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import json
import os
from typing import Sequence
from openai import OpenAI
os.environ["OPENAI_BASE_URL"] = "http://192.168.0.1:8000/v1"
os.environ["OPENAI_API_KEY"] = "0"
def calculate_gpa(grades: Sequence[str], hours: Sequence[int]) -> float:
grade_to_score = {"A": 4, "B": 3, "C": 2}
total_score, total_hour = 0, 0
for grade, hour in zip(grades, hours):
total_score += grade_to_score[grade] * hour
total_hour += hour
return total_score / total_hour
tool_map = {"calculate_gpa": calculate_gpa}
if __name__ == "__main__":
client = OpenAI()
tools = [
{
"type": "function",
"function": {
"name": "calculate_gpa",
"description": "Calculate the Grade Point Average (GPA) based on grades and credit hours",
"parameters": {
"type": "object",
"properties": {
"grades": {"type": "array", "items": {"type": "string"}, "description": "The grades"},
"hours": {"type": "array", "items": {"type": "integer"}, "description": "The credit hours"},
},
"required": ["grades", "hours"],
},
},
}
]
messages = []
messages.append({"role": "user", "content": "My grades are A, A, B, and C. The credit hours are 3, 4, 3, and 2."})
result = client.chat.completions.create(messages=messages, model="test", tools=tools)
tool_call = result.choices[0].message.tool_calls[0].function
name, arguments = tool_call.name, json.loads(tool_call.arguments)
messages.append(
{"role": "function", "content": json.dumps({"name": name, "argument": arguments}, ensure_ascii=False)}
)
tool_result = tool_map[name](**arguments)
messages.append({"role": "tool", "content": json.dumps({"gpa": tool_result}, ensure_ascii=False)})
result = client.chat.completions.create(messages=messages, model="test", tools=tools)
print(result.choices[0].message.content)
# Based on your grades and credit hours, your calculated Grade Point Average (GPA) is 3.4166666666666665.
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