LangChain 为常见应用程序提供标准接口、大量集成和端到端链
文档: https://python.langchain.com/en/latest/ecosystem.html
中文文档:
pip install langchain
pip install openai
from langchain.vectorstores import FAISS
from langchain import HuggingFaceHub
from langchain.docstore import InMemoryDocstore
from langchain import LLMChain, PromptTemplate
from langchain.llms import BaseLLM
from langchain.vectorstores.base import VectorStore
from langchain.chains.base import Chain
from langchain.experimental import BabyAGI
embeddings_model = HuggingFaceEmbedding.newEmbeddingFunction
embedding_size = 1536
index = faiss.IndexFlatL2(embedding_size)
vectorstore = FAISS(embeddings_model, index, InMemoryDocstore({}), {})
verbose = False
int_max_iterations = input("Enter the maximum number of iterations: (Suggest from 3 and 5) ")
max_iterations = int(int_max_iterations)
max_iterations: Optional[int] = max_iterations
baby_agi = BabyAGI.from_llm(
llm=llm, vectorstore=vectorstore, verbose=verbose, max_iterations=max_iterations
)
选择 chatgpt或 HuggingChat
from langchain.agents import create_csv_agent
from langchain.utilities import PythonREPL
CG_TOKEN = input("Insert chatgpt token >>> ")
os.environ["CHATGPT_TOKEN"] = CG_TOKEN
start_chat = input("Do you want start a chat from existing chat? (y/n): ") # ask if you want start a chat from existing chat
if start_chat == "y":
chat_id = input("Insert chat-id (chat.openai.com/c/(IS THIS ->)58XXXX0f-XXXX-XXXX-XXXX-faXXXXd2b50f) ->") # ask the chat id
llm= ChatGPTAPI.ChatGPT(token=os.environ["CHATGPT_TOKEN"], conversation=chat_id)
else:
# llm= ChatGPTAPI.ChatGPT(token=os.environ["CHATGPT_TOKEN"])
llm=HuggingChatAPI.HuggingChat()
agent = create_csv_agent(llm=llm, tool=PythonREPL(), path=path_csv, verbose=True)
prompt = input("(Enter your task or question) >> ")
while prompt != "exit":
agent.run(prompt)
prompt = input("(Enter your task or question) >> ")