// Must precede any llm module imports
import * as Langtrace from "@langtrase/typescript-sdk";
Langtrace.init({ api_key: "<LANGTRACE_API_KEY>" });

# Must precede any llm module imports
from langtrace_python_sdk import langtrace
langtrace.init(api_key = '<LANGTRACE_API_KEY>')

import * as Langtrace from '@langtrace/typescript-sdk';
import OpenAI from 'openai';

// Initialize dotenv
import dotenv from 'dotenv'
dotenv.config()

// Initialize Langtrace SDK
Langtrace.init()

const openai = new OpenAI()

// Function to handle OpenAI interaction and user feedback
export const run = async (): Promise<void> => {
  await Langtrace.withLangTraceRootSpan(async (spanId, traceId) => {
    const response = await openai.chat.completions.create({
      model: 'gpt-4o-mini',
      messages: [
        { role: 'system', content: 'Talk like a pirate' },
        { role: 'user', content: 'Tell me a story in 3 sentences or less.' }
      ],
      stream: false
    })

    // Send traceId and spanId to your client
    // Collect user feedback (This is likely going to be another route in your application) For this example, we are sending the feedback immediately after the interaction
    const userScore = 5 // Example user score
    const userId = 'user123' // Example user ID
    await Langtrace.sendUserFeedback({ spanId, traceId, userScore, userId })
  })
}

from dotenv import find_dotenv, load_dotenv
from openai import OpenAI
from langtrace_python_sdk import langtrace, with_langtrace_root_span, SendUserFeedback

_ = load_dotenv(find_dotenv())

# Initialize Langtrace SDK
langtrace.init()
client = OpenAI()


def api(span_id, trace_id):
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "user", "content": "What is the best place to live in the US?"},
        ],
        stream=False,
    )

    # Collect user feedback and send it to Langtrace
    user_score = 1  # Example user score
    user_id = 'user_1234'  # Example user ID
    data = {
        "userScore": user_score,
        "userId": user_id,
        "spanId": span_id,
        "traceId": trace_id
    }
    SendUserFeedback().evaluate(data=data)

    # Return the response
    return response.choices[0].message.content


# wrap the API call with the Langtrace root span
wrapped_api = with_langtrace_root_span()(api)

# Call the wrapped API
wrapped_api()

import * as Langtrace from "@langtrase/typescript-sdk";
await Langtrace.sendUserFeedback({spanId, traceId, userScore, userId});

from langtrace_python_sdk import SendUserFeedback
SendUserFeedback.evaluate(spanId, traceId, userScore, userId)