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Observed since 21 Oct, 10:38 UTC
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Agentic AI Evaluation reference implementation from Vector Institute AI Engineering
Shared library for Vector Institute's Agentic AI Evaluation Bootcamp. Provides reusable components for building, running, and evaluating LLM agents with Google ADK and Langfuse.
| Module | Description |
|---|---|
aieng.agent_evals.knowledge_qa | ReAct agent that answers questions using live web search. Includes evaluation against the DeepSearchQA benchmark with LLM-as-a-judge metrics (precision/recall/F1). |
aieng.agent_evals.aml_investigation | Agent that investigates Anti-Money Laundering cases by querying a SQLite database of financial transactions via a read-only SQL tool. |
aieng.agent_evals.report_generation | Agent that generates structured Excel reports from a relational database based on natural language queries. |
aieng.agent_evals.tools)search — Google Search with response grounding and citationsweb — HTML and PDF content fetchingfile — Download and search data files (CSV, XLSX, JSON)sql_database — Read-only SQL database access via ReadOnlySqlDatabaseaieng.agent_evals.evaluation)Wrappers around Langfuse for running agent experiments:
run_experiment — Run a dataset through an agent and score outputsrun_experiment_with_trace_evals — Run experiments with trace-level evaluationrun_trace_evaluations — Score existing Langfuse traces with LLM-based or heuristic gradersdisplay — Rich-based terminal and Jupyter display helpers for metrics and agent responsesprogress — Progress tracking for batch evaluation runsconfigs — Pydantic-based configuration loading from .envlangfuse — Langfuse client and trace utilitiesdb_manager — Database connection managementpip install aieng-eval-agents
Requires Python 3.12+.
Full reference implementations and documentation are in the eval-agents repository.
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.3.1 | 17 Apr 2026 | 22 |
This describes our collected data; it is not a security assessment.
Observed since 21 Oct, 10:38 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:cb298f96b8e283afafc1f186030a5a582ea103486bb8390f837ae552c4749a81