Update src/app.py

src/app.py

@@ -1,11 +1,14 @@
 import streamlit as st
 import os
-import uuid
 from utils import *
+import uuid
+
+st.write("Token exists:", bool(os.getenv("HUGGINGFACEHUB_API_TOKEN")))
 
 if 'unique_id' not in st.session_state:
     st.session_state['unique_id'] = ''
 
+
 def main():
     st.set_page_config(page_title="Resume Screening Assistance")
     st.title("HR - Resume Screening Assistance...💁 ")
@@ -23,14 +26,6 @@ def main():
             st.error("ERROR: HUGGINGFACEHUB_API_TOKEN not found. Set it in Hugging Face Space Secrets.")
             return
 
-        try:
-            document_count = int(document_count)
-        except ValueError:
-            document_count = 5
-
-        from huggingface_hub import InferenceClient
-        hf_client = InferenceClient(token=API_TOKEN)
-
         with st.spinner('Wait for it...'):
             st.session_state['unique_id'] = uuid.uuid4().hex
             final_docs_list = create_docs(pdf, st.session_state['unique_id'])
@@ -39,8 +34,10 @@ def main():
 
             embeddings = create_embeddings_load_data()
 
+            # --- CHROMADB REPLACEMENT ---
             push_to_chroma(st.session_state['unique_id'], embeddings, final_docs_list)
             relavant_docs = similar_docs(job_description, document_count, st.session_state['unique_id'])
+            # ---------------------------
 
             st.write(":heavy_minus_sign:" * 30)
 
@@ -50,10 +47,11 @@ def main():
 
                 with st.expander('Show me 👀'):
                     st.info("**Match Score** : " + str(relavant_docs[item][1]))
-                    summary = get_summary(relavant_docs[item][0], hf_client)
+                    summary = get_summary(relavant_docs[item][0])
                     st.write("**Summary** : " + summary)
 
         st.success("Hope I was able to save your time❤️")
 
+
 if __name__ == '__main__':
     main()