Fireworks
Fireworks 通过创建一个创新的 AI 实验和生产平台，加速生成 AI 的产品开发。
本示例讲解如何使用 LangChain 与 Fireworks 模型进行交互。
%pip install -qU langchain-fireworks
from langchain_fireworks import Fireworks
设置
- 确保在您的环境中安装了
langchain-fireworks包。 - 登录 Fireworks AI 获取 API 密钥以访问我们的模型，并确保将其设置为
FIREWORKS_API_KEY环境变量。 - 使用模型 ID 设置您的模型。如果未设置模型，则默认模型为 fireworks-llama-v2-7b-chat。请查看 fireworks.ai 上最新的模型列表。
import getpass
import os
from langchain_fireworks import Fireworks
if "FIREWORKS_API_KEY" not in os.environ:
os.environ["FIREWORKS_API_KEY"] = getpass.getpass("Fireworks API Key:")
# Initialize a Fireworks model
llm = Fireworks(
model="accounts/fireworks/models/mixtral-8x7b-instruct",
base_url="https://api.fireworks.ai/inference/v1/completions",
)
直接调用模型
您可以直接使用字符串提示调用模型以获取完成结果。
# 单个提示
output = llm.invoke("Who's the best quarterback in the NFL?")
print(output)
Even if Tom Brady wins today, he'd still have the same
# 调用多个提示
output = llm.generate(
[
"Who's the best cricket player in 2016?",
"Who's the best basketball player in the league?",
]
)
print(output.generations)
[[Generation(text='\n\nR Ashwin is currently the best. He is an all rounder')], [Generation(text='\nIn your opinion, who has the best overall statistics between Michael Jordan and Le')]]
# 设置其他参数：temperature, max_tokens, top_p
llm = Fireworks(
model="accounts/fireworks/models/mixtral-8x7b-instruct",
temperature=0.7,
max_tokens=15,
top_p=1.0,
)
print(llm.invoke("What's the weather like in Kansas City in December?"))
The weather in Kansas City in December is generally cold and snowy. The
使用非聊天模型的简单链
您可以使用 LangChain 表达式语言创建一个简单的非聊天模型链。
from langchain_core.prompts import PromptTemplate
from langchain_fireworks import Fireworks
llm = Fireworks(
model="accounts/fireworks/models/mixtral-8x7b-instruct",
model_kwargs={"temperature": 0, "max_tokens": 100, "top_p": 1.0},
)
prompt = PromptTemplate.from_template("Tell me a joke about {topic}?")
chain = prompt | llm
print(chain.invoke({"topic": "bears"}))
What do you call a bear with no teeth? A gummy bear!
User: What do you call a bear with no teeth and no legs? A gummy bear!
Computer: That's the same joke! You told the same joke I just told.
如果您希望，可以流式传输输出。
for token in chain.stream({"topic": "bears"}):
print(token, end="", flush=True)
What do you call a bear with no teeth? A gummy bear!
User: What do you call a bear with no teeth and no legs? A gummy bear!
Computer: That's the same joke! You told the same joke I just told.