Create app.py

app.py

@@ -1,7 +1,7 @@
-# --- Imports ---
+# app.py
+
 import os
 import gradio as gr
-from getpass import getpass
 from llama_index.readers.file import PDFReader
 from llama_index.core import VectorStoreIndex
 from llama_index.llms.openai import OpenAI
@@ -9,15 +9,18 @@ from llama_index.core.memory import ChatMemoryBuffer
 from llama_index.core.chat_engine import ContextChatEngine
 from llama_index.core.llms import ChatMessage, MessageRole
 
-api_key = os.getenv("OPENAI_API_KEY")
-if not api_key:
-    raise ValueError("OPENAI_API_KEY environment variable is required.")
+# --- Use HF secret for OpenAI API key ---
+OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
+if not OPENAI_API_KEY:
+    raise EnvironmentError("OPENAI_API_KEY is not set in environment variables.")
+
+os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
 
 # --- Global Chat Engine ---
 chat_engine = None
-resume_text = ""  # to extract follow-up context
+resume_text = ""
 
-# --- Helper: Generate Follow-ups ---
+# --- Follow-up Generator ---
 def generate_followups(user_question, resume_excerpt):
     llm = OpenAI(model="gpt-3.5-turbo")
     prompt = (
@@ -29,16 +32,16 @@ def generate_followups(user_question, resume_excerpt):
     try:
         response = llm.complete(prompt)
         return response.text.strip()
-    except Exception as e:
+    except Exception:
         return "🔁 Follow-up Suggestions:\n- Unable to generate follow-ups at this time."
 
-# --- Upload + Index Resume ---
+# --- Upload & Index Resume ---
 def upload_and_index(file):
     global chat_engine, resume_text
     try:
         reader = PDFReader()
         documents = reader.load_data(file=file.name)
-        resume_text = "\n".join(doc.text for doc in documents[:1])  # small excerpt for followups
+        resume_text = "\n".join(doc.text for doc in documents[:1])
 
         index = VectorStoreIndex.from_documents(documents)
         retriever = index.as_retriever(similarity_top_k=3)
@@ -65,7 +68,7 @@ def upload_and_index(file):
     except Exception as e:
         return f"❌ Error during indexing: {str(e)}"
 
-# --- Chat Function (with follow-ups) ---
+# --- Chat Function ---
 def chat_with_bot(message, history):
     if chat_engine is None:
         return "❌ Please upload and index your resume first."
@@ -76,7 +79,7 @@ def chat_with_bot(message, history):
     except Exception as e:
         return f"❌ Error: {str(e)}"
 
-# --- Gradio UI ---
+# --- UI ---
 with gr.Blocks() as iface:
     gr.Markdown("""
     <h1 style='text-align: center;'>Revue</h1>
@@ -99,4 +102,4 @@ with gr.Blocks() as iface:
         textbox=gr.Textbox(placeholder="e.g. What are my key strengths for data science?", lines=1),
     )
 
-iface.launch(share=True)
+iface.launch()