ساخت نمایندگان هوش مصنوعی با رشته ها: قسمت 2 – ادغام ابزار

import logging
from strands import Agent
from strands_tools import current_time, http_request

subject_expert = Agent(
    system_prompt="""You are a Computer Science Subject Expert specializing
    in explaining technical concepts clearly and concisely. Your expertise
    covers programming languages, data structures, algorithms, computer
    architecture, and software engineering principles.

    You have access to tools that help you provide more accurate and timely
    information. Use these tools when appropriate to enhance your explanations.

    When explaining concepts:
    1. Start with a clear, concise definition
    2. Provide relevant examples to illustrate the concept
    3. Explain practical applications where applicable
    4. Use tools when additional information would be valuable
    5. Cite sources when you reference external information
    """,
    tools=[current_time, http_request]
)

# Test the agent with a query that might benefit from tools
query = """
Answer the following questions:
1. What is the current time in UTC?
2. Based on Wikipedia, which CS concept can be traced back to Paul Bachmann?
"""

response = subject_expert(query)

I'll answer both of your questions using the appropriate tools for accurate information.

### Question 1: What is the current time in UTC?

Let me get the current UTC time for you:
Tool #1: current_time

The current time in UTC is 2025-05-21T14:21:29.562062+00:00, which translates to May 21, 2025, at 14:21:29 UTC.

### Question 2: Based on Wikipedia, which CS concept can be traced back to Paul Bachmann?

Let me search for this information on Wikipedia:
Tool #2: http_request

Based on the Wikipedia article I've accessed, one of the key computer science concepts that can be traced back to Paul Bachmann is **Big O notation**.

import os
import json
from typing import Optional
from strands import Agent, tool
from strands_tools import calculator, file_read, file_write

# Define a custom tool to manage CS terminology
@tool
def cs_glossary(action: str, term: Optional[str] = None, definition: Optional[str] = None) -> str:
    """
    Manage a glossary of computer science terms.

    Args:
        action: The action to perform: 'lookup', 'add', 'update', or 'list'.
        term: The term to look up, add, or update (not needed for 'list').
        definition: The definition to add or update (only needed for 'add' and 'update').
    """
    glossary_file = "cs_glossary.json"

    def load_glossary():
        if not os.path.exists(glossary_file):
            with open(glossary_file, "w") as f:
                json.dump({}, f)
        with open(glossary_file, "r") as f:
            return json.load(f)

    def save_glossary(glossary):
        with open(glossary_file, "w") as f:
            json.dump(glossary, f)

    glossary = load_glossary()

    if action == "lookup":
        if not term:
            return "Error: Term is required for lookup"
        return glossary.get(term, f"Term '{term}' not found in the glossary")

    elif action == "add":
        if not term or not definition:
            return "Error: Both term and definition are required"
        if term in glossary:
            return f"Error: '{term}' already exists. Use 'update' instead."
        glossary[term] = definition
        save_glossary(glossary)
        return f"Added '{term}' to the glossary"

    elif action == "update":
        if not term or not definition:
            return "Error: Both term and definition are required"
        if term not in glossary:
            return f"Error: Term '{term}' not found. Use 'add' instead."
        glossary[term] = definition
        save_glossary(glossary)
        return f"Updated definition for '{term}'"

    elif action == "list":
        if not glossary:
            return "The glossary is empty"
        return "\n".join(f"- {t}" for t in sorted(glossary))

    return f"Error: Unknown action '{action}'. Use 'lookup', 'add', 'update', or 'list'."

# Glossary @tool implementation as shown above
# ...

# Create an enhanced subject expert agent with multiple tools
subject_expert = Agent(
    system_prompt="""You are a Computer Science Subject Expert specializing
    in explaining technical concepts clearly and concisely. Your expertise
    covers programming languages, data structures, algorithms, computer
    architecture, and software engineering principles.

    You can manage a glossary of computer science terms with the cs_glossary tool.
    You can perform calculations with the calculator tool.
    You can read and write files with the file_read and file_write tools.

    When explaining concepts:
    1. Start with a clear, concise definition
    2. Check the glossary for any related terms
    3. Add important terms to the glossary if they're not already there
    4. Provide relevant examples to illustrate the concept
    5. Use calculations when appropriate to demonstrate complexity or performance

    Your goal is to help learners build a solid understanding of computer
    science fundamentals.
    """,
    tools=[calculator, file_read, file_write, cs_glossary]
)

def interactive_session():
    print("Computer Science Subject Expert (type 'exit' to quit)")
    print("---------------------------------------------------")
    print("Suggested commands to try:")
    print("- 'Add recursion to the glossary'")
    print("- 'What terms are in the glossary?'")
    print("- 'Explain the time complexity of binary search'")

    while True:
        user_input = input("\nYour question: ")

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("Goodbye!")
            break

        print("\nThinking...\n")
        response = subject_expert(user_input)
        print(response)

if __name__ == "__main__":
    interactive_session()

Computer Science Subject Expert (type 'exit' to quit)
---------------------------------------------------
Suggested commands to try:
- 'Add recursion to the glossary'
- 'What terms are in the glossary?'
- 'Explain the time complexity of binary search'

Your question: _

# Look up a term directly
definition = subject_expert.tool.cs_glossary(action="lookup", term="recursion")
print(f"Definition: {definition}")

# Perform a calculation directly
result = subject_expert.tool.calculator(expression="2^10")
print(f"Calculation result: {result}")