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Public evaluation

TrendIdentification

Evaluate the LlamaIndex agent system's accuracy in identifying key AI trends, precision in sentiment analysis (including emotional cues from Hume AI), and the coherence of generated strategic insights.

Evaluation type
task based
Challenge
Developer Sentiment & AI Trend Analysis Agent
Difficulty
Advanced
Rigor
Unspecified

Evaluation overview

How the linked challenge is judged: tasks, benchmarks, and criteria count.

Tasks
1
Benchmarks
0
Criteria
0

Task templates

Inputs and expected outputs.

Task 1

TrendIdentification

Assess the agent system's ability to identify emerging AI trends and associated developer sentiment from a corpus of tech news, forums, and simulated voice feedback.

Input format

JSON object with 'articles' (array of {title, content, source}), 'forum_posts' (array of {author, text, timestamp}), and 'voice_feedback_transcripts' (array of {speaker, transcript, audio_url_mock}).

Output format

JSON object with 'identified_trends' (array of {name, keywords, sentiment_score, confidence, supporting_evidence}), and 'overall_developer_sentiment' (string, e.g., 'positive', 'neutral', 'negative').