V4 APIs (Python)

import thinkhive
 
client = thinkhive.ThinkHive(
    api_key='thk_your_api_key',
    endpoint='https://app.thinkhive.ai'  # optional
)

from thinkhive import TraceData, SpanData
 
# Submit a trace
result = client.trace(TraceData(
    agent_id='agent_abc123',
    spans=[
        SpanData(
            name='customer-chat',
            type='llm',
            input='How do I reset my password?',
            output='To reset your password...',
            model='gpt-4',
            tokens={'input': 25, 'output': 150}
        )
    ],
    outcome='success'
))
 
print(result.trace_id)  # 'tr_xyz789'
 
# Retrieve a trace
trace = client.get_trace('tr_xyz789')

# Analyze traces
analysis = client.explainer.analyze(
    traces=[{
        'userMessage': 'How do I reset my password?',
        'agentResponse': 'To reset your password...',
        'retrievedDocuments': [{'content': '...', 'score': 0.92}]
    }],
    options={
        'tier': 'full_llm',
        'includeRagEvaluation': True,
        'includeHallucinationDetection': True
    }
)
 
print(analysis.overall_score)
print(analysis.rag_evaluation.groundedness)

# Get RAG quality scores for a trace
rag_scores = client.quality.get_rag_scores('tr_xyz789')
print(rag_scores.groundedness)
print(rag_scores.faithfulness)
 
# Detect hallucinations
hallucination_report = client.quality.detect_hallucinations({
    'input': user_message,
    'output': agent_response,
    'context': retrieved_context
})
 
if hallucination_report.detected:
    for h in hallucination_report.hallucinations:
        print(f'{h.type}: {h.description} (confidence: {h.confidence})')

# Get ROI summary
roi = client.analytics.get_roi_summary()
print(f'Total ROI: {roi.total_roi}')
print(f'Cost savings: {roi.cost_savings}')
 
# Per-agent ROI
agent_roi = client.analytics.get_roi_by_agent('agent_abc123')

from thinkhive import Feedback
 
# Submit feedback on a trace
client.feedback(Feedback(
    trace_id='tr_xyz789',
    rating=5,
    comment='Accurate response'
))

# Automatically trace LLM calls from supported frameworks
thinkhive.auto_instrument(
    frameworks=['openai', 'langchain', 'llamaindex', 'anthropic']
)
 
# Now all OpenAI/LangChain/etc. calls are automatically traced
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(...)  # Automatically traced