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import json |
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import os |
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from typing import Sequence |
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from openai import OpenAI |
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os.environ["OPENAI_BASE_URL"] = "http://192.168.0.1:8000/v1" |
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os.environ["OPENAI_API_KEY"] = "0" |
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def calculate_gpa(grades: Sequence[str], hours: Sequence[int]) -> float: |
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grade_to_score = {"A": 4, "B": 3, "C": 2} |
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total_score, total_hour = 0, 0 |
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for grade, hour in zip(grades, hours): |
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total_score += grade_to_score[grade] * hour |
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total_hour += hour |
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return total_score / total_hour |
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tool_map = {"calculate_gpa": calculate_gpa} |
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if __name__ == "__main__": |
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client = OpenAI() |
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tools = [ |
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{ |
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"type": "function", |
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"function": { |
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"name": "calculate_gpa", |
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"description": "Calculate the Grade Point Average (GPA) based on grades and credit hours", |
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"parameters": { |
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"type": "object", |
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"properties": { |
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"grades": {"type": "array", "items": {"type": "string"}, "description": "The grades"}, |
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"hours": {"type": "array", "items": {"type": "integer"}, "description": "The credit hours"}, |
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}, |
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"required": ["grades", "hours"], |
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}, |
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}, |
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} |
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] |
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messages = [] |
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messages.append({"role": "user", "content": "My grades are A, A, B, and C. The credit hours are 3, 4, 3, and 2."}) |
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result = client.chat.completions.create(messages=messages, model="test", tools=tools) |
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tool_call = result.choices[0].message.tool_calls[0].function |
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name, arguments = tool_call.name, json.loads(tool_call.arguments) |
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messages.append( |
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{"role": "function", "content": json.dumps({"name": name, "argument": arguments}, ensure_ascii=False)} |
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) |
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tool_result = tool_map[name](**arguments) |
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messages.append({"role": "tool", "content": json.dumps({"gpa": tool_result}, ensure_ascii=False)}) |
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result = client.chat.completions.create(messages=messages, model="test", tools=tools) |
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print(result.choices[0].message.content) |
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