Update app.py

app.py

@@ -8,7 +8,7 @@ from bs4 import BeautifulSoup
 from sentence_transformers import SentenceTransformer
 from langchain_community.vectorstores import FAISS
 from langchain.embeddings.base import Embeddings
-from transformers import pipeline
+from transformers import pipeline, HfApi, HfFolder
 
 # === Embeddings Wrapper ===
 class SentenceTransformerEmbeddings(Embeddings):
@@ -35,6 +35,13 @@ def split_text(text, chunk_size=500, overlap=50):
         start += chunk_size - overlap
     return chunks
 
+def login_to_huggingface(api_key):
+    try:
+        HfFolder.save_token(api_key)
+        st.success("✅ Logged into Hugging Face successfully!")
+    except Exception as e:
+        st.error(f"❌ Failed to log in: {e}")
+
 def ask_mistral(question, context, hf_api_key):
     # Load the Hugging Face Mistral model pipeline
     nlp = pipeline("question-answering", model="mistralai/Mistral-7B-v0.3", tokenizer="mistralai/Mistral-7B-v0.3", use_auth_token=hf_api_key)
@@ -77,6 +84,8 @@ st.title("🔍 RAG Assistant: Chat with PDF, CSV, or Website")
 with st.sidebar:
     data_source = st.selectbox("📂 Select Input Type", ["PDF", "CSV", "Website URL"])
     hf_api_key = st.text_input("🔑 Enter Hugging Face API Key", type="password")
+    if hf_api_key:
+        login_to_huggingface(hf_api_key)
 
 # === Logic by Data Source ===
 vectorstore = None