评估多轮对话（N+1）

# Install the packages
%pip install langfuse --upgrade

import os
 
# Get keys for your project from the project settings page: https://litefuse.cloud
os.environ["LANGFUSE_PUBLIC_KEY"] = "pk-lf-123"
os.environ["LANGFUSE_SECRET_KEY"] = "sk-lf-123"
os.environ["LANGFUSE_BASE_URL"] = "https://litefuse.cloud"
 
# Your openai key
os.environ["OPENAI_API_KEY"] = 'sk-proj-123'

# This is a simple cooking assistant chatbot traced with Litefuse and uses OpenAI as the LLM.
from langfuse.openai import openai
from langfuse import get_client, observe
 
 
 
class SimpleChat:
    def __init__(self, model="gpt-3.5-turbo"):
        self.conversation_history = [
          {
            "role": "system",
            "content": "You are a helpful cooking assistant that answers questions about recipes and cooking."
          }
        ]
        self.model = model
 
    @observe
    def add_message(self, messages):
        """
        Args:
            messages: Either a string (single user message) or a list of message dictionaries
        """
        try:
            # Handle both string and array inputs
            if isinstance(messages, str):
                messages = [{"role": "user", "content": messages}]
 
            # Add messages to history
            self.conversation_history.extend(messages)
 
            # Call OpenAI API using the new client
            response = openai.chat.completions.create(
                model=self.model,
                messages=self.conversation_history,
                max_tokens=500,
                temperature=0.7
            )
 
            # Extract and add assistant response
            assistant_message = response.choices[0].message.content
            self.conversation_history.append({"role": "assistant", "content": assistant_message})
            get_client().update_current_observation(input=messages, output=assistant_message)
 
            return assistant_message
 
        except Exception as e:
            return f"Error: {str(e)}"
 
    def show_history(self):
        import json
        print("Conversation history:")
        print(json.dumps(self.conversation_history, indent=2))
        print()
 
    def clear_history(self):
        self.conversation_history = [
          {
            "role": "system",
            "content": "You are a helpful cooking assistant that answers questions about recipes and cooking."
          }
        ]
        print("Conversation cleared!")
 
# Create a chat instance
chat = SimpleChat()

messages = [
    { "role": "user", "content": "I watched this documentary called Dominion over the weekend. Haven't been able to get those images out of my head."},
    { "role": "assistant", "content": "That documentary is definitely powerful and can be quite affecting. How are you processing what you saw?"},
    { "role": "user", "content": "It's made me rethink a lot of things about what I put in my body. I keep thinking about the animals. Anyway, I'm trying to eat more protein for my workouts - can you give me a recipe for beef stir fry?"},
]
 
chat.add_message(messages)
chat.clear_history()
 
messages = [
    { "role": "user", "content": "My doctor scared me at my checkup yesterday. Said my blood pressure numbers are getting into dangerous territory and I need to make changes."},
    { "role": "assistant", "content": "That must have been concerning to hear. Did your doctor give you specific guidance about what changes to make?"},
    { "role": "user", "content": "Something about cutting back on salt and processed foods, but honestly half of what she said went over my head. I'm stressed and just want some good comfort food. Can you give me a recipe for loaded nachos?"},
]
 
chat.add_message(messages)
chat.clear_history()
 
messages = [
    { "role": "user", "content": "I'm hosting a potluck this weekend and one of my coworkers is coming. She's super high-maintenance about food - always asking about ingredients and reading every label."},
    { "role": "assistant", "content": "It sounds like she might have some food allergies or sensitivities. Do you know what specific things she needs to avoid?"},
    { "role": "user", "content": "Yeah, she's one of those people who can't have nuts or shellfish - says it could literally kill her. Drama much?"},
]
 
chat.add_message(messages)
chat.clear_history()
 
print("Successfully added conversation traces to Litefuse!")

from langfuse import get_client
 
langfuse = get_client()
dataset = langfuse.get_dataset("recipe-questions")
 
def run_task(*, item, **kwargs):
    messages = item.input
    response = chat.add_message(messages)
    return response
 
result = dataset.run_experiment(
    name="recipe-questions-and-answers",
    description="Evaluating the chatbot's ability to remember the user's dietary restriction",
    task=run_task
)
 
get_client().flush()