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# Self-Reflection Evaluation Sample
This sample demonstrates the self-reflection pattern using Agent Framework and Azure AI Foundry's Groundedness Evaluator. For details, see [Reflexion: Language Agents with Verbal Reinforcement Learning](https://arxiv.org/abs/2303.11366) (NeurIPS 2023).
## Overview
**What it demonstrates:**
- Iterative self-reflection loop that automatically improves responses based on groundedness evaluation
- Batch processing of prompts from JSONL files with progress tracking
- Using `AzureOpenAIChatClient` with Azure CLI authentication
- Comprehensive summary statistics and detailed result tracking
## Prerequisites
### Azure Resources
- **Azure OpenAI**: Deploy models (default: gpt-4.1 for both agent and judge)
- **Azure CLI**: Run `az login` to authenticate
### Python Environment
```bash
pip install agent-framework-core azure-ai-projects pandas --pre
```
### Environment Variables
```bash
# .env file
AZURE_AI_PROJECT_ENDPOINT=https://<your-ai-resource>.services.ai.azure.com/api/projects/<your-ai-project>/
```
## Running the Sample
```bash
# Basic usage
python self_reflection.py
# With options
python self_reflection.py --input my_prompts.jsonl \
--output results.jsonl \
--max-reflections 5 \
-n 10
```
**CLI Options:**
- `--input`, `-i`: Input JSONL file
- `--output`, `-o`: Output JSONL file
- `--agent-model`, `-m`: Agent model name (default: gpt-4.1)
- `--judge-model`, `-e`: Evaluator model name (default: gpt-4.1)
- `--max-reflections`: Max iterations (default: 3)
- `--limit`, `-n`: Process only first N prompts
## Understanding Results
The agent iteratively improves responses:
1. Generate initial response
2. Evaluate groundedness (1-5 scale)
3. If score < 5, provide feedback and retry
4. Stop at max iterations or perfect score (5/5)
**Example output:**
```
[1/31] Processing prompt 0...
Self-reflection iteration 1/3...
Groundedness score: 3/5
Self-reflection iteration 2/3...
Groundedness score: 5/5
✓ Perfect groundedness score achieved!
✓ Completed with score: 5/5 (best at iteration 2/3)
```
## Related Resources
- [Reflexion Paper](https://arxiv.org/abs/2303.11366)
- [Azure AI Evaluation SDK](https://learn.microsoft.com/azure/ai-studio/how-to/develop/evaluate-sdk)
- [Agent Framework](https://github.com/microsoft/agent-framework)