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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() | |