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feat(ai): add Google Cloud Code Assist provider
- Add new API type 'google-cloud-code-assist' for Gemini CLI / Antigravity auth - Extract shared Google utilities to google-shared.ts - Implement streaming provider for Cloud Code Assist endpoint - Add 7 models: gemini-3-pro-high/low, gemini-3-flash, claude-sonnet/opus, gpt-oss Models use OAuth authentication and have sh cost (uses Google account quota). OAuth flow will be implemented in coding-agent in a follow-up.
This commit is contained in:
Mario Zechner
parent
04dcdebbc6
commit
36e17933d5
10 changed files with 1208 additions and 178 deletions
429
packages/ai/src/providers/google-cloud-code-assist.ts
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429
packages/ai/src/providers/google-cloud-code-assist.ts
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@ -0,0 +1,429 @@
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/**
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* Google Cloud Code Assist provider for Gemini CLI / Antigravity authentication.
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* Uses the Cloud Code Assist API endpoint to access Gemini and Claude models.
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*/
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import type { Content, ThinkingConfig } from "@google/genai";
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import { calculateCost } from "../models.js";
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import type {
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Api,
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AssistantMessage,
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Context,
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Model,
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StreamFunction,
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StreamOptions,
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TextContent,
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ThinkingContent,
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ToolCall,
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} from "../types.js";
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import { AssistantMessageEventStream } from "../utils/event-stream.js";
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import { sanitizeSurrogates } from "../utils/sanitize-unicode.js";
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import { convertMessages, convertTools, mapStopReasonString, mapToolChoice } from "./google-shared.js";
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export interface GoogleCloudCodeAssistOptions extends StreamOptions {
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toolChoice?: "auto" | "none" | "any";
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thinking?: {
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enabled: boolean;
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budgetTokens?: number;
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};
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projectId?: string;
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}
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const ENDPOINT = "https://cloudcode-pa.googleapis.com";
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const HEADERS = {
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"User-Agent": "google-api-nodejs-client/9.15.1",
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"X-Goog-Api-Client": "gl-node/22.17.0",
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"Client-Metadata": "ideType=IDE_UNSPECIFIED,platform=PLATFORM_UNSPECIFIED,pluginType=GEMINI",
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};
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// Counter for generating unique tool call IDs
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let toolCallCounter = 0;
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interface CloudCodeAssistRequest {
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project: string;
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model: string;
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request: {
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contents: Content[];
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systemInstruction?: { parts: { text: string }[] };
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generationConfig?: {
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maxOutputTokens?: number;
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temperature?: number;
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thinkingConfig?: ThinkingConfig;
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};
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tools?: ReturnType<typeof convertTools>;
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toolConfig?: {
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functionCallingConfig: {
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mode: ReturnType<typeof mapToolChoice>;
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};
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};
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};
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userAgent?: string;
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requestId?: string;
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}
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interface CloudCodeAssistResponseChunk {
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response?: {
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candidates?: Array<{
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content?: {
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role: string;
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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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name: string;
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args: Record<string, unknown>;
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id?: string;
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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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candidatesTokenCount?: number;
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thoughtsTokenCount?: number;
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totalTokenCount?: number;
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cachedContentTokenCount?: number;
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};
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modelVersion?: string;
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responseId?: string;
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};
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traceId?: string;
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}
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export const streamGoogleCloudCodeAssist: StreamFunction<"google-cloud-code-assist"> = (
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model: Model<"google-cloud-code-assist">,
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context: Context,
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options?: GoogleCloudCodeAssistOptions,
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): AssistantMessageEventStream => {
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const stream = new AssistantMessageEventStream();
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(async () => {
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const output: AssistantMessage = {
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role: "assistant",
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content: [],
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api: "google-cloud-code-assist" as Api,
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provider: model.provider,
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model: model.id,
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usage: {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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totalTokens: 0,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
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},
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stopReason: "stop",
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timestamp: Date.now(),
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};
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try {
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const apiKey = options?.apiKey;
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if (!apiKey) {
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throw new Error("Google Cloud Code Assist requires an OAuth access token");
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}
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const projectId = options?.projectId;
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if (!projectId) {
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throw new Error("Google Cloud Code Assist requires a project ID");
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}
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const requestBody = buildRequest(model, context, projectId, options);
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const url = `${ENDPOINT}/v1internal:streamGenerateContent?alt=sse`;
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const response = await fetch(url, {
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method: "POST",
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headers: {
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Authorization: `Bearer ${apiKey}`,
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"Content-Type": "application/json",
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Accept: "text/event-stream",
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...HEADERS,
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},
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body: JSON.stringify(requestBody),
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signal: options?.signal,
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});
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(`Cloud Code Assist API error (${response.status}): ${errorText}`);
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}
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if (!response.body) {
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throw new Error("No response body");
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}
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stream.push({ type: "start", partial: output });
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let currentBlock: TextContent | ThinkingContent | null = null;
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const blocks = output.content;
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const blockIndex = () => blocks.length - 1;
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// Read SSE stream
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const reader = response.body.getReader();
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const decoder = new TextDecoder();
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let buffer = "";
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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buffer += decoder.decode(value, { stream: true });
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const lines = buffer.split("\n");
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buffer = lines.pop() || "";
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for (const line of lines) {
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if (!line.startsWith("data:")) continue;
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const jsonStr = line.slice(5).trim();
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if (!jsonStr) continue;
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let chunk: CloudCodeAssistResponseChunk;
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try {
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chunk = JSON.parse(jsonStr);
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} catch {
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continue;
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}
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// Unwrap the response
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const responseData = chunk.response;
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if (!responseData) continue;
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const candidate = responseData.candidates?.[0];
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if (candidate?.content?.parts) {
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for (const part of candidate.content.parts) {
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if (part.text !== undefined) {
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const isThinking = part.thought === true;
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if (
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!currentBlock ||
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(isThinking && currentBlock.type !== "thinking") ||
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(!isThinking && currentBlock.type !== "text")
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) {
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if (currentBlock) {
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if (currentBlock.type === "text") {
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stream.push({
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type: "text_end",
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contentIndex: blocks.length - 1,
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content: currentBlock.text,
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partial: output,
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});
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} else {
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stream.push({
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type: "thinking_end",
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contentIndex: blockIndex(),
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content: currentBlock.thinking,
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partial: output,
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});
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}
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}
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if (isThinking) {
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currentBlock = { type: "thinking", thinking: "", thinkingSignature: undefined };
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output.content.push(currentBlock);
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stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
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} else {
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currentBlock = { type: "text", text: "" };
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output.content.push(currentBlock);
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stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
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}
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}
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if (currentBlock.type === "thinking") {
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currentBlock.thinking += part.text;
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currentBlock.thinkingSignature = part.thoughtSignature;
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stream.push({
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type: "thinking_delta",
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contentIndex: blockIndex(),
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delta: part.text,
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partial: output,
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});
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} else {
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currentBlock.text += part.text;
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stream.push({
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type: "text_delta",
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contentIndex: blockIndex(),
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delta: part.text,
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partial: output,
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});
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}
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}
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if (part.functionCall) {
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if (currentBlock) {
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if (currentBlock.type === "text") {
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stream.push({
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type: "text_end",
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contentIndex: blockIndex(),
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content: currentBlock.text,
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partial: output,
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});
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} else {
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stream.push({
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type: "thinking_end",
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contentIndex: blockIndex(),
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content: currentBlock.thinking,
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partial: output,
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});
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}
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currentBlock = null;
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}
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const providedId = part.functionCall.id;
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const needsNewId =
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!providedId || output.content.some((b) => b.type === "toolCall" && b.id === providedId);
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const toolCallId = needsNewId
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? `${part.functionCall.name}_${Date.now()}_${++toolCallCounter}`
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: providedId;
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const toolCall: ToolCall = {
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type: "toolCall",
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id: toolCallId,
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name: part.functionCall.name || "",
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arguments: part.functionCall.args as Record<string, unknown>,
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...(part.thoughtSignature && { thoughtSignature: part.thoughtSignature }),
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};
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output.content.push(toolCall);
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stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
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stream.push({
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type: "toolcall_delta",
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contentIndex: blockIndex(),
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delta: JSON.stringify(toolCall.arguments),
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partial: output,
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});
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stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
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}
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}
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}
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if (candidate?.finishReason) {
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output.stopReason = mapStopReasonString(candidate.finishReason);
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if (output.content.some((b) => b.type === "toolCall")) {
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output.stopReason = "toolUse";
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}
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}
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if (responseData.usageMetadata) {
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output.usage = {
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input: responseData.usageMetadata.promptTokenCount || 0,
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output:
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(responseData.usageMetadata.candidatesTokenCount || 0) +
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(responseData.usageMetadata.thoughtsTokenCount || 0),
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cacheRead: responseData.usageMetadata.cachedContentTokenCount || 0,
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cacheWrite: 0,
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totalTokens: responseData.usageMetadata.totalTokenCount || 0,
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cost: {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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total: 0,
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},
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};
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calculateCost(model, output.usage);
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}
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}
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}
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if (currentBlock) {
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if (currentBlock.type === "text") {
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stream.push({
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type: "text_end",
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contentIndex: blockIndex(),
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content: currentBlock.text,
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partial: output,
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});
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} else {
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stream.push({
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type: "thinking_end",
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contentIndex: blockIndex(),
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content: currentBlock.thinking,
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partial: output,
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});
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}
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}
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if (options?.signal?.aborted) {
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throw new Error("Request was aborted");
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}
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if (output.stopReason === "aborted" || output.stopReason === "error") {
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throw new Error("An unknown error occurred");
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}
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stream.push({ type: "done", reason: output.stopReason, message: output });
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stream.end();
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} catch (error) {
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for (const block of output.content) {
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if ("index" in block) {
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delete (block as { index?: number }).index;
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}
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}
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output.stopReason = options?.signal?.aborted ? "aborted" : "error";
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output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
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stream.push({ type: "error", reason: output.stopReason, error: output });
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stream.end();
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}
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})();
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return stream;
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};
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function buildRequest(
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model: Model<"google-cloud-code-assist">,
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context: Context,
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projectId: string,
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options: GoogleCloudCodeAssistOptions = {},
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): CloudCodeAssistRequest {
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const contents = convertMessages(model, context);
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const generationConfig: CloudCodeAssistRequest["request"]["generationConfig"] = {};
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if (options.temperature !== undefined) {
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generationConfig.temperature = options.temperature;
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}
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if (options.maxTokens !== undefined) {
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generationConfig.maxOutputTokens = options.maxTokens;
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}
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// Thinking config
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if (options.thinking?.enabled && model.reasoning) {
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generationConfig.thinkingConfig = {
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includeThoughts: true,
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};
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if (options.thinking.budgetTokens !== undefined) {
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generationConfig.thinkingConfig.thinkingBudget = options.thinking.budgetTokens;
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}
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}
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const request: CloudCodeAssistRequest["request"] = {
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contents,
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};
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// System instruction must be object with parts, not plain string
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if (context.systemPrompt) {
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request.systemInstruction = {
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parts: [{ text: sanitizeSurrogates(context.systemPrompt) }],
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};
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}
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if (Object.keys(generationConfig).length > 0) {
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request.generationConfig = generationConfig;
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}
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if (context.tools && context.tools.length > 0) {
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request.tools = convertTools(context.tools);
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if (options.toolChoice) {
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request.toolConfig = {
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functionCallingConfig: {
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mode: mapToolChoice(options.toolChoice),
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},
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};
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}
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}
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return {
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project: projectId,
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model: model.id,
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request,
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userAgent: "pi-coding-agent",
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requestId: `pi-${Date.now()}-${Math.random().toString(36).slice(2, 11)}`,
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};
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}
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203
packages/ai/src/providers/google-shared.ts
Normal file
203
packages/ai/src/providers/google-shared.ts
Normal file
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@ -0,0 +1,203 @@
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/**
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* Shared utilities for Google Generative AI and Google Cloud Code Assist providers.
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*/
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import { type Content, FinishReason, FunctionCallingConfigMode, type Part, type Schema } from "@google/genai";
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import type { Context, ImageContent, Model, StopReason, TextContent, Tool } from "../types.js";
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import { sanitizeSurrogates } from "../utils/sanitize-unicode.js";
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import { transformMessages } from "./transorm-messages.js";
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type GoogleApiType = "google-generative-ai" | "google-cloud-code-assist";
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/**
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* Convert internal messages to Gemini Content[] format.
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*/
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export function convertMessages<T extends GoogleApiType>(model: Model<T>, context: Context): Content[] {
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const contents: Content[] = [];
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const transformedMessages = transformMessages(context.messages, model);
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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: sanitizeSurrogates(msg.content) }],
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});
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} else {
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const parts: Part[] = msg.content.map((item) => {
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if (item.type === "text") {
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return { text: sanitizeSurrogates(item.text) };
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} else {
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return {
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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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});
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const filteredParts = !model.input.includes("image") ? parts.filter((p) => p.text !== undefined) : parts;
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if (filteredParts.length === 0) continue;
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contents.push({
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role: "user",
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parts: filteredParts,
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});
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}
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} else if (msg.role === "assistant") {
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const parts: Part[] = [];
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for (const block of msg.content) {
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if (block.type === "text") {
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parts.push({ text: sanitizeSurrogates(block.text) });
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} else if (block.type === "thinking") {
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const thinkingPart: Part = {
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thought: true,
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thoughtSignature: block.thinkingSignature,
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text: sanitizeSurrogates(block.thinking),
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};
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parts.push(thinkingPart);
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} else if (block.type === "toolCall") {
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const part: Part = {
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functionCall: {
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id: block.id,
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name: block.name,
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args: block.arguments,
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},
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};
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if (block.thoughtSignature) {
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part.thoughtSignature = block.thoughtSignature;
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}
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parts.push(part);
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}
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}
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if (parts.length === 0) continue;
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contents.push({
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role: "model",
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parts,
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});
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} else if (msg.role === "toolResult") {
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// Build parts array with functionResponse and/or images
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const parts: Part[] = [];
|
||||
|
||||
// Extract text and image content
|
||||
const textContent = msg.content.filter((c): c is TextContent => c.type === "text");
|
||||
const textResult = textContent.map((c) => c.text).join("\n");
|
||||
const imageContent = model.input.includes("image")
|
||||
? msg.content.filter((c): c is ImageContent => c.type === "image")
|
||||
: [];
|
||||
|
||||
// Always add functionResponse with text result (or placeholder if only images)
|
||||
const hasText = textResult.length > 0;
|
||||
const hasImages = imageContent.length > 0;
|
||||
|
||||
// Use "output" key for success, "error" key for errors as per SDK documentation
|
||||
const responseValue = hasText ? sanitizeSurrogates(textResult) : hasImages ? "(see attached image)" : "";
|
||||
|
||||
parts.push({
|
||||
functionResponse: {
|
||||
id: msg.toolCallId,
|
||||
name: msg.toolName,
|
||||
response: msg.isError ? { error: responseValue } : { output: responseValue },
|
||||
},
|
||||
});
|
||||
|
||||
// Add any images as inlineData parts
|
||||
for (const imageBlock of imageContent) {
|
||||
parts.push({
|
||||
inlineData: {
|
||||
mimeType: imageBlock.mimeType,
|
||||
data: imageBlock.data,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return contents;
|
||||
}
|
||||
|
||||
/**
|
||||
* Convert tools to Gemini function declarations format.
|
||||
*/
|
||||
export function convertTools(
|
||||
tools: Tool[],
|
||||
): { functionDeclarations: { name: string; description?: string; parameters: Schema }[] }[] | undefined {
|
||||
if (tools.length === 0) return undefined;
|
||||
return [
|
||||
{
|
||||
functionDeclarations: tools.map((tool) => ({
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters as Schema,
|
||||
})),
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
/**
|
||||
* Map tool choice string to Gemini FunctionCallingConfigMode.
|
||||
*/
|
||||
export function mapToolChoice(choice: string): FunctionCallingConfigMode {
|
||||
switch (choice) {
|
||||
case "auto":
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
case "none":
|
||||
return FunctionCallingConfigMode.NONE;
|
||||
case "any":
|
||||
return FunctionCallingConfigMode.ANY;
|
||||
default:
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Map Gemini FinishReason to our StopReason.
|
||||
*/
|
||||
export function mapStopReason(reason: FinishReason): StopReason {
|
||||
switch (reason) {
|
||||
case FinishReason.STOP:
|
||||
return "stop";
|
||||
case FinishReason.MAX_TOKENS:
|
||||
return "length";
|
||||
case FinishReason.BLOCKLIST:
|
||||
case FinishReason.PROHIBITED_CONTENT:
|
||||
case FinishReason.SPII:
|
||||
case FinishReason.SAFETY:
|
||||
case FinishReason.IMAGE_SAFETY:
|
||||
case FinishReason.IMAGE_PROHIBITED_CONTENT:
|
||||
case FinishReason.IMAGE_RECITATION:
|
||||
case FinishReason.IMAGE_OTHER:
|
||||
case FinishReason.RECITATION:
|
||||
case FinishReason.FINISH_REASON_UNSPECIFIED:
|
||||
case FinishReason.OTHER:
|
||||
case FinishReason.LANGUAGE:
|
||||
case FinishReason.MALFORMED_FUNCTION_CALL:
|
||||
case FinishReason.UNEXPECTED_TOOL_CALL:
|
||||
case FinishReason.NO_IMAGE:
|
||||
return "error";
|
||||
default: {
|
||||
const _exhaustive: never = reason;
|
||||
throw new Error(`Unhandled stop reason: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Map string finish reason to our StopReason (for raw API responses).
|
||||
*/
|
||||
export function mapStopReasonString(reason: string): StopReason {
|
||||
switch (reason) {
|
||||
case "STOP":
|
||||
return "stop";
|
||||
case "MAX_TOKENS":
|
||||
return "length";
|
||||
default:
|
||||
return "error";
|
||||
}
|
||||
}
|
||||
|
|
@ -1,12 +1,7 @@
|
|||
import {
|
||||
type Content,
|
||||
FinishReason,
|
||||
FunctionCallingConfigMode,
|
||||
type GenerateContentConfig,
|
||||
type GenerateContentParameters,
|
||||
GoogleGenAI,
|
||||
type Part,
|
||||
type Schema,
|
||||
type ThinkingConfig,
|
||||
type ThinkingLevel,
|
||||
} from "@google/genai";
|
||||
|
|
@ -15,20 +10,16 @@ import type {
|
|||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
ImageContent,
|
||||
Model,
|
||||
StopReason,
|
||||
StreamFunction,
|
||||
StreamOptions,
|
||||
TextContent,
|
||||
ThinkingContent,
|
||||
Tool,
|
||||
ToolCall,
|
||||
} from "../types.js";
|
||||
import { AssistantMessageEventStream } from "../utils/event-stream.js";
|
||||
import { sanitizeSurrogates } from "../utils/sanitize-unicode.js";
|
||||
|
||||
import { transformMessages } from "./transorm-messages.js";
|
||||
import { convertMessages, convertTools, mapStopReason, mapToolChoice } from "./google-shared.js";
|
||||
|
||||
export interface GoogleOptions extends StreamOptions {
|
||||
toolChoice?: "auto" | "none" | "any";
|
||||
|
|
@ -337,169 +328,3 @@ function buildParams(
|
|||
|
||||
return params;
|
||||
}
|
||||
function convertMessages(model: Model<"google-generative-ai">, context: Context): Content[] {
|
||||
const contents: Content[] = [];
|
||||
const transformedMessages = transformMessages(context.messages, model);
|
||||
|
||||
for (const msg of transformedMessages) {
|
||||
if (msg.role === "user") {
|
||||
if (typeof msg.content === "string") {
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: [{ text: sanitizeSurrogates(msg.content) }],
|
||||
});
|
||||
} else {
|
||||
const parts: Part[] = msg.content.map((item) => {
|
||||
if (item.type === "text") {
|
||||
return { text: sanitizeSurrogates(item.text) };
|
||||
} else {
|
||||
return {
|
||||
inlineData: {
|
||||
mimeType: item.mimeType,
|
||||
data: item.data,
|
||||
},
|
||||
};
|
||||
}
|
||||
});
|
||||
const filteredParts = !model.input.includes("image") ? parts.filter((p) => p.text !== undefined) : parts;
|
||||
if (filteredParts.length === 0) continue;
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: filteredParts,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
const parts: Part[] = [];
|
||||
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "text") {
|
||||
parts.push({ text: sanitizeSurrogates(block.text) });
|
||||
} else if (block.type === "thinking") {
|
||||
const thinkingPart: Part = {
|
||||
thought: true,
|
||||
thoughtSignature: block.thinkingSignature,
|
||||
text: sanitizeSurrogates(block.thinking),
|
||||
};
|
||||
parts.push(thinkingPart);
|
||||
} else if (block.type === "toolCall") {
|
||||
const part: Part = {
|
||||
functionCall: {
|
||||
id: block.id,
|
||||
name: block.name,
|
||||
args: block.arguments,
|
||||
},
|
||||
};
|
||||
if (block.thoughtSignature) {
|
||||
part.thoughtSignature = block.thoughtSignature;
|
||||
}
|
||||
parts.push(part);
|
||||
}
|
||||
}
|
||||
|
||||
if (parts.length === 0) continue;
|
||||
contents.push({
|
||||
role: "model",
|
||||
parts,
|
||||
});
|
||||
} else if (msg.role === "toolResult") {
|
||||
// Build parts array with functionResponse and/or images
|
||||
const parts: Part[] = [];
|
||||
|
||||
// Extract text and image content
|
||||
const textContent = msg.content.filter((c): c is TextContent => c.type === "text");
|
||||
const textResult = textContent.map((c) => c.text).join("\n");
|
||||
const imageContent = model.input.includes("image")
|
||||
? msg.content.filter((c): c is ImageContent => c.type === "image")
|
||||
: [];
|
||||
|
||||
// Always add functionResponse with text result (or placeholder if only images)
|
||||
const hasText = textResult.length > 0;
|
||||
const hasImages = imageContent.length > 0;
|
||||
|
||||
// Use "output" key for success, "error" key for errors as per SDK documentation
|
||||
const responseValue = hasText ? sanitizeSurrogates(textResult) : hasImages ? "(see attached image)" : "";
|
||||
|
||||
parts.push({
|
||||
functionResponse: {
|
||||
id: msg.toolCallId,
|
||||
name: msg.toolName,
|
||||
response: msg.isError ? { error: responseValue } : { output: responseValue },
|
||||
},
|
||||
});
|
||||
|
||||
// Add any images as inlineData parts
|
||||
for (const imageBlock of imageContent) {
|
||||
parts.push({
|
||||
inlineData: {
|
||||
mimeType: imageBlock.mimeType,
|
||||
data: imageBlock.data,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return contents;
|
||||
}
|
||||
|
||||
function convertTools(
|
||||
tools: Tool[],
|
||||
): { functionDeclarations: { name: string; description?: string; parameters: Schema }[] }[] | undefined {
|
||||
if (tools.length === 0) return undefined;
|
||||
return [
|
||||
{
|
||||
functionDeclarations: tools.map((tool) => ({
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters as Schema, // TypeBox generates JSON Schema compatible with SDK Schema type
|
||||
})),
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
function mapToolChoice(choice: string): FunctionCallingConfigMode {
|
||||
switch (choice) {
|
||||
case "auto":
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
case "none":
|
||||
return FunctionCallingConfigMode.NONE;
|
||||
case "any":
|
||||
return FunctionCallingConfigMode.ANY;
|
||||
default:
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
}
|
||||
}
|
||||
|
||||
function mapStopReason(reason: FinishReason): StopReason {
|
||||
switch (reason) {
|
||||
case FinishReason.STOP:
|
||||
return "stop";
|
||||
case FinishReason.MAX_TOKENS:
|
||||
return "length";
|
||||
case FinishReason.BLOCKLIST:
|
||||
case FinishReason.PROHIBITED_CONTENT:
|
||||
case FinishReason.SPII:
|
||||
case FinishReason.SAFETY:
|
||||
case FinishReason.IMAGE_SAFETY:
|
||||
case FinishReason.IMAGE_PROHIBITED_CONTENT:
|
||||
case FinishReason.IMAGE_RECITATION:
|
||||
case FinishReason.IMAGE_OTHER:
|
||||
case FinishReason.RECITATION:
|
||||
case FinishReason.FINISH_REASON_UNSPECIFIED:
|
||||
case FinishReason.OTHER:
|
||||
case FinishReason.LANGUAGE:
|
||||
case FinishReason.MALFORMED_FUNCTION_CALL:
|
||||
case FinishReason.UNEXPECTED_TOOL_CALL:
|
||||
case FinishReason.NO_IMAGE:
|
||||
return "error";
|
||||
default: {
|
||||
const _exhaustive: never = reason;
|
||||
throw new Error(`Unhandled stop reason: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue