feat(harness): EmbeddingsConfig bin/start_cmd + ensure_ollama preflight orchestration

2026-06-29 19:15:28 +02:00
parent f66e8e41d9
commit 5f5cac05d5
3 changed files with 226 additions and 0 deletions
@@ -0,0 +1,108 @@
+"""`tht ollama` -- embeddings preflight (ensure Ollama up + model warm).
+
+The system REQUIRES embeddings: any condition that makes them unavailable is a hard
+error (the caller refuses the session). "Load" = warm the already-installed model.
+"""
+from __future__ import annotations
+
+import subprocess
+import time
+
+
+# --- low-level ops (real implementations; injected as fakes in tests) ----------
+
+def _probe(base_url: str, timeout: float = 2.0) -> bool:
+    import requests
+
+    try:
+        return requests.get(f"{base_url.rstrip('/')}/api/tags", timeout=timeout).status_code == 200
+    except requests.RequestException:
+        return False
+
+
+def _installed_models(base_url: str, timeout: float = 5.0) -> set[str]:
+    import requests
+
+    resp = requests.get(f"{base_url.rstrip('/')}/api/tags", timeout=timeout)
+    resp.raise_for_status()
+    return {m.get("name", "") for m in resp.json().get("models", [])}
+
+
+def _start(start_cmd: list[str]) -> None:
+    # Detached so the server outlives this short-lived CLI process.
+    subprocess.Popen(  # noqa: S603
+        start_cmd, start_new_session=True,
+        stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL,
+    )
+
+
+def _warm(cfg) -> None:
+    from tht.vectorstore.embeddings import OllamaEmbeddings
+
+    OllamaEmbeddings(cfg.embeddings).embed_query("ping")
+
+
+def _model_present(installed: set[str], model: str) -> bool:
+    """Match the configured model against installed names, allowing the implicit ':latest'."""
+    if model in installed:
+        return True
+    base = model.split(":")[0]
+    return any(name == base or name.split(":")[0] == base for name in installed)
+
+
+# --- orchestration (pure: returns a result dict, never raises for control flow) ----
+
+def ensure_ollama(
+    cfg,
+    *,
+    timeout: int,
+    no_start: bool,
+    probe=_probe,
+    installed_models=_installed_models,
+    start=_start,
+    warm=_warm,
+    sleep=time.sleep,
+    clock=time.monotonic,
+) -> dict:
+    if cfg.embeddings is None:
+        return {"ok": False, "stage": "config",
+                "error": "il sistema richiede embeddings ma il workspace non li configura"}
+    emb = cfg.embeddings
+    base_url = emb.base_url
+    start_cmd = emb.start_cmd if emb.start_cmd is not None else [emb.bin, "serve"]
+
+    server_state = "up"
+    if not probe(base_url):
+        if no_start or start_cmd == []:
+            return {"ok": False, "stage": "server",
+                    "error": f"Ollama non raggiungibile su {base_url} e avvio disabilitato"}
+        start(start_cmd)
+        server_state = "started"
+        deadline = clock() + timeout
+        up = False
+        while clock() < deadline:
+            sleep(1.0)
+            if probe(base_url):
+                up = True
+                break
+        if not up:
+            return {"ok": False, "stage": "server",
+                    "error": f"Ollama non raggiungibile su {base_url} entro {timeout}s"}
+
+    try:
+        installed = installed_models(base_url)
+    except Exception as e:  # noqa: BLE001 - any read failure is a hard error
+        return {"ok": False, "stage": "server",
+                "error": f"impossibile leggere i modelli da {base_url}: {e}"}
+    if not _model_present(installed, emb.model):
+        return {"ok": False, "stage": "model",
+                "error": f"modello '{emb.model}' non installato in Ollama: "
+                         f"esegui `ollama pull {emb.model}` o importalo"}
+
+    try:
+        warm(cfg)
+    except Exception as e:  # noqa: BLE001 - warm failure is a hard error
+        return {"ok": False, "stage": "warm",
+                "error": f"warm del modello '{emb.model}' fallito: {e}"}
+
+    return {"ok": True, "server": server_state, "model": "warmed", "model_name": emb.model}