Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -10,6 +10,7 @@ from langchain.text_splitter import RecursiveCharacterTextSplitter
|
|
10 |
from langchain.vectorstores import Chroma
|
11 |
from langchain_groq import ChatGroq
|
12 |
from dotenv import load_dotenv
|
|
|
13 |
|
14 |
load_dotenv() # Load environment variables from .env file
|
15 |
|
@@ -48,7 +49,9 @@ if process_url_clicked:
|
|
48 |
chunk_size=1000
|
49 |
)
|
50 |
main_placeholder.text("Text Splitting...Started...β
β
β
")
|
51 |
-
docs =
|
|
|
|
|
52 |
|
53 |
# Create embeddings and save to Chroma vector store
|
54 |
embedding_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
|
|
|
10 |
from langchain.vectorstores import Chroma
|
11 |
from langchain_groq import ChatGroq
|
12 |
from dotenv import load_dotenv
|
13 |
+
from langchain.schema import Document
|
14 |
|
15 |
load_dotenv() # Load environment variables from .env file
|
16 |
|
|
|
49 |
chunk_size=1000
|
50 |
)
|
51 |
main_placeholder.text("Text Splitting...Started...β
β
β
")
|
52 |
+
docs = [Document(page_content=text) for text in data]
|
53 |
+
docs = text_splitter.split_documents(docs)
|
54 |
+
#docs = text_splitter.split_documents(data)
|
55 |
|
56 |
# Create embeddings and save to Chroma vector store
|
57 |
embedding_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
|