Spaces:
Sleeping
Sleeping
File size: 1,984 Bytes
5f45c2f feab02f 5f45c2f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 |
import os
import json
from langchain_core.documents import Document
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_community.vectorstores import FAISS
from langchain_huggingface import HuggingFaceEmbeddings
from langchain_openai import ChatOpenAI
from langchain.chains import RetrievalQA
import chainlit as cl
# === Load and prepare data ===
with open("combined_data.json", "r") as f:
raw_data = json.load(f)
all_docs = [
Document(page_content=entry["content"], metadata=entry["metadata"])
for entry in raw_data
]
# === Split documents into chunks ===
splitter = RecursiveCharacterTextSplitter(chunk_size=800, chunk_overlap=50)
chunked_docs = splitter.split_documents(all_docs)
# === Use your fine-tuned Hugging Face embeddings ===
embedding_model = HuggingFaceEmbeddings(
model_name="bsmith3715/legal-ft-demo_final"
)
# === Set up FAISS vector store ===
vectorstore = FAISS.from_documents(chunked_docs, embedding_model)
retriever = vectorstore.as_retriever(search_kwargs={"k": 5})
# === Load LLM ===
llm = ChatOpenAI(model_name="gpt-4o", temperature=0, streaming = True)
qa_chain = RetrievalQA.from_chain_type(llm=llm, retriever=retriever)
# === Chainlit start event ===
@cl.on_chat_start
async def start():
await cl.Message(content =
"""👋 Welcome to your Reformer Pilates AI!
Here’s what you can do:
• Ask questions about Reformer Pilates
• Get individualized workouts based on your level, goals, and equipment
• Get instant exercise modifications based on injuries or limitations
Let’s get started! 🚀""").send()
cl.user_session.set("qa_chain", qa_chain)
# === Chainlit message handler ===
@cl.on_message
async def handle_message(message: cl.Message):
chain = cl.user_session.get("qa_chain")
if chain:
try:
response = chain.run(message.content)
except Exception as e:
response = f"⚠️ Error: {str(e)}"
await cl.Message(response).send()
|