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- # coding=utf-8
- # Copyright 2024 the LlamaFactory team.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- import json
- import os
- from typing import Sequence
- from openai import OpenAI
- from transformers.utils.versions import require_version
- require_version("openai>=1.5.0", "To fix: pip install openai>=1.5.0")
- 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 round(total_score / total_hour, 2)
- def main():
- client = OpenAI(
- api_key="{}".format(os.environ.get("API_KEY", "0")),
- base_url="http://localhost:{}/v1".format(os.environ.get("API_PORT", 8000)),
- )
- 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"],
- },
- },
- }
- ]
- tool_map = {"calculate_gpa": calculate_gpa}
- 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)
- if result.choices[0].message.tool_calls is None:
- raise ValueError("Cannot retrieve function call from the response.")
- messages.append(result.choices[0].message)
- tool_call = result.choices[0].message.tool_calls[0].function
- print(tool_call)
- # Function(arguments='{"grades": ["A", "A", "B", "C"], "hours": [3, 4, 3, 2]}', name='calculate_gpa')
- name, arguments = tool_call.name, json.loads(tool_call.arguments)
- 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 the grades and credit hours you provided, your Grade Point Average (GPA) is 3.42.
- if __name__ == "__main__":
- main()
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