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Interactive conversational RAG query engine for Q&A over documents
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基于 SOC 职业分类
| name | rag-qa-engine |
| description | Interactive conversational RAG query engine for Q&A over documents |
| applyTo | **/*.agent.md |
RAG Reference: Retrieval-augmented Generation (RAG) in Azure AI Search - Microsoft Learn
Status: Production Version: 1.0 Last Updated: May 13, 2026
Provides an interactive conversational interface for querying documents via RAG. Users ask questions in natural language and receive answers from their indexed knowledge base with source attribution.
This skill:
from pathlib import Path
import sys
sys.path.insert(0, str(Path(__file__).parent / ".github" / "skills" / "rag-qa-engine"))
from chat_engine import RAGChatEngine
engine = RAGChatEngine(
azure_openai_endpoint="https://myapp-openai.openai.azure.com/",
azure_search_endpoint="https://myapp-search.search.windows.net/"
)
engine.connect()
response = engine.query("What is the procedure for X?")
print(response["answer"])
print(response["sources"])
exit_code = engine.run_interactive()
python .github/skills/rag-qa-engine/chat_engine.py
python run-rag.py --agent chat
| Parámetro | Tipo | Descripción | Ejemplo |
|---|---|---|---|
azure_openai_endpoint | str | Endpoint del servicio OpenAI | https://app-openai.openai.azure.com/ |
azure_search_endpoint | str | Endpoint de AI Search | https://app-search.search.windows.net/ |
| Parámetro | Tipo | Descripción |
|---|---|---|
question | str | Pregunta en lenguaje natural |
{
"answer": "str - Respuesta generada por RAG",
"sources": [
{
"title": "str - Nombre del documento",
"confidence": "float - 0.0-1.0"
}
],
"tokens_used": "int - Tokens OpenAI consumidos"
}
Loop de Q&A en tiempo real con:
You: [pregunta]quit, exit, salirInput del Usuario
↓
[Análisis de Pregunta]
↓
[Búsqueda Semántica] → Encontrar docs relevantes en Azure Search
↓
[Preparación de Contexto] → Formatear top-K docs como contexto
↓
[Llamada gpt-4o] → Generar respuesta con contexto
↓
[Atribución de Fuentes] → Devolver fuentes + confianza
↓
Mostrar al Usuario
Azure OpenAI Service
.envAzure AI Search
AZURE_OPENAI_ENDPOINT=https://[resource]-openai.openai.azure.com/
AZURE_OPENAI_API_KEY=<key>
AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o
AZURE_SEARCH_ENDPOINT=https://[resource]-search.search.windows.net/
AZURE_SEARCH_API_KEY=<key>
| Comando | Efecto |
|---|---|
quit | Finalizar sesión |
exit | Finalizar sesión |
salir | Finalizar sesión |
Ctrl+C | Interrumpir |
| línea vacía | Saltar, continuar prompt |
You: What are the procedures for X?
RAG: Based on your documentation, the procedures for X include...
Sources:
• procedures.docx (confidence: 0.95)
• manual_chapter_3.pdf (confidence: 0.87)
Tokens used: 342
You: [pregunta]
Error: Failed to connect to Azure Search
[Continúa solicitando]
Registrado en:
outputs/rag-chat.log (si logging de archivo habilitado)Reemplazar el mock engine con llamadas reales a Azure OpenAI y Azure Search usando las credenciales del .env.
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