import { init, runs, traceLLM, shutdown } from '@thinkhive/sdk';

// Initialize the SDK
init({
  apiKey: 'thk_your_api_key',
  serviceName: 'my-ai-agent',
  autoInstrument: true,
  frameworks: ['langchain', 'openai'],
});

// Create a run (atomic unit of work)
const run = await runs.create({
  agentId: 'weather-agent',
  conversationMessages: [
    { role: 'user', content: 'What is the weather in San Francisco?' },
    { role: 'assistant', content: 'The weather in San Francisco is currently 65°F and sunny.' }
  ],
  outcome: 'success',
});

console.log(`Run ID: ${run.id}`);

// Shutdown when done
await shutdown();

import { init, traceLLM, traceRetrieval, traceTool, traceChain } from '@thinkhive/sdk';

init({ apiKey: 'thk_your_api_key', serviceName: 'my-agent' });

// Trace an LLM call
const response = await traceLLM({
  name: 'generate-response',
  modelName: 'gpt-4',
  provider: 'openai',
  input: { prompt: 'Hello!' }
}, async () => {
  // Your LLM call here
  return await openai.chat.completions.create({...});
});

// Trace a retrieval operation
const docs = await traceRetrieval({
  name: 'search-knowledge-base',
  query: 'refund policy',
  topK: 5
}, async () => {
  return await vectorStore.similaritySearch(query, 5);
});

// Trace a tool call
const result = await traceTool({
  name: 'lookup-order',
  toolName: 'order_lookup',
  parameters: { orderId: '12345' }
}, async () => {
  return await lookupOrder('12345');
});

import { analyzer } from '@thinkhive/sdk';

// Estimate cost before running analysis
const estimate = await analyzer.estimateCost({
  traceIds: ['trace-1', 'trace-2', 'trace-3'],
  tier: 'standard',
});
console.log(`Estimated cost: $${estimate.estimatedCost}`);

// Analyze specific traces
const analysis = await analyzer.analyze({
  traceIds: ['trace-1', 'trace-2'],
  tier: 'standard',
  includeRootCause: true,
  includeLayers: true,
});

// Analyze traces by time window with smart sampling
const windowAnalysis = await analyzer.analyzeWindow({
  agentId: 'support-agent',
  startDate: new Date('2024-01-01'),
  endDate: new Date('2024-01-31'),
  filters: { outcomes: ['failure'], minSeverity: 'medium' },
  sampling: { strategy: 'smart', samplePercent: 10 },
});

// Get aggregated insights
const summary = await analyzer.summarize({
  agentId: 'support-agent',
  startDate: new Date('2024-01-01'),
  endDate: new Date('2024-01-31'),
});

import { issues } from '@thinkhive/sdk';

// List issues for an agent
const issueList = await issues.list('support-agent', {
  status: 'open',
  limit: 10,
});

// Get a specific issue
const issue = await issues.get('issue-123');

// Get fixes for an issue
const fixes = await issues.getFixes('issue-123');

import { apiKeys, hasPermission, canAccessAgent } from '@thinkhive/sdk';

// Create a scoped API key
const result = await apiKeys.create({
  name: 'CI Pipeline Key',
  permissions: {
    read: true,
    write: true,
    delete: false
  },
  scopeType: 'agent', // Restrict to specific agents
  allowedAgentIds: ['agent-prod-001'],
  environment: 'production',
  expiresAt: new Date(Date.now() + 90 * 24 * 60 * 60 * 1000) // 90 days
});

console.log(`Key created: ${result.name} (${result.keyPrefix}...)`);

// Check permissions
if (hasPermission(key, 'write')) {
  // Can write data
}

// Check agent access
if (canAccessAgent(key, 'agent-123')) {
  // Can access this agent
}

import { claims, isFact, isInference, getHighConfidenceClaims } from '@thinkhive/sdk';

// List claims for a run
const claimList = await claims.list(runId);

// Filter by type
const facts = claimList.filter(isFact);
const inferences = claimList.filter(isInference);

// Get high confidence claims
const confident = getHighConfidenceClaims(claimList, 0.9);

import { calibration, calculateBrierScore, isWellCalibrated } from '@thinkhive/sdk';

// Get calibration status for a prediction type
const status = await calibration.status(agentId, 'churn_risk');

// Get all calibration metrics
const metrics = await calibration.allMetrics(agentId);

// Calculate Brier score for predictions
const brierScore = calculateBrierScore(predictions);

// Check if well calibrated
if (isWellCalibrated(brierScore)) {
  console.log('Agent predictions are well calibrated');
}

import {
  businessMetrics,
  isMetricReady,
  needsMoreTraces,
  getStatusMessage
} from '@thinkhive/sdk';

// Get current metric value with status
const metric = await businessMetrics.current('agent-123', 'Deflection Rate');
console.log(`${metric.metricName}: ${metric.valueFormatted}`);

if (metric.status === 'insufficient_data') {
  console.log(`Need ${metric.minTraceThreshold - metric.traceCount} more traces`);
}

// Get historical data for graphing
const history = await businessMetrics.history('agent-123', 'Deflection Rate', {
  startDate: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000),
  endDate: new Date(),
  granularity: 'daily',
});

console.log(`${history.dataPoints.length} data points`);
console.log(`Change: ${history.summary.changePercent}%`);

// Record external metric values (from CRM, surveys, etc.)
await businessMetrics.record('agent-123', {
  metricName: 'CSAT/NPS',
  value: 4.5,
  unit: 'score',
  periodStart: '2024-01-01T00:00:00Z',
  periodEnd: '2024-01-07T23:59:59Z',
  source: 'survey_system',
  sourceDetails: { surveyId: 'survey_456', responseCount: 150 },
});

import {
  linking,
  generateZendeskMarker,
  linkRunToZendeskTicket
} from '@thinkhive/sdk';

// Generate a marker to embed in ticket
const marker = generateZendeskMarker(runId);
// Returns: <!-- thinkhive:run:abc123 -->

// Link a run to a ticket
await linkRunToZendeskTicket(runId, ticketId);

// Get best linking method
import { getBestLinkMethod } from '@thinkhive/sdk';
const method = getBestLinkMethod(runData);
// Returns: 'conversation_id' | 'subject_hash' | 'marker' | etc.

import { init } from '@thinkhive/sdk';

// Initialize with auto-instrumentation
init({
  apiKey: 'thk_your_api_key',
  serviceName: 'my-ai-agent',
  autoInstrument: true,
  frameworks: ['langchain', 'openai', 'anthropic']
});

// Now all LangChain, OpenAI, and Anthropic calls are automatically traced!