Combining retrieval with agent reasoning in Agentic AI - Model Pipeline Trace

Model Pipeline - Combining retrieval with agent reasoning

This pipeline shows how an AI agent uses retrieval of information from a knowledge base combined with its own reasoning to answer questions better. It first finds relevant facts, then thinks step-by-step to give a smart answer.

Data Flow - 4 Stages

1Input Question

1 question string→Receive user question→1 question string

"What causes rainbows?"

↓

2Information Retrieval

1 question string→Search knowledge base for relevant documents→5 documents (text snippets)

["Rainbows form when light bends through water droplets.", "Light refracts and reflects inside droplets.", "Sunlight splits into colors.", "Water droplets act like prisms.", "Rainbows appear opposite the sun."]

↓

3Agent Reasoning

1 question string + 5 documents→Analyze retrieved info and reason step-by-step→1 reasoned answer string

"Rainbows happen because sunlight bends and splits inside raindrops, creating colors you see in the sky."

↓

4Output Answer

1 reasoned answer string→Return final answer to user→1 answer string

"Rainbows happen because sunlight bends and splits inside raindrops, creating colors you see in the sky."

Training Trace - Epoch by Epoch

Loss
1.0 |***************
0.8 |**********     
0.6 |*******        
0.4 |****           
0.2 |**             
0.0 +--------------
     1 2 3 4 5 Epochs

Epoch	Loss ↓	Accuracy ↑	Observation
1	0.85	0.4	Model starts learning to retrieve relevant documents and reason roughly.
2	0.65	0.55	Retrieval improves, reasoning becomes more coherent.
3	0.45	0.7	Agent better combines retrieved info with reasoning.
4	0.3	0.82	Loss decreases steadily; reasoning answers become clearer.
5	0.2	0.9	Model converges with high accuracy on reasoning and retrieval.

Prediction Trace - 4 Layers

Layer 1: Input Question

Layer 2: Information Retrieval

Layer 3: Agent Reasoning

Layer 4: Output Answer

Model Quiz - 3 Questions

What is the main role of the retrieval step in this pipeline?

A Clean the input question text

B Generate the final answer directly

C Find relevant information from a knowledge base

D Evaluate the model's accuracy

Key Insight

Combining retrieval with agent reasoning helps the AI use real facts and think clearly, leading to better and more accurate answers than using either alone.