mirror of https://github.com/buster-so/buster.git
migrating over to sdk v5
This commit is contained in:
dal
parent
5883fc8762
commit
fcbe1838a1
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@ -0,0 +1,30 @@
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import { describe, it, expect } from 'vitest';
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import { getThinkAndPrepAgentSystemPrompt } from './get-think-and-prep-agent-system-prompt';
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describe('getThinkAndPrepAgentSystemPrompt', () => {
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it('should return system prompt with SQL dialect guidance', () => {
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const sqlDialectGuidance = 'PostgreSQL specific guidance';
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const result = getThinkAndPrepAgentSystemPrompt(sqlDialectGuidance);
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expect(result).toContain('You are Buster, a specialized AI agent');
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expect(result).toContain('PostgreSQL specific guidance');
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expect(result).toContain("Today's date is");
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});
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it('should include all necessary sections', () => {
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const sqlDialectGuidance = 'MySQL specific guidance';
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const result = getThinkAndPrepAgentSystemPrompt(sqlDialectGuidance);
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// Check for key sections
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expect(result).toContain('<intro>');
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expect(result).toContain('<prep_mode_capability>');
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expect(result).toContain('<event_stream>');
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expect(result).toContain('<agent_loop>');
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expect(result).toContain('<todo_list>');
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expect(result).toContain('<todo_rules>');
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expect(result).toContain('<tool_use_rules>');
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expect(result).toContain('<sequential_thinking_rules>');
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expect(result).toContain('<execute_sql_rules>');
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expect(result).toContain('<sql_best_practices>');
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});
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});
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@ -1,16 +1,4 @@
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import { getPermissionedDatasets } from '@buster/access-controls';
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import type { RuntimeContext } from '@mastra/core/runtime-context';
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import type { AnalystRuntimeContext } from '../../workflows/analyst-workflow';
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import { getSqlDialectGuidance } from '../shared/sql-dialect-guidance';
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// Define the required template parameters
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interface ThinkAndPrepTemplateParams {
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databaseContext: string;
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sqlDialectGuidance: string;
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}
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// Template string as a function that requires parameters
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const createThinkAndPrepInstructions = (params: ThinkAndPrepTemplateParams): string => {
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export const getThinkAndPrepAgentSystemPrompt = (sqlDialectGuidance: string): string => {
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return `
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You are Buster, a specialized AI agent within an AI-powered data analyst system.
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@ -398,7 +386,7 @@ Once all TODO list items are addressed and submitted for review, the system will
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<sql_best_practices>
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- Current SQL Dialect Guidance:
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${params.sqlDialectGuidance}
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${sqlDialectGuidance}
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- Keep Queries Simple: Strive for simplicity and clarity in your SQL. Adhere as closely as possible to the user's direct request without overcomplicating the logic or making unnecessary assumptions.
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- Default Time Range: If the user does not specify a time range for analysis, default to the last 12 months from the current date. Clearly state this assumption if making it.
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- Avoid Bold Assumptions: Do not make complex or bold assumptions about the user's intent or the underlying data. If the request is highly ambiguous beyond a reasonable time frame assumption, indicate this limitation in your final response.
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@ -583,46 +571,6 @@ ${params.sqlDialectGuidance}
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Start by using the \`sequentialThinking\` to immediately start checking off items on your TODO list
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Today's date is ${new Date().toLocaleDateString()}.
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---
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<database_context>
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${params.databaseContext}
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</database_context>
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`;
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};
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export const getThinkAndPrepInstructions = async ({
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runtimeContext,
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}: { runtimeContext: RuntimeContext<AnalystRuntimeContext> }): Promise<string> => {
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const userId = runtimeContext.get('userId');
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const dataSourceSyntax = runtimeContext.get('dataSourceSyntax');
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const datasets = await getPermissionedDatasets(userId, 0, 1000);
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// Extract yml_content from each dataset and join with separators
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const assembledYmlContent = datasets
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.map((dataset: { ymlFile: string | null | undefined }) => dataset.ymlFile)
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.filter((content: string | null | undefined) => content !== null && content !== undefined)
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.join('\n---\n');
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// Get dialect-specific guidance
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const sqlDialectGuidance = getSqlDialectGuidance(dataSourceSyntax);
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return createThinkAndPrepInstructions({
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databaseContext: assembledYmlContent,
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sqlDialectGuidance,
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});
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};
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// Export the template function without dataset context for use in step files
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export const createThinkAndPrepInstructionsWithoutDatasets = (
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sqlDialectGuidance: string
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): string => {
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return createThinkAndPrepInstructions({
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databaseContext: '',
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sqlDialectGuidance,
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})
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.replace(/<database_context>[\s\S]*?<\/database_context>/, '')
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.trim();
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};
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@ -1,4 +1,6 @@
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import { Agent } from '@mastra/core';
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import { hasToolCall, type ModelMessage, stepCountIs, streamText } from "ai";
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import { wrapTraced } from "braintrust";
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import z from "zod";
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import {
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executeSql,
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messageUserClarifyingQuestion,
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@ -7,21 +9,53 @@ import {
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submitThoughts,
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} from '../../tools';
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import { Sonnet4 } from '../../utils/models/sonnet-4';
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import { getThinkAndPrepAgentSystemPrompt } from './get-think-and-prep-agent-system-prompt';
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const DEFAULT_OPTIONS = {
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maxSteps: 18,
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temperature: 0,
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maxTokens: 10000,
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providerOptions: {
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anthropic: {
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disableParallelToolCalls: true,
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},
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},
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const DEFAULT_CACHE_OPTIONS = {
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anthropic: { cacheControl: { type: "ephemeral", ttl: "1h" } },
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};
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export const thinkAndPrepAgent = new Agent({
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name: 'Think and Prep Agent',
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instructions: '', // We control the system messages in the step at stream instantiation
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const STOP_CONDITIONS = [
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stepCountIs(18),
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hasToolCall("submitThoughts"),
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hasToolCall("respondWithoutAssetCreation"),
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hasToolCall("messageUserClarifyingQuestion")
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];
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const ThinkAndPrepAgentOptionsSchema = z.object({
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sql_dialect_guidance: z
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.string()
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.describe("The SQL dialect guidance for the think and prep agent."),
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});
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const ThinkAndPrepStreamOptionsSchema = z.object({
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messages: z
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.array(z.custom<ModelMessage>())
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.describe("The messages to send to the think and prep agent."),
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});
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export type ThinkAndPrepAgentOptionsSchema = z.infer<
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typeof ThinkAndPrepAgentOptionsSchema
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>;
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export type ThinkAndPrepStreamOptions = z.infer<typeof ThinkAndPrepStreamOptionsSchema>;
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export function createThinkAndPrepAgent(
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thinkAndPrepAgentSchema: ThinkAndPrepAgentOptionsSchema,
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) {
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const steps: never[] = [];
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const systemMessage = {
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role: "system",
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content: getThinkAndPrepAgentSystemPrompt(
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thinkAndPrepAgentSchema.sql_dialect_guidance,
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),
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providerOptions: DEFAULT_CACHE_OPTIONS,
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} as ModelMessage;
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async function stream({ messages }: ThinkAndPrepStreamOptions) {
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return wrapTraced(
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() =>
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streamText({
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model: Sonnet4,
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tools: {
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sequentialThinking,
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@ -30,6 +64,24 @@ export const thinkAndPrepAgent = new Agent({
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submitThoughts,
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messageUserClarifyingQuestion,
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},
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defaultGenerateOptions: DEFAULT_OPTIONS,
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defaultStreamOptions: DEFAULT_OPTIONS,
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});
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messages: [systemMessage, ...messages],
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stopWhen: STOP_CONDITIONS,
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toolChoice: "required",
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maxOutputTokens: 10000,
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temperature: 0,
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}),
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{
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name: "Think and Prep Agent",
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},
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)();
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}
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async function getSteps() {
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return steps;
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}
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return {
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stream,
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getSteps,
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};
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}
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@ -6,8 +6,8 @@ import type { CoreMessage } from 'ai';
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import { wrapTraced } from 'braintrust';
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import { z } from 'zod';
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import { getSqlDialectGuidance } from '../agents/shared/sql-dialect-guidance';
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import { thinkAndPrepAgent } from '../agents/think-and-prep-agent/think-and-prep-agent';
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import { createThinkAndPrepInstructionsWithoutDatasets } from '../agents/think-and-prep-agent/think-and-prep-instructions';
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import { createThinkAndPrepAgent } from '../agents/think-and-prep-agent/think-and-prep-agent';
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import { getThinkAndPrepAgentSystemPrompt } from '../agents/think-and-prep-agent/get-think-and-prep-agent-system-prompt';
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import type { thinkAndPrepWorkflowInputSchema } from '../schemas/workflow-schemas';
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import { ChunkProcessor } from '../utils/database/chunk-processor';
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import {
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@ -248,33 +248,30 @@ ${databaseContext}
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),
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});
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// Create the agent instance
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const thinkAndPrepAgent = createThinkAndPrepAgent({
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sql_dialect_guidance: sqlDialectGuidance,
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});
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const wrappedStream = wrapTraced(
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async () => {
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// Create system messages with dataset context and instructions
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const systemMessages: CoreMessage[] = [
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{
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role: 'system',
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content: createThinkAndPrepInstructionsWithoutDatasets(sqlDialectGuidance),
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providerOptions: DEFAULT_CACHE_OPTIONS,
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},
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{
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// Create dataset system message
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const datasetSystemMessage: CoreMessage = {
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role: 'system',
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content: createDatasetSystemMessage(assembledYmlContent),
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providerOptions: DEFAULT_CACHE_OPTIONS,
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},
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];
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};
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// Combine system messages with conversation messages
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const messagesWithSystem = [...systemMessages, ...messages];
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// Combine dataset system message with conversation messages
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const messagesWithDataset = [datasetSystemMessage, ...messages];
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// Create stream directly without retryableAgentStreamWithHealing
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const stream = await thinkAndPrepAgent.stream(messagesWithSystem, {
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toolCallStreaming: true,
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runtimeContext,
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maxRetries: 5,
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abortSignal: abortController.signal,
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toolChoice: 'required',
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onChunk: createOnChunkHandler({
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// Create stream using the new agent pattern
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const stream = await thinkAndPrepAgent.stream({
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messages: messagesWithDataset,
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});
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// Handle streaming with chunk processor
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stream.onChunk = createOnChunkHandler({
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chunkProcessor,
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abortController,
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finishingToolNames: [
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@ -293,15 +290,6 @@ ${databaseContext}
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finished = true;
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}
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},
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}),
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onError: createRetryOnErrorHandler({
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retryCount,
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maxRetries,
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workflowContext: {
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currentStep: 'think-and-prep',
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availableTools,
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},
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}),
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});
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return stream;
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@ -1,279 +0,0 @@
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import type { CoreMessage } from 'ai';
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import { describe, expect, test } from 'vitest';
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import { validateArrayAccess } from '../validation-helpers';
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import { extractMessageHistory } from './message-history';
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describe('AI SDK Message Bundling Issues', () => {
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test('identify when AI SDK returns bundled messages', () => {
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// The AI SDK tends to bundle multiple tool calls in a single assistant message
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// when parallel tool calls are made, even with disableParallelToolCalls
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const aiSdkResponse: CoreMessage[] = [
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{
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role: 'user',
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content: 'Analyze our customer data',
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},
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{
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role: 'assistant',
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content: [
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{
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type: 'tool-call',
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toolCallId: 'call_ABC123',
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toolName: 'sequentialThinking',
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args: { thought: 'First, I need to understand the data structure' },
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},
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{
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type: 'tool-call',
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toolCallId: 'call_DEF456',
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toolName: 'executeSql',
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args: { statements: ['SELECT COUNT(*) FROM customers'] },
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},
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{
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type: 'tool-call',
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toolCallId: 'call_GHI789',
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toolName: 'submitThoughts',
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args: {},
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},
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],
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},
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'call_ABC123',
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toolName: 'sequentialThinking',
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result: { success: true },
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},
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],
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},
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'call_DEF456',
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toolName: 'executeSql',
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result: { results: [{ count: 100 }] },
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},
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],
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},
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'call_GHI789',
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toolName: 'submitThoughts',
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result: {},
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},
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],
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},
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];
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// Our extraction should fix this
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const fixed = extractMessageHistory(aiSdkResponse);
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// Should be properly interleaved now
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expect(fixed).toHaveLength(7); // user + 3*(assistant + tool)
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// Check the pattern
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const msg0 = validateArrayAccess(fixed, 0, 'fixed messages');
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const msg1 = validateArrayAccess(fixed, 1, 'fixed messages');
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const msg2 = validateArrayAccess(fixed, 2, 'fixed messages');
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const msg3 = validateArrayAccess(fixed, 3, 'fixed messages');
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const msg4 = validateArrayAccess(fixed, 4, 'fixed messages');
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const msg5 = validateArrayAccess(fixed, 5, 'fixed messages');
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const msg6 = validateArrayAccess(fixed, 6, 'fixed messages');
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expect(msg0.role).toBe('user');
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expect(msg1.role).toBe('assistant');
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if (msg1.role === 'assistant' && Array.isArray(msg1.content)) {
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const content = validateArrayAccess(msg1.content, 0, 'assistant content');
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if ('toolCallId' in content) {
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expect(content.toolCallId).toBe('call_ABC123');
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}
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}
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expect(msg2.role).toBe('tool');
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if (msg2.role === 'tool' && Array.isArray(msg2.content)) {
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const content = validateArrayAccess(msg2.content, 0, 'tool content');
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if ('toolCallId' in content) {
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expect(content.toolCallId).toBe('call_ABC123');
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}
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}
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expect(msg3.role).toBe('assistant');
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if (msg3.role === 'assistant' && Array.isArray(msg3.content)) {
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const content = validateArrayAccess(msg3.content, 0, 'assistant content');
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if ('toolCallId' in content) {
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expect(content.toolCallId).toBe('call_DEF456');
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}
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}
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expect(msg4.role).toBe('tool');
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if (msg4.role === 'tool' && Array.isArray(msg4.content)) {
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const content = validateArrayAccess(msg4.content, 0, 'tool content');
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if ('toolCallId' in content) {
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expect(content.toolCallId).toBe('call_DEF456');
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}
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}
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expect(msg5.role).toBe('assistant');
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if (msg5.role === 'assistant' && Array.isArray(msg5.content)) {
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const content = validateArrayAccess(msg5.content, 0, 'assistant content');
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if ('toolCallId' in content) {
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expect(content.toolCallId).toBe('call_GHI789');
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}
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}
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expect(msg6.role).toBe('tool');
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if (msg6.role === 'tool' && Array.isArray(msg6.content)) {
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const content = validateArrayAccess(msg6.content, 0, 'tool content');
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if ('toolCallId' in content) {
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expect(content.toolCallId).toBe('call_GHI789');
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}
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}
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});
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test('handle case where AI SDK partially bundles messages', () => {
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// Sometimes the AI SDK might bundle some calls but not others
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const partiallyBundled: CoreMessage[] = [
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{
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role: 'user',
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content: 'Test',
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},
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{
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role: 'assistant',
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content: [
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{
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type: 'tool-call',
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toolCallId: 'id1',
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toolName: 'tool1',
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args: {},
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},
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],
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},
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'id1',
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toolName: 'tool1',
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result: {},
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},
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],
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},
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{
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role: 'assistant',
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content: [
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{
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type: 'tool-call',
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toolCallId: 'id2',
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toolName: 'tool2',
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args: {},
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},
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{
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type: 'tool-call',
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toolCallId: 'id3',
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toolName: 'tool3',
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args: {},
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},
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],
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},
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{
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role: 'tool',
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content: [
|
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{
|
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type: 'tool-result',
|
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toolCallId: 'id2',
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toolName: 'tool2',
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result: {},
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},
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],
|
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},
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{
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role: 'tool',
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content: [
|
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{
|
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type: 'tool-result',
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toolCallId: 'id3',
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toolName: 'tool3',
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result: {},
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},
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],
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},
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];
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||||
const fixed = extractMessageHistory(partiallyBundled);
|
||||
|
||||
// Should fix only the bundled part
|
||||
expect(fixed).toHaveLength(7);
|
||||
|
||||
// First part should remain unchanged
|
||||
const fixedMsg0 = validateArrayAccess(fixed, 0, 'fixed messages');
|
||||
const fixedMsg1 = validateArrayAccess(fixed, 1, 'fixed messages');
|
||||
const fixedMsg2 = validateArrayAccess(fixed, 2, 'fixed messages');
|
||||
const fixedMsg3 = validateArrayAccess(fixed, 3, 'fixed messages');
|
||||
const fixedMsg4 = validateArrayAccess(fixed, 4, 'fixed messages');
|
||||
const fixedMsg5 = validateArrayAccess(fixed, 5, 'fixed messages');
|
||||
const fixedMsg6 = validateArrayAccess(fixed, 6, 'fixed messages');
|
||||
|
||||
const partialMsg0 = validateArrayAccess(partiallyBundled, 0, 'partially bundled messages');
|
||||
const partialMsg1 = validateArrayAccess(partiallyBundled, 1, 'partially bundled messages');
|
||||
const partialMsg2 = validateArrayAccess(partiallyBundled, 2, 'partially bundled messages');
|
||||
|
||||
expect(fixedMsg0).toEqual(partialMsg0);
|
||||
expect(fixedMsg1).toEqual(partialMsg1);
|
||||
expect(fixedMsg2).toEqual(partialMsg2);
|
||||
|
||||
// Second part should be unbundled
|
||||
if (fixedMsg3.role === 'assistant' && Array.isArray(fixedMsg3.content)) {
|
||||
const content = validateArrayAccess(fixedMsg3.content, 0, 'assistant content');
|
||||
if ('toolCallId' in content) {
|
||||
expect(content.toolCallId).toBe('id2');
|
||||
}
|
||||
}
|
||||
if (fixedMsg4.role === 'tool' && Array.isArray(fixedMsg4.content)) {
|
||||
const content = validateArrayAccess(fixedMsg4.content, 0, 'tool content');
|
||||
if ('toolCallId' in content) {
|
||||
expect(content.toolCallId).toBe('id2');
|
||||
}
|
||||
}
|
||||
if (fixedMsg5.role === 'assistant' && Array.isArray(fixedMsg5.content)) {
|
||||
const content = validateArrayAccess(fixedMsg5.content, 0, 'assistant content');
|
||||
if ('toolCallId' in content) {
|
||||
expect(content.toolCallId).toBe('id3');
|
||||
}
|
||||
}
|
||||
if (fixedMsg6.role === 'tool' && Array.isArray(fixedMsg6.content)) {
|
||||
const content = validateArrayAccess(fixedMsg6.content, 0, 'tool content');
|
||||
if ('toolCallId' in content) {
|
||||
expect(content.toolCallId).toBe('id3');
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
test('verify already correct messages pass through unchanged', () => {
|
||||
const correctlyFormatted: CoreMessage[] = [
|
||||
{ role: 'user', content: 'Test' },
|
||||
{
|
||||
role: 'assistant',
|
||||
content: [{ type: 'tool-call', toolCallId: 'id1', toolName: 'tool1', args: {} }],
|
||||
},
|
||||
{
|
||||
role: 'tool',
|
||||
content: [{ type: 'tool-result', toolCallId: 'id1', toolName: 'tool1', result: {} }],
|
||||
},
|
||||
{
|
||||
role: 'assistant',
|
||||
content: [{ type: 'tool-call', toolCallId: 'id2', toolName: 'tool2', args: {} }],
|
||||
},
|
||||
{
|
||||
role: 'tool',
|
||||
content: [{ type: 'tool-result', toolCallId: 'id2', toolName: 'tool2', result: {} }],
|
||||
},
|
||||
];
|
||||
|
||||
const result = extractMessageHistory(correctlyFormatted);
|
||||
|
||||
// Should be unchanged
|
||||
expect(result).toEqual(correctlyFormatted);
|
||||
expect(result).toHaveLength(5);
|
||||
});
|
||||
});
|
||||
Loading…
Reference in New Issue