"""Reference solution — the LLM gateway and model abstraction layer. The gateway is the platform's choke point, in the good sense: one place to enforce, one place to observe, one place to change providers. It owns normalization, routing, budget-aware fallback, caching, rate limiting, quotas, token accounting and cost attribution — and it is the only component that knows which provider actually ran. Deterministic: the clock is injected, providers are scripted, and money is integer micro-USD so accumulated cost is exact. ``python solution.py`` runs a worked session. """ from __future__ import annotations import hashlib import math from dataclasses import dataclass, field, replace from enum import Enum from typing import Callable, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple # ====================================================================================== # 1. The normalized request/response — the abstraction layer proper # ====================================================================================== class TaskClass(str, Enum): """What the caller is doing. Routing keys off this, not off a model name.""" CHAT = "chat" EXTRACTION = "extraction" SUMMARIZATION = "summarization" CLASSIFICATION = "classification" REASONING = "reasoning" EMBEDDING = "embedding" @dataclass(frozen=True) class Message: role: str # "system" | "user" | "assistant" | "tool" content: str @dataclass(frozen=True) class NormalizedRequest: """One request shape for every provider. The fields that are NOT about the model — tenant, agent, classification, residency, latency budget, side_effecting — are why this type exists. A provider SDK's request object cannot carry them, and every one of them is load-bearing for routing, caching or safety. """ messages: Tuple[Message, ...] task_class: TaskClass tenant: str agent_id: str max_output_tokens: int = 512 temperature: float = 0.0 data_classification: str = "internal" residency: str = "any" # "any" | a region the data must stay in latency_budget_ms: int = 3000 side_effecting: bool = False # this call will trigger a tool that changes state cacheable: bool = True def __post_init__(self) -> None: if not self.messages: raise ValueError("a request needs at least one message") if self.max_output_tokens <= 0: raise ValueError("max_output_tokens must be > 0") if not 0.0 <= self.temperature <= 2.0: raise ValueError("temperature must be in [0, 2]") if self.latency_budget_ms <= 0: raise ValueError("latency_budget_ms must be > 0") def prompt_text(self) -> str: return "\n".join(f"{m.role}: {m.content}" for m in self.messages) def stable_prefix(self) -> str: """Everything before the last user turn — the cacheable part. Prefix caching rewards putting stable content (system prompt, tool schemas) first and volatile content last. This method encodes that assumption. """ return "\n".join(f"{m.role}: {m.content}" for m in self.messages[:-1]) class FinishReason(str, Enum): """Normalized finish reasons. Providers disagree wildly on the strings; the caller must not have to care, and `LENGTH` in particular must be detectable because it means the answer is truncated.""" STOP = "stop" LENGTH = "length" TOOL_CALL = "tool_call" CONTENT_FILTER = "content_filter" @dataclass(frozen=True) class Usage: input_tokens: int = 0 cached_input_tokens: int = 0 output_tokens: int = 0 def __post_init__(self) -> None: if min(self.input_tokens, self.cached_input_tokens, self.output_tokens) < 0: raise ValueError("token counts must be >= 0") if self.cached_input_tokens > self.input_tokens: raise ValueError("cached_input_tokens cannot exceed input_tokens") @property def total(self) -> int: return self.input_tokens + self.output_tokens @dataclass(frozen=True) class NormalizedResponse: text: str finish_reason: FinishReason usage: Usage deployment: str provider: str model: str latency_ms: int cost_micros: int = 0 cache: str = "miss" # "miss" | "exact" | "semantic" attempts: Tuple[str, ...] = () # deployments tried, in order # ====================================================================================== # 2. Normalized errors — the hard half of a model abstraction layer # ====================================================================================== class GatewayError(Exception): retryable = False fall_over = False # may we try the NEXT deployment? def __init__(self, message: str, *, provider: str = "") -> None: super().__init__(message) self.message = message self.provider = provider class RateLimited(GatewayError): """HTTP 429 from a provider. Retryable, and a reason to move on.""" retryable = True fall_over = True class ProviderTimeout(GatewayError): retryable = True fall_over = True class ProviderUnavailable(GatewayError): """5xx.""" retryable = True fall_over = True class ContentFiltered(GatewayError): """The provider's own safety system refused. NOT retryable and NOT a reason to fall over: trying another provider until one answers is 'shopping for a compliant model', which is exactly the behaviour a regulator would ask you about. """ retryable = False fall_over = False class InvalidRequest(GatewayError): """4xx that is our fault. Retrying sends the same bad request.""" retryable = False fall_over = False class QuotaExceeded(GatewayError): retryable = False fall_over = False class NoRouteAvailable(GatewayError): retryable = False fall_over = False class BudgetExhausted(GatewayError): """The latency budget ran out before a fallback could be attempted.""" retryable = False fall_over = False # ====================================================================================== # 3. Deployments and providers # ====================================================================================== class Capacity(str, Enum): PAYG = "payg" # shared pool, per-token billing PROVISIONED = "provisioned" # PTUs / provisioned throughput SELF_HOSTED = "self_hosted" # your GPUs @dataclass(frozen=True) class Deployment: """One addressable place a request can go. A 'model' is not a routing target — a *deployment* is. The same model in two regions with two capacity types has two different latencies, two different prices and two different residency answers. """ name: str provider: str # azure | bedrock | openai | anthropic | vertex | cohere model: str region: str capacity: Capacity input_micros_per_1k: int cached_input_micros_per_1k: int output_micros_per_1k: int expected_latency_ms: int max_classification: str = "restricted" weight: int = 1 def cost_micros(self, usage: Usage) -> int: fresh = usage.input_tokens - usage.cached_input_tokens total = (fresh * self.input_micros_per_1k + usage.cached_input_tokens * self.cached_input_micros_per_1k + usage.output_tokens * self.output_micros_per_1k) return total // 1000 #: A provider adapter: takes the normalized request, returns a normalized response. #: Raising a GatewayError subclass is how a provider reports failure — normalizing the #: error taxonomy is the part of an abstraction layer that actually earns its keep. ProviderAdapter = Callable[[NormalizedRequest, Deployment], NormalizedResponse] _CLASSIFICATION_ORDER = ("public", "internal", "confidential", "restricted") def classification_rank(name: str) -> int: try: return _CLASSIFICATION_ORDER.index(name) except ValueError: raise ValueError(f"unknown data classification: {name!r}") from None # ====================================================================================== # 4. Routing # ====================================================================================== @dataclass(frozen=True) class RoutingRule: """Match on what the caller *is*, not on what model it wants. A caller that names a model has hard-coded a vendor decision into an agent, and you will find every one of those references the day you need to migrate. """ name: str deployments: Tuple[str, ...] # ordered: primary first, then fallbacks task_classes: Tuple[TaskClass, ...] = () tenants: Tuple[str, ...] = () classifications: Tuple[str, ...] = () # empty = any; else an exact membership test priority: int = 100 # lower wins def __post_init__(self) -> None: for name in self.classifications: classification_rank(name) # reject a typo at construction, not at 3 a.m. def matches(self, request: NormalizedRequest) -> bool: if self.task_classes and request.task_class not in self.task_classes: return False if self.tenants and request.tenant not in self.tenants: return False if self.classifications and request.data_classification not in self.classifications: return False return True class Router: """Turns a request into an ordered list of candidate deployments.""" def __init__(self, deployments: Mapping[str, Deployment], rules: Sequence[RoutingRule]) -> None: self.deployments = dict(deployments) for rule in rules: unknown = set(rule.deployments) - set(self.deployments) if unknown: raise ValueError(f"rule {rule.name!r} names unknown deployments: {sorted(unknown)}") self.rules = sorted(rules, key=lambda r: (r.priority, r.name)) def candidates(self, request: NormalizedRequest) -> List[Deployment]: """The ordered fallback chain, after applying the constraints a rule cannot express: residency and per-deployment classification ceilings.""" for rule in self.rules: if not rule.matches(request): continue chain = [self.deployments[name] for name in rule.deployments] chain = [d for d in chain if self._admissible(d, request)] if chain: return chain return [] def _admissible(self, deployment: Deployment, request: NormalizedRequest) -> bool: if request.residency != "any" and deployment.region != request.residency: return False if classification_rank(deployment.max_classification) < classification_rank(request.data_classification): return False return True # ====================================================================================== # 5. Rate limiting and quotas # ====================================================================================== class TokenBucket: """Capacity ``C``, refill rate ``r`` per second. Never goes negative.""" def __init__(self, capacity: float, refill_per_second: float, *, now: Callable[[], float]) -> None: if capacity <= 0 or refill_per_second <= 0: raise ValueError("capacity and refill_per_second must be > 0") self.capacity = float(capacity) self.refill_per_second = float(refill_per_second) self.now = now self.tokens = float(capacity) self.last = now() def _refill(self) -> None: current = self.now() elapsed = max(0.0, current - self.last) self.tokens = min(self.capacity, self.tokens + elapsed * self.refill_per_second) self.last = current def try_consume(self, amount: float) -> bool: if amount < 0: raise ValueError("amount must be >= 0") self._refill() if self.tokens >= amount: self.tokens -= amount return True return False def retry_after_seconds(self, amount: float) -> float: self._refill() deficit = amount - self.tokens return max(0.0, deficit / self.refill_per_second) @dataclass class TenantLimits: """Both limits are needed. One request can be 100 000 tokens, so an RPM-only limit does not protect the provider — and a TPM-only limit does not protect you from a flood of tiny requests.""" requests_per_minute: int tokens_per_minute: int monthly_budget_micros: int class RateLimiter: def __init__(self, limits: Mapping[str, TenantLimits], *, now: Callable[[], float]) -> None: self.limits = dict(limits) self.now = now self._rpm: Dict[str, TokenBucket] = {} self._tpm: Dict[str, TokenBucket] = {} def _buckets(self, tenant: str) -> Tuple[TokenBucket, TokenBucket]: limits = self.limits.get(tenant) if limits is None: raise QuotaExceeded(f"tenant {tenant!r} has no configured limits") if tenant not in self._rpm: self._rpm[tenant] = TokenBucket(limits.requests_per_minute, limits.requests_per_minute / 60.0, now=self.now) self._tpm[tenant] = TokenBucket(limits.tokens_per_minute, limits.tokens_per_minute / 60.0, now=self.now) return self._rpm[tenant], self._tpm[tenant] def admit(self, tenant: str, estimated_tokens: int) -> None: """Raise RateLimited if either bucket refuses. Consumes only when BOTH admit — otherwise a rejected request still spends the request budget.""" rpm, tpm = self._buckets(tenant) if rpm.tokens < 1 or tpm.tokens < estimated_tokens: rpm._refill() tpm._refill() if rpm.tokens < 1: raise RateLimited( f"tenant {tenant!r} over request rate; retry after " f"{rpm.retry_after_seconds(1):.2f}s") if tpm.tokens < estimated_tokens: raise RateLimited( f"tenant {tenant!r} over token rate; retry after " f"{tpm.retry_after_seconds(estimated_tokens):.2f}s") rpm.try_consume(1) tpm.try_consume(estimated_tokens) class QuotaLedger: """Per-tenant monthly spend, with a hard stop. Unbounded consumption is an availability risk as much as a budget one: one tenant burning the provider's shared capacity degrades everybody. """ def __init__(self, limits: Mapping[str, TenantLimits]) -> None: self.limits = dict(limits) self._spent: Dict[str, int] = {} def check(self, tenant: str) -> None: limits = self.limits.get(tenant) if limits is None: raise QuotaExceeded(f"tenant {tenant!r} has no configured budget") if self._spent.get(tenant, 0) >= limits.monthly_budget_micros: raise QuotaExceeded( f"tenant {tenant!r} has exhausted its monthly budget " f"({limits.monthly_budget_micros} micro-USD)") def record(self, tenant: str, cost_micros: int) -> None: self._spent[tenant] = self._spent.get(tenant, 0) + cost_micros def spent(self, tenant: str) -> int: return self._spent.get(tenant, 0) def remaining(self, tenant: str) -> int: limits = self.limits[tenant] return max(0, limits.monthly_budget_micros - self.spent(tenant)) # ====================================================================================== # 6. Caching # ====================================================================================== def hash_embed(text: str, dimensions: int = 64) -> List[float]: """A deterministic hashing bag-of-words embedder. Real gateways call an embedding model. What matters here is that similarity is a function of the text and nothing else, so the cache's behaviour is testable. """ vector = [0.0] * dimensions for token in text.lower().split(): digest = hashlib.blake2b(token.encode("utf-8"), digest_size=8).digest() index = int.from_bytes(digest[:4], "big") % dimensions sign = 1.0 if digest[4] % 2 == 0 else -1.0 vector[index] += sign norm = math.sqrt(sum(v * v for v in vector)) if norm == 0.0: return vector return [v / norm for v in vector] def cosine(a: Sequence[float], b: Sequence[float]) -> float: return sum(x * y for x, y in zip(a, b)) def cache_key(request: NormalizedRequest, deployment_name: str) -> str: """Tenant FIRST. Every cache key in a multi-tenant platform starts with the tenant — a semantic cache that can cross a tenant boundary is a data breach with an excellent hit rate.""" material = "|".join([ request.tenant, deployment_name, request.task_class.value, f"{request.temperature:.4f}", str(request.max_output_tokens), request.prompt_text(), ]) return hashlib.blake2b(material.encode("utf-8"), digest_size=16).hexdigest() class ExactCache: def __init__(self, *, ttl_seconds: float, now: Callable[[], float], capacity: int = 1024) -> None: self.ttl = ttl_seconds self.now = now self.capacity = capacity self._entries: Dict[str, Tuple[float, NormalizedResponse]] = {} self.hits = 0 self.misses = 0 def get(self, key: str) -> Optional[NormalizedResponse]: entry = self._entries.get(key) if entry is None: self.misses += 1 return None stored_at, response = entry if self.now() - stored_at > self.ttl: del self._entries[key] self.misses += 1 return None self.hits += 1 return response def put(self, key: str, response: NormalizedResponse) -> None: if len(self._entries) >= self.capacity: oldest = min(self._entries, key=lambda k: self._entries[k][0]) del self._entries[oldest] self._entries[key] = (self.now(), response) @dataclass class SemanticEntry: tenant: str vector: Tuple[float, ...] response: NormalizedResponse stored_at: float class SemanticCache: """Similarity-keyed cache. Three non-negotiables, all enforced here: 1. **tenant-scoped** — entries are partitioned, never merely filtered; 2. **a similarity floor** — tuned against negative examples, not guessed; 3. **never for entitlement-dependent answers** — the caller marks a request ``cacheable=False`` and the gateway obeys. """ def __init__(self, *, threshold: float, ttl_seconds: float, now: Callable[[], float], capacity_per_tenant: int = 256) -> None: if not 0.0 < threshold <= 1.0: raise ValueError("threshold must be in (0, 1]") self.threshold = threshold self.ttl = ttl_seconds self.now = now self.capacity_per_tenant = capacity_per_tenant self._by_tenant: Dict[str, List[SemanticEntry]] = {} self.hits = 0 self.misses = 0 def get(self, request: NormalizedRequest) -> Optional[NormalizedResponse]: entries = self._by_tenant.get(request.tenant, []) live = [e for e in entries if self.now() - e.stored_at <= self.ttl] self._by_tenant[request.tenant] = live if not live: self.misses += 1 return None query = hash_embed(request.prompt_text()) best: Optional[Tuple[float, SemanticEntry]] = None for entry in live: score = cosine(query, entry.vector) if best is None or score > best[0]: best = (score, entry) if best is None or best[0] < self.threshold: self.misses += 1 return None self.hits += 1 return best[1].response def put(self, request: NormalizedRequest, response: NormalizedResponse) -> None: entries = self._by_tenant.setdefault(request.tenant, []) if len(entries) >= self.capacity_per_tenant: entries.pop(0) entries.append(SemanticEntry(request.tenant, tuple(hash_embed(request.prompt_text())), response, self.now())) # ====================================================================================== # 7. Accounting # ====================================================================================== @dataclass(frozen=True) class AccountingRecord: tenant: str agent_id: str deployment: str provider: str model: str task_class: TaskClass usage: Usage cost_micros: int latency_ms: int cache: str attempts: Tuple[str, ...] outcome: str # "ok" | error class name class Accounting: """Token accounting and cost attribution. Records EVERY outcome, including failures — a cost model that only counts successes under-reports exactly during an incident, when the provider produced tokens before the timeout. """ def __init__(self) -> None: self.records: List[AccountingRecord] = [] def record(self, record: AccountingRecord) -> None: self.records.append(record) def cost_by(self, key: str) -> Dict[str, int]: if key not in ("tenant", "agent_id", "deployment", "provider", "model"): raise ValueError(f"cannot attribute by {key!r}") out: Dict[str, int] = {} for record in self.records: value = getattr(record, key) value = value.value if isinstance(value, Enum) else value out[value] = out.get(value, 0) + record.cost_micros return dict(sorted(out.items())) def tokens_by_tenant(self) -> Dict[str, int]: out: Dict[str, int] = {} for record in self.records: out[record.tenant] = out.get(record.tenant, 0) + record.usage.total return dict(sorted(out.items())) def cache_hit_rate(self) -> float: if not self.records: return 0.0 hits = sum(1 for r in self.records if r.cache != "miss") return hits / len(self.records) def failover_rate(self) -> float: """The metric that tells you a provider is degrading before the error rate does.""" if not self.records: return 0.0 failed_over = sum(1 for r in self.records if len(r.attempts) > 1) return failed_over / len(self.records) # ====================================================================================== # 8. The gateway # ====================================================================================== def estimate_tokens(text: str) -> int: return (len(text) + 3) // 4 class Gateway: def __init__( self, *, router: Router, adapters: Mapping[str, ProviderAdapter], rate_limiter: RateLimiter, quotas: QuotaLedger, accounting: Accounting, now: Callable[[], float], exact_cache: Optional[ExactCache] = None, semantic_cache: Optional[SemanticCache] = None, ) -> None: self.router = router self.adapters = dict(adapters) self.rate_limiter = rate_limiter self.quotas = quotas self.accounting = accounting self.now = now self.exact_cache = exact_cache self.semantic_cache = semantic_cache def complete(self, request: NormalizedRequest) -> NormalizedResponse: """The full path, in the order that matters. Rate limit and quota come FIRST — they are the cheapest checks and they protect capacity. The cache comes before routing, because a hit needs no route. Routing, then budget-aware fallback. Accounting happens on every outcome. """ started = self.now() estimated = estimate_tokens(request.prompt_text()) + request.max_output_tokens try: self.quotas.check(request.tenant) self.rate_limiter.admit(request.tenant, estimated) except GatewayError as exc: self._record_failure(request, exc, started, ()) raise candidates = self.router.candidates(request) if not candidates: exc = NoRouteAvailable( f"no deployment satisfies tenant={request.tenant!r} " f"class={request.data_classification!r} residency={request.residency!r}") self._record_failure(request, exc, started, ()) raise exc cached = self._cache_lookup(request, candidates[0]) if cached is not None: self.accounting.record(AccountingRecord( tenant=request.tenant, agent_id=request.agent_id, deployment=cached.deployment, provider=cached.provider, model=cached.model, task_class=request.task_class, usage=Usage(), cost_micros=0, latency_ms=self._elapsed_ms(started), cache=cached.cache, attempts=(), outcome="ok")) return cached response = self._execute_with_fallback(request, candidates, started) self._cache_store(request, candidates[0], response) return response # -- internals ---------------------------------------------------------------- def _elapsed_ms(self, started: float) -> int: return int(round((self.now() - started) * 1000)) def _cache_lookup(self, request: NormalizedRequest, primary: Deployment) -> Optional[NormalizedResponse]: if not request.cacheable: return None # A hit reports cost_micros=0: `cost` means "what THIS call cost", and a served # cache entry cost nothing. Reporting the original cost double-counts spend. if self.exact_cache is not None: hit = self.exact_cache.get(cache_key(request, primary.name)) if hit is not None: return replace(hit, cache="exact", cost_micros=0, attempts=()) if self.semantic_cache is not None: hit = self.semantic_cache.get(request) if hit is not None: return replace(hit, cache="semantic", cost_micros=0, attempts=()) return None def _cache_store(self, request: NormalizedRequest, primary: Deployment, response: NormalizedResponse) -> None: if not request.cacheable: return # Never cache a truncated or filtered answer: it is not the answer. if response.finish_reason is not FinishReason.STOP: return if self.exact_cache is not None: self.exact_cache.put(cache_key(request, primary.name), response) if self.semantic_cache is not None: self.semantic_cache.put(request, response) def _execute_with_fallback(self, request: NormalizedRequest, candidates: Sequence[Deployment], started: float) -> NormalizedResponse: attempts: List[str] = [] last: Optional[GatewayError] = None for index, deployment in enumerate(candidates): if index > 0: # Two independent reasons to refuse a fallback. if request.side_effecting: exc = last or ProviderUnavailable("primary failed") self._record_failure(request, exc, started, tuple(attempts)) raise exc remaining = request.latency_budget_ms - self._elapsed_ms(started) if remaining < deployment.expected_latency_ms: exc = BudgetExhausted( f"{remaining}ms left; {deployment.name} needs " f"{deployment.expected_latency_ms}ms") self._record_failure(request, exc, started, tuple(attempts)) raise exc attempts.append(deployment.name) adapter = self.adapters.get(deployment.provider) if adapter is None: last = InvalidRequest(f"no adapter for provider {deployment.provider!r}") continue try: response = adapter(request, deployment) except GatewayError as exc: last = exc if not exc.fall_over: self._record_failure(request, exc, started, tuple(attempts)) raise continue cost = deployment.cost_micros(response.usage) final = replace(response, cost_micros=cost, attempts=tuple(attempts), latency_ms=self._elapsed_ms(started)) self.quotas.record(request.tenant, cost) self.accounting.record(AccountingRecord( tenant=request.tenant, agent_id=request.agent_id, deployment=deployment.name, provider=deployment.provider, model=deployment.model, task_class=request.task_class, usage=response.usage, cost_micros=cost, latency_ms=final.latency_ms, cache="miss", attempts=tuple(attempts), outcome="ok")) return final exc = last or NoRouteAvailable("every candidate failed") self._record_failure(request, exc, started, tuple(attempts)) raise exc def _record_failure(self, request: NormalizedRequest, exc: GatewayError, started: float, attempts: Tuple[str, ...]) -> None: self.accounting.record(AccountingRecord( tenant=request.tenant, agent_id=request.agent_id, deployment=attempts[-1] if attempts else "-", provider="-", model="-", task_class=request.task_class, usage=Usage(), cost_micros=0, latency_ms=self._elapsed_ms(started), cache="miss", attempts=attempts, outcome=type(exc).__name__)) # ====================================================================================== # 9. Provider adapters — the normalization work, made concrete # ====================================================================================== def make_scripted_adapter( provider: str, *, reply: Callable[[NormalizedRequest], str], failures: Sequence[Optional[GatewayError]] = (), input_tokens: Optional[Callable[[NormalizedRequest], int]] = None, output_tokens: int = 64, cached_fraction: float = 0.0, finish_reason: FinishReason = FinishReason.STOP, ) -> ProviderAdapter: """Build a deterministic provider adapter. ``failures`` is consumed one entry per call: a GatewayError is raised, None succeeds. That is how a test scripts "the primary 429s twice, then works". """ pending = list(failures) def adapter(request: NormalizedRequest, deployment: Deployment) -> NormalizedResponse: if pending: failure = pending.pop(0) if failure is not None: raise failure raw_input = (input_tokens or (lambda r: estimate_tokens(r.prompt_text())))(request) cached = int(raw_input * cached_fraction) return NormalizedResponse( text=reply(request), finish_reason=finish_reason, usage=Usage(input_tokens=raw_input, cached_input_tokens=cached, output_tokens=output_tokens), deployment=deployment.name, provider=provider, model=deployment.model, latency_ms=deployment.expected_latency_ms, ) return adapter # ====================================================================================== # Worked example # ====================================================================================== def _clock(step: float = 0.05) -> Callable[[], float]: state = {"t": -step} def now() -> float: state["t"] += step return round(state["t"], 6) return now def _build(now): deployments = { "azure-gpt-uae-ptu": Deployment( "azure-gpt-uae-ptu", "azure", "gpt-frontier", "uae-north", Capacity.PROVISIONED, input_micros_per_1k=2500, cached_input_micros_per_1k=250, output_micros_per_1k=10000, expected_latency_ms=700), "azure-gpt-uae-payg": Deployment( "azure-gpt-uae-payg", "azure", "gpt-frontier", "uae-north", Capacity.PAYG, input_micros_per_1k=3000, cached_input_micros_per_1k=300, output_micros_per_1k=12000, expected_latency_ms=900), "anthropic-eu": Deployment( "anthropic-eu", "anthropic", "claude-frontier", "eu-west", Capacity.PAYG, input_micros_per_1k=3000, cached_input_micros_per_1k=300, output_micros_per_1k=15000, expected_latency_ms=800, max_classification="confidential"), "self-hosted-uae": Deployment( "self-hosted-uae", "vllm", "llama-open", "uae-north", Capacity.SELF_HOSTED, input_micros_per_1k=400, cached_input_micros_per_1k=400, output_micros_per_1k=800, expected_latency_ms=1400), } rules = [ RoutingRule("restricted-must-stay-onshore", deployments=("azure-gpt-uae-ptu", "azure-gpt-uae-payg", "self-hosted-uae"), classifications=("restricted",), priority=10), RoutingRule("cheap-classification", deployments=("self-hosted-uae", "azure-gpt-uae-payg"), task_classes=(TaskClass.CLASSIFICATION,), priority=20), RoutingRule("default", deployments=("azure-gpt-uae-ptu", "anthropic-eu", "azure-gpt-uae-payg"), priority=100), ] limits = { "wholesale": TenantLimits(requests_per_minute=60, tokens_per_minute=120_000, monthly_budget_micros=50_000_000), "retail": TenantLimits(requests_per_minute=6, tokens_per_minute=6_000, monthly_budget_micros=1_000_000), } accounting = Accounting() gateway = Gateway( router=Router(deployments, rules), adapters={ "azure": make_scripted_adapter("azure", reply=lambda r: "azure says: held pending review", cached_fraction=0.4), "anthropic": make_scripted_adapter("anthropic", reply=lambda r: "anthropic says: held"), "vllm": make_scripted_adapter("vllm", reply=lambda r: "llama says: held"), }, rate_limiter=RateLimiter(limits, now=now), quotas=QuotaLedger(limits), accounting=accounting, now=now, exact_cache=ExactCache(ttl_seconds=300, now=now), semantic_cache=SemanticCache(threshold=0.92, ttl_seconds=300, now=now), ) return gateway, deployments, accounting def _request(**kwargs) -> NormalizedRequest: kwargs.setdefault("messages", (Message("system", "You are a payments investigator."), Message("user", "Why is payment PMT-771 held?"))) kwargs.setdefault("task_class", TaskClass.REASONING) kwargs.setdefault("tenant", "wholesale") kwargs.setdefault("agent_id", "payments-investigator") return NormalizedRequest(**kwargs) def main() -> None: # pragma: no cover - narrative output now = _clock() gateway, deployments, accounting = _build(now) print("=" * 78) print("1. ONE INTERFACE, MANY PROVIDERS") print("=" * 78) response = gateway.complete(_request()) print(f" routed to : {response.deployment} ({response.provider}/{response.model})") print(f" finish : {response.finish_reason.value}") print(f" usage : in={response.usage.input_tokens} " f"cached={response.usage.cached_input_tokens} out={response.usage.output_tokens}") print(f" cost : {response.cost_micros} micro-USD") print(f" attempts : {list(response.attempts)}") print() print("=" * 78) print("2. ROUTING IS A POLICY, NOT A MODEL NAME") print("=" * 78) for label, req in [ ("default reasoning", _request()), ("classification (cheap)", _request(task_class=TaskClass.CLASSIFICATION)), ("restricted data", _request(data_classification="restricted")), ("residency: uae-north", _request(residency="uae-north")), ]: chain = gateway.router.candidates(req) print(f" {label:<24} -> {[d.name for d in chain]}") blocked = _request(data_classification="restricted", residency="eu-west") print(f" {'restricted + eu-west':<24} -> {[d.name for d in gateway.router.candidates(blocked)]}" f" (nothing satisfies both)") print() print("=" * 78) print("3. BUDGET-AWARE FALLBACK") print("=" * 78) now2 = _clock() gw2, _, acc2 = _build(now2) gw2.adapters["azure"] = make_scripted_adapter( "azure", reply=lambda r: "recovered", failures=[RateLimited("429 from azure", provider="azure")]) ok = gw2.complete(_request()) print(f" primary 429 -> fell over to {ok.deployment}, attempts={list(ok.attempts)}") now3 = _clock(step=0.6) # 600 ms per clock read: the budget burns fast gw3, _, _ = _build(now3) gw3.adapters["azure"] = make_scripted_adapter( "azure", reply=lambda r: "recovered", failures=[ProviderTimeout("timeout", provider="azure")]) try: gw3.complete(_request(latency_budget_ms=1000)) except BudgetExhausted as exc: print(f" no headroom -> {type(exc).__name__}: {exc.message}") now4 = _clock() gw4, _, _ = _build(now4) gw4.adapters["azure"] = make_scripted_adapter( "azure", reply=lambda r: "recovered", failures=[ProviderTimeout("timeout", provider="azure")]) try: gw4.complete(_request(side_effecting=True)) except ProviderTimeout as exc: print(f" side-effecting -> refused to fall over: {exc.message}") now5 = _clock() gw5, _, _ = _build(now5) gw5.adapters["azure"] = make_scripted_adapter( "azure", reply=lambda r: "x", failures=[ContentFiltered("blocked by provider safety", provider="azure")]) try: gw5.complete(_request()) except ContentFiltered as exc: print(f" content filter -> no failover (never shop for a compliant model)") print() print("=" * 78) print("4. CACHING") print("=" * 78) now6 = _clock() gw6, _, acc6 = _build(now6) first = gw6.complete(_request()) second = gw6.complete(_request()) print(f" identical request -> cache={second.cache}, cost={second.cost_micros}") near = _request(messages=(Message("system", "You are a payments investigator."), Message("user", "Why is payment PMT-771 held? "))) third = gw6.complete(near) print(f" near-duplicate -> cache={third.cache}") other = _request(tenant="retail") fourth = gw6.complete(other) print(f" same text, tenant 'retail' -> cache={fourth.cache} " f"(tenant is the first component of every key)") print(f" exact hits/misses : {gw6.exact_cache.hits}/{gw6.exact_cache.misses}") print(f" semantic hits/miss : {gw6.semantic_cache.hits}/{gw6.semantic_cache.misses}") uncacheable = gw6.complete(_request(cacheable=False)) print(f" cacheable=False -> cache={uncacheable.cache} (entitlement-dependent answers)") print() print("=" * 78) print("5. RATE LIMITS AND QUOTAS") print("=" * 78) now7 = _clock(step=0.0) # frozen clock: no refill gw7, _, _ = _build(now7) admitted = 0 try: for _ in range(20): gw7.complete(_request(tenant="retail", cacheable=False, messages=(Message("user", f"q{admitted}"),))) admitted += 1 except RateLimited as exc: print(f" retail admitted {admitted} requests, then: {exc.message}") now8 = _clock() gw8, _, _ = _build(now8) gw8.quotas.record("retail", 1_000_000) try: gw8.complete(_request(tenant="retail")) except QuotaExceeded as exc: print(f" budget exhausted -> {exc.message}") print() print("=" * 78) print("6. ACCOUNTING AND ATTRIBUTION") print("=" * 78) now9 = _clock() gw9, _, acc9 = _build(now9) for tenant, agent in [("wholesale", "payments-investigator"), ("wholesale", "kyc-refresh"), ("retail", "collections")]: for i in range(3): gw9.complete(_request(tenant=tenant, agent_id=agent, cacheable=False, messages=(Message("user", f"{agent} question {i}"),))) print(f" cost by tenant : {acc9.cost_by('tenant')}") print(f" cost by agent : {acc9.cost_by('agent_id')}") print(f" cost by deployment : {acc9.cost_by('deployment')}") print(f" tokens by tenant : {acc9.tokens_by_tenant()}") print(f" cache hit rate : {acc9.cache_hit_rate():.0%}") print(f" failover rate : {acc9.failover_rate():.0%}") print() print("=" * 78) print("7. FAILURES ARE ACCOUNTED TOO") print("=" * 78) now10 = _clock() gw10, _, acc10 = _build(now10) gw10.adapters["azure"] = make_scripted_adapter( "azure", reply=lambda r: "x", failures=[ContentFiltered("blocked", provider="azure")]) try: gw10.complete(_request()) except ContentFiltered: pass for record in acc10.records: print(f" outcome={record.outcome:<16} attempts={list(record.attempts)} " f"cost={record.cost_micros} latency={record.latency_ms}ms") print(" -> a cost model that counts only successes under-reports during incidents.") if __name__ == "__main__": # pragma: no cover main()