Initial commit from Martins Github
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Jake Kasper
207
app/services/ai.py
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207
app/services/ai.py
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"""
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AI engine for P5G Marvis.
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Phase 1: rule-based with real network data.
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Phase 2: swap MARVIS_AI_MODE=openai or MARVIS_AI_MODE=ollama to route through LLM.
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"""
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from datetime import datetime
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from app.config import AI_MODE, OPENAI_API_KEY, OPENAI_MODEL, OPENAI_BASE_URL, OLLAMA_URL, OLLAMA_MODEL
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async def answer(query: str, network_state: dict, alerts: list) -> str:
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if AI_MODE == "openai":
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return await _call_openai(query, network_state, alerts)
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if AI_MODE == "ollama":
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return await _call_ollama(query, network_state, alerts)
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return _rule_based(query, network_state, alerts)
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# ── Rule-based engine ──────────────────────────────────────────────────────
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def _rule_based(query: str, network_state: dict, alerts: list) -> str:
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q = query.lower()
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nfs = network_state.get("nfs", [])
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up = [n for n in nfs if n["state"] == "up"]
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down = [n for n in nfs if n["state"] == "down"]
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if any(w in q for w in ["hello", "hi ", "hey", "howdy"]):
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return ("Hello! I'm **P5G Marvis**, your AI network assistant for HPE Private 5G.\n"
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"Ask me about network health, specific functions, alerts, or performance.")
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if any(w in q for w in ["help", "what can", "capabilities", "commands", "features"]):
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return (
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"Here's what I can help with:\n\n"
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"• **Network health** — overall P5G status overview\n"
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"• **Network functions** — ask about AMF, SMF, UPF, UDM, NRF, etc.\n"
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"• **Alerts** — active alarms and their severity\n"
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"• **Subscribers** — UE registration and session analysis\n"
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"• **Sessions** — PDU session and data plane health\n\n"
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"_Tip: Connect an LLM by setting `MARVIS_AI_MODE=openai` or `=ollama`._"
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)
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# Specific NF query
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from app.config import ALL_NFS
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for nf_name in ALL_NFS:
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if nf_name.lower() in q:
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return _nf_detail(nf_name, nfs, alerts)
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if any(w in q for w in ["alert", "alarm", "warning", "critical", "incident", "problem", "issue"]):
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return _alerts_summary(alerts)
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if any(w in q for w in ["subscriber", "ue ", "device", "phone", "handset", "registration", "attach"]):
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return _subscriber_analysis(nfs, alerts)
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if any(w in q for w in ["session", "pdu", "bearer", "user plane", "traffic", "throughput"]):
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return _session_analysis(nfs, alerts)
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# Default → health summary
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return _health_summary(up, down, alerts)
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def _health_summary(up: list, down: list, alerts: list) -> str:
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ts = datetime.now().strftime("%H:%M:%S")
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crit = [a for a in alerts if a.get("severity") == "critical"]
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warn = [a for a in alerts if a.get("severity") != "critical"]
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lines = [f"**P5G Network Health — {ts}**\n"]
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if up:
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lines.append(f"✅ **{len(up)} UP**: {', '.join(n['name'] for n in up)}")
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if down:
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lines.append(f"🔴 **{len(down)} DOWN**: {', '.join(n['name'] for n in down)}")
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lines.append(f" ⚡ Action: check `podman logs <nf>` on the VM")
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if alerts:
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lines.append(f"\n⚠️ **{len(alerts)} alert(s)** — {len(crit)} critical, {len(warn)} warning")
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for a in alerts[:4]:
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icon = "🔴" if a.get("severity") == "critical" else "🟡"
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lines.append(f" {icon} {a['name']}: {a.get('summary', a.get('instance', ''))}")
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else:
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lines.append("\n✅ **No active alerts**")
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if not down and not alerts:
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lines.append("\n🟢 All systems nominal.")
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return "\n".join(lines)
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def _nf_detail(nf_name: str, nfs: list, alerts: list) -> str:
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nf = next((n for n in nfs if n["name"] == nf_name), None)
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nf_alerts = [a for a in alerts
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if nf_name in a.get("name", "") or nf_name.lower() in a.get("instance", "").lower()]
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if not nf or nf["state"] == "unknown":
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return (f"ℹ️ No Prometheus data found for **{nf_name}**.\n"
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f"Check: `podman ps | grep {nf_name.lower()}`")
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icon = "✅" if nf["state"] == "up" else "🔴"
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lines = [f"{icon} **{nf_name}** is **{nf['state'].upper()}**",
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f"Instance: `{nf.get('instance', 'n/a')}`"]
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if nf_alerts:
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lines.append(f"\n⚠️ {len(nf_alerts)} alert(s) for {nf_name}:")
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for a in nf_alerts:
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lines.append(f" → {a['name']}: {a.get('summary', '')}")
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else:
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lines.append("No active alerts for this function.")
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return "\n".join(lines)
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def _alerts_summary(alerts: list) -> str:
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if not alerts:
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return "✅ **No active alerts.** Network is running cleanly."
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crit = [a for a in alerts if a.get("severity") == "critical"]
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warn = [a for a in alerts if a.get("severity") != "critical"]
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lines = [f"⚠️ **{len(alerts)} active alert(s)** — {len(crit)} critical, {len(warn)} warning\n"]
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for a in alerts:
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icon = "🔴" if a.get("severity") == "critical" else "🟡"
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lines.append(f"{icon} **{a['name']}**")
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if a.get("summary"):
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lines.append(f" {a['summary']}")
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if a.get("instance"):
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lines.append(f" `{a['instance']}`")
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return "\n".join(lines)
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def _subscriber_analysis(nfs: list, alerts: list) -> str:
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amf = next((n for n in nfs if n["name"] == "AMF"), None)
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smf = next((n for n in nfs if n["name"] == "SMF"), None)
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lines = ["**Subscriber & Registration Analysis**\n"]
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lines.append(f"AMF (registration/mobility): {'✅ UP' if amf and amf['state'] == 'up' else '🔴 DOWN — subscribers cannot register'}")
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lines.append(f"SMF (session management): {'✅ UP' if smf and smf['state'] == 'up' else '🔴 DOWN — no new data sessions'}")
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sub_alerts = [a for a in alerts if any(k in a.get("name", "").lower()
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for k in ["ue", "subscriber", "session", "attach", "registration"])]
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if sub_alerts:
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lines.append(f"\n⚠️ {len(sub_alerts)} subscriber-related alert(s) active.")
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else:
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lines.append("\nNo subscriber-related alerts detected.")
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return "\n".join(lines)
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def _session_analysis(nfs: list, alerts: list) -> str:
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smf = next((n for n in nfs if n["name"] == "SMF"), None)
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upf = next((n for n in nfs if n["name"] == "UPF"), None)
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lines = ["**PDU Session & Data Plane Analysis**\n"]
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lines.append(f"SMF: {'✅ UP' if smf and smf['state'] == 'up' else '🔴 DOWN'}")
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lines.append(f"UPF: {'✅ UP' if upf and upf['state'] == 'up' else '🔴 DOWN'}")
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if (not smf or smf["state"] != "up") or (not upf or upf["state"] != "up"):
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lines.append("\n⚡ **Impact**: PDU sessions will fail until both SMF and UPF are operational.")
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else:
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lines.append("\nBoth SMF and UPF operational — sessions should be establishing normally.")
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return "\n".join(lines)
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# ── LLM backends ──────────────────────────────────────────────────────────
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def _build_context(network_state: dict, alerts: list) -> str:
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nfs = network_state.get("nfs", [])
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up = [n["name"] for n in nfs if n["state"] == "up"]
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down = [n["name"] for n in nfs if n["state"] == "down"]
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return (
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f"NFs UP: {', '.join(up) or 'none'}\n"
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f"NFs DOWN: {', '.join(down) or 'none'}\n"
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f"Active alerts: {', '.join(a.get('name','') for a in alerts[:5]) or 'none'}"
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)
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async def _call_openai(query: str, network_state: dict, alerts: list) -> str:
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try:
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import httpx
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ctx = _build_context(network_state, alerts)
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messages = [
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{"role": "system", "content":
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f"You are P5G Marvis, an AI network assistant for HPE Private 5G.\n"
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f"Current network state:\n{ctx}\n\nRespond concisely, use markdown."},
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{"role": "user", "content": query},
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]
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base = OPENAI_BASE_URL.rstrip("/")
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headers = {"Content-Type": "application/json"}
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if OPENAI_API_KEY:
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headers["Authorization"] = f"Bearer {OPENAI_API_KEY}"
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# disable cert verification for self-signed local LLM servers
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verify = base.startswith("https://api.openai.com")
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async with httpx.AsyncClient(timeout=120, verify=verify) as client:
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resp = await client.post(
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f"{base}/v1/chat/completions",
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headers=headers,
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json={"model": OPENAI_MODEL, "messages": messages, "max_tokens": 1024},
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)
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msg = resp.json()["choices"][0]["message"]
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# some reasoning models put the answer in content, others in reasoning_content
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return msg.get("content") or msg.get("reasoning_content") or "(empty response)"
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except Exception as e:
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return f"LLM error: {e}\n\n" + _rule_based(query, network_state, alerts)
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async def _call_ollama(query: str, network_state: dict, alerts: list) -> str:
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try:
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import httpx
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ctx = _build_context(network_state, alerts)
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prompt = (f"You are P5G Marvis, an AI network assistant.\n"
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f"Network state:\n{ctx}\n\nUser: {query}\nAssistant:")
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async with httpx.AsyncClient(timeout=60) as client:
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resp = await client.post(
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f"{OLLAMA_URL}/api/generate",
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json={"model": OLLAMA_MODEL, "prompt": prompt, "stream": False},
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)
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return resp.json().get("response", "No response.")
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except Exception as e:
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return f"Ollama error: {e}\n\n" + _rule_based(query, network_state, alerts)
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