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Interactive CLI for searching and querying documents indexed in a RAG system using Azure AI Search and Azure OpenAI. Supports hybrid search, source tracking, response generation, and UTF-8 compatibility on Windows.
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| name | rag-query-cli |
| description | Interactive CLI for searching and querying documents indexed in a RAG system using Azure AI Search and Azure OpenAI. Supports hybrid search, source tracking, response generation, and UTF-8 compatibility on Windows. |
Query your RAG system interactively from the command line.
Interactive CLI for searching and querying documents indexed in your RAG system using Azure AI Search + Azure OpenAI.
.env file with credentials:
AZURE_OPENAI_KEYAZURE_OPENAI_ENDPOINTAZURE_SEARCH_ENDPOINTAZURE_SEARCH_KEYAZURE_SEARCH_INDEXAZURE_OPENAI_MODEL# Dependencies in ../.../requirements.txt
pip install -r .github/requirements.txt
# From the project root
python .github/skills/rag-query-cli/query.py "Your question here"
# Example
python .github/skills/rag-query-cli/query.py "What is the user onboarding process?"
from query import RAGExecutor
executor = RAGExecutor()
result = executor.execute("your question", verbose=True)
print(result['response'])
print("Sources:", result['sources'])
print("Metrics:", result['metrics'])
[QUERY] What is the user onboarding process?
[SEARCHING] Searching documents...
[OK] Found 5 relevant documents
[GENERATING] Generating response...
[OK] Response generated
[RESPONSE]
Based on documentation, the user onboarding process involves...
[SOURCES]
- knowledge/pdfs/Onboarding_Manual.pdf
- knowledge/procedures/User_Setup.docx
[METRICS]
Search: 234ms
Inference: 1523ms
Total: 1757ms
Tokens: 412
# Retrieve more context (default is 5)
python .github/skills/rag-query-cli/query.py "question" --top 10
# Only answer output
python .github/skills/rag-query-cli/query.py "question" --quiet