fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480)
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Teknium
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6 changed files with 301 additions and 22 deletions
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@ -1112,8 +1112,32 @@ def _model_flow_custom(config):
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effective_key = api_key or current_key
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from hermes_cli.models import probe_api_models
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probe = probe_api_models(effective_key, effective_url)
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if probe.get("used_fallback") and probe.get("resolved_base_url"):
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print(
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f"Warning: endpoint verification worked at {probe['resolved_base_url']}/models, "
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f"not the exact URL you entered. Saving the working base URL instead."
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)
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effective_url = probe["resolved_base_url"]
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if base_url:
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base_url = effective_url
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elif probe.get("models") is not None:
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print(
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f"Verified endpoint via {probe.get('probed_url')} "
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f"({len(probe.get('models') or [])} model(s) visible)"
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)
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else:
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print(
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f"Warning: could not verify this endpoint via {probe.get('probed_url')}. "
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f"Hermes will still save it."
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)
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if probe.get("suggested_base_url"):
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print(f" If this server expects /v1, try base URL: {probe['suggested_base_url']}")
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if base_url:
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save_env_value("OPENAI_BASE_URL", base_url)
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save_env_value("OPENAI_BASE_URL", effective_url)
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if api_key:
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save_env_value("OPENAI_API_KEY", api_key)
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@ -308,6 +308,62 @@ def _fetch_anthropic_models(timeout: float = 5.0) -> Optional[list[str]]:
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return None
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def probe_api_models(
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api_key: Optional[str],
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base_url: Optional[str],
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timeout: float = 5.0,
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) -> dict[str, Any]:
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"""Probe an OpenAI-compatible ``/models`` endpoint with light URL heuristics."""
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normalized = (base_url or "").strip().rstrip("/")
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if not normalized:
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return {
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"models": None,
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"probed_url": None,
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"resolved_base_url": "",
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"suggested_base_url": None,
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"used_fallback": False,
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}
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if normalized.endswith("/v1"):
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alternate_base = normalized[:-3].rstrip("/")
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else:
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alternate_base = normalized + "/v1"
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candidates: list[tuple[str, bool]] = [(normalized, False)]
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if alternate_base and alternate_base != normalized:
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candidates.append((alternate_base, True))
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tried: list[str] = []
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headers: dict[str, str] = {}
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if api_key:
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headers["Authorization"] = f"Bearer {api_key}"
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for candidate_base, is_fallback in candidates:
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url = candidate_base.rstrip("/") + "/models"
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tried.append(url)
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req = urllib.request.Request(url, headers=headers)
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try:
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with urllib.request.urlopen(req, timeout=timeout) as resp:
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data = json.loads(resp.read().decode())
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return {
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"models": [m.get("id", "") for m in data.get("data", [])],
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"probed_url": url,
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"resolved_base_url": candidate_base.rstrip("/"),
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"suggested_base_url": alternate_base if alternate_base != candidate_base else normalized,
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"used_fallback": is_fallback,
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}
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except Exception:
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continue
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return {
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"models": None,
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"probed_url": tried[-1] if tried else normalized.rstrip("/") + "/models",
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"resolved_base_url": normalized,
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"suggested_base_url": alternate_base if alternate_base != normalized else None,
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"used_fallback": False,
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}
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def fetch_api_models(
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api_key: Optional[str],
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base_url: Optional[str],
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@ -318,22 +374,7 @@ def fetch_api_models(
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Returns a list of model ID strings, or ``None`` if the endpoint could not
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be reached (network error, timeout, auth failure, etc.).
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"""
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if not base_url:
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return None
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url = base_url.rstrip("/") + "/models"
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headers: dict[str, str] = {}
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if api_key:
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headers["Authorization"] = f"Bearer {api_key}"
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req = urllib.request.Request(url, headers=headers)
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try:
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with urllib.request.urlopen(req, timeout=timeout) as resp:
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data = json.loads(resp.read().decode())
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# Standard OpenAI format: {"data": [{"id": "model-name", ...}, ...]}
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return [m.get("id", "") for m in data.get("data", [])]
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except Exception:
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return None
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return probe_api_models(api_key, base_url, timeout=timeout).get("models")
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def validate_requested_model(
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@ -376,13 +417,53 @@ def validate_requested_model(
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"message": "Model names cannot contain spaces.",
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}
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# Custom endpoints can serve any model — skip validation
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if normalized == "custom":
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probe = probe_api_models(api_key, base_url)
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api_models = probe.get("models")
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if api_models is not None:
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if requested in set(api_models):
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return {
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"accepted": True,
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"persist": True,
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"recognized": True,
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"message": None,
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}
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suggestions = get_close_matches(requested, api_models, n=3, cutoff=0.5)
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suggestion_text = ""
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if suggestions:
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suggestion_text = "\n Similar models: " + ", ".join(f"`{s}`" for s in suggestions)
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message = (
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f"Note: `{requested}` was not found in this custom endpoint's model listing "
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f"({probe.get('probed_url')}). It may still work if the server supports hidden or aliased models."
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f"{suggestion_text}"
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)
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if probe.get("used_fallback"):
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message += (
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f"\n Endpoint verification succeeded after trying `{probe.get('resolved_base_url')}`. "
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f"Consider saving that as your base URL."
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)
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return {
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"accepted": True,
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"persist": True,
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"recognized": False,
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"message": message,
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}
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message = (
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f"Note: could not reach this custom endpoint's model listing at `{probe.get('probed_url')}`. "
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f"Hermes will still save `{requested}`, but the endpoint should expose `/models` for verification."
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)
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if probe.get("suggested_base_url"):
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message += f"\n If this server expects `/v1`, try base URL: `{probe.get('suggested_base_url')}`"
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return {
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"accepted": True,
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"persist": True,
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"recognized": False,
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"message": None,
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"message": message,
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}
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# Probe the live API to check if the model actually exists
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@ -933,11 +933,35 @@ def setup_model_provider(config: dict):
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base_url = prompt(
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" API base URL (e.g., https://api.example.com/v1)", current_url
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)
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).strip()
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api_key = prompt(" API key", password=True)
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model_name = prompt(" Model name (e.g., gpt-4, claude-3-opus)", current_model)
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if base_url:
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from hermes_cli.models import probe_api_models
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probe = probe_api_models(api_key, base_url)
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if probe.get("used_fallback") and probe.get("resolved_base_url"):
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print_warning(
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f"Endpoint verification worked at {probe['resolved_base_url']}/models, "
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f"not the exact URL you entered. Saving the working base URL instead."
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)
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base_url = probe["resolved_base_url"]
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elif probe.get("models") is not None:
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print_success(
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f"Verified endpoint via {probe.get('probed_url')} "
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f"({len(probe.get('models') or [])} model(s) visible)"
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)
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else:
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print_warning(
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f"Could not verify this endpoint via {probe.get('probed_url')}. "
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f"Hermes will still save it."
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)
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if probe.get("suggested_base_url"):
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print_info(
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f" If this server expects /v1, try base URL: {probe['suggested_base_url']}"
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)
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save_env_value("OPENAI_BASE_URL", base_url)
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if api_key:
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save_env_value("OPENAI_API_KEY", api_key)
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