Files
odysseus/src/agent_runtime/context_resolution.py
T
Alexandre Teixeira 0054557027 fix(runtime): resolve compact-turn context once at the chat route
The first checkpoint removed terminal-metrics discovery, but a normal
compact chat turn still ran two context systems: build_chat_context's
legacy untyped lookup (directly or inside maybe_compact) and the typed
resolver inside stream_preview.

Resolve the typed ContextResolution once, at the chat route, before
build_chat_context, using the session's provider credentials. The
predicate mirrors _clean_v3_preview; every input it needs is known at
that point and the native-workspace term cannot veto a requested clean
route. The same object then:

- sizes legacy history shaping in build_chat_context through a new
  maybe_compact(context_length=...) override, so no legacy probe runs;
  an unknown window still shapes with DEFAULT_CONTEXT but gains no
  provenance;
- crosses stream_agent_loop (one new parameter, forwarded only at the
  compact dispatch) into stream_preview, which reuses it and probes only
  for callers that arrive without one or with one bound to another
  route.

ContextResolution now records the endpoint and model it describes
(endpoint URL excluded from repr and metrics). The bare legacy
context_length is never converted into typed evidence.

Credential scoping: origins compare with default ports normalized, an
empty host is never trusted, and the probe client never follows
redirects. Tests cover the configured origin, the server-resolved
Tailscale form, scheme/port/lookalike/userinfo/path origins, redirects,
and secret-free errors, logs and metrics.

The conftest guard now replaces only the resolver's I/O edges (HTTP
client and DNS-capable URL building) instead of the whole probe, and
exposes a context_probe_ledger fixture, so route integration tests run
the real resolver offline and can count metadata requests.
2026-10-01 22:31:21 +01:00

520 lines
20 KiB
Python

"""Effective model context window, resolved once per logical turn.
A turn resolves the window it budgets against at preparation time, before any
model request, and keeps the value together with the evidence that chose it.
Terminal metrics report that stored resolution; they never start discovery.
Evidence classes are kept apart instead of being folded into one "known" flag:
* ``runtime_confirmed``: the serving process reported its active window
(llama.cpp ``/slots`` or ``/props``) or rejected a request of this turn with
an explicit limit.
* ``provider_advertised``: the provider's model catalog lists a window.
* ``operator_declared``: the client or operator declared a transport window.
It caps runtime or provider evidence and replaces weaker evidence.
* ``known_table``: the static ``KNOWN_CONTEXT_WINDOWS`` fallback.
* ``unknown``: nothing above is available. The value is 0, never a default.
Any disagreement between sources is recorded as a conflict. An operator value
below a measured value is a cap, not a contradiction; an operator value above
it is a contradiction.
Context sizing is not authority: nothing here grants or denies an operation.
"""
from __future__ import annotations
import asyncio
from dataclasses import dataclass, field, replace
from enum import Enum
import hashlib
import json
import logging
import time
from typing import Any, Mapping, Optional
from urllib.parse import urlparse
import httpx
logger = logging.getLogger(__name__)
# Upper bound for all provider metadata I/O of one turn preparation. A slow
# or unreachable metadata endpoint costs at most this much before the turn
# proceeds with whatever evidence it has.
PROBE_DEADLINE_SECONDS = 3.0
# Remote provider metadata changes rarely; failures are retried sooner so a
# transient outage does not pin a turn to weaker evidence for long. Local
# servers are always re-probed because they can restart with another window.
PROBE_CACHE_TTL_SECONDS = 600.0
PROBE_FAILURE_TTL_SECONDS = 60.0
# Headers that describe the chat request body rather than the caller.
_REQUEST_ONLY_HEADERS = frozenset({"content-type", "content-length", "accept", "accept-encoding"})
class ContextEvidence(str, Enum):
RUNTIME_CONFIRMED = "runtime_confirmed"
PROVIDER_ADVERTISED = "provider_advertised"
OPERATOR_DECLARED = "operator_declared"
KNOWN_TABLE = "known_table"
UNKNOWN = "unknown"
@dataclass(frozen=True)
class ContextObservation:
evidence: ContextEvidence
value: int
source: str
def to_dict(self) -> dict:
return {"evidence": self.evidence.value, "value": self.value, "source": self.source}
@dataclass(frozen=True)
class ContextConflict:
first: ContextObservation
second: ContextObservation
def to_dict(self) -> dict:
return {"first": self.first.to_dict(), "second": self.second.to_dict()}
@dataclass(frozen=True)
class ContextResolution:
"""The effective window of one turn and why it was chosen."""
effective: int
evidence: ContextEvidence
source: str
observations: tuple[ContextObservation, ...] = ()
conflicts: tuple[ContextConflict, ...] = ()
provider_io: bool = False
cached: bool = False
probe_errors: tuple[str, ...] = ()
# The route this resolution describes. Empty for resolutions built
# directly from observations by internal callers. The URL can carry
# credentials, so it stays out of repr() and to_dict().
endpoint_url: str = field(default="", repr=False)
model: str = ""
@property
def mismatch(self) -> bool:
return bool(self.conflicts)
@property
def budget_limit(self) -> int:
"""Window the runtime may budget against; 0 means budget reactively."""
return self.effective if self.evidence is not ContextEvidence.UNKNOWN else 0
@property
def shaping_window(self) -> int:
"""Window for the legacy history compaction/trim helpers.
Those helpers predate typed evidence and always size against some
window, using DEFAULT_CONTEXT when none is known. This only feeds them
a number; it never creates provenance for that number.
"""
if self.budget_limit:
return self.budget_limit
from src.model_context import DEFAULT_CONTEXT
return DEFAULT_CONTEXT
def applies_to(self, endpoint_url: str, model: str) -> bool:
"""Whether this resolution may be reused for the given route."""
if not self.endpoint_url and not self.model:
return True
return self.endpoint_url == endpoint_url and self.model == model
def observe_runtime_limit(self, limit: Any, source: str = "provider_rejection") -> "ContextResolution":
"""Fold a limit the provider stated during this turn. Performs no I/O."""
try:
value = int(limit or 0)
except (TypeError, ValueError):
return self
if value <= 0:
return self
observation = ContextObservation(ContextEvidence.RUNTIME_CONFIRMED, value, source)
if observation in self.observations:
return self
combined = combine_observations((*self.observations, observation))
return replace(
combined,
provider_io=self.provider_io,
cached=self.cached,
probe_errors=self.probe_errors,
endpoint_url=self.endpoint_url,
model=self.model,
)
def to_dict(self) -> dict:
return {
"effective": self.effective,
"evidence": self.evidence.value,
"source": self.source,
"mismatch": self.mismatch,
"conflicts": [conflict.to_dict() for conflict in self.conflicts],
"observations": [observation.to_dict() for observation in self.observations],
"provider_io": self.provider_io,
"cached": self.cached,
"probe_errors": list(self.probe_errors),
}
UNRESOLVED_CONTEXT = ContextResolution(0, ContextEvidence.UNKNOWN, "none")
_MEASURED = (ContextEvidence.RUNTIME_CONFIRMED, ContextEvidence.PROVIDER_ADVERTISED)
def _conflicts(observations: tuple[ContextObservation, ...]) -> tuple[ContextConflict, ...]:
conflicts = []
for index, first in enumerate(observations):
for second in observations[index + 1:]:
if first.value == second.value:
continue
classes = {first.evidence, second.evidence}
if ContextEvidence.OPERATOR_DECLARED in classes:
operator, other = (
(first, second) if first.evidence is ContextEvidence.OPERATOR_DECLARED
else (second, first)
)
# A declared window replaces the static table and may cap a
# measured window. Only a declaration above what the runtime
# or provider supports contradicts it.
if other.evidence not in _MEASURED or operator.value < other.value:
continue
conflicts.append(ContextConflict(first, second))
return tuple(conflicts)
def _strongest(observations, evidence: ContextEvidence) -> Optional[ContextObservation]:
matching = [observation for observation in observations if observation.evidence is evidence]
return min(matching, key=lambda observation: observation.value) if matching else None
def combine_observations(observations) -> ContextResolution:
"""Choose the effective window deterministically from observations.
The smallest runtime-confirmed value wins, else the smallest provider
value. An operator declaration caps either, and replaces the known table
or an unknown window. The known table is used only when nothing stronger
exists. No observation yields an unknown window of 0.
"""
observations = tuple(observations)
measured = (
_strongest(observations, ContextEvidence.RUNTIME_CONFIRMED)
or _strongest(observations, ContextEvidence.PROVIDER_ADVERTISED)
)
operator = _strongest(observations, ContextEvidence.OPERATOR_DECLARED)
if measured and operator:
chosen = operator if operator.value < measured.value else measured
else:
chosen = measured or operator or _strongest(observations, ContextEvidence.KNOWN_TABLE)
conflicts = _conflicts(observations)
if chosen is None:
return replace(UNRESOLVED_CONTEXT, observations=observations, conflicts=conflicts)
return ContextResolution(
chosen.value, chosen.evidence, chosen.source,
observations=observations, conflicts=conflicts,
)
# ---------------------------------------------------------------------------
# Provider metadata probe
# ---------------------------------------------------------------------------
@dataclass(frozen=True)
class _ProbeResult:
observations: tuple[ContextObservation, ...] = ()
errors: tuple[str, ...] = ()
io: bool = False
_probe_cache: dict[tuple[str, str, str], tuple[float, _ProbeResult]] = {}
def clear_probe_cache() -> None:
_probe_cache.clear()
_DEFAULT_PORTS = {"http": 80, "https": 443}
def _origin(url: str) -> tuple[str, str, Optional[int]]:
parsed = urlparse(url or "")
scheme = parsed.scheme.lower()
try:
port = parsed.port
except ValueError:
return ("", "", None)
return (scheme, (parsed.hostname or "").lower(), port or _DEFAULT_PORTS.get(scheme))
def _http_client(timeout: float):
# Credentials must never follow a redirect to another location.
return httpx.AsyncClient(timeout=timeout, follow_redirects=False)
def _provider_urls(endpoint_url: str) -> tuple[Optional[str], str]:
"""Models catalog URL and the server-resolved form of the endpoint.
Both come from the existing endpoint resolver, which may rewrite an
unresolvable host to its Tailscale address. Blocking (DNS, subprocess);
call it off the event loop.
"""
from src.endpoint_resolver import build_models_url, resolve_url
return build_models_url(endpoint_url), resolve_url(endpoint_url)
def _probe_headers(trusted_origins, target_url: str, headers: Optional[Mapping[str, Any]]) -> dict:
"""Forward the turn's provider credentials only to the provider's origin."""
origin = _origin(target_url)
if not headers or not origin[1] or origin not in trusted_origins:
return {}
return {
str(name): str(value) for name, value in headers.items()
if value is not None and str(name).lower() not in _REQUEST_ONLY_HEADERS
}
def _auth_fingerprint(headers: Optional[Mapping[str, Any]]) -> str:
if not headers:
return ""
material = json.dumps(
sorted((str(k).lower(), str(v)) for k, v in headers.items()
if v is not None and str(k).lower() not in _REQUEST_ONLY_HEADERS),
separators=(",", ":"),
)
return hashlib.sha256(material.encode("utf-8")).hexdigest()[:16]
def _serving_base(endpoint_url: str) -> str:
# Same derivation the regular runtime uses for llama.cpp server routes.
return endpoint_url.split("/v1")[0] if "/v1" in endpoint_url else endpoint_url.rsplit("/", 1)[0]
async def _get_json(client, url, headers, errors, label):
try:
response = await client.get(url, headers=headers)
except httpx.TimeoutException:
errors.append(f"{label}:timeout")
return None
except httpx.TransportError:
errors.append(f"{label}:transport_error")
return None
status = getattr(response, "status_code", 0)
if not (200 <= int(status or 0) < 300):
errors.append(f"{label}:http_{status}")
return None
try:
return response.json()
except Exception:
errors.append(f"{label}:invalid_payload")
return None
def _positive_int(value) -> int:
if isinstance(value, bool) or not isinstance(value, (int, float)) or value <= 0:
return 0
return int(value)
async def _probe(endpoint_url, model, headers, is_local, observations, errors, timeout):
from src.copilot import is_copilot_base
from src.model_context import _model_ctx_from_entry
# Credentials go only to the configured provider's origin, or to the
# form of that same endpoint the server-owned resolver produced.
trusted = {_origin(endpoint_url)}
async with _http_client(timeout) as client:
if is_local:
base = _serving_base(endpoint_url)
slots = await _get_json(
client, f"{base}/slots", _probe_headers(trusted, f"{base}/slots", headers),
errors, "slots",
)
n_ctx = _positive_int(slots[0].get("n_ctx")) if (
isinstance(slots, list) and slots and isinstance(slots[0], dict)
) else 0
if not n_ctx:
props = await _get_json(
client, f"{base}/props", _probe_headers(trusted, f"{base}/props", headers),
errors, "props",
)
generation = props.get("default_generation_settings") if isinstance(props, dict) else None
n_ctx = _positive_int(generation.get("n_ctx")) if isinstance(generation, dict) else 0
source = "llamacpp_props"
else:
source = "llamacpp_slots"
if n_ctx:
observations.append(
ContextObservation(ContextEvidence.RUNTIME_CONFIRMED, n_ctx, source)
)
# Copilot's catalog needs headers this layer does not own; an
# unauthenticated probe only fails. Its models are table-covered.
if is_copilot_base(endpoint_url):
errors.append("models:unsupported_endpoint")
return
# URL building may resolve the host (DNS, tailscale lookup); keep that
# off the event loop and inside the probe deadline.
models_url, resolved_endpoint = await asyncio.to_thread(_provider_urls, endpoint_url)
if not models_url:
errors.append("models:unsupported_endpoint")
return
trusted.add(_origin(resolved_endpoint))
payload = await _get_json(
client, models_url, _probe_headers(trusted, models_url, headers),
errors, "models",
)
if payload is None:
return
entries = payload.get("data") if isinstance(payload, dict) else None
if not isinstance(entries, list):
errors.append("models:invalid_payload")
return
wanted = model.split("/")[-1]
for entry in entries:
if not isinstance(entry, dict):
continue
entry_id = str(entry.get("id") or "")
if entry_id == model or entry_id.split("/")[-1] == wanted:
value = _model_ctx_from_entry(entry)
if value:
observations.append(ContextObservation(
ContextEvidence.PROVIDER_ADVERTISED, int(value), "models_catalog",
))
else:
errors.append("models:no_window_listed")
return
errors.append("models:model_not_listed")
async def probe_provider_context(
endpoint_url: str,
model: str,
*,
headers: Optional[Mapping[str, Any]] = None,
deadline_seconds: float = PROBE_DEADLINE_SECONDS,
is_local: Optional[bool] = None,
) -> _ProbeResult:
"""Query provider metadata once, bounded by ``deadline_seconds``.
Never raises: every failure is reported as a short, secret-free error code
so a turn can continue with other evidence.
"""
observations: list[ContextObservation] = []
errors: list[str] = []
if is_local is None:
is_local = await _is_local(endpoint_url)
timeout = max(0.1, float(deadline_seconds))
try:
await asyncio.wait_for(
_probe(endpoint_url, model, headers, is_local, observations, errors, timeout),
timeout=timeout,
)
except asyncio.TimeoutError:
errors.append("deadline_exceeded")
except Exception as exc:
logger.debug("Context window probe failed: %s", type(exc).__name__)
errors.append("probe_failed")
return _ProbeResult(tuple(observations), tuple(errors), io=True)
async def _is_local(endpoint_url: str) -> bool:
from src.model_context import is_local_endpoint
try:
# Reads configured endpoints from the local database on the calling
# thread, as the regular runtime does. Moving it to worker threads
# gives SQLite sessions per-thread connections the app never uses.
return bool(is_local_endpoint(endpoint_url))
except Exception:
return False
async def _cached_probe(endpoint_url, model, headers, deadline_seconds, clock):
is_local = await _is_local(endpoint_url)
key = (endpoint_url, model, _auth_fingerprint(headers))
if not is_local:
cached = _probe_cache.get(key)
if cached and cached[0] > clock():
return cached[1], True
result = await probe_provider_context(
endpoint_url, model, headers=headers, deadline_seconds=deadline_seconds,
is_local=is_local,
)
if not is_local:
ttl = PROBE_CACHE_TTL_SECONDS if result.observations else PROBE_FAILURE_TTL_SECONDS
_probe_cache[key] = (clock() + ttl, result)
return result, False
def declared_context_window(client_runtime_context: Any) -> int:
"""Operator/client declared transport window, or 0."""
if not isinstance(client_runtime_context, Mapping):
return 0
try:
value = int(client_runtime_context.get("model_context_window") or 0)
except (TypeError, ValueError):
return 0
return value if value > 0 else 0
async def resolve_effective_context(
endpoint_url: str,
model: str,
*,
headers: Optional[Mapping[str, Any]] = None,
client_runtime_context: Any = None,
deadline_seconds: float = PROBE_DEADLINE_SECONDS,
probe: bool = True,
clock=time.monotonic,
) -> ContextResolution:
"""Resolve the effective context window for one turn preparation."""
from src.model_context import _lookup_known
observations: list[ContextObservation] = []
errors: tuple[str, ...] = ()
provider_io = cached = False
if probe and endpoint_url and model:
result, cached = await _cached_probe(
endpoint_url, model, headers, deadline_seconds, clock,
)
observations.extend(result.observations)
errors = result.errors
provider_io = result.io and not cached
declared = declared_context_window(client_runtime_context)
if declared:
observations.append(ContextObservation(
ContextEvidence.OPERATOR_DECLARED, declared, "client_runtime_context",
))
known = _lookup_known(model or "")
if known:
observations.append(ContextObservation(ContextEvidence.KNOWN_TABLE, int(known), "known_table"))
resolution = combine_observations(observations)
resolution = replace(
resolution, provider_io=provider_io, cached=cached, probe_errors=errors,
endpoint_url=endpoint_url or "", model=model or "",
)
if resolution.mismatch:
logger.info(
"Context window sources disagree for %s: %s",
model, [conflict.to_dict() for conflict in resolution.conflicts],
)
return resolution
def context_metrics(resolution: Optional[ContextResolution], request_tokens: int) -> dict:
"""Metrics fields derived only from a stored resolution. Performs no I/O."""
resolution = resolution or UNRESOLVED_CONTEXT
length = resolution.budget_limit
percent = (
min(round((request_tokens / length) * 100, 1), 100.0)
if length and request_tokens else 0
)
return {
"context_length": length,
"context_percent": percent,
"context_resolution": resolution.to_dict(),
}