Enterprise-level AI Agent for Router + ReAct + Function Calling

User Query
      ↓
1️⃣ Intent Router
      ↓
┌───────────────┬──────────────────┐
│ Simple QA     │ Tool Required    │
│ (LLM only)    │ (ReAct loop)     │
└───────────────┴──────────────────┘
                      ↓
            2️⃣ ReAct Tool Loop
                      ↓
            3️⃣ Structured Tool Layer
                      ↓
            4️⃣ Guardrails & Policies
                      ↓
                   Final Output

prompt = ‘

    You are a task classifier.
    User query: {query}
 
    Classify the user query into one of:
 
    1. simple_qa
    2. retrieval
    3. tool_call
    4. multi_step
 
    Return JSON:
    {
        "type": "..."
    }
’

1. simple_qa ==> LLM answers directly

2. retrieval ==> Call vector database for direct retrieval / call Browser for retrieval

3. tool_call ==> Enter ReAct loop
4. multi_step ==> Enter ReAct loop

LLM decides next action
↓
Call one tool
↓
Append tool result
↓
Repeat

while True:
 
    response = llm(messages, tools=tool_schema)
 
    if response.tool_calls:
        result = execute_tool(...)
        messages.append(tool_result)
 
    else:
        break

max_steps = 15

if tool = send_mail:
    require confirmation

Advantages:

1. Generality      Very High
2. Controllability High
3. Extensibility   Very High
4. Complex Tasks   Very High
5. Simple Task Efficiency Very High