Add provider connectivity probes to haiku-rag doctor

This commit is contained in:
Yiorgis Gozadinos 2026-06-23 10:34:27 +03:00
parent c2cb3cedf3
commit cc1d8d1e4c
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5 changed files with 467 additions and 25 deletions

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@ -3,7 +3,7 @@
### Added
- `haiku-rag doctor` checks a database for consistency (orphaned chunks/items, documents without chunks, dangling `doc_item_refs`, vector-dimension mismatch, unembedded chunks, missing picture data, settings/embedding drift, pending migrations, vector-index coverage, provider API keys) and exits 1 when any check fails.
- `haiku-rag doctor` checks a database for consistency (orphaned chunks/items, documents without chunks, dangling `doc_item_refs`, vector-dimension mismatch, unembedded chunks, missing picture data, settings/embedding drift, pending migrations, vector-index coverage, provider API keys) and probes configured provider endpoints (Ollama `/api/tags` with model presence, docling-serve `/health`, OpenAI-compatible/vLLM `/models`); exits 1 when any check fails.
## [0.60.0] - 2026-06-22

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@ -308,6 +308,14 @@ Checks include:
- the vector index covers all chunks
- API keys are set for configured providers
It also probes the external endpoints the config uses and reports them under a Providers section:
- Ollama is reachable and the configured models are installed (`{base_url}/api/tags`)
- docling-serve is reachable when used as the converter or chunker (`{base_url}/health`)
- custom OpenAI-compatible and vLLM endpoints respond (`{base_url}/models`)
SaaS providers (OpenAI, Anthropic, Cohere, Jina, ZeroEntropy, Voyage) are covered by the API-key check rather than a network probe. In-process local models (sentence-transformers, cross-encoder, mxbai, jina-local) have no endpoint and are reported as such.
Each failure prints the command that fixes it (`rebuild`, `create-index`, `migrate`, `rebuild --set-embedder`). `doctor` makes no changes. It exits with status 1 when any check fails, so it can gate CI or monitoring.
### Migrate Database

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@ -220,14 +220,25 @@ class HaikuRAGApp: # pragma: no cover
Severity.WARN: "[yellow]![/yellow]",
Severity.FAIL: "[red]✗[/red]",
}
self.console.rule()
for result in report.results:
def render(result):
self.console.print(f"{glyphs[result.severity]} {result.message}")
for detail in result.details:
self.console.print(f" [dim]{detail}[/dim]")
if result.remediation:
self.console.print(f" [dim]→ {result.remediation}[/dim]")
database = [r for r in report.results if not r.name.startswith("provider:")]
providers = [r for r in report.results if r.name.startswith("provider:")]
self.console.rule("[bold]Database[/bold]")
for result in database:
render(result)
if providers:
self.console.rule("[bold]Providers[/bold]")
for result in providers:
render(result)
self.console.rule()
self.console.print(
f"[green]{report.count(Severity.OK)} ok[/green], "

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@ -1,7 +1,9 @@
import asyncio
import json
from enum import StrEnum
from pathlib import Path
import httpx
import numpy as np
from pydantic import BaseModel, Field
@ -28,6 +30,12 @@ _PROVIDER_ENV_VARS: dict[str, str] = {
"zeroentropy": "ZEROENTROPY_API_KEY",
}
# Providers backed by in-process local models — no endpoint to probe.
_LOCAL_PROVIDERS = {"sentence-transformers", "mxbai", "cross-encoder", "jina-local"}
# Operators care whether an endpoint answers now, not eventually.
_PROBE_TIMEOUT_S = 2.0
class Severity(StrEnum):
OK = "ok"
@ -448,6 +456,161 @@ def _check_vector_index(stats: dict) -> CheckResult:
)
def _resolve_endpoint(
provider: str, base_url: str | None, ollama_base: str
) -> tuple[str, str, str] | str | None:
"""Map a model's provider to a probe target.
Returns ``(probe_url, kind, display)``, the literal ``"local"`` for an
in-process model, or ``None`` for a SaaS provider covered by the API-key
check.
"""
if provider == "ollama":
base = (base_url or ollama_base).rstrip("/")
if base.endswith("/v1"):
base = base[:-3].rstrip("/")
return f"{base}/api/tags", "ollama", base
if provider == "vllm":
base = (base_url or "http://localhost:8000/v1").rstrip("/")
if not base.endswith("/v1"):
base = f"{base}/v1"
return f"{base}/models", "openai", base
if provider == "openai" and base_url:
base = base_url.rstrip("/")
return f"{base}/models", "openai", base
if provider in _LOCAL_PROVIDERS:
return "local"
return None
def _provider_targets(
config: AppConfig,
) -> tuple[dict[str, dict], set[str]]:
"""Collect probe targets (keyed by probe URL) and local-only providers."""
targets: dict[str, dict] = {}
local: set[str] = set()
ollama_base = config.providers.ollama.base_url
def add_model(provider: str, name: str, base_url: str | None) -> None:
resolved = _resolve_endpoint(provider, base_url, ollama_base)
if resolved is None:
return
if resolved == "local":
local.add(provider)
return
probe_url, kind, display = resolved
entry = targets.setdefault(
probe_url, {"kind": kind, "display": display, "models": set()}
)
if name:
entry["models"].add(name)
proc = config.processing
if proc.converter == "docling-serve" or proc.chunker == "docling-serve":
for url in config.providers.docling_serve.base_urls:
base = url.rstrip("/")
targets.setdefault(
f"{base}/health",
{"kind": "docling-serve", "display": base, "models": set()},
)
add_model(
config.embeddings.model.provider,
config.embeddings.model.name,
config.embeddings.model.base_url,
)
for model in (config.reranking.model, config.qa.model, config.analysis.model):
if model is not None:
add_model(model.provider, model.name, model.base_url)
return targets, local
def _model_present(expected: str, available: set[str]) -> bool:
if expected in available:
return True
if ":" not in expected:
return any(a.split(":", 1)[0] == expected for a in available)
return False
async def _probe_endpoint(
client: httpx.AsyncClient, url: str
) -> tuple[bool, str | None, dict | None]:
try:
response = await client.get(url)
except httpx.HTTPError as exc:
return False, str(exc), None
if not response.is_success:
return False, f"HTTP {response.status_code}", None
try:
return True, None, response.json()
except ValueError:
return True, None, None
def _endpoint_result(
url: str, entry: dict, reachable: bool, error: str | None, payload: dict | None
) -> CheckResult:
kind = entry["kind"]
display = entry["display"]
name = f"provider:{display}"
if not reachable:
return CheckResult(
name=name,
severity=Severity.FAIL,
message=f"{kind} at {display} is unreachable.",
remediation="Start the service or fix the configured base_url.",
details=[error] if error else [],
)
if kind == "ollama":
available = {m.get("name", "") for m in (payload or {}).get("models", [])}
missing = [
model
for model in sorted(entry["models"])
if not _model_present(model, available)
]
if missing:
return CheckResult(
name=name,
severity=Severity.WARN,
message=f"ollama at {display} is reachable but missing model(s).",
remediation="ollama pull <model>",
details=missing,
)
return CheckResult(
name=name,
severity=Severity.OK,
message=f"{kind} at {display} is reachable.",
)
async def run_provider_checks(config: AppConfig) -> list[CheckResult]:
"""Probe the external endpoints the current config actually uses."""
targets, local = _provider_targets(config)
results: list[CheckResult] = []
if targets:
async with httpx.AsyncClient(timeout=_PROBE_TIMEOUT_S) as client:
probes = await asyncio.gather(
*(_probe_endpoint(client, url) for url in targets)
)
for url, (reachable, error, payload) in zip(targets, probes):
results.append(
_endpoint_result(url, targets[url], reachable, error, payload)
)
for provider in sorted(local):
results.append(
CheckResult(
name=f"provider:{provider}",
severity=Severity.OK,
message=f"{provider}: local model, nothing to probe.",
)
)
return results
async def run_doctor(
config: AppConfig, db_path: Path, environ: dict[str, str]
) -> DoctorReport:
@ -459,29 +622,29 @@ async def run_doctor(
db = await connect_lancedb(config, db_path)
stats = await get_database_stats(db)
results: list[CheckResult] = []
if not any(entry["exists"] for entry in stats.values()):
return DoctorReport(
results=[
CheckResult(
name="tables_present",
severity=Severity.FAIL,
message="Database is empty.",
remediation="haiku-rag init",
)
]
results.append(
CheckResult(
name="tables_present",
severity=Severity.FAIL,
message="Database is empty.",
remediation="haiku-rag init",
)
)
results = [_check_tables_present(stats)]
missing = [name for name in REQUIRED_TABLES if not stats[name]["exists"]]
if not missing:
async with Store(
db_path,
config=config,
skip_validation=True,
read_only=True,
skip_migration_check=True,
) as store:
results += await run_db_checks(store, config, stats)
else:
results.append(_check_tables_present(stats))
missing = [name for name in REQUIRED_TABLES if not stats[name]["exists"]]
if not missing:
async with Store(
db_path,
config=config,
skip_validation=True,
read_only=True,
skip_migration_check=True,
) as store:
results += await run_db_checks(store, config, stats)
results.append(_check_api_keys(config, environ))
results += await run_provider_checks(config)
return DoctorReport(results=results)

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@ -7,15 +7,27 @@ import pytest
from typer.testing import CliRunner
from haiku.rag.cli import _cli as cli
from haiku.rag.config.models import AppConfig, EmbeddingModelConfig, EmbeddingsConfig
from haiku.rag.config.models import (
AppConfig,
DoclingServeConfig,
EmbeddingModelConfig,
EmbeddingsConfig,
ProcessingConfig,
ProvidersConfig,
)
from haiku.rag.doctor import (
CheckResult,
DoctorReport,
Severity,
_check_embedding_drift,
_check_vector_index,
_model_present,
_probe_endpoint,
_provider_targets,
_resolve_endpoint,
_sample,
run_doctor,
run_provider_checks,
)
from haiku.rag.store.engine import (
DocumentItemRecord,
@ -110,6 +122,28 @@ def _result(report: DoctorReport, name: str) -> CheckResult:
return next(r for r in report.results if r.name == name)
@pytest.fixture(autouse=True)
def _stub_provider_probe(monkeypatch):
"""Default every provider probe to reachable with the test models present,
so database-integrity tests don't depend on a live Ollama. Provider tests
re-patch this with their own behavior."""
async def probe(_client, _url):
return (
True,
None,
{
"models": [
{"name": "test"},
{"name": "gpt-oss:latest"},
{"name": "qwen3-embedding:4b"},
]
},
)
monkeypatch.setattr("haiku.rag.doctor._probe_endpoint", probe)
@pytest.mark.asyncio
async def test_healthy_db_all_ok(temp_db_path):
await _build_db(temp_db_path)
@ -423,3 +457,229 @@ def test_cli_doctor_exits_1_on_failure(monkeypatch):
monkeypatch.setattr("haiku.rag.cli.create_app", lambda *_a, **_k: app)
result = runner.invoke(cli, ["doctor", "--db", "/tmp/whatever.lancedb"])
assert result.exit_code == 1
# --- Provider connectivity ---
def test_resolve_endpoint_ollama_strips_v1():
assert _resolve_endpoint("ollama", "http://h:1/v1", "http://fallback") == (
"http://h:1/api/tags",
"ollama",
"http://h:1",
)
def test_resolve_endpoint_ollama_uses_provider_fallback():
assert _resolve_endpoint("ollama", None, "http://fallback:11434") == (
"http://fallback:11434/api/tags",
"ollama",
"http://fallback:11434",
)
def test_resolve_endpoint_vllm_default_and_models_path():
assert _resolve_endpoint("vllm", None, "http://o") == (
"http://localhost:8000/v1/models",
"openai",
"http://localhost:8000/v1",
)
def test_resolve_endpoint_vllm_appends_v1():
assert _resolve_endpoint("vllm", "http://vllm:8000", "http://o") == (
"http://vllm:8000/v1/models",
"openai",
"http://vllm:8000/v1",
)
def test_resolve_endpoint_openai_saas_is_skipped():
assert _resolve_endpoint("openai", None, "http://o") is None
def test_resolve_endpoint_openai_with_base_url():
assert _resolve_endpoint("openai", "http://lmstudio:1234/v1", "http://o") == (
"http://lmstudio:1234/v1/models",
"openai",
"http://lmstudio:1234/v1",
)
def test_resolve_endpoint_local_provider():
assert _resolve_endpoint("sentence-transformers", None, "http://o") == "local"
def test_model_present_tag_insensitive():
assert _model_present("gpt-oss", {"gpt-oss:latest"})
assert _model_present("qwen:4b", {"qwen:4b"})
assert not _model_present("qwen:4b", {"qwen:8b"})
def test_provider_targets_default_groups_ollama_models():
targets, local = _provider_targets(AppConfig())
assert not local
assert len(targets) == 1
entry = next(iter(targets.values()))
assert entry["kind"] == "ollama"
assert {"qwen3-embedding:4b", "gpt-oss"} <= entry["models"]
def test_provider_targets_includes_docling_serve():
config = AppConfig(
processing=ProcessingConfig(converter="docling-serve"),
providers=ProvidersConfig(
docling_serve=DoclingServeConfig(base_url="http://docling:5001")
),
)
targets, _ = _provider_targets(config)
assert "http://docling:5001/health" in targets
assert targets["http://docling:5001/health"]["kind"] == "docling-serve"
def test_provider_targets_collects_local_providers():
config = AppConfig(
embeddings=EmbeddingsConfig(
model=EmbeddingModelConfig(
provider="sentence-transformers", name="x", vector_dim=4
)
)
)
_, local = _provider_targets(config)
assert "sentence-transformers" in local
def _fake_probe(result):
async def probe(_client, _url):
return result
return probe
@pytest.mark.asyncio
async def test_provider_check_ok_when_models_present(monkeypatch):
monkeypatch.setattr(
"haiku.rag.doctor._probe_endpoint",
_fake_probe(
(
True,
None,
{
"models": [
{"name": "qwen3-embedding:4b"},
{"name": "gpt-oss:latest"},
]
},
)
),
)
results = await run_provider_checks(AppConfig())
assert all(r.severity is Severity.OK for r in results)
@pytest.mark.asyncio
async def test_provider_check_warns_on_missing_model(monkeypatch):
monkeypatch.setattr(
"haiku.rag.doctor._probe_endpoint",
_fake_probe((True, None, {"models": [{"name": "something-else"}]})),
)
results = await run_provider_checks(AppConfig())
result = next(r for r in results if r.name.startswith("provider:"))
assert result.severity is Severity.WARN
assert result.details
@pytest.mark.asyncio
async def test_provider_check_fails_when_unreachable(monkeypatch):
monkeypatch.setattr(
"haiku.rag.doctor._probe_endpoint",
_fake_probe((False, "Connection refused", None)),
)
results = await run_provider_checks(AppConfig())
result = next(r for r in results if r.name.startswith("provider:"))
assert result.severity is Severity.FAIL
assert "Connection refused" in result.details
@pytest.mark.asyncio
async def test_provider_check_reports_local_provider(monkeypatch):
monkeypatch.setattr(
"haiku.rag.doctor._probe_endpoint",
_fake_probe((True, None, {"models": [{"name": "gpt-oss:latest"}]})),
)
config = AppConfig(
embeddings=EmbeddingsConfig(
model=EmbeddingModelConfig(
provider="sentence-transformers", name="x", vector_dim=4
)
)
)
results = await run_provider_checks(config)
local = next(r for r in results if r.name == "provider:sentence-transformers")
assert local.severity is Severity.OK
assert "local" in local.message
@pytest.mark.asyncio
async def test_run_doctor_includes_provider_results(temp_db_path, monkeypatch):
await _build_db(temp_db_path)
monkeypatch.setattr(
"haiku.rag.doctor._probe_endpoint",
_fake_probe(
(True, None, {"models": [{"name": "test"}, {"name": "gpt-oss:latest"}]})
),
)
report = await run_doctor(_config(), temp_db_path, {})
assert any(r.name.startswith("provider:") for r in report.results)
assert not report.failed
async def _probe_with_handler(handler):
import httpx
transport = httpx.MockTransport(handler)
async with httpx.AsyncClient(transport=transport) as client:
return await _probe_endpoint(client, "http://x")
@pytest.mark.asyncio
async def test_probe_endpoint_success_with_json():
import httpx
reachable, error, payload = await _probe_with_handler(
lambda _request: httpx.Response(200, json={"models": []})
)
assert reachable and error is None and payload == {"models": []}
@pytest.mark.asyncio
async def test_probe_endpoint_success_non_json():
import httpx
reachable, _, payload = await _probe_with_handler(
lambda _request: httpx.Response(200, content=b"not json")
)
assert reachable and payload is None
@pytest.mark.asyncio
async def test_probe_endpoint_http_error_status():
import httpx
reachable, error, _ = await _probe_with_handler(
lambda _request: httpx.Response(503)
)
assert not reachable
assert error is not None and "503" in error
@pytest.mark.asyncio
async def test_probe_endpoint_connection_error():
import httpx
def handler(_request):
raise httpx.ConnectError("refused")
reachable, error, _ = await _probe_with_handler(handler)
assert not reachable
assert error is not None and "refused" in error