DESKTOP-I1T6TF3\Q
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Add a `tag` option to chat() and have it print one `[cache] <tag> hit=X miss=Y rate=Z%` line per call. Three Usage-shape variants are probed in order so the same logger works across providers: - DeepSeek (v3+): usage.prompt_cache_hit_tokens / *_miss_tokens - OpenAI / o-series: usage.prompt_tokens_details.cached_tokens - Anthropic: usage.cache_read_input_tokens / *_creation_* When none of them are present (MiMo / local Ollama / others) we still print prompt + completion totals so the cost baseline is visible. Tag every callsite so the log is greppable: architect / writer / character-designer / cinematographer / insert-beat This is the prerequisite for the prefix-cache reordering work that follows — without per-agent visibility there's no way to tell if a prompt rearrangement actually moved the needle. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
87 lines
3.2 KiB
TypeScript
87 lines
3.2 KiB
TypeScript
import { chat } from "@infiplot/ai-client";
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import type { BeatActiveCharacter, ProviderConfig } from "@infiplot/types";
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import { parseJsonLoose } from "../jsonParser";
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import {
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CINEMATOGRAPHER_SYSTEM,
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buildCinematographerUserMessage,
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} from "../prompts";
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// ──────────────────────────────────────────────────────────────────────
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// Cinematographer agent — translates the Writer's narrative scene
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// summary into an English compositional prompt for FLUX.
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//
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// Reads: sceneSummary + entry beat's activeCharacters (poses)
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// + prior sceneKey (for continuity hints)
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// Writes: { shotType, integratedPrompt }
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//
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// Does NOT describe character APPEARANCE — that's appended at the
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// Painter stage from session.characters[].visualDescription. The
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// Cinematographer only positions named characters in the frame and
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// describes the environment + lighting + camera framing.
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//
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// This separation lets the Cinematographer run IN PARALLEL with the
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// CharacterDesigner — neither needs the other's output. They both
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// feed independently into the Painter prompt.
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// ──────────────────────────────────────────────────────────────────────
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export type CinematographerOutput = {
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shotType: string;
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integratedPrompt: string;
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};
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type RawCinematographerOutput = {
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shotType?: string;
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integratedPrompt?: string;
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};
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export type CinematographerInput = {
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sceneSummary: string;
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styleGuide: string;
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entryBeatActive: BeatActiveCharacter[];
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/** Entry beat's speaker — drives the dynamic camera policy:
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* NPC name → NPC looks toward camera (close-up)
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* "你" → medium shot, NPC listens
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* undefined → wide establishing shot */
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entryBeatSpeaker?: string;
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priorSceneKey?: string;
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currentSceneKey?: string;
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};
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export async function runCinematographer(
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config: ProviderConfig,
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input: CinematographerInput,
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): Promise<CinematographerOutput> {
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const raw = await chat(
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config,
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[
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{ role: "system", content: CINEMATOGRAPHER_SYSTEM },
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{
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role: "user",
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content: buildCinematographerUserMessage(
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input.sceneSummary,
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input.styleGuide,
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input.entryBeatActive,
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input.entryBeatSpeaker,
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input.priorSceneKey,
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input.currentSceneKey,
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),
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},
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],
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{ temperature: 0.6, responseFormat: "json_object", tag: "cinematographer" },
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);
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const parsed = parseJsonLoose<RawCinematographerOutput>(raw);
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// Fallback: if the LLM produced nothing usable, synthesize a minimal
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// integratedPrompt from the Writer's sceneSummary so the Painter has
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// SOMETHING to work with rather than blowing up the whole pipeline.
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const integratedPrompt =
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parsed.integratedPrompt?.trim() ||
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`A cinematic illustration depicting: ${input.sceneSummary}. Wide establishing shot, natural lighting, atmospheric mood.`;
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return {
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shotType: parsed.shotType?.trim() || "medium shot",
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integratedPrompt,
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};
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}
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