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137 lines
3.9 KiB
Python
137 lines
3.9 KiB
Python
import json
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import logging
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from dotenv import load_dotenv
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from openai import OpenAI
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from humanlayer import HumanLayer
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load_dotenv()
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hl = HumanLayer(
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verbose=True,
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# run_id is optional -it can be used to identify the agent in approval history
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run_id="openai-math-example",
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)
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PROMPT = "multiply 2 and 5, then add 32 to the result"
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def add(x: int, y: int) -> int:
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"""Add two numbers together."""
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return x + y
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@hl.require_approval()
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def multiply(x: int, y: int) -> int:
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"""multiply two numbers"""
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return x * y
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math_tools_map = {
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"add": add,
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"multiply": multiply,
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}
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math_tools_openai = [
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{
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"type": "function",
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"function": {
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"name": "add",
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"description": "Add two numbers together.",
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"parameters": {
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"type": "object",
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"properties": {
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"x": {"type": "number"},
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"y": {"type": "number"},
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},
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"required": ["x", "y"],
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},
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},
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},
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{
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"type": "function",
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"function": {
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"name": "multiply",
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"description": "multiply two numbers",
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"parameters": {
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"type": "object",
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"properties": {
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"x": {"type": "number"},
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"y": {"type": "number"},
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},
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"required": ["x", "y"],
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},
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},
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},
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]
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logger = logging.getLogger(__name__)
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def run_chain(prompt: str, tools_openai: list[dict], tools_map: dict) -> str:
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client = OpenAI()
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messages = [{"role": "user", "content": prompt}]
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response = client.chat.completions.create(
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model="gpt-4o",
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messages=messages,
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tools=tools_openai,
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tool_choice="auto",
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)
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while response.choices[0].finish_reason != "stop":
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response_message = response.choices[0].message
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tool_calls = response_message.tool_calls
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if tool_calls:
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messages.append(response_message) # extend conversation with assistant's reply
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logger.info(
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"last message led to %s tool calls: %s",
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len(tool_calls),
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[(tool_call.function.name, tool_call.function.arguments) for tool_call in tool_calls],
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)
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for tool_call in tool_calls:
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function_name = tool_call.function.name
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function_to_call = tools_map[function_name]
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function_args = json.loads(tool_call.function.arguments)
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logger.info("CALL tool %s with %s", function_name, function_args)
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function_response_json: str
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try:
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function_response = function_to_call(**function_args)
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function_response_json = json.dumps(function_response)
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except Exception as e:
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function_response_json = json.dumps(
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{
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"error": str(e),
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}
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)
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logger.info(
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"tool %s responded with %s",
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function_name,
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function_response_json[:200],
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)
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messages.append(
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{
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"tool_call_id": tool_call.id,
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"role": "tool",
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"name": function_name,
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"content": function_response_json,
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}
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) # extend conversation with function response
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response = client.chat.completions.create(
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model="gpt-4o",
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messages=messages,
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tools=tools_openai,
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)
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return response.choices[0].message.content
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if __name__ == "__main__":
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logging.basicConfig(level=logging.INFO)
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result = run_chain(PROMPT, math_tools_openai, math_tools_map)
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print("\n\n----------Result----------\n\n")
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print(result)
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