Cookbook: OpenAI Integration (Python)

%pip install langfuse openai --upgrade

import os
 
# get keys for your project from https://cloud.langfuse.com
os.environ["LANGFUSE_PUBLIC_KEY"] = ""
os.environ["LANGFUSE_SECRET_KEY"] = ""
 
# your openai key
os.environ["OPENAI_API_KEY"] = ""
 
# Your host, defaults to https://cloud.langfuse.com
# For US data region, set to "https://us.cloud.langfuse.com"
# os.environ["LANGFUSE_HOST"] = "http://localhost:3000"

# instead of: import openai
from langfuse.openai import openai

# For debugging, checks the SDK connection with the server. Do not use in production as it adds latency.
from langfuse.openai import auth_check
 
auth_check()

completion = openai.chat.completions.create(
  name="test-chat",
  model="gpt-3.5-turbo",
  messages=[
      {"role": "system", "content": "You are a very accurate calculator. You output only the result of the calculation."},
      {"role": "user", "content": "1 + 1 = "}],
  temperature=0,
  metadata={"someMetadataKey": "someValue"},
)

completion = openai.chat.completions.create(
  name="test-chat",
  model="gpt-3.5-turbo",
  messages=[
      {"role": "system", "content": "You are a professional comedian."},
      {"role": "user", "content": "Tell me a joke."}],
  temperature=0,
  metadata={"someMetadataKey": "someValue"},
  stream=True
)
 
for chunk in completion:
  print(chunk.choices[0].delta.content, end="")

from langfuse.openai import AsyncOpenAI
 
async_client = AsyncOpenAI()

completion = await async_client.chat.completions.create(
  name="test-chat",
  model="gpt-3.5-turbo",
  messages=[
      {"role": "system", "content": "You are a very accurate calculator. You output only the result of the calculation."},
      {"role": "user", "content": "1 + 100 = "}],
  temperature=0,
  metadata={"someMetadataKey": "someValue"},
)

%pip install pydantic --upgrade

from typing import List
from pydantic import BaseModel
 
class StepByStepAIResponse(BaseModel):
    title: str
    steps: List[str]
schema = StepByStepAIResponse.schema() # returns a dict like JSON schema

import json
response = openai.chat.completions.create(
    name="test-function",
    model="gpt-3.5-turbo-0613",
    messages=[
       {"role": "user", "content": "Explain how to assemble a PC"}
    ],
    functions=[
        {
          "name": "get_answer_for_user_query",
          "description": "Get user answer in series of steps",
          "parameters": StepByStepAIResponse.schema()
        }
    ],
    function_call={"name": "get_answer_for_user_query"}
)
 
output = json.loads(response.choices[0].message.function_call.arguments)

# create random trace_id
# could also use existing id from your application, e.g. conversation id
from uuid import uuid4
trace_id = str(uuid4())
 
# create multiple completions, pass trace_id to each
 
country = "Bulgaria"
 
capital = openai.chat.completions.create(
  name="geography-teacher",
  model="gpt-3.5-turbo",
  messages=[
      {"role": "system", "content": "You are a Geography teacher helping students learn the capitals of countries. Output only the capital when being asked."},
      {"role": "user", "content": country}],
  temperature=0,
  trace_id=trace_id
).choices[0].message.content
 
poem = openai.chat.completions.create(
  name="poet",
  model="gpt-3.5-turbo",
  messages=[
      {"role": "system", "content": "You are a poet. Create a poem about a city."},
      {"role": "user", "content": capital}],
  temperature=1,
  max_tokens=200,
  trace_id=trace_id
).choices[0].message.content

from langfuse import Langfuse
 
# initialize SDK
langfuse = Langfuse()
 
# create trace and add params
trace = langfuse.trace(
    # optional, if you want to use your own id
    # id = "my-trace-id",
 
    name = "country-poems",
    user_id = "user@example.com",
    metadata = {
        "env": "development",
    },
    release = "v0.0.21"
)
 
# get traceid to pass to openai calls
trace_id = trace.id
 
# create multiple completions, pass trace_id to each
 
country = "Bulgaria"
 
capital = openai.chat.completions.create(
  name="geography-teacher",
  model="gpt-3.5-turbo",
  messages=[
      {"role": "system", "content": "You are a Geography teacher helping students learn the capitals of countries. Output only the capital when being asked."},
      {"role": "user", "content": country}],
  temperature=0,
  trace_id=trace_id
).choices[0].message.content
 
poem = openai.chat.completions.create(
  name="poet",
  model="gpt-3.5-turbo",
  messages=[
      {"role": "system", "content": "You are a poet. Create a poem about a city."},
      {"role": "user", "content": capital}],
  temperature=1,
  max_tokens=200,
  trace_id=trace_id
).choices[0].message.content

from langfuse import Langfuse
 
langfuse = Langfuse()
 
langfuse.score(
    trace_id=trace_id,
    name="my-score-name",
    value=1
);