Files
nanobot/nanobot/providers/fallback_provider.py
T
chengyongru 913b0774d8 feat(runner): add model failover with fallback_models
When the primary model returns a non-transient error and no content
has been streamed yet, the runner now tries each model listed in the
active preset's fallback_models in order.  Each fallback model may
reside on a different provider — a temporary provider instance is
created on-the-fly via make_provider(config, model=...).

Key design:
- Failover is request-scoped (does not affect subagents/dream/consolidator)
- Provider is restored via try/finally after each fallback attempt
- Skipped when content was already streamed to avoid duplicate output
- Recursive failover prevented by clearing fallback_models on fallback spec
- Circuit breaker trips open after 3 consecutive primary failures (60s cooldown)
- Cross-provider routing: fallback model prefix (e.g. groq/) determines provider

Fixes: cross-provider fallback was broken because the factory passed the
original preset (with provider forced to primary's provider) when creating
fallback providers.  Now uses provider="auto" so the model string prefix
correctly routes to the right provider.

Also fixes: log messages now distinguish between primary-failed,
previous-fallback-failed, and circuit-open scenarios.

closes: https://github.com/HKUDS/nanobot/issues/3376
2026-05-13 17:30:49 +08:00

187 lines
6.8 KiB
Python

"""Provider wrapper that transparently fails over to fallback models on error."""
from __future__ import annotations
import time
from collections.abc import Awaitable, Callable
from typing import Any
from loguru import logger
from nanobot.providers.base import LLMProvider, LLMResponse
# Circuit breaker tuned to match OpenAICompatProvider's Responses API breaker.
_PRIMARY_FAILURE_THRESHOLD = 3
_PRIMARY_COOLDOWN_S = 60
class FallbackProvider(LLMProvider):
"""Wrap a primary provider and transparently failover to fallback models.
When the primary model returns an error and no content has been streamed yet,
the wrapper tries each fallback model in order. Each fallback model may
reside on a different provider — a factory callable creates the underlying
provider on-the-fly.
Key design:
- Failover is request-scoped (the wrapper itself is stateless between turns).
- Skipped when content was already streamed to avoid duplicate output.
- Recursive failover is prevented by the factory returning plain providers.
- Primary provider is circuit-broken after repeated failures to avoid
wasting requests on a known-bad endpoint.
"""
def __init__(
self,
primary: LLMProvider,
fallback_models: list[str],
provider_factory: Callable[[str], LLMProvider],
):
self._primary = primary
self._fallback_models = list(fallback_models)
self._provider_factory = provider_factory
self._has_fallbacks = bool(fallback_models)
self._primary_failures = 0
self._primary_tripped_at: float | None = None
@property
def generation(self):
return self._primary.generation
@generation.setter
def generation(self, value):
self._primary.generation = value
def get_default_model(self) -> str:
return self._primary.get_default_model()
def _primary_available(self) -> bool:
"""Return True if the primary provider is not currently tripped."""
if self._primary_tripped_at is None:
return True
if time.monotonic() - self._primary_tripped_at >= _PRIMARY_COOLDOWN_S:
# Half-open: allow one probe attempt.
return True
return False
async def chat(self, **kwargs: Any) -> LLMResponse:
if not self._has_fallbacks:
return await self._primary.chat(**kwargs)
return await self._try_with_fallback(
lambda p, kw: p.chat(**kw), kwargs, has_streamed=None
)
async def chat_stream(self, **kwargs: Any) -> LLMResponse:
if not self._has_fallbacks:
return await self._primary.chat_stream(**kwargs)
has_streamed: list[bool] = [False]
original_delta = kwargs.get("on_content_delta")
async def _tracking_delta(text: str) -> None:
if text:
has_streamed[0] = True
if original_delta:
await original_delta(text)
kwargs["on_content_delta"] = _tracking_delta
return await self._try_with_fallback(
lambda p, kw: p.chat_stream(**kw), kwargs, has_streamed=has_streamed
)
async def _try_with_fallback(
self,
call: Callable[[LLMProvider, dict[str, Any]], Awaitable[LLMResponse]],
kwargs: dict[str, Any],
has_streamed: list[bool] | None,
) -> LLMResponse:
primary_model = kwargs.get("model") or self._primary.get_default_model()
if self._primary_available():
response = await call(self._primary, kwargs)
if response.finish_reason != "error":
self._primary_failures = 0
self._primary_tripped_at = None
return response
if has_streamed is not None and has_streamed[0]:
logger.warning(
"Primary model error but content already streamed; skipping failover"
)
return response
self._primary_failures += 1
if self._primary_failures >= _PRIMARY_FAILURE_THRESHOLD:
self._primary_tripped_at = time.monotonic()
logger.warning(
"Primary model '{}' circuit open after {} consecutive failures",
primary_model, self._primary_failures,
)
else:
logger.debug("Primary model '{}' circuit open; skipping", primary_model)
last_response: LLMResponse | None = None
primary_skipped = not self._primary_available()
for idx, fallback_model in enumerate(self._fallback_models):
if has_streamed is not None and has_streamed[0]:
break
if idx == 0 and primary_skipped:
logger.info(
"Primary model '{}' circuit open, trying fallback '{}'",
primary_model, fallback_model,
)
elif idx == 0:
logger.info(
"Primary model '{}' failed, trying fallback '{}'",
primary_model, fallback_model,
)
else:
logger.info(
"Fallback '{}' also failed, trying next fallback '{}'",
self._fallback_models[idx - 1], fallback_model,
)
try:
fallback_provider = self._provider_factory(fallback_model)
except Exception as exc:
logger.warning(
"Failed to create provider for fallback '{}': {}", fallback_model, exc
)
continue
original_model = kwargs.get("model")
kwargs["model"] = fallback_model
try:
fallback_response = await call(fallback_provider, kwargs)
finally:
if original_model is not None:
kwargs["model"] = original_model
else:
kwargs.pop("model", None)
if fallback_response.finish_reason != "error":
logger.info(
"Fallback '{}' succeeded after primary '{}' failed",
fallback_model, primary_model,
)
return fallback_response
last_response = fallback_response
logger.warning(
"Fallback '{}' also failed: {}",
fallback_model,
(fallback_response.content or "")[:120],
)
logger.warning(
"All {} fallback model(s) failed",
len(self._fallback_models),
)
# Return the last error response we saw (primary or last fallback).
if last_response is not None:
return last_response
# Primary was tripped and we have no fallbacks — synthesize an error.
return LLMResponse(
content=f"Primary model '{primary_model}' circuit open and no fallbacks available",
finish_reason="error",
)