Metadata-Version: 2.4
Name: aieng-eval-agents
Version: 0.3.1
Summary: Agentic AI Evaluation reference implementation from Vector Institute AI Engineering
Author-email: Vector AI Engineering <ai_engineering@vectorinstitute.ai>
License-Expression: MIT
Requires-Python: <4.0,>=3.12
Requires-Dist: google-adk>=1.23.0
Requires-Dist: google-genai>=1.52.0
Requires-Dist: gradio>=6.7.0
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Requires-Dist: httpx>=0.27.0
Requires-Dist: kagglehub>=0.4.1
Requires-Dist: langfuse>=3.10.3
Requires-Dist: openai-agents>=0.6.1
Requires-Dist: openai>=2.8.1
Requires-Dist: openinference-instrumentation-google-adk>=0.1.0
Requires-Dist: opentelemetry-exporter-otlp-proto-http>=1.20.0
Requires-Dist: opentelemetry-sdk>=1.20.0
Requires-Dist: pandas>=2.3.0
Requires-Dist: pydantic-settings>=2.12.0
Requires-Dist: pydantic>=2.12.0
Requires-Dist: pypdf>=6.7.5
Requires-Dist: python-dotenv>=1.0.0
Requires-Dist: rich>=13.9.0
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Requires-Dist: weaviate-client>=4.18.3
Description-Content-Type: text/markdown

# aieng-eval-agents

[![PyPI](https://img.shields.io/pypi/v/aieng-eval-agents)](https://pypi.org/project/aieng-eval-agents/)
[![Python](https://img.shields.io/badge/python-3.12%2B-blue)](https://pypi.org/project/aieng-eval-agents/)
[![License](https://img.shields.io/github/license/VectorInstitute/eval-agents)](https://github.com/VectorInstitute/eval-agents/blob/main/LICENSE)

Shared library for Vector Institute's Agentic AI Evaluation Bootcamp. Provides reusable components for building, running, and evaluating LLM agents with [Google ADK](https://google.github.io/adk-docs/) and [Langfuse](https://langfuse.com/).

## What's included

### Agent implementations

| 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. |

### Reusable tools (`aieng.agent_evals.tools`)

- `search` — Google Search with response grounding and citations
- `web` — HTML and PDF content fetching
- `file` — Download and search data files (CSV, XLSX, JSON)
- `sql_database` — Read-only SQL database access via `ReadOnlySqlDatabase`

### Evaluation harness (`aieng.agent_evals.evaluation`)

Wrappers around Langfuse for running agent experiments:

- `run_experiment` — Run a dataset through an agent and score outputs
- `run_experiment_with_trace_evals` — Run experiments with trace-level evaluation
- `run_trace_evaluations` — Score existing Langfuse traces with LLM-based or heuristic graders

### Utilities

- `display` — Rich-based terminal and Jupyter display helpers for metrics and agent responses
- `progress` — Progress tracking for batch evaluation runs
- `configs` — Pydantic-based configuration loading from `.env`
- `langfuse` — Langfuse client and trace utilities
- `db_manager` — Database connection management

## Installation

```bash
pip install aieng-eval-agents
```

Requires Python 3.12+.

## Source

Full reference implementations and documentation are in the [eval-agents](https://github.com/VectorInstitute/eval-agents) repository.
