Skip to main content

​
1. Setup clients

Initialize Freeplay and OpenAI client SDKs.

​
2. Fetch prompt from Freeplay

Pull in the formatted prompt with Freeplay. The prompt contains tools schema that’ll we’ll pass down below.

​
3. Call OpenAI with the tools

When creating a new completion, pass in the tools schema from the prompt we fetched.

​
4. Handle tool call

When LLM responds back with a tool call, call the external function in your service. As an example here, we are calling get_temperature function

​
5. Record tool call and schema

Pass in the schema and completion response to capture the tool call and its associated schema.

​
Examples

import os
import time
import json
from openai import OpenAI

from freeplay import Freeplay, RecordPayload, ResponseInfo, CallInfo

# A mock function that gets temperature for a location
def get_temperature(location: str) -> float:
    return 72.5

fpclient = Freeplay(
    freeplay_api_key=os.environ['FREEPLAY_API_KEY'],
    api_base=f"{os.environ['FREEPLAY_API_URL']}/api"
)
client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
project_id=os.environ['FREEPLAY_PROJECT_ID']

input_variables = {'location': "Boulder, CO"}
formatted_prompt = fpclient.prompts.get_formatted(
    project_id=project_id,
    template_name='my-openai-prompt',
    environment='latest',
    variables=input_variables
)

start = time.time()
completion = client.chat.completions.create(
    messages=formatted_prompt.llm_prompt,
    model=formatted_prompt.prompt_info.model,
    tools=formatted_prompt.tool_schema,
    **formatted_prompt.prompt_info.model_parameters
)
end = time.time()

# Append the completion to list of messages
messages = formatted_prompt.all_messages(completion.choices[0].message)
if completion.choices[0].message.tool_calls:
    for tool_call in completion.choices[0].message.tool_calls:
        if tool_call.function.name == "weather_of_location":
            args = json.loads(tool_call.function.arguments)
            temperature = get_temperature(args["location"])

            tool_response_message = {
                "tool_call_id": tool_call.id,
                "role": "tool",
                "content": str(temperature),
            }
            messages.append(tool_response_message)

session = fpclient.sessions.create()
fpclient.recordings.create(
  RecordPayload(
				project_id=project_id,
        all_messages=messages,
        session_info=session.session_info,
        inputs=input_variables,
        prompt_version_info=formatted_prompt.prompt_info,
        call_info=CallInfo.from_prompt_info(formatted_prompt.prompt_info, start, end),
        tool_schema=formatted_prompt.tool_schema,
        response_info=ResponseInfo(is_complete=completion.choices[0].finish_reason == 'stop'),
    )
)