Refine fallback routing on model presets

nanobot/agent/runner.py

@@ -16,6 +16,7 @@ from nanobot.agent.hook import AgentHook, AgentHookContext
 from nanobot.agent.tools.ask import AskUserInterrupt
 from nanobot.agent.tools.registry import ToolRegistry
 from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
+from nanobot.providers.failover import ModelCandidate, ModelRouter
 from nanobot.utils.helpers import (
     build_assistant_message,
     estimate_message_tokens,
@@ -621,24 +622,14 @@ class AgentRunner:
             messages,
             tools=spec.tools.get_definitions(),
         )
-        response = await self._call_provider(self.provider, kwargs, hook, context, spec, timeout_s)
-
-        if response.finish_reason == "error" and spec.fallback_models:
-            for fb_model in spec.fallback_models:
-                logger.warning(
-                    "Primary model {} failed, trying fallback: {}",
-                    spec.model,
-                    fb_model,
-                )
-                fb_provider, resolved_model = self._resolve_fallback_provider(fb_model)
-                fb_kwargs = dict(kwargs, model=resolved_model)
-                response = await self._call_provider(
-                    fb_provider, fb_kwargs, hook, context, spec, timeout_s,
-                )
-                if response.finish_reason != "error":
-                    break
-
-        return response
+        provider: LLMProvider = self.provider
+        request_timeout = timeout_s
+        if spec.fallback_models:
+            provider = self._build_model_router(spec, timeout_s)
+            # ModelRouter applies the same timeout per candidate, preserving
+            # fallback on primary timeouts instead of timing out the whole chain.
+            request_timeout = None
+        return await self._call_provider(provider, kwargs, hook, context, spec, request_timeout)
 
     async def _call_provider(
         self,
@@ -716,6 +707,25 @@ class AgentRunner:
             return provider, provider.get_default_model()
         return self.provider, model
 
+    def _build_model_router(
+        self,
+        spec: AgentRunSpec,
+        timeout_s: float | None,
+    ) -> ModelRouter:
+        candidates = [
+            ModelCandidate(
+                label=model,
+                resolver=lambda m=model: self._resolve_fallback_provider(m),
+            )
+            for model in spec.fallback_models
+        ]
+        return ModelRouter(
+            primary_provider=self.provider,
+            primary_model=spec.model,
+            fallback_candidates=candidates,
+            per_candidate_timeout_s=timeout_s,
+        )
+
     async def _request_finalization_retry(
         self,
         spec: AgentRunSpec,

nanobot/cli/commands.py

@@ -527,8 +527,7 @@ def _make_cli_provider_factory(config: Config):
     def factory(model_or_preset: str):
         preset = presets.get(model_or_preset)
         actual_model = preset.model if preset else model_or_preset
-        provider_name = config.get_provider_name(actual_model)
-        key = provider_name or actual_model
+        key = actual_model
         if key not in cache:
             cache[key] = _make_provider_for_model(config, actual_model, preset=preset)
         return cache[key]

nanobot/nanobot.py

@@ -220,8 +220,7 @@ def _make_provider_factory(config: Any):
     def factory(model_or_preset: str):
         preset = presets.get(model_or_preset)
         actual_model = preset.model if preset else model_or_preset
-        provider_name = config.get_provider_name(actual_model)
-        key = provider_name or actual_model
+        key = actual_model
         if key not in cache:
             cache[key] = _make_provider_for_model(config, actual_model, preset=preset)
         return cache[key]

nanobot/providers/failover.py

@@ -0,0 +1,276 @@
+"""Provider-like failover router used after provider-local retry is exhausted."""
+
+from __future__ import annotations
+
+import asyncio
+from collections.abc import Awaitable, Callable
+from dataclasses import dataclass
+from typing import Any
+
+from loguru import logger
+
+from nanobot.providers.base import GenerationSettings, LLMProvider, LLMResponse
+
+
+@dataclass(frozen=True)
+class ModelCandidate:
+    """A lazily resolved model/provider candidate."""
+
+    label: str
+    resolver: Callable[[], tuple[LLMProvider, str]]
+
+
+class ModelRouter(LLMProvider):
+    """Try fallback model candidates for eligible transient final errors."""
+
+    supports_progress_deltas = False
+
+    _BLOCKED_STATUS_CODES = frozenset({400, 401, 403, 404, 422})
+    _QUOTA_MARKERS = (
+        "insufficient_quota",
+        "insufficient quota",
+        "quota exceeded",
+        "quota_exceeded",
+        "quota exhausted",
+        "quota_exhausted",
+        "billing hard limit",
+        "billing_hard_limit_reached",
+        "billing not active",
+        "insufficient balance",
+        "insufficient_balance",
+        "credit balance too low",
+        "payment required",
+        "out of credits",
+        "out of quota",
+        "exceeded your current quota",
+    )
+    _NON_FAILOVER_MARKERS = (
+        "context length",
+        "context_length",
+        "maximum context",
+        "max context",
+        "token budget",
+        "too many tokens",
+        "schema",
+        "invalid request",
+        "invalid_request",
+        "invalid parameter",
+        "invalid_parameter",
+        "unsupported",
+        "unauthorized",
+        "authentication",
+        "permission",
+        "forbidden",
+        "refusal",
+        "content policy",
+        "content_filter",
+        "policy violation",
+        "safety",
+    )
+
+    def __init__(
+        self,
+        *,
+        primary_provider: LLMProvider,
+        primary_model: str,
+        fallback_candidates: list[ModelCandidate],
+        per_candidate_timeout_s: float | None = None,
+    ) -> None:
+        super().__init__(
+            api_key=getattr(primary_provider, "api_key", None),
+            api_base=getattr(primary_provider, "api_base", None),
+        )
+        self.primary_provider = primary_provider
+        self.primary_model = primary_model
+        self.fallback_candidates = list(fallback_candidates)
+        self.per_candidate_timeout_s = per_candidate_timeout_s
+        self.generation = getattr(primary_provider, "generation", GenerationSettings())
+
+    def get_default_model(self) -> str:
+        return self.primary_model
+
+    async def chat(self, **kwargs: Any) -> LLMResponse:
+        return await self.primary_provider.chat(**kwargs)
+
+    async def chat_stream(self, **kwargs: Any) -> LLMResponse:
+        return await self.primary_provider.chat_stream(**kwargs)
+
+    @classmethod
+    def _is_quota_error(cls, response: LLMResponse) -> bool:
+        tokens = {
+            cls._normalize_error_token(response.error_type),
+            cls._normalize_error_token(response.error_code),
+        }
+        if any(token in cls._NON_RETRYABLE_429_ERROR_TOKENS for token in tokens if token):
+            return True
+        content = (response.content or "").lower()
+        return any(marker in content for marker in cls._QUOTA_MARKERS)
+
+    @classmethod
+    def _is_blocked_error(cls, response: LLMResponse) -> bool:
+        status = response.error_status_code
+        if status is not None and int(status) in cls._BLOCKED_STATUS_CODES:
+            return True
+        if response.finish_reason in {"refusal", "content_filter"}:
+            return True
+        content = (response.content or "").lower()
+        return any(marker in content for marker in cls._NON_FAILOVER_MARKERS)
+
+    @classmethod
+    def _should_failover(cls, response: LLMResponse) -> bool:
+        if response.finish_reason != "error":
+            return False
+        if cls._is_blocked_error(response):
+            return False
+        if cls._is_quota_error(response):
+            return False
+        return cls._is_transient_response(response)
+
+    async def _with_timeout(self, coro: Awaitable[LLMResponse]) -> LLMResponse:
+        timeout_s = self.per_candidate_timeout_s
+        if timeout_s is None:
+            return await coro
+        try:
+            return await asyncio.wait_for(coro, timeout=timeout_s)
+        except asyncio.TimeoutError:
+            return LLMResponse(
+                content=f"Error calling LLM: timed out after {timeout_s:g}s",
+                finish_reason="error",
+                error_kind="timeout",
+            )
+
+    @staticmethod
+    def _resolver_error(candidate: ModelCandidate, exc: Exception) -> LLMResponse:
+        logger.warning("Failed to resolve fallback model {}: {}", candidate.label, exc)
+        return LLMResponse(
+            content=f"Error configuring fallback model {candidate.label}: {exc}",
+            finish_reason="error",
+            error_kind="configuration",
+            error_should_retry=False,
+        )
+
+    def _candidate_chain(self) -> list[ModelCandidate]:
+        return [
+            ModelCandidate(
+                label=self.primary_model,
+                resolver=lambda: (self.primary_provider, self.primary_model),
+            ),
+            *self.fallback_candidates,
+        ]
+
+    async def _route(
+        self,
+        call: Callable[[LLMProvider, str, Callable[[str], Awaitable[None]] | None], Awaitable[LLMResponse]],
+        *,
+        on_content_delta: Callable[[str], Awaitable[None]] | None = None,
+    ) -> LLMResponse:
+        last_response: LLMResponse | None = None
+        chain = self._candidate_chain()
+        for index, candidate in enumerate(chain):
+            try:
+                provider, model = candidate.resolver()
+            except asyncio.CancelledError:
+                raise
+            except Exception as exc:
+                response = self._resolver_error(candidate, exc)
+            else:
+                response = await self._with_timeout(call(provider, model, on_content_delta))
+
+            if response.finish_reason != "error":
+                if index > 0:
+                    logger.info("LLM failover selected model={}", candidate.label)
+                return response
+
+            last_response = response
+            if not self._should_failover(response):
+                return response
+            if index + 1 >= len(chain):
+                logger.warning("LLM failover exhausted after model={}", candidate.label)
+                return response
+            logger.warning(
+                "LLM failover model={} next_model={} status={} kind={}",
+                candidate.label,
+                chain[index + 1].label,
+                response.error_status_code,
+                response.error_kind or response.error_type or response.error_code or "unknown",
+            )
+
+        return last_response or LLMResponse(
+            content="No available fallback model candidate.",
+            finish_reason="error",
+            error_kind="configuration",
+            error_should_retry=False,
+        )
+
+    async def chat_with_retry(
+        self,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        model: str | None = None,
+        max_tokens: object = LLMProvider._SENTINEL,
+        temperature: object = LLMProvider._SENTINEL,
+        reasoning_effort: object = LLMProvider._SENTINEL,
+        tool_choice: str | dict[str, Any] | None = None,
+        retry_mode: str = "standard",
+        on_retry_wait: Callable[[str], Awaitable[None]] | None = None,
+    ) -> LLMResponse:
+        async def call(
+            provider: LLMProvider,
+            candidate_model: str,
+            _delta: Callable[[str], Awaitable[None]] | None,
+        ) -> LLMResponse:
+            return await provider.chat_with_retry(
+                messages=messages,
+                tools=tools,
+                model=candidate_model,
+                max_tokens=max_tokens,
+                temperature=temperature,
+                reasoning_effort=reasoning_effort,
+                tool_choice=tool_choice,
+                retry_mode=retry_mode,
+                on_retry_wait=on_retry_wait,
+            )
+
+        return await self._route(call)
+
+    async def chat_stream_with_retry(
+        self,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        model: str | None = None,
+        max_tokens: object = LLMProvider._SENTINEL,
+        temperature: object = LLMProvider._SENTINEL,
+        reasoning_effort: object = LLMProvider._SENTINEL,
+        tool_choice: str | dict[str, Any] | None = None,
+        on_content_delta: Callable[[str], Awaitable[None]] | None = None,
+        retry_mode: str = "standard",
+        on_retry_wait: Callable[[str], Awaitable[None]] | None = None,
+    ) -> LLMResponse:
+        async def call(
+            provider: LLMProvider,
+            candidate_model: str,
+            external_delta: Callable[[str], Awaitable[None]] | None,
+        ) -> LLMResponse:
+            buffered: list[str] = []
+
+            async def buffer_delta(delta: str) -> None:
+                buffered.append(delta)
+
+            response = await provider.chat_stream_with_retry(
+                messages=messages,
+                tools=tools,
+                model=candidate_model,
+                max_tokens=max_tokens,
+                temperature=temperature,
+                reasoning_effort=reasoning_effort,
+                tool_choice=tool_choice,
+                on_content_delta=buffer_delta if external_delta else None,
+                retry_mode=retry_mode,
+                on_retry_wait=on_retry_wait,
+            )
+            if response.finish_reason != "error" and external_delta:
+                for delta in buffered:
+                    await external_delta(delta)
+            return response
+
+        return await self._route(call, on_content_delta=on_content_delta)

tests/agent/test_runner_fallback.py

@@ -6,7 +6,8 @@ from unittest.mock import AsyncMock, MagicMock
 
 import pytest
 
-from nanobot.agent.runner import AgentRunSpec, AgentRunner
+from nanobot.agent.hook import AgentHook, AgentHookContext
+from nanobot.agent.runner import AgentRunner, AgentRunSpec
 from nanobot.providers.base import LLMResponse
 
 
@@ -24,6 +25,10 @@ def _make_provider(*, model_response: LLMResponse | None = None):
     return p
 
 
+def _transient_error(content: str = "server unavailable") -> LLMResponse:
+    return LLMResponse(content=content, finish_reason="error", error_status_code=503)
+
+
 def _base_spec(**overrides) -> AgentRunSpec:
     defaults = dict(
         initial_messages=[
@@ -56,7 +61,7 @@ async def test_no_fallback_when_primary_succeeds():
 @pytest.mark.asyncio
 async def test_fallback_triggered_on_primary_error():
     """Primary fails -> first fallback succeeds."""
-    err = LLMResponse(content=None, finish_reason="error", usage={})
+    err = _transient_error()
     ok = LLMResponse(content="fallback-ok", tool_calls=[], usage={})
 
     primary = _make_provider(model_response=err)
@@ -76,12 +81,12 @@ async def test_fallback_triggered_on_primary_error():
 @pytest.mark.asyncio
 async def test_all_fallbacks_fail_returns_last_error():
     """Primary + all fallbacks fail -> return last error response."""
-    err = LLMResponse(content=None, finish_reason="error", usage={})
+    err = _transient_error()
 
     primary = _make_provider(model_response=err)
     fb1 = _make_provider(model_response=err)
     fb2 = _make_provider(model_response=LLMResponse(
-        content="last-error", finish_reason="error", usage={},
+        content="last-error", finish_reason="error", error_status_code=500, usage={},
     ))
 
     providers = {"fb-1": fb1, "fb-2": fb2}
@@ -110,7 +115,7 @@ async def test_empty_fallback_list_no_retry():
 @pytest.mark.asyncio
 async def test_cross_provider_fallback():
     """Fallback uses a different provider instance (cross-provider)."""
-    err = LLMResponse(content=None, finish_reason="error", usage={})
+    err = _transient_error()
     ok = LLMResponse(content="cross-provider-ok", tool_calls=[], usage={})
 
     primary = _make_provider(model_response=err)
@@ -132,7 +137,7 @@ async def test_cross_provider_fallback():
 @pytest.mark.asyncio
 async def test_fallback_skips_to_second_on_first_error():
     """First fallback also fails -> second fallback succeeds."""
-    err = LLMResponse(content=None, finish_reason="error", usage={})
+    err = _transient_error()
     ok = LLMResponse(content="second-fb-ok", tool_calls=[], usage={})
 
     primary = _make_provider(model_response=err)
@@ -158,7 +163,7 @@ async def test_fallback_reuses_same_provider_without_factory():
     async def chat_with_retry(*, messages, model, **kw):
         call_count["n"] += 1
         if call_count["n"] == 1:
-            return LLMResponse(content=None, finish_reason="error", usage={})
+            return _transient_error()
         return LLMResponse(content=f"ok-via-{model}", tool_calls=[], usage={})
 
     primary = MagicMock()
@@ -173,7 +178,7 @@ async def test_fallback_reuses_same_provider_without_factory():
 @pytest.mark.asyncio
 async def test_fallback_provider_cached():
     """Provider factory is called once per unique provider, not per attempt."""
-    err = LLMResponse(content=None, finish_reason="error", usage={})
+    err = _transient_error()
     ok = LLMResponse(content="cached-ok", tool_calls=[], usage={})
 
     primary = _make_provider(model_response=err)
@@ -188,3 +193,77 @@ async def test_fallback_provider_cached():
     result = await runner.run(_base_spec(fallback_models=["same-provider-model-a", "same-provider-model-b"]))
 
     assert result.final_content == "cached-ok"
+
+
+@pytest.mark.asyncio
+async def test_non_transient_error_does_not_fallback():
+    """Auth/config-style errors should surface instead of hiding bugs via fallback."""
+    primary = _make_provider(model_response=LLMResponse(
+        content="401 unauthorized",
+        finish_reason="error",
+        error_status_code=401,
+    ))
+    fallback = _make_provider(model_response=LLMResponse(content="fallback-ok"))
+    factory = MagicMock(return_value=fallback)
+
+    runner = AgentRunner(primary, provider_factory=factory)
+    result = await runner.run(_base_spec(fallback_models=["fb-model"]))
+
+    factory.assert_not_called()
+    assert result.error is not None
+
+
+@pytest.mark.asyncio
+async def test_quota_error_does_not_fallback_by_default():
+    """Quota/billing/payment 429s should not route by default."""
+    primary = _make_provider(model_response=LLMResponse(
+        content="insufficient quota",
+        finish_reason="error",
+        error_status_code=429,
+        error_code="insufficient_quota",
+    ))
+    fallback = _make_provider(model_response=LLMResponse(content="fallback-ok"))
+    factory = MagicMock(return_value=fallback)
+
+    runner = AgentRunner(primary, provider_factory=factory)
+    result = await runner.run(_base_spec(fallback_models=["fb-model"]))
+
+    factory.assert_not_called()
+    assert result.error is not None
+
+
+@pytest.mark.asyncio
+async def test_streaming_fallback_discards_failed_primary_deltas():
+    """Buffered streaming prevents primary partial output from leaking on fallback."""
+    streamed: list[str] = []
+
+    class StreamingHook(AgentHook):
+        def wants_streaming(self) -> bool:
+            return True
+
+        async def on_stream(self, context: AgentHookContext, delta: str) -> None:
+            streamed.append(delta)
+
+    async def primary_stream(*, on_content_delta, **kwargs):
+        await on_content_delta("bad partial")
+        return _transient_error()
+
+    async def fallback_stream(*, on_content_delta, **kwargs):
+        await on_content_delta("good")
+        await on_content_delta(" answer")
+        return LLMResponse(content="good answer", tool_calls=[], usage={})
+
+    primary = MagicMock()
+    primary.chat_stream_with_retry = primary_stream
+    fallback = MagicMock()
+    fallback.chat_stream_with_retry = fallback_stream
+    factory = MagicMock(return_value=fallback)
+
+    runner = AgentRunner(primary, provider_factory=factory)
+    result = await runner.run(_base_spec(
+        fallback_models=["fb-model"],
+        hook=StreamingHook(),
+    ))
+
+    assert result.final_content == "good answer"
+    assert streamed == ["good", " answer"]