open-multi-agent/examples/integrations/with-engram/research-team.ts

226 lines
8.0 KiB
TypeScript

/**
* Engram Research Team
*
* Three agents collaborate on a research topic using Engram shared memory:
*
* 1. **Researcher** — explores the topic and commits findings as facts
* 2. **Fact-checker** — verifies claims, commits corrections, and audits
* any auto-resolved conflicts
* 3. **Writer** — queries settled facts and produces a briefing document
*
* Works with every provider the framework supports. Set the provider and model
* via environment variables:
*
* AGENT_PROVIDER — anthropic | openai | gemini | grok | copilot | deepseek | minimax | azure-openai
* AGENT_MODEL — model name for the chosen provider
*
* Defaults to anthropic / claude-sonnet-4-6 when unset.
*
* Run:
* npx tsx examples/integrations/with-engram/research-team.ts
*
* Examples:
* # Anthropic (default)
* ANTHROPIC_API_KEY=sk-... ENGRAM_INVITE_KEY=ek_live_... npx tsx examples/integrations/with-engram/research-team.ts
*
* # OpenAI
* AGENT_PROVIDER=openai AGENT_MODEL=gpt-4o OPENAI_API_KEY=sk-... ENGRAM_INVITE_KEY=ek_live_... npx tsx examples/integrations/with-engram/research-team.ts
*
* # Gemini
* AGENT_PROVIDER=gemini AGENT_MODEL=gemini-2.5-flash GEMINI_API_KEY=... ENGRAM_INVITE_KEY=ek_live_... npx tsx examples/integrations/with-engram/research-team.ts
*
* # Grok
* AGENT_PROVIDER=grok AGENT_MODEL=grok-3 XAI_API_KEY=... ENGRAM_INVITE_KEY=ek_live_... npx tsx examples/integrations/with-engram/research-team.ts
*
* # DeepSeek
* AGENT_PROVIDER=deepseek AGENT_MODEL=deepseek-chat DEEPSEEK_API_KEY=... ENGRAM_INVITE_KEY=ek_live_... npx tsx examples/integrations/with-engram/research-team.ts
*
* Prerequisites:
* - API key env var for your chosen provider
* - Engram server running at http://localhost:7474
* - ENGRAM_INVITE_KEY env var
*/
import {
Agent,
ToolExecutor,
ToolRegistry,
registerBuiltInTools,
} from '../../../src/index.js'
import type { SupportedProvider } from '../../../src/index.js'
import { EngramToolkit } from './engram-toolkit.js'
// ---------------------------------------------------------------------------
// Provider / model configuration
// ---------------------------------------------------------------------------
const PROVIDER = (process.env.AGENT_PROVIDER ?? 'anthropic') as SupportedProvider
const MODEL = process.env.AGENT_MODEL ?? 'claude-sonnet-4-6'
const PROVIDER_ENV_KEYS: Record<string, string> = {
anthropic: 'ANTHROPIC_API_KEY',
openai: 'OPENAI_API_KEY',
gemini: 'GEMINI_API_KEY',
grok: 'XAI_API_KEY',
copilot: 'GITHUB_TOKEN',
deepseek: 'DEEPSEEK_API_KEY',
minimax: 'MINIMAX_API_KEY',
'azure-openai': 'AZURE_OPENAI_API_KEY',
}
const envKey = PROVIDER_ENV_KEYS[PROVIDER]
if (envKey && !process.env[envKey]?.trim()) {
console.error(`Missing ${envKey}: required for provider "${PROVIDER}".`)
process.exit(1)
}
if (!process.env.ENGRAM_INVITE_KEY?.trim()) {
console.error('Missing ENGRAM_INVITE_KEY: set your Engram workspace invite key in the environment.')
process.exit(1)
}
// ---------------------------------------------------------------------------
// Shared setup
// ---------------------------------------------------------------------------
const TOPIC = 'the current state of AI agent memory systems'
const engramTools = ['engram_commit', 'engram_query', 'engram_conflicts', 'engram_resolve']
function buildAgent(config: {
name: string
systemPrompt: string
}): Agent {
const registry = new ToolRegistry()
registerBuiltInTools(registry)
new EngramToolkit().registerAll(registry)
const executor = new ToolExecutor(registry)
return new Agent(
{
name: config.name,
model: MODEL,
provider: PROVIDER,
tools: engramTools,
systemPrompt: config.systemPrompt,
},
registry,
executor,
)
}
// ---------------------------------------------------------------------------
// Agents
// ---------------------------------------------------------------------------
const researcher = buildAgent({
name: 'researcher',
systemPrompt: `You are a research agent investigating: "${TOPIC}".
Your job:
1. Think through the key dimensions of this topic (architectures, open problems,
leading projects, recent breakthroughs).
2. For each finding, use engram_commit to record it as a shared fact with
scope="research" and an appropriate confidence level.
3. Commit at least 5 distinct facts covering different aspects.
Be specific and cite concrete systems or papers where possible.`,
})
const factChecker = buildAgent({
name: 'fact-checker',
systemPrompt: `You are a fact-checking agent. Your job:
1. Use engram_query with topic="${TOPIC}" to retrieve what the researcher committed.
2. Evaluate each fact for accuracy and completeness.
3. If a fact is wrong or misleading, use engram_commit with operation="update"
to commit a corrected version in the same scope.
4. After committing corrections, call engram_conflicts to review any
auto-resolved conflicts. You are auditing the resolutions — do NOT manually
resolve them unless an auto-resolution is clearly wrong.
5. Summarize your findings at the end.`,
})
const writer = buildAgent({
name: 'writer',
systemPrompt: `You are a technical writer. Your job:
1. Use engram_query with topic="${TOPIC}" to retrieve all settled facts.
2. Synthesize the facts into a concise executive briefing (300-500 words).
3. Structure the briefing with clear sections: Overview, Key Systems,
Open Challenges, and Outlook.
4. Only include claims that are grounded in the queried facts — do not
fabricate or speculate beyond what the team has verified.
5. Output the briefing as your final response.`,
})
// ---------------------------------------------------------------------------
// Sequential execution
// ---------------------------------------------------------------------------
console.log('Engram Research Team')
console.log('='.repeat(60))
console.log(`Provider: ${PROVIDER}`)
console.log(`Model: ${MODEL}`)
console.log(`Topic: ${TOPIC}\n`)
// Step 1: Research
console.log('[1/3] Researcher is exploring the topic...')
const researchResult = await researcher.run(
`Research "${TOPIC}" and commit your findings to Engram shared memory.`,
)
console.log(` Done — ${researchResult.toolCalls.length} tool calls, ` +
`${researchResult.tokenUsage.output_tokens} output tokens\n`)
// Step 2: Fact-check
console.log('[2/3] Fact-checker is verifying claims...')
const checkResult = await factChecker.run(
`Review and fact-check the research on "${TOPIC}" in Engram shared memory. ` +
`Commit corrections and audit any auto-resolved conflicts.`,
)
console.log(` Done — ${checkResult.toolCalls.length} tool calls, ` +
`${checkResult.tokenUsage.output_tokens} output tokens\n`)
// Step 3: Write briefing
console.log('[3/3] Writer is producing the briefing...')
const writeResult = await writer.run(
`Query Engram for settled facts on "${TOPIC}" and write an executive briefing.`,
)
console.log(` Done — ${writeResult.toolCalls.length} tool calls, ` +
`${writeResult.tokenUsage.output_tokens} output tokens\n`)
// ---------------------------------------------------------------------------
// Output
// ---------------------------------------------------------------------------
console.log('='.repeat(60))
console.log('EXECUTIVE BRIEFING')
console.log('='.repeat(60))
console.log()
console.log(writeResult.output)
console.log()
console.log('-'.repeat(60))
// Token summary
const agents = [
{ name: 'researcher', result: researchResult },
{ name: 'fact-checker', result: checkResult },
{ name: 'writer', result: writeResult },
]
let totalInput = 0
let totalOutput = 0
console.log('\nToken Usage:')
for (const { name, result } of agents) {
totalInput += result.tokenUsage.input_tokens
totalOutput += result.tokenUsage.output_tokens
console.log(
` ${name.padEnd(14)} — input: ${result.tokenUsage.input_tokens}, output: ${result.tokenUsage.output_tokens}`,
)
}
console.log('-'.repeat(60))
console.log(` ${'TOTAL'.padEnd(14)} — input: ${totalInput}, output: ${totalOutput}`)
console.log(`\nView shared memory and conflicts: http://localhost:7474/dashboard`)