cc1efa7a21
- Add COMPLETIONS_API_KEY to config.py (env var + auto-generated fallback) - Fix perplexity auto-search: upstream sends logprobs=true, parse_llama_stream_chunk extracts per-token logprobs, all_logprobs populated during streaming - Fix all /api/models endpoints to target LLAMA_SERVER_BASE (port 8081) not OLLAMA_BASE - Fix RAG embedding endpoint URL from port 11434 (Ollama) to 8081 (llama-server) - Correct misleading error messages: 'inference server' not 'Ollama' - Remove raw_results leak from SSE event stream in /api/search - Fix weather query extractor: pattern-match instead of unconditional suffix append - Escape FTS5 operator keywords (AND/OR/NOT/NEAR) in memory search - Move auth.py BODY_LIMIT_DEFAULT_BYTES imports to module level - Change RAG injection log level from warning to info - Fix all 8 test files after modular refactor (rewire imports from correct modules) - Update AGENTS.md and README.md to reflect v1.8.0 changes
78 lines
2.6 KiB
Python
78 lines
2.6 KiB
Python
"""
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JarvisChat routers - Model listing, system stats.
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"""
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import logging
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from typing import Optional
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import httpx
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import psutil
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from fastapi import APIRouter, HTTPException, Request
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from config import LLAMA_SERVER_BASE
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from gpu import get_gpu_stats
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from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES
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log = logging.getLogger("jarvischat")
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router = APIRouter()
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@router.get("/api/models")
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async def list_models():
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async with httpx.AsyncClient() as client:
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try:
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resp = await client.get(f"{LLAMA_SERVER_BASE}/v1/models", timeout=10)
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data = resp.json()
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models = [{"name": m["id"], "model": m["id"]} for m in data.get("data", [])]
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return {"models": models}
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except httpx.ConnectError:
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raise HTTPException(status_code=502, detail="Cannot connect to inference server.")
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@router.get("/api/ps")
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async def running_models():
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async with httpx.AsyncClient() as client:
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try:
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resp = await client.get(f"{LLAMA_SERVER_BASE}/v1/models", timeout=10)
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return resp.json()
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except httpx.ConnectError:
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raise HTTPException(status_code=502, detail="Cannot connect to inference server.")
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@router.post("/api/show")
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async def show_model(request: Request):
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body = await read_json_body(request, BODY_LIMIT_DEFAULT_BYTES)
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async with httpx.AsyncClient() as client:
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try:
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resp = await client.post(f"{LLAMA_SERVER_BASE}/api/show", json=body, timeout=10)
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return resp.json()
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except httpx.ConnectError:
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raise HTTPException(status_code=502, detail="Cannot connect to inference server.")
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@router.get("/api/stats")
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async def system_stats():
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cpu_percent = psutil.cpu_percent(interval=0.1)
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memory = psutil.virtual_memory()
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gpu = get_gpu_stats()
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return {
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"cpu_percent": round(cpu_percent, 1),
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"memory_percent": round(memory.percent, 1),
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"memory_used_gb": round(memory.used / (1024**3), 1),
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"memory_total_gb": round(memory.total / (1024**3), 1),
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"gpu_percent": gpu["gpu_percent"],
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"vram_percent": gpu["vram_percent"],
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"gpu_available": gpu["available"],
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}
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@router.get("/api/search/status")
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async def search_status():
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from config import SEARXNG_BASE
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async with httpx.AsyncClient() as client:
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try:
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resp = await client.get(f"{SEARXNG_BASE}/search",
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params={"q": "test", "format": "json"}, timeout=5)
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return {"available": resp.status_code == 200}
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except Exception:
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return {"available": False}
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