Prompt 中的变量

from langfuse import get_client
 
langfuse = get_client()
 
# Text prompt with variables
langfuse.create_prompt(
    name="movie-critic",
    type="text",
    prompt="As a {{criticLevel}} movie critic, do you like {{movie}}?",
    labels=["production"],
)
 
# Chat prompt with variables
langfuse.create_prompt(
    name="movie-critic-chat",
    type="chat",
    prompt=[
        {
            "role": "system",
            "content": "You are a {{criticLevel}} movie critic."
        },
        {
            "role": "user",
            "content": "What do you think about {{movie}}?"
        }
    ],
    labels=["production"],
)

import { LangfuseClient } from "@langfuse/client";
 
const langfuse = new LangfuseClient();
 
// Text prompt with variables
await langfuse.prompt.create({
  name: "movie-critic",
  type: "text",
  prompt: "As a {{criticLevel}} movie critic, do you like {{movie}}?",
  labels: ["production"],
});
 
// Chat prompt with variables
await langfuse.prompt.create({
  name: "movie-critic-chat",
  type: "chat",
  prompt: [
    {
      role: "system",
      content: "You are a {{criticLevel}} movie critic.",
    },
    {
      role: "user",
      content: "What do you think about {{movie}}?",
    },
  ],
  labels: ["production"],
});

from langfuse import get_client
 
langfuse = get_client()
 
# Get the prompt
prompt = langfuse.get_prompt("movie-critic")
 
# Compile with variable values
compiled_prompt = prompt.compile(
    criticLevel="expert",
    movie="Dune 2"
)
 
# -> compiled_prompt = "As an expert movie critic, do you like Dune 2?"
 
# Use with your LLM
response = openai.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": compiled_prompt}]
)

import { LangfuseClient } from "@langfuse/client";
 
const langfuse = new LangfuseClient();
 
// Get the prompt
const prompt = await langfuse.prompt.get("movie-critic", {
  type: "text",
});
 
// Compile with variable values
const compiledPrompt = prompt.compile({
  criticLevel: "expert",
  movie: "Dune 2",
});
 
// -> compiledPrompt = "As an expert movie critic, do you like Dune 2?"
 
// Use with your LLM
const response = await openai.chat.completions.create({
  model: "gpt-4",
  messages: [{ role: "user", content: compiledPrompt }],
});

from langfuse import get_client
from langchain_core.prompts import PromptTemplate, ChatPromptTemplate
 
langfuse = get_client()
 
# For text prompts
langfuse_prompt = langfuse.get_prompt("movie-critic")
langchain_prompt = PromptTemplate.from_template(langfuse_prompt.get_langchain_prompt())
 
# Compile with variables
compiled = langchain_prompt.format(criticLevel="expert", movie="Dune 2")
# -> "As an expert movie critic, do you like Dune 2?"
 
# For chat prompts
langfuse_chat_prompt = langfuse.get_prompt("movie-critic-chat")
langchain_chat_prompt = ChatPromptTemplate.from_template(
    langfuse_chat_prompt.get_langchain_prompt()
)
 
# Compile with variables
compiled_messages = langchain_chat_prompt.format_messages(
    criticLevel="expert",
    movie="Dune 2"
)

import { LangfuseClient } from "@langfuse/client";
import { PromptTemplate, ChatPromptTemplate } from "@langchain/core/prompts";
 
const langfuse = new LangfuseClient();
 
// For text prompts
const langfusePrompt = await langfuse.prompt.get("movie-critic", {
  type: "text",
});
const langchainPrompt = PromptTemplate.fromTemplate(
  langfusePrompt.getLangchainPrompt()
);
 
// Compile with variables
const compiled = await langchainPrompt.format({
  criticLevel: "expert",
  movie: "Dune 2",
});
// -> "As an expert movie critic, do you like Dune 2?"
 
// For chat prompts
const langfuseChatPrompt = await langfuse.prompt.get("movie-critic-chat", {
  type: "chat",
});
const langchainChatPrompt = ChatPromptTemplate.fromTemplate(
  langfuseChatPrompt.getLangchainPrompt()
);
 
// Compile with variables
const compiledMessages = await langchainChatPrompt.formatMessages({
  criticLevel: "expert",
  movie: "Dune 2",
});