mirror of
https://github.com/openclaw/openclaw.git
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748 lines
24 KiB
TypeScript
748 lines
24 KiB
TypeScript
import type { StreamFn } from "@mariozechner/pi-agent-core";
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import {
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calculateCost,
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getEnvApiKey,
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type Context,
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type Model,
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type SimpleStreamOptions,
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type ThinkingLevel,
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} from "@mariozechner/pi-ai";
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import { parseGeminiAuth } from "../infra/gemini-auth.js";
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import { normalizeGoogleApiBaseUrl } from "../infra/google-api-base-url.js";
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import { normalizeLowercaseStringOrEmpty } from "../shared/string-coerce.js";
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import { buildGuardedModelFetch } from "./provider-transport-fetch.js";
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import { stripSystemPromptCacheBoundary } from "./system-prompt-cache-boundary.js";
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import { transformTransportMessages } from "./transport-message-transform.js";
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import {
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createEmptyTransportUsage,
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createWritableTransportEventStream,
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failTransportStream,
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finalizeTransportStream,
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mergeTransportHeaders,
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sanitizeTransportPayloadText,
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type WritableTransportStream,
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} from "./transport-stream-shared.js";
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type GoogleTransportModel = Model<"google-generative-ai"> & {
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headers?: Record<string, string>;
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provider: string;
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};
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type GoogleThinkingLevel = "MINIMAL" | "LOW" | "MEDIUM" | "HIGH";
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type GoogleTransportOptions = SimpleStreamOptions & {
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cachedContent?: string;
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toolChoice?:
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| "auto"
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| "none"
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| "any"
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| "required"
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| {
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type: "function";
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function: {
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name: string;
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};
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};
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thinking?: {
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enabled: boolean;
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budgetTokens?: number;
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level?: GoogleThinkingLevel;
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};
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};
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type GoogleGenerateContentRequest = {
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cachedContent?: string;
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contents: Array<Record<string, unknown>>;
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generationConfig?: Record<string, unknown>;
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systemInstruction?: Record<string, unknown>;
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tools?: Array<Record<string, unknown>>;
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toolConfig?: Record<string, unknown>;
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};
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type GoogleTransportContentBlock =
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| { type: "text"; text: string; textSignature?: string }
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| { type: "thinking"; thinking: string; thinkingSignature?: string }
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| { type: "toolCall"; id: string; name: string; arguments: Record<string, unknown> };
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type MutableAssistantOutput = {
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role: "assistant";
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content: Array<GoogleTransportContentBlock>;
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api: "google-generative-ai";
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provider: string;
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model: string;
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usage: {
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input: number;
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output: number;
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cacheRead: number;
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cacheWrite: number;
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totalTokens: number;
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cost: { input: number; output: number; cacheRead: number; cacheWrite: number; total: number };
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};
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stopReason: string;
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timestamp: number;
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responseId?: string;
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errorMessage?: string;
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};
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type GoogleSseChunk = {
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responseId?: string;
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candidates?: Array<{
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content?: {
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parts?: Array<{
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text?: string;
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thought?: boolean;
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thoughtSignature?: string;
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functionCall?: {
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id?: string;
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name?: string;
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args?: Record<string, unknown>;
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};
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}>;
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};
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finishReason?: string;
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}>;
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usageMetadata?: {
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promptTokenCount?: number;
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cachedContentTokenCount?: number;
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candidatesTokenCount?: number;
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thoughtsTokenCount?: number;
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totalTokenCount?: number;
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};
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};
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let toolCallCounter = 0;
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function isGemini3ProModel(modelId: string): boolean {
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return /gemini-3(?:\.\d+)?-pro/.test(normalizeLowercaseStringOrEmpty(modelId));
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}
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function isGemini3FlashModel(modelId: string): boolean {
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return /gemini-3(?:\.\d+)?-flash/.test(normalizeLowercaseStringOrEmpty(modelId));
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}
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function requiresToolCallId(modelId: string): boolean {
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return modelId.startsWith("claude-") || modelId.startsWith("gpt-oss-");
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}
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function supportsMultimodalFunctionResponse(modelId: string): boolean {
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const match = normalizeLowercaseStringOrEmpty(modelId).match(/^gemini(?:-live)?-(\d+)/);
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if (!match) {
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return true;
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}
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return Number.parseInt(match[1] ?? "", 10) >= 3;
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}
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function retainThoughtSignature(existing: string | undefined, incoming: string | undefined) {
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if (typeof incoming === "string" && incoming.length > 0) {
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return incoming;
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}
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return existing;
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}
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function mapToolChoice(
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choice: GoogleTransportOptions["toolChoice"],
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): { mode: "AUTO" | "NONE" | "ANY"; allowedFunctionNames?: string[] } | undefined {
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if (!choice) {
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return undefined;
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}
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if (typeof choice === "object" && choice.type === "function") {
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return { mode: "ANY", allowedFunctionNames: [choice.function.name] };
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}
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switch (choice) {
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case "none":
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return { mode: "NONE" };
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case "any":
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case "required":
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return { mode: "ANY" };
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default:
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return { mode: "AUTO" };
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}
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}
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function mapStopReasonString(reason: string): "stop" | "length" | "error" {
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switch (reason) {
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case "STOP":
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return "stop";
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case "MAX_TOKENS":
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return "length";
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default:
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return "error";
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}
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}
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function normalizeToolCallId(id: string): string {
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return id.replace(/[^a-zA-Z0-9_-]/g, "_").slice(0, 64);
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}
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function resolveGoogleModelPath(modelId: string): string {
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if (modelId.startsWith("models/") || modelId.startsWith("tunedModels/")) {
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return modelId;
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}
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return `models/${modelId}`;
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}
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function buildGoogleRequestUrl(model: GoogleTransportModel): string {
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const baseUrl = normalizeGoogleApiBaseUrl(model.baseUrl);
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return `${baseUrl}/${resolveGoogleModelPath(model.id)}:streamGenerateContent?alt=sse`;
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}
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function resolveThinkingLevel(level: ThinkingLevel, modelId: string): GoogleThinkingLevel {
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if (isGemini3ProModel(modelId)) {
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switch (level) {
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case "minimal":
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case "low":
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return "LOW";
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case "medium":
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case "high":
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case "xhigh":
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return "HIGH";
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}
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}
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switch (level) {
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case "minimal":
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return "MINIMAL";
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case "low":
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return "LOW";
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case "medium":
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return "MEDIUM";
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case "high":
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case "xhigh":
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return "HIGH";
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}
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throw new Error("Unsupported thinking level");
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}
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function getDisabledThinkingConfig(modelId: string): Record<string, unknown> {
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if (isGemini3ProModel(modelId)) {
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return { thinkingLevel: "LOW" };
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}
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if (isGemini3FlashModel(modelId)) {
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return { thinkingLevel: "MINIMAL" };
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}
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return { thinkingBudget: 0 };
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}
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function getGoogleThinkingBudget(
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modelId: string,
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effort: ThinkingLevel,
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customBudgets?: GoogleTransportOptions["thinkingBudgets"],
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): number | undefined {
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const normalizedEffort = effort === "xhigh" ? "high" : effort;
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if (customBudgets?.[normalizedEffort] !== undefined) {
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return customBudgets[normalizedEffort];
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}
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if (modelId.includes("2.5-pro")) {
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return { minimal: 128, low: 2048, medium: 8192, high: 32768 }[normalizedEffort];
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}
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if (modelId.includes("2.5-flash")) {
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return { minimal: 128, low: 2048, medium: 8192, high: 24576 }[normalizedEffort];
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}
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return undefined;
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}
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function resolveGoogleThinkingConfig(
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model: GoogleTransportModel,
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options: GoogleTransportOptions | undefined,
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): Record<string, unknown> | undefined {
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if (!model.reasoning) {
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return undefined;
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}
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if (options?.thinking) {
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if (!options.thinking.enabled) {
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return getDisabledThinkingConfig(model.id);
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}
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const config: Record<string, unknown> = { includeThoughts: true };
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if (options.thinking.level) {
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config.thinkingLevel = options.thinking.level;
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} else if (typeof options.thinking.budgetTokens === "number") {
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config.thinkingBudget = options.thinking.budgetTokens;
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}
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return config;
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}
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if (!options?.reasoning) {
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return getDisabledThinkingConfig(model.id);
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}
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if (isGemini3ProModel(model.id) || isGemini3FlashModel(model.id)) {
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return {
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includeThoughts: true,
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thinkingLevel: resolveThinkingLevel(options.reasoning, model.id),
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};
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}
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const budget = getGoogleThinkingBudget(model.id, options.reasoning, options.thinkingBudgets);
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return {
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includeThoughts: true,
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...(typeof budget === "number" ? { thinkingBudget: budget } : {}),
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};
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}
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function convertGoogleMessages(model: GoogleTransportModel, context: Context) {
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const contents: Array<Record<string, unknown>> = [];
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const transformedMessages = transformTransportMessages(context.messages, model, (id) =>
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requiresToolCallId(model.id) ? normalizeToolCallId(id) : id,
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);
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for (const msg of transformedMessages) {
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if (msg.role === "user") {
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if (typeof msg.content === "string") {
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contents.push({
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role: "user",
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parts: [{ text: sanitizeTransportPayloadText(msg.content) }],
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});
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continue;
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}
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const parts = msg.content
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.map((item) =>
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item.type === "text"
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? { text: sanitizeTransportPayloadText(item.text) }
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: {
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inlineData: {
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mimeType: item.mimeType,
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data: item.data,
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},
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},
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)
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.filter((item) => model.input.includes("image") || !("inlineData" in item));
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if (parts.length > 0) {
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contents.push({ role: "user", parts });
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}
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continue;
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}
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if (msg.role === "assistant") {
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const isSameProviderAndModel = msg.provider === model.provider && msg.model === model.id;
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const parts: Array<Record<string, unknown>> = [];
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for (const block of msg.content) {
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if (block.type === "text") {
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if (!block.text.trim()) {
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continue;
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}
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parts.push({
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text: sanitizeTransportPayloadText(block.text),
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...(isSameProviderAndModel && block.textSignature
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? { thoughtSignature: block.textSignature }
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: {}),
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});
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continue;
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}
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if (block.type === "thinking") {
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if (!block.thinking.trim()) {
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continue;
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}
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if (isSameProviderAndModel) {
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parts.push({
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thought: true,
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text: sanitizeTransportPayloadText(block.thinking),
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...(block.thinkingSignature ? { thoughtSignature: block.thinkingSignature } : {}),
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});
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} else {
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parts.push({ text: sanitizeTransportPayloadText(block.thinking) });
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}
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continue;
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}
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if (block.type === "toolCall") {
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parts.push({
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functionCall: {
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name: block.name,
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args: block.arguments ?? {},
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...(requiresToolCallId(model.id) ? { id: block.id } : {}),
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},
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...(isSameProviderAndModel && block.thoughtSignature
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? { thoughtSignature: block.thoughtSignature }
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: {}),
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});
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}
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}
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if (parts.length > 0) {
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contents.push({ role: "model", parts });
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}
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continue;
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}
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if (msg.role === "toolResult") {
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const textResult = msg.content
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.filter(
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(item): item is Extract<(typeof msg.content)[number], { type: "text" }> =>
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item.type === "text",
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)
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.map((item) => item.text)
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.join("\n");
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const imageContent = model.input.includes("image")
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? msg.content.filter(
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(item): item is Extract<(typeof msg.content)[number], { type: "image" }> =>
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item.type === "image",
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)
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: [];
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const responseValue = textResult
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? sanitizeTransportPayloadText(textResult)
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: imageContent.length > 0
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? "(see attached image)"
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: "";
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const imageParts = imageContent.map((imageBlock) => ({
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inlineData: {
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mimeType: imageBlock.mimeType,
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data: imageBlock.data,
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},
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}));
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const functionResponse = {
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functionResponse: {
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name: msg.toolName,
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response: msg.isError ? { error: responseValue } : { output: responseValue },
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...(supportsMultimodalFunctionResponse(model.id) && imageParts.length > 0
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? { parts: imageParts }
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: {}),
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...(requiresToolCallId(model.id) ? { id: msg.toolCallId } : {}),
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},
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};
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const last = contents[contents.length - 1];
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if (
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last?.role === "user" &&
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Array.isArray(last.parts) &&
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last.parts.some((part) => "functionResponse" in part)
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) {
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(last.parts as Array<Record<string, unknown>>).push(functionResponse);
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} else {
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contents.push({ role: "user", parts: [functionResponse] });
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}
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if (imageParts.length > 0 && !supportsMultimodalFunctionResponse(model.id)) {
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contents.push({ role: "user", parts: [{ text: "Tool result image:" }, ...imageParts] });
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}
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}
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}
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return contents;
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}
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function convertGoogleTools(tools: NonNullable<Context["tools"]>) {
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if (tools.length === 0) {
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return undefined;
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}
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return [
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{
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functionDeclarations: tools.map((tool) => ({
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name: tool.name,
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description: tool.description,
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parametersJsonSchema: tool.parameters,
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})),
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},
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];
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}
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export function buildGoogleGenerativeAiParams(
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model: GoogleTransportModel,
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context: Context,
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options?: GoogleTransportOptions,
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): GoogleGenerateContentRequest {
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const generationConfig: Record<string, unknown> = {};
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if (typeof options?.temperature === "number") {
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generationConfig.temperature = options.temperature;
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}
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if (typeof options?.maxTokens === "number") {
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generationConfig.maxOutputTokens = options.maxTokens;
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}
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const thinkingConfig = resolveGoogleThinkingConfig(model, options);
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if (thinkingConfig) {
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generationConfig.thinkingConfig = thinkingConfig;
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}
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const params: GoogleGenerateContentRequest = {
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contents: convertGoogleMessages(model, context),
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};
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if (typeof options?.cachedContent === "string" && options.cachedContent.trim()) {
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params.cachedContent = options.cachedContent.trim();
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}
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if (Object.keys(generationConfig).length > 0) {
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params.generationConfig = generationConfig;
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}
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if (context.systemPrompt) {
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params.systemInstruction = {
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parts: [
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{
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text: sanitizeTransportPayloadText(stripSystemPromptCacheBoundary(context.systemPrompt)),
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},
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],
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};
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}
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if (context.tools?.length) {
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params.tools = convertGoogleTools(context.tools);
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const toolChoice = mapToolChoice(options?.toolChoice);
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if (toolChoice) {
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params.toolConfig = {
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functionCallingConfig: toolChoice,
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};
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}
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}
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return params;
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}
|
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|
|
function buildGoogleHeaders(
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model: GoogleTransportModel,
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apiKey: string | undefined,
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optionHeaders: Record<string, string> | undefined,
|
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): Record<string, string> {
|
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const authHeaders = apiKey ? parseGeminiAuth(apiKey).headers : undefined;
|
|
return (
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mergeTransportHeaders(
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{
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|
accept: "text/event-stream",
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|
},
|
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authHeaders,
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model.headers,
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optionHeaders,
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) ?? {
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accept: "text/event-stream",
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}
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);
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}
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|
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async function* parseGoogleSseChunks(
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response: Response,
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|
signal?: AbortSignal,
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|
): AsyncGenerator<GoogleSseChunk> {
|
|
if (!response.body) {
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throw new Error("No response body");
|
|
}
|
|
const reader = response.body.getReader();
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|
const decoder = new TextDecoder();
|
|
let buffer = "";
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|
const abortHandler = () => {
|
|
void reader.cancel().catch(() => undefined);
|
|
};
|
|
signal?.addEventListener("abort", abortHandler);
|
|
try {
|
|
while (true) {
|
|
if (signal?.aborted) {
|
|
throw new Error("Request was aborted");
|
|
}
|
|
const { done, value } = await reader.read();
|
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if (done) {
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break;
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}
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buffer += decoder.decode(value, { stream: true }).replace(/\r/g, "");
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let boundary = buffer.indexOf("\n\n");
|
|
while (boundary >= 0) {
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const rawEvent = buffer.slice(0, boundary);
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buffer = buffer.slice(boundary + 2);
|
|
boundary = buffer.indexOf("\n\n");
|
|
const data = rawEvent
|
|
.split("\n")
|
|
.filter((line) => line.startsWith("data:"))
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.map((line) => line.slice(5).trim())
|
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.join("\n");
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if (!data || data === "[DONE]") {
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continue;
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}
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yield JSON.parse(data) as GoogleSseChunk;
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}
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}
|
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} finally {
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signal?.removeEventListener("abort", abortHandler);
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}
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}
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|
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function updateUsage(
|
|
output: MutableAssistantOutput,
|
|
model: GoogleTransportModel,
|
|
chunk: GoogleSseChunk,
|
|
) {
|
|
const usage = chunk.usageMetadata;
|
|
if (!usage) {
|
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return;
|
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}
|
|
const promptTokens = usage.promptTokenCount || 0;
|
|
const cacheRead = usage.cachedContentTokenCount || 0;
|
|
output.usage = {
|
|
input: Math.max(0, promptTokens - cacheRead),
|
|
output: (usage.candidatesTokenCount || 0) + (usage.thoughtsTokenCount || 0),
|
|
cacheRead,
|
|
cacheWrite: 0,
|
|
totalTokens: usage.totalTokenCount || 0,
|
|
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
|
};
|
|
calculateCost(model, output.usage);
|
|
}
|
|
|
|
function pushTextBlockEnd(
|
|
stream: WritableTransportStream,
|
|
output: MutableAssistantOutput,
|
|
blockIndex: number,
|
|
) {
|
|
const block = output.content[blockIndex];
|
|
if (!block) {
|
|
return;
|
|
}
|
|
if (block.type === "thinking") {
|
|
stream.push({
|
|
type: "thinking_end",
|
|
contentIndex: blockIndex,
|
|
content: block.thinking,
|
|
partial: output as never,
|
|
});
|
|
return;
|
|
}
|
|
if (block.type === "text") {
|
|
stream.push({
|
|
type: "text_end",
|
|
contentIndex: blockIndex,
|
|
content: block.text,
|
|
partial: output as never,
|
|
});
|
|
}
|
|
}
|
|
|
|
export function createGoogleGenerativeAiTransportStreamFn(): StreamFn {
|
|
return (rawModel, context, rawOptions) => {
|
|
const model = rawModel as GoogleTransportModel;
|
|
const options = rawOptions as GoogleTransportOptions | undefined;
|
|
const { eventStream, stream } = createWritableTransportEventStream();
|
|
void (async () => {
|
|
const output: MutableAssistantOutput = {
|
|
role: "assistant",
|
|
content: [],
|
|
api: "google-generative-ai",
|
|
provider: model.provider,
|
|
model: model.id,
|
|
usage: createEmptyTransportUsage(),
|
|
stopReason: "stop",
|
|
timestamp: Date.now(),
|
|
};
|
|
try {
|
|
const apiKey = options?.apiKey ?? getEnvApiKey(model.provider) ?? undefined;
|
|
const fetch = buildGuardedModelFetch(model);
|
|
let params = buildGoogleGenerativeAiParams(model, context, options);
|
|
const nextParams = await options?.onPayload?.(params, model);
|
|
if (nextParams !== undefined) {
|
|
params = nextParams as GoogleGenerateContentRequest;
|
|
}
|
|
const response = await fetch(buildGoogleRequestUrl(model), {
|
|
method: "POST",
|
|
headers: buildGoogleHeaders(model, apiKey, options?.headers),
|
|
body: JSON.stringify(params),
|
|
signal: options?.signal,
|
|
});
|
|
if (!response.ok) {
|
|
const message = await response.text().catch(() => "");
|
|
throw new Error(`Google Generative AI API error (${response.status}): ${message}`);
|
|
}
|
|
stream.push({ type: "start", partial: output as never });
|
|
let currentBlockIndex = -1;
|
|
for await (const chunk of parseGoogleSseChunks(response, options?.signal)) {
|
|
output.responseId ||= chunk.responseId;
|
|
updateUsage(output, model, chunk);
|
|
const candidate = chunk.candidates?.[0];
|
|
if (candidate?.content?.parts) {
|
|
for (const part of candidate.content.parts) {
|
|
if (typeof part.text === "string") {
|
|
const isThinking = part.thought === true;
|
|
const currentBlock = output.content[currentBlockIndex];
|
|
if (
|
|
currentBlockIndex < 0 ||
|
|
!currentBlock ||
|
|
(isThinking && currentBlock.type !== "thinking") ||
|
|
(!isThinking && currentBlock.type !== "text")
|
|
) {
|
|
if (currentBlockIndex >= 0) {
|
|
pushTextBlockEnd(stream, output, currentBlockIndex);
|
|
}
|
|
if (isThinking) {
|
|
output.content.push({ type: "thinking", thinking: "" });
|
|
currentBlockIndex = output.content.length - 1;
|
|
stream.push({
|
|
type: "thinking_start",
|
|
contentIndex: currentBlockIndex,
|
|
partial: output as never,
|
|
});
|
|
} else {
|
|
output.content.push({ type: "text", text: "" });
|
|
currentBlockIndex = output.content.length - 1;
|
|
stream.push({
|
|
type: "text_start",
|
|
contentIndex: currentBlockIndex,
|
|
partial: output as never,
|
|
});
|
|
}
|
|
}
|
|
const activeBlock = output.content[currentBlockIndex];
|
|
if (activeBlock?.type === "thinking") {
|
|
activeBlock.thinking += part.text;
|
|
activeBlock.thinkingSignature = retainThoughtSignature(
|
|
activeBlock.thinkingSignature,
|
|
part.thoughtSignature,
|
|
);
|
|
stream.push({
|
|
type: "thinking_delta",
|
|
contentIndex: currentBlockIndex,
|
|
delta: part.text,
|
|
partial: output as never,
|
|
});
|
|
} else if (activeBlock?.type === "text") {
|
|
activeBlock.text += part.text;
|
|
activeBlock.textSignature = retainThoughtSignature(
|
|
activeBlock.textSignature,
|
|
part.thoughtSignature,
|
|
);
|
|
stream.push({
|
|
type: "text_delta",
|
|
contentIndex: currentBlockIndex,
|
|
delta: part.text,
|
|
partial: output as never,
|
|
});
|
|
}
|
|
}
|
|
if (part.functionCall) {
|
|
if (currentBlockIndex >= 0) {
|
|
pushTextBlockEnd(stream, output, currentBlockIndex);
|
|
currentBlockIndex = -1;
|
|
}
|
|
const providedId = part.functionCall.id;
|
|
const isDuplicate = output.content.some(
|
|
(block) => block.type === "toolCall" && block.id === providedId,
|
|
);
|
|
const toolCallId =
|
|
providedId && !isDuplicate
|
|
? providedId
|
|
: `${part.functionCall.name || "tool"}_${Date.now()}_${++toolCallCounter}`;
|
|
const toolCall: GoogleTransportContentBlock = {
|
|
type: "toolCall",
|
|
id: toolCallId,
|
|
name: part.functionCall.name || "",
|
|
arguments: part.functionCall.args ?? {},
|
|
};
|
|
output.content.push(toolCall);
|
|
const blockIndex = output.content.length - 1;
|
|
stream.push({
|
|
type: "toolcall_start",
|
|
contentIndex: blockIndex,
|
|
partial: output as never,
|
|
});
|
|
stream.push({
|
|
type: "toolcall_delta",
|
|
contentIndex: blockIndex,
|
|
delta: JSON.stringify(toolCall.arguments),
|
|
partial: output as never,
|
|
});
|
|
stream.push({
|
|
type: "toolcall_end",
|
|
contentIndex: blockIndex,
|
|
toolCall,
|
|
partial: output as never,
|
|
});
|
|
}
|
|
}
|
|
}
|
|
if (typeof candidate?.finishReason === "string") {
|
|
output.stopReason = mapStopReasonString(candidate.finishReason);
|
|
if (output.content.some((block) => block.type === "toolCall")) {
|
|
output.stopReason = "toolUse";
|
|
}
|
|
}
|
|
}
|
|
if (currentBlockIndex >= 0) {
|
|
pushTextBlockEnd(stream, output, currentBlockIndex);
|
|
}
|
|
finalizeTransportStream({ stream, output, signal: options?.signal });
|
|
} catch (error) {
|
|
failTransportStream({ stream, output, signal: options?.signal, error });
|
|
}
|
|
})();
|
|
return eventStream as unknown as ReturnType<StreamFn>;
|
|
};
|
|
}
|