AI & MACHINE LEARNING PROGRAM • LEVEL 22 — GENERATIVE AI, RAG & AGENTS
Build a Grounded RAG Prompt with Python
Learn build a grounded rag prompt with python with a short, executable Python example.
PROBLEM UNDERSTANDING
Input and expected output
No input required
Context: CGPA is updated semester-wise. Question: How is CGPA updated?
COMPLETE PYTHON PROGRAM
Complete Python implementation
context='CGPA is updated semester-wise.'
question='How is CGPA updated?'
print(f'Context: {context} Question: {question}')CURRENT STEP
Select Start to walk through the important lines.
SELECTED LINE
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EXPECTED OUTPUT FOR THE SAMPLE
Context: CGPA is updated semester-wise. Question: How is CGPA updated?
PROGRAM EXPLANATION
Algorithm and explanation
- Initialize the sample values used to build a grounded rag prompt.
- Apply Prompt and Grounding to compute the required result.
- Display the result for build a grounded rag prompt and compare it with the documented sample output.
This example of build a grounded rag prompt computes the result directly from the prepared sample data. It demonstrates Prompt, Grounding, and RAG and prints a deterministic result that can be checked against the sample output.
EFFICIENCY
Time and space complexity
O(n)
O(n)
DEBUGGING CHECKLIST
Common mistakes
For build a grounded rag prompt, keep the data shape and value types consistent with Prompt.
Apply Prompt in the same order shown by the algorithm; changing the order can change the result.
Verify the final Prompt and Grounding result against the sample before trying new data.