mirror of
https://github.com/lukaszraczylo/traefik-llmgateway.git
synced 2026-10-12 04:54:45 +00:00
lukaszraczylo
e3996d88bf
The generated pricing_data_gen.go header used to stamp today's date on every `make pricing-sync` run, so a re-run against genuinely unchanged upstream data still touched the file and produced a spurious daily diff with nothing real to review. The header now records a short SHA-256 digest of the FETCHED bytes instead — identical upstream data always reproduces a byte-identical generated file. Folded review minor.
267 lines
12 KiB
Go
267 lines
12 KiB
Go
package main
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import (
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"go/parser"
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"go/token"
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"reflect"
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"strings"
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"testing"
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)
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// fixtureJSON is a small, hand-built stand-in for LiteLLM's real
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// model_prices_and_context_window.json, covering every branch of the
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// pruning rule documented on this package (main.go's own doc comment):
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// the sample_spec schema-example entry, a disallowed provider, a
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// disallowed mode, null cost fields, a bare-vs-provider-prefixed
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// collision with identical values, a three-way collision with
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// DIFFERING values across providers (deepseek-v4-flash, mirroring the
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// real dashscope/deepseek disagreement this tool was built against), an
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// xai entry with float-valued (not int) max_input_tokens/max_tokens, an
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// embedding-mode entry with a genuine zero output cost, and an entry
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// with no max_input_tokens/max_tokens at all.
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const fixtureJSON = `{
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"sample_spec": {
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"litellm_provider": "one of https://docs.litellm.ai/docs/providers",
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"input_cost_per_token": 0.0,
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"output_cost_per_token": 0.0,
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"max_input_tokens": "max input tokens, if the provider specifies it."
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},
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"gpt-5": {
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"litellm_provider": "openai", "mode": "chat",
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"input_cost_per_token": 1.25e-06, "output_cost_per_token": 1.0e-05,
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"max_input_tokens": 400000, "max_tokens": 128000
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},
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"bedrock/some-model": {
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"litellm_provider": "bedrock", "mode": "chat",
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"input_cost_per_token": 1e-06, "output_cost_per_token": 1e-06,
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"max_input_tokens": 100000
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},
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"openai/dalle": {
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"litellm_provider": "openai", "mode": "image_generation",
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"output_cost_per_image": 0.04
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},
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"openai/null-cost": {
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"litellm_provider": "openai", "mode": "chat",
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"input_cost_per_token": null, "output_cost_per_token": null,
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"max_input_tokens": 1000
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},
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"deepseek-chat": {
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"litellm_provider": "deepseek", "mode": "chat",
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"input_cost_per_token": 2.8e-07, "output_cost_per_token": 4.2e-07,
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"max_input_tokens": 131072, "max_tokens": 8192
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},
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"deepseek/deepseek-chat": {
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"litellm_provider": "deepseek", "mode": "chat",
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"input_cost_per_token": 2.8e-07, "output_cost_per_token": 4.2e-07,
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"max_input_tokens": 131072, "max_tokens": 8192
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},
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"dashscope/deepseek-v4-flash": {
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"litellm_provider": "dashscope", "mode": "chat",
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"input_cost_per_token": 2e-07, "output_cost_per_token": 4e-07,
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"max_input_tokens": 1000000
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},
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"deepseek-v4-flash": {
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"litellm_provider": "deepseek", "mode": "chat",
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"input_cost_per_token": 4.4e-07, "output_cost_per_token": 1.32e-06,
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"max_input_tokens": 131072
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},
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"deepseek/deepseek-v4-flash": {
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"litellm_provider": "deepseek", "mode": "chat",
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"input_cost_per_token": 4.4e-07, "output_cost_per_token": 1.32e-06,
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"max_input_tokens": 131072
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},
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"xai/grok-4-fast-reasoning": {
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"litellm_provider": "xai", "mode": "chat",
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"input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07,
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"max_input_tokens": 2000000.0, "max_tokens": 2000000.0
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},
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"openai/whisper-notmode": {
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"litellm_provider": "openai", "mode": "audio_transcription",
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"input_cost_per_token": 1e-06, "output_cost_per_token": 1e-06,
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"max_input_tokens": 16000
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},
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"text-embedding-3-large": {
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"litellm_provider": "openai", "mode": "embedding",
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"input_cost_per_token": 1.3e-07, "output_cost_per_token": 0.0,
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"max_input_tokens": 8191, "max_tokens": 8191
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},
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"openai/no-max-tokens-at-all": {
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"litellm_provider": "openai", "mode": "chat",
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"input_cost_per_token": 1e-06, "output_cost_per_token": 2e-06
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},
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"minimax/MiniMax-M2.1-lightning": {
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"litellm_provider": "minimax", "mode": "chat",
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"input_cost_per_token": 3e-07, "output_cost_per_token": 2.4e-06,
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"max_input_tokens": 1000000
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},
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"claude-haiku-4-5": {
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"litellm_provider": "anthropic", "mode": "chat",
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"input_cost_per_token": 1e-06, "output_cost_per_token": 5e-06,
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"max_input_tokens": 200000, "max_tokens": 64000
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},
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"moonshot/kimi-k2.5": {
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"litellm_provider": "moonshot", "mode": "chat",
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"input_cost_per_token": 6e-07, "output_cost_per_token": 2.5e-06,
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"max_input_tokens": 262144
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}
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}`
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// fixtureUpstreamKeyCount is fixtureJSON's total top-level key count
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// (including every pruned-out entry and sample_spec) — parseAndPrune's
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// second return value.
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const fixtureUpstreamKeyCount = 17
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// TestParseAndPrune_Golden is the generator's golden test (task
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// requirement): a small fixture JSON in, an exact expected pruned table
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// out, covering every pruning-rule branch fixtureJSON's own doc comment
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// lists.
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func TestParseAndPrune_Golden(t *testing.T) {
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got, totalUpstream, err := parseAndPrune([]byte(fixtureJSON))
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if err != nil {
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t.Fatalf("parseAndPrune: %v", err)
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}
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if totalUpstream != fixtureUpstreamKeyCount {
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t.Errorf("totalUpstream = %d, want %d", totalUpstream, fixtureUpstreamKeyCount)
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}
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want := map[string]builtinEntry{
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"gpt-5": {ContextTokens: 400000, InputCostPerMTokMicroUSD: 1_250_000, OutputCostPerMTokMicroUSD: 10_000_000},
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// deepseek-chat: bare key wins over the identical-valued
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// "deepseek/deepseek-chat" prefixed key (rule: bare beats
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// prefixed regardless of value equality).
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"deepseek-chat": {ContextTokens: 131072, InputCostPerMTokMicroUSD: 280_000, OutputCostPerMTokMicroUSD: 420_000},
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// deepseek-v4-flash: three colliding keys, DIFFERING values
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// between "dashscope/..." and the deepseek-provider ones — the
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// bare "deepseek-v4-flash" key wins (rule 1: bare beats
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// prefixed), not the higher- or lower-priced alternative.
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"deepseek-v4-flash": {ContextTokens: 131072, InputCostPerMTokMicroUSD: 440_000, OutputCostPerMTokMicroUSD: 1_320_000},
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"grok-4-fast-reasoning": {ContextTokens: 2_000_000, InputCostPerMTokMicroUSD: 200_000, OutputCostPerMTokMicroUSD: 500_000},
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// text-embedding-3-large: a genuine, known zero output cost
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// (embeddings bill input tokens only) must survive, not be
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// treated as "missing".
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"text-embedding-3-large": {ContextTokens: 8191, InputCostPerMTokMicroUSD: 130_000, OutputCostPerMTokMicroUSD: 0},
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// no-max-tokens-at-all: neither max_input_tokens nor max_tokens
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// present at all -> ContextTokens 0 (unknown), cost still kept.
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"no-max-tokens-at-all": {ContextTokens: 0, InputCostPerMTokMicroUSD: 1_000_000, OutputCostPerMTokMicroUSD: 2_000_000},
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// MiniMax-M2.1-lightning: LiteLLM's own entry, kept as-is.
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"MiniMax-M2.1-lightning": {ContextTokens: 1_000_000, InputCostPerMTokMicroUSD: 300_000, OutputCostPerMTokMicroUSD: 2_400_000},
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// MiniMax-M2.1-highspeed: the naming-bridge duplicate (generator
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// addendum) — identical values, no LiteLLM entry of its own in
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// this fixture.
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"MiniMax-M2.1-highspeed": {ContextTokens: 1_000_000, InputCostPerMTokMicroUSD: 300_000, OutputCostPerMTokMicroUSD: 2_400_000},
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// Coverage-audit sanity (addendum, 2026-08): openai-family and
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// anthropic bare ids resolve as LiteLLM's own canonical bare
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// keys, with no bridging or prefix-stripping needed — "gpt-5"
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// above already covers the openai family; this covers anthropic.
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"claude-haiku-4-5": {ContextTokens: 200_000, InputCostPerMTokMicroUSD: 1_000_000, OutputCostPerMTokMicroUSD: 5_000_000},
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// moonshot: Kimi models (coverage-audit addendum) — a
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// provider-prefixed key, bareModelID strips "moonshot/" the same
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// way it strips any other allowlisted provider's own prefix.
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"kimi-k2.5": {ContextTokens: 262144, InputCostPerMTokMicroUSD: 600_000, OutputCostPerMTokMicroUSD: 2_500_000},
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}
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if !reflect.DeepEqual(got, want) {
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t.Errorf("parseAndPrune(fixtureJSON) =\n%#v\nwant\n%#v", got, want)
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}
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}
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// TestRenderGoSource_ValidSortedGo asserts renderGoSource produces
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// syntactically valid, gofmt-canonical Go source (parseable by go/
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// parser) whose entries appear in sorted key order, and that its header
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// documents the pruning provenance (source URL, content digest, counts).
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func TestRenderGoSource_ValidSortedGo(t *testing.T) {
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table := map[string]builtinEntry{
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"zzz-model": {ContextTokens: 1, InputCostPerMTokMicroUSD: 1, OutputCostPerMTokMicroUSD: 1},
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"aaa-model": {ContextTokens: 2, InputCostPerMTokMicroUSD: 2, OutputCostPerMTokMicroUSD: 2},
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}
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src, err := renderGoSource(table, sourceMeta{sourceDigest: "deadbeefcafe", totalUpstream: 3111, kept: 2})
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if err != nil {
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t.Fatalf("renderGoSource: %v", err)
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}
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if _, err := parser.ParseFile(token.NewFileSet(), "pricing_data_gen.go", src, parser.AllErrors); err != nil {
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t.Fatalf("generated source does not parse as valid Go: %v\n%s", err, src)
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}
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if !strings.Contains(src, "package traefikllmgateway") {
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t.Error("generated source missing package declaration")
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}
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if !strings.Contains(src, litellmSourceURL) {
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t.Error("generated source missing source URL provenance comment")
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}
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if !strings.Contains(src, "deadbeefcafe") || !strings.Contains(src, "3111") {
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t.Error("generated source missing source-digest / upstream count provenance comment")
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}
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if got, want := strings.Index(src, `"aaa-model"`), strings.Index(src, `"zzz-model"`); got == -1 || want == -1 || got > want {
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t.Errorf(`entries not sorted: index("aaa-model")=%d, index("zzz-model")=%d, want aaa before zzz`, got, want)
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}
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}
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// TestChooseWinner_Deterministic asserts chooseWinner's tiebreak order
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// (bare > provider priority > lexicographic full key) directly, beyond
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// what the golden test above exercises indirectly.
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func TestChooseWinner_Deterministic(t *testing.T) {
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cands := []candidate{
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{fullKey: "dashscope/x", provider: "dashscope", bare: false, entry: builtinEntry{ContextTokens: 1}},
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{fullKey: "deepseek/x", provider: "deepseek", bare: false, entry: builtinEntry{ContextTokens: 2}},
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{fullKey: "x", provider: "deepseek", bare: true, entry: builtinEntry{ContextTokens: 3}},
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}
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if got := chooseWinner(cands); got.entry.ContextTokens != 3 {
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t.Errorf("chooseWinner picked ContextTokens=%d, want 3 (the bare candidate)", got.entry.ContextTokens)
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}
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// With no bare candidate, provider priority decides: "deepseek"
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// precedes "dashscope" in providerPriority.
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noBare := []candidate{
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{fullKey: "dashscope/x", provider: "dashscope", bare: false, entry: builtinEntry{ContextTokens: 1}},
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{fullKey: "deepseek/x", provider: "deepseek", bare: false, entry: builtinEntry{ContextTokens: 2}},
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}
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if got := chooseWinner(noBare); got.entry.ContextTokens != 2 {
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t.Errorf("chooseWinner picked ContextTokens=%d, want 2 (deepseek outranks dashscope)", got.entry.ContextTokens)
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}
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}
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// TestApplyNamingBridges_DoesNotOverwriteExistingEntry asserts a bridged
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// id that LiteLLM already prices directly (its own independent winning
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// candidate) is left untouched by the bridge — an entry LiteLLM prices
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// directly always wins over a bridged duplicate (generator addendum).
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func TestApplyNamingBridges_DoesNotOverwriteExistingEntry(t *testing.T) {
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winners := map[string]candidate{
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"MiniMax-M2.1-lightning": {provider: "minimax", entry: builtinEntry{ContextTokens: 1_000_000, InputCostPerMTokMicroUSD: 300_000, OutputCostPerMTokMicroUSD: 2_400_000}},
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// A directly-priced, independent "-highspeed" entry with a
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// DIFFERENT value than the lightning entry would bridge to.
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"MiniMax-M2.1-highspeed": {provider: "minimax", entry: builtinEntry{ContextTokens: 500_000, InputCostPerMTokMicroUSD: 999, OutputCostPerMTokMicroUSD: 999}},
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}
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table := make(map[string]builtinEntry, len(winners))
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for bare, w := range winners {
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table[bare] = w.entry
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}
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applyNamingBridges(table, winners)
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want := builtinEntry{ContextTokens: 500_000, InputCostPerMTokMicroUSD: 999, OutputCostPerMTokMicroUSD: 999}
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if got := table["MiniMax-M2.1-highspeed"]; got != want {
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t.Errorf(`table["MiniMax-M2.1-highspeed"] = %+v, want %+v (its own direct LiteLLM entry, not the bridged duplicate)`, got, want)
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}
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}
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// TestContentDigest covers the review-fix replacement for a wall-clock
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// snapshot date: identical bytes must always produce an identical
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// digest (the whole point — a `make pricing-sync` re-run against
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// unchanged upstream data must reproduce a byte-identical file, with no
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// spurious diff), different bytes must produce a different digest, and
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// the digest is always exactly contentDigestLen hex characters.
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func TestContentDigest(t *testing.T) {
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a := contentDigest([]byte(`{"gpt-5":{}}`))
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b := contentDigest([]byte(`{"gpt-5":{}}`))
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c := contentDigest([]byte(`{"gpt-5":{"changed":true}}`))
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if a != b {
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t.Errorf("contentDigest is not deterministic: %q != %q for identical input", a, b)
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}
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if a == c {
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t.Errorf("contentDigest(%q) == contentDigest(%q) = %q, want different digests for different input", `{"gpt-5":{}}`, `{"gpt-5":{"changed":true}}`, a)
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}
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if len(a) != contentDigestLen {
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t.Errorf("len(contentDigest(...)) = %d, want %d", len(a), contentDigestLen)
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}
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}
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