File size: 1,053 Bytes
3af157b
786f732
3af157b
 
786f732
3af157b
 
 
 
 
 
 
 
 
 
786f732
3af157b
f2b7073
786f732
3af157b
 
 
786f732
3af157b
 
 
 
 
 
 
 
 
 
 
 
 
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
import streamlit as st

from langchain_huggingface import HuggingFaceEmbeddings
from langchain_chroma import Chroma
from langchain_community.vectorstores import InMemoryVectorStore
from langchain_community.document_loaders import PyPDFLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter


@st.cache_resource()
def load_embedding_model(model):
    model = HuggingFaceEmbeddings(model_name=model)
    return model


@st.cache_resource()
def load_vector_store():
    model = load_embedding_model("sentence-transformers/all-MiniLM-L12-v2")

    vector_store = Chroma(
        collection_name="main_store",
        embedding_function=model,
        persist_directory="./chroma",
    )
    return vector_store


def process_pdf(pdf, vector_store):
    """
    Loads a pdf and splits it into chunks
    """
    loader = PyPDFLoader(pdf)
    docs = loader.load()
    text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
    splits = text_splitter.split_documents(docs)
    vector_store.add_documents(splits)