import chromadb, httpx +from chromadb.utils.embedding_functions import OllamaEmbeddingFunction +from fastapi import FastAPI, HTTPException, Request, BackgroundTasks +from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import StreamingResponse +from pydantic import BaseModel + +logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s") +log = logging.getLogger("rag") + +OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434") +CHROMA_URL = os.getenv("CHROMA_URL", "http://chromadb:8000") +EMBED_MODEL = os.getenv("EMBED_MODEL", "nomic-embed-text") +CHAT_MODEL = os.getenv("CHAT_MODEL", "qwen2.5:14b") +PAPERS_DIR = Path(os.getenv("PAPERS_DIR", "/papers")) +REPOS_DIR = Path(os.getenv("REPOS_DIR", "/repos")) +TOP_K = int(os.getenv("TOP_K", "6")) + +CODE_EXTS = {".py",".js",".ts",".tsx",".jsx",".go",".rs",".java",".c",".cpp", + ".h",".cs",".rb",".sh",".yaml",".yml",".toml",".sql",".md"} +SKIP_DIRS = {"node_modules",".git","__pycache__","dist","build",".venv","venv","target"} +MAX_BYTES = 400_000 + +app = FastAPI(title="RAG Server") +app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"]) + +def _embed_fn(): + return OllamaEmbeddingFunction(url=f"{OLLAMA_URL}/api/embeddings", model_name=EMBED_MODEL) + +def _chroma(): + host, port = CHROMA_URL.replace("http://","").split(":") + return chromadb.HttpClient(host=host, port=int(port)) + +def get_col(name): + return _chroma().get_or_create_collection(name, embedding_function=_embed_fn()) + +def _doc_id(text, key): + return hashlib.md5(f"{key}|{text[:200]}".encode()).hexdigest() + +def _sliding(text, size=1000, overlap=150): + chunks, i = [], 0 + while i < len(text): + chunks.append(text[i:i+size]); i += size - overlap + return [c for c in chunks if c.strip()] + +def _chunk_python(src): + try: tree = ast.parse(src) + except SyntaxError: return [] + lines = src.splitlines(); out = [] + for node in ast.iter_child_nodes(tree): + if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef)): + out.append((node.name, "\n".join(lines[node.lineno-1:node.end_lineno])[:4000])) + return out + +def _chunk_file(path, src): + if path.suffix == ".py": + pairs = _chunk_python(src) + if pairs: return pairs + pat = re.compile(r'(?:^|\n)(?=(?:export\s+)?(?:async\s+)?(?:function|class)|^func |^type |^impl |^pub fn |^fn )', re.M) + parts = [p.strip() for p in pat.split(src) if p.strip()] + if len(parts) > 1: return [(f"s{i}", p[:4000]) for i,p in enumerate(parts)] + return [(f"c{i}", c) for i,c in enumerate(_sliding(src, 1200, 200))] + +def ingest_file(col, fpath, repo=""): + if fpath.stat().st_size > MAX_BYTES: return + if any(fnmatch.fnmatch(fpath.name, p) for p in ("*.min.js","*.map","package-lock.json","yarn.lock")): return + try: src = fpath.read_text(encoding="utf-8", errors="ignore") + except: return + if not src.strip(): return + rel = str(fpath) + pairs = _chunk_file(fpath, src) if fpath.suffix in CODE_EXTS else \ + [(f"c{i}",c) for i,c in enumerate(_sliding(src))] + ids,docs,metas = [],[],[] + for label,chunk in pairs: + if not chunk.strip(): continue + ids.append(_doc_id(chunk, rel+label)); docs.append(chunk) + metas.append({"source":rel,"label":label,"repo":repo,"lang":fpath.suffix.lstrip(".")}) + if ids: col.upsert(ids=ids, documents=docs, metadatas=metas) + +def ingest_dir(col, directory, repo=""): + count = 0 + for f in directory.rglob("*"): + if not f.is_file() or any(p in f.parts for p in SKIP_DIRS): continue + ingest_file(col, f, repo); count += 1 + log.info("Indexed %d files from %s", count, directory); return count + +def ingest_pdfs(col): + try: import pypdf + except ImportError: return 0 + n = 0 + for pdf in PAPERS_DIR.glob("*.pdf"): + try: + text = "\n".join(p.extract_text() or "" for p in pypdf.PdfReader(str(pdf)).pages) + for i,chunk in enumerate(_sliding(text)): + col.upsert(ids=[_doc_id(chunk,str(pdf)+str(i))], documents=[chunk], + metadatas=[{"source":str(pdf),"label":f"p{i}","repo":"","lang":"pdf"}]) + n += 1 + except Exception as e: log.warning("PDF %s: %s", pdf.name, e) + return n + +def _startup(): + for _ in range(40): + try: + r = httpx.get(f"{OLLAMA_URL}/api/tags", timeout=5) + if any(EMBED_MODEL in m["name"] for m in r.json().get("models",[])): break + except: pass + log.info("Waiting for embed model..."); time.sleep(5) + code_col = get_col("code"); papers_col = get_col("papers") + for d in REPOS_DIR.iterdir(): + if d.is_dir(): ingest_dir(code_col, d, d.name) + ingest_pdfs(papers_col) + for f in PAPERS_DIR.glob("*.txt"): ingest_file(papers_col, f) + log.info("Startup index done") + +@app.on_event("startup") +async def on_startup(): threading.Thread(target=_startup, daemon=True).start() + +@app.get("/health") +async def health(): + try: + cc = _chroma() + return {"status":"ok", + "code": cc.get_collection("code", embedding_function=_embed_fn()).count(), + "papers": cc.get_collection("papers", embedding_function=_embed_fn()).count()} + except Exception as e: return {"status":"error","detail":str(e)} + +class RepoReq(BaseModel): + url: str; name: str = ""; branch: str = "main" + +@app.post("/ingest/repo") +async def ingest_repo(req: RepoReq): + 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)) + return {"status":"ok","repo":name,"files":ingest_dir(get_col("code"),dest,name)} + +@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): + 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) + return {"status":"ok","repo":name,"files":ingest_dir(get_col("code"),dest,name)} + +@app.post("/webhook/gitea") +async def wh_gitea(r: Request): return await _webhook(await r.json()) +@app.post("/webhook/github") +async def wh_github(r: Request): return await _webhook(await r.json()) + +def _ctx(query, cols): + parts = [] + for cn in cols: + try: + col = get_col(cn) + 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```{meta.get('lang','')}\n{doc}\n```") + except Exception as e: log.warning("col %s: %s", cn, e) + return "\n\n".join(parts) + +class ChatReq(BaseModel): + model: str = CHAT_MODEL; messages: list[dict[str,Any]] + stream: bool = False; collections: list[str] = ["code","papers"] + +@app.post("/v1/chat/completions") +async def chat(req: ChatReq): + query = next((m["content"] for m in reversed(req.messages) if m.get("role")=="user"), "") + ctx = _ctx(query, req.collections) + msgs = [{"role":"system","content":f"You are a coding assistant. Use context below.\n\n## Context\n{ctx}"}] + req.messages + payload = {"model":req.model,"messages":msgs,"stream":req.stream} + if req.stream: + async def gen(): + async with httpx.AsyncClient(timeout=300) as c: + async with c.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 c: + r = await c.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) +PY + +# ============================================================================= +section "Writing mcp_server.py" +# ============================================================================= +write_if_new "$BASE/mcp_server.py" << 'PY' +import json, os, re, subprocess +from pathlib import Path +import httpx +from mcp.server.fastmcp import FastMCP + +WORKSPACE = Path(os.getenv("WORKSPACE_DIR", "/workspace")) +REPOS_DIR = Path(os.getenv("REPOS_DIR", "/repos")) +GITEA_URL = os.getenv("GITEA_URL", "http://gitea:3000") +GITEA_TOKEN = os.getenv("GITEA_TOKEN", "") +GITHUB_TOKEN = os.getenv("GITHUB_TOKEN","") +RAG_URL = os.getenv("RAG_URL", "http://rag-server:8001") + +mcp = FastMCP("local-dev-tools") + +@mcp.tool() +def bash(command: str, cwd: str = "") -> str: + """Run a shell command. Default cwd is /workspace.""" + work = Path(cwd) if cwd else WORKSPACE + work.mkdir(parents=True, exist_ok=True) + try: + r = subprocess.run(command, shell=True, cwd=work, timeout=120, capture_output=True, text=True) + out = r.stdout + (f"\n[stderr]\n{r.stderr}" if r.stderr else "") + if r.returncode != 0: out += f"\n[exit {r.returncode}]" + return out or "(no output)" + except subprocess.TimeoutExpired: return "[timeout]" + except Exception as e: return f"[error] {e}" + +@mcp.tool() +def read_file(path: str) -> str: + """Read a file. Absolute or relative to /workspace.""" + p = Path(path) if Path(path).is_absolute() else WORKSPACE / path + if not p.exists(): return f"[not found] {p}" + if p.stat().st_size > 500_000: return f"[too large: {p.stat().st_size//1024}KB]" + return p.read_text(encoding="utf-8", errors="replace") + +@mcp.tool() +def write_file(path: str, content: str) -> str: + """Write content to a file. Relative to /workspace.""" + p = Path(path) if Path(path).is_absolute() else WORKSPACE / path + p.parent.mkdir(parents=True, exist_ok=True) + p.write_text(content, encoding="utf-8") + return f"Wrote {len(content)} chars to {p}" + +@mcp.tool() +def list_files(path: str = "", pattern: str = "**/*") -> str: + """List files matching a glob pattern.""" + base = Path(path) if path else WORKSPACE + if not base.exists(): return f"[not found] {base}" + files = sorted(str(f.relative_to(base)) for f in base.glob(pattern) if f.is_file()) + return "\n".join(files[:500]) or "(empty)" + +@mcp.tool() +def search_code(query: str, path: str = "", glob: str = "", case_sensitive: bool = False) -> str: + """Search file contents with ripgrep.""" + base = path or str(WORKSPACE) + cmd = ["rg", "--line-number", "--no-heading"] + if not case_sensitive: cmd.append("-i") + if glob: cmd += ["-g", glob] + cmd += [query, base] + try: + r = subprocess.run(cmd, capture_output=True, text=True, timeout=30) + lines = r.stdout.strip().splitlines() + if len(lines) > 200: lines = lines[:200] + [f"...({len(r.stdout.splitlines())-200} more)"] + return "\n".join(lines) or "(no matches)" + except FileNotFoundError: + r = subprocess.run(["grep","-rn",query,base], capture_output=True, text=True, timeout=30) + return r.stdout[:8000] or "(no matches)" + +@mcp.tool() +def fetch_url(url: str, extract_text: bool = True) -> str: + """Fetch the content of a URL.""" + try: + r = httpx.get(url, timeout=30, follow_redirects=True, headers={"User-Agent":"Mozilla/5.0"}) + content = r.text + if extract_text: + content = re.sub(r']*>.*?', '', content, flags=re.DOTALL) + content = re.sub(r']*>.*?', '', content, flags=re.DOTALL) + content = re.sub(r'<[^>]+>', '', content) + content = re.sub(r'\n{3,}', '\n\n', content).strip() + return content[:20000] + except Exception as e: return f"[error] {e}" + +def _git(args, repo=""): + cwd = Path(repo) if repo else WORKSPACE + r = subprocess.run(["git"]+args, cwd=cwd, capture_output=True, text=True, timeout=60) + return (r.stdout + r.stderr).strip() or "(no output)" + +@mcp.tool() +def git_status(repo: str = "") -> str: + """Show git status.""" + return _git(["status","--short"], repo) + +@mcp.tool() +def git_diff(repo: str = "", cached: bool = False) -> str: + """Show git diff.""" + flag = ["--cached"] if cached else [] + return _git(["diff","--stat"]+flag, repo) + "\n\n" + _git(["diff"]+flag, repo) + +@mcp.tool() +def git_log(repo: str = "", n: int = 10) -> str: + """Show last n commits.""" + return _git(["log",f"-{n}","--oneline","--decorate"], repo) + +@mcp.tool() +def git_commit(message: str, repo: str = "", add_all: bool = True) -> str: + """Stage all and commit.""" + if add_all: _git(["add","-A"], repo) + return _git(["commit","-m",message], repo) + +@mcp.tool() +def git_checkout(branch: str, repo: str = "", create: bool = False) -> str: + """Checkout or create a branch.""" + return _git(["checkout","-b",branch] if create else ["checkout",branch], repo) + +def _gitea(method, path, body=None): + if not GITEA_TOKEN: return {"error":"GITEA_TOKEN not set in .env"} + r = httpx.request(method, f"{GITEA_URL}/api/v1{path}", + json=body, headers={"Authorization":f"token {GITEA_TOKEN}"}, timeout=30) + try: return r.json() + except: return {"status":r.status_code,"text":r.text} + +@mcp.tool() +def gitea_list_repos() -> str: + """List your Gitea repos.""" + d = _gitea("GET", "/repos/search?limit=50") + if "error" in d: return d["error"] + return "\n".join(f"{r['full_name']} — {r.get('description','')}" for r in d.get("data",[])) + +@mcp.tool() +def gitea_create_repo(name: str, private: bool = True, description: str = "") -> str: + """Create a Gitea repo.""" + r = _gitea("POST","/user/repos",{"name":name,"private":private,"description":description,"auto_init":True,"default_branch":"main"}) + return r.get("html_url") or str(r) + +@mcp.tool() +def gitea_create_issue(repo: str, title: str, body: str = "") -> str: + """Create a Gitea issue (owner/repo).""" + r = _gitea("POST",f"/repos/{repo}/issues",{"title":title,"body":body}) + return r.get("html_url") or str(r) + +@mcp.tool() +def github_api(method: str, endpoint: str, body: str = "") -> str: + """Call GitHub REST API. endpoint e.g. /repos/owner/repo/issues""" + if not GITHUB_TOKEN: return "GITHUB_TOKEN not set in .env" + r = httpx.request(method.upper(), f"https://api.github.com{endpoint}", + json=json.loads(body) if body else None, + headers={"Authorization":f"Bearer {GITHUB_TOKEN}","Accept":"application/vnd.github+json"}, + timeout=30) + try: return json.dumps(r.json(), indent=2) + except: return r.text + +@mcp.tool() +def ingest_repo(url: str, name: str = "", branch: str = "main") -> str: + """Clone a repo and index it in RAG.""" + r = httpx.post(f"{RAG_URL}/ingest/repo", json={"url":url,"name":name,"branch":branch}, timeout=300) + return r.text + +@mcp.tool() +def rag_health() -> str: + """Check RAG server status.""" + try: return httpx.get(f"{RAG_URL}/health", timeout=10).text + except Exception as e: return f"RAG unreachable: {e}" + +if __name__ == "__main__": + import uvicorn + uvicorn.run(mcp.get_asgi_app(), host="0.0.0.0", port=8002) +PY + +# ============================================================================= +section "Requirements" +# ============================================================================= +cat > "$BASE/requirements.txt" << 'REQ' +fastapi +uvicorn[standard] +httpx +pydantic +chromadb +pypdf +python-multipart +REQ + +cat > "$BASE/mcp_requirements.txt" << 'REQ' +mcp[cli] +fastapi +uvicorn[standard] +httpx +REQ +ok "requirements.txt + mcp_requirements.txt" + +# ============================================================================= +section "SearXNG Config" +# ============================================================================= +write_if_new "$BASE/searxng/settings.yml" << SEARXNG +use_default_settings: true +general: + instance_name: "Local Search" +server: + secret_key: "$(openssl rand -hex 32)" + limiter: false +search: + safe_search: 0 + default_lang: "en" + formats: [html, json] +SEARXNG + +# ============================================================================= +section ".env (tokens — never overwritten)" +# ============================================================================= +if [[ ! -f "$BASE/.env" ]]; then + cat > "$BASE/.env" << ENV +# Local AI Stack — edit to add your API tokens +GITEA_TOKEN=your-gitea-token-here +GITHUB_TOKEN=your-github-token-here +ENV + ok "Created .env" +else + info "Kept .env" +fi + +# ============================================================================= +section "Docker Compose" +# ============================================================================= +cat > "$BASE/docker-compose.yml" << COMPOSE +# Local AI Stack — 2026-03-20 +# GPU: OLLAMA_NUM_GPU=999 uses all available VRAM automatically (V100/RTX/any) +# Context: OLLAMA_NUM_CTX= set by detected VRAM (GB) + +services: + + ollama: + image: ollama/ollama:latest + container_name: ollama + restart: unless-stopped + ports: ["0.0.0.0:11434:11434"] + volumes: [ollama-models:/root/.ollama] + environment: + - OLLAMA_NUM_GPU=999 + - OLLAMA_NUM_CTX= + - OLLAMA_KEEP_ALIVE=24h + - OLLAMA_MAX_LOADED_MODELS=1 + deploy: + resources: + reservations: + devices: + - driver: nvidia + count: all + capabilities: [gpu] + healthcheck: + test: ["CMD","ollama","list"] + interval: 30s; timeout: 10s; retries: 5 + + open-webui: + image: ghcr.io/open-webui/open-webui:main + container_name: open-webui + restart: unless-stopped + ports: ["0.0.0.0:3000:8080"] + volumes: [open-webui-data:/app/backend/data] + environment: + - OLLAMA_BASE_URL=http://ollama:11434 + - OPENAI_API_BASE_URL=http://rag-server:8001/v1 + - OPENAI_API_KEY=local-rag + - ENABLE_OPENAI_API=true + - ENABLE_RAG_WEB_SEARCH=true + - RAG_WEB_SEARCH_ENGINE=searxng + - SEARXNG_QUERY_URL=http://searxng:8080/search?q=&format=json + - WEBUI_AUTH=false + depends_on: + ollama: {condition: service_healthy} + + chromadb: + image: chromadb/chroma:latest + container_name: chromadb + restart: unless-stopped + ports: ["0.0.0.0:8000:8000"] + volumes: [$BASE/index:/chroma/chroma] + environment: + - IS_PERSISTENT=TRUE + - ANONYMIZED_TELEMETRY=FALSE + healthcheck: + test: ["CMD-SHELL","wget -qO- http://localhost:8000/api/v2/heartbeat || exit 1"] + interval: 15s; timeout: 5s; retries: 5 + + rag-server: + image: python:3.11-slim + container_name: rag-server + restart: unless-stopped + ports: ["0.0.0.0:8001:8001"] + volumes: + - $BASE/papers:/papers + - $BASE/repos:/repos + - $BASE/index:/index + - $BASE/server.py:/app/server.py + - $BASE/requirements.txt:/app/requirements.txt + working_dir: /app + environment: + - OLLAMA_URL=http://ollama:11434 + - CHROMA_URL=http://chromadb:8000 + - EMBED_MODEL=nomic-embed-text + - CHAT_MODEL= + command: > + bash -c "apt-get update -qq && apt-get install -y --no-install-recommends git && + pip install --no-cache-dir -r requirements.txt && + uvicorn server:app --host 0.0.0.0 --port 8001" + depends_on: + chromadb: {condition: service_healthy} + ollama: {condition: service_healthy} + + mcp-server: + image: python:3.11-slim + container_name: mcp-server + restart: unless-stopped + ports: ["0.0.0.0:8002:8002"] + volumes: + - $BASE/workspace:/workspace + - $BASE/repos:/repos + - $BASE/mcp_server.py:/app/mcp_server.py + - $BASE/mcp_requirements.txt:/app/mcp_requirements.txt + working_dir: /app + env_file: $BASE/.env + environment: + - WORKSPACE_DIR=/workspace + - REPOS_DIR=/repos + - GITEA_URL=http://gitea:3000 + - RAG_URL=http://rag-server:8001 + command: > + bash -c "apt-get update -qq && apt-get install -y --no-install-recommends git ripgrep && + pip install --no-cache-dir -r mcp_requirements.txt && + python mcp_server.py" + depends_on: [rag-server] + + searxng: + image: searxng/searxng:latest + container_name: searxng + restart: unless-stopped + ports: ["0.0.0.0:8888:8080"] + volumes: [$BASE/searxng:/etc/searxng] + cap_drop: [ALL] + cap_add: [CHOWN, SETGID, SETUID] + + kiwix: + image: ghcr.io/kiwix/kiwix-serve:latest + container_name: kiwix + restart: unless-stopped + ports: ["0.0.0.0:8181:8080"] + volumes: [$BASE/kiwix:/data] + command: "*.zim" + + gitea: + image: gitea/gitea:latest + container_name: gitea + restart: unless-stopped + ports: ["0.0.0.0:3001:3000","0.0.0.0:2222:22"] + volumes: + - $BASE/gitea:/data + - /etc/timezone:/etc/timezone:ro + - /etc/localtime:/etc/localtime:ro + environment: + - USER_UID=1000 + - USER_GID=1000 + - GITEA__database__DB_TYPE=sqlite3 + - GITEA__database__PATH=/data/gitea/gitea.db + - GITEA__webhook__ALLOWED_HOST_LIST=rag-server,mcp-server + + invokeai: + image: ghcr.io/invoke-ai/invokeai:latest + container_name: invokeai + restart: unless-stopped + ports: ["0.0.0.0:9090:9090"] + volumes: + - invokeai-models:/invokeai/models + - $BASE/invokeai-outputs:/invokeai/outputs + - $BASE/invokeai-data:/invokeai/databases + environment: + - INVOKEAI_HOST=0.0.0.0 + - INVOKEAI_PORT=9090 + - INVOKEAI_PRECISION=float16 + deploy: + resources: + reservations: + devices: + - driver: nvidia + count: all + capabilities: [gpu] + + portainer: + image: portainer/portainer-ce:latest + container_name: portainer + restart: unless-stopped + ports: ["0.0.0.0:9000:9000","0.0.0.0:9443:9443"] + volumes: + - /var/run/docker.sock:/var/run/docker.sock + - $BASE/portainer-data:/data + +volumes: + ollama-models: + open-webui-data: + invokeai-models: +COMPOSE +ok "docker-compose.yml" + +# ============================================================================= +section "Firewall" +# ============================================================================= +if command -v ufw &>/dev/null && [[ ! -f "$BASE/.ufw-done" ]] || $FORCE; then + read -rp " LAN subnet [192.168.1.0/24]: " LAN; LAN="${LAN:-192.168.1.0/24}" + [[ "$LAN" =~ /[0-9]+$ ]] || LAN="${LAN}/24" + for pc in "3000:Open WebUI" "11434:Ollama" "8001:RAG" "8002:MCP" \ + "8000:ChromaDB" "8888:SearXNG" "8181:Kiwix" \ + "3001:Gitea" "2222:Gitea SSH" "9090:InvokeAI" \ + "9000:Portainer" "9443:Portainer S"; do + sudo ufw allow from "$LAN" to any port "${pc%%:*}" proto tcp comment "${pc##*:}" >/dev/null + done + sudo ufw reload >/dev/null; ok "UFW rules set for $LAN"; touch "$BASE/.ufw-done" +fi + +# ============================================================================= +section "Helper Scripts" +# ============================================================================= +cat > "$BASE/start.sh" << STARTSH +#!/bin/bash +cd "$BASE" +docker compose pull --quiet 2>/dev/null +docker compose up -d +echo "" +echo " Open WebUI → http://$LOCAL_IP:3000" +echo " InvokeAI → http://$LOCAL_IP:9090" +echo " SearXNG → http://$LOCAL_IP:8888" +echo " Kiwix → http://$LOCAL_IP:8181 (run kiwix_download.sh first)" +echo " Gitea → http://$LOCAL_IP:3001" +echo " RAG → http://$LOCAL_IP:8001/health" +echo " MCP SSE → http://$LOCAL_IP:8002/sse" +echo " Portainer → https://$LOCAL_IP:9443" +echo "" +echo " claude mcp add local http://$LOCAL_IP:8002/sse" +STARTSH +chmod +x "$BASE/start.sh" + +cat > "$BASE/stop.sh" << STOPSH +#!/bin/bash +cd "$BASE" && docker compose down +STOPSH +chmod +x "$BASE/stop.sh" + +cat > "$BASE/status.sh" << 'STATUSSH' +#!/bin/bash +echo "=== GPU ===" && nvidia-smi --query-gpu=name,memory.used,memory.total \ + --format=csv,noheader 2>/dev/null || echo "(no GPU)" +echo "" && echo "=== Containers ===" && docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Ports}}" +echo "" && echo "=== Ollama ===" && docker exec ollama ollama ps 2>/dev/null || echo "(not running)" +echo "" && echo "=== RAG ===" && curl -s http://localhost:8001/health | python3 -m json.tool 2>/dev/null +STATUSSH +chmod +x "$BASE/status.sh" + +cat > "$BASE/pull-models.sh" << PULLSH +#!/bin/bash +echo "Waiting for Ollama..." +until docker exec ollama ollama list &>/dev/null; do sleep 3; done + +echo "Embed model (RAG — required)..." +docker exec ollama ollama pull $EMBED_MODEL + +echo "Fast chat model..." +docker exec ollama ollama pull qwen2.5:7b + +echo "Smart chat model..." +docker exec ollama ollama pull $CHAT_MODEL + +echo "Code model..." +docker exec ollama ollama pull $CODE_MODEL + +echo "Reasoning model (DeepSeek-R1 14B — optional)..." +read -rp "Pull DeepSeek-R1:14b for planning/reasoning? [y/N]: " DR +[[ "\${DR,,}" == "y" ]] && docker exec ollama ollama pull deepseek-r1:14b + +echo "" && docker exec ollama ollama list +PULLSH +chmod +x "$BASE/pull-models.sh" +ok "start.sh stop.sh status.sh pull-models.sh" + +# ============================================================================= +section "Systemd" +# ============================================================================= +sudo tee /etc/systemd/system/local-ai.service >/dev/null << SYSD +[Unit] +Description=Local AI Stack +After=docker.service network-online.target +Requires=docker.service + +[Service] +Type=oneshot +RemainAfterExit=yes +User=$USER +WorkingDirectory=$BASE +ExecStart=/bin/bash $BASE/start.sh +ExecStop=/bin/bash $BASE/stop.sh +TimeoutStartSec=300 + +[Install] +WantedBy=multi-user.target +SYSD +sudo systemctl daemon-reload && sudo systemctl enable local-ai.service +ok "Systemd: local-ai.service enabled" + +# ============================================================================= +section "Starting Stack" +# ============================================================================= +cd "$BASE" +info "Pulling images..." +docker compose pull --quiet +docker compose up -d +ok "Stack running" + +if ! $IS_UPDATE && ! $NO_PULL; then + echo "" + read -rp "Pull Ollama models now? (~15-30 min) [Y/n]: " DO_PULL + [[ "${DO_PULL,,}" != "n" ]] && bash "$BASE/pull-models.sh" +fi + +# ============================================================================= +echo "" +echo -e "${GREEN}${BOLD}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}" +echo -e "${GREEN}${BOLD} Done! GPU: ${VRAM_GB}GB → $TIER${NC}" +echo -e "${GREEN}${BOLD}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}" +echo "" +echo -e " ${CYAN}Open WebUI${NC} → http://$LOCAL_IP:3000" +echo -e " ${CYAN}InvokeAI${NC} → http://$LOCAL_IP:9090" +echo -e " ${CYAN}SearXNG${NC} → http://$LOCAL_IP:8888" +echo -e " ${CYAN}Kiwix${NC} → http://$LOCAL_IP:8181" +echo -e " ${CYAN}Gitea${NC} → http://$LOCAL_IP:3001" +echo -e " ${CYAN}RAG${NC} → http://$LOCAL_IP:8001/health" +echo -e " ${CYAN}MCP SSE${NC} → http://$LOCAL_IP:8002/sse" +echo -e " ${CYAN}Portainer${NC} → https://$LOCAL_IP:9443" +echo "" +echo -e " ${YELLOW}Add MCP to Claude Code:${NC}" +echo " claude mcp add local http://$LOCAL_IP:8002/sse" +echo "" +echo -e " ${YELLOW}Tokens:${NC} $BASE/.env" +echo -e " ${YELLOW}PDFs:${NC} $BASE/papers/" +echo -e " ${YELLOW}Workspace:${NC} $BASE/workspace/" +echo -e " ${YELLOW}ZIMs:${NC} ./kiwix_download.sh" +echo "" +echo -e " ${YELLOW}Save Claude usage:${NC} use local 14B for boilerplate, docs," +echo " simple fixes. Use Claude Sonnet 4.6 for hard bugs," +echo " multi-file refactoring, architecture decisions." +echo ""