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app.py

@@ -1,3 +1,7 @@
+# ✅ Mount Google Drive
+from google.colab import drive
+drive.mount('/content/drive')
+
 # ✅ Set up your OpenAI API Key
 import os
 os.environ["OPENAI_API_KEY"] = "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"  # 🔐 Replace with your key
@@ -25,8 +29,8 @@ def build_rag_agent(pdf_path):
     return RetrievalQA.from_chain_type(llm=llm, retriever=retriever, chain_type="stuff")
 
 # ✅ Create RAG agents for course syllabi
-stat6371_agent = build_rag_agent("ds6371syllabusVer7.pdf")
-ds6306_agent = build_rag_agent("DDSSyllabus2025.pdf")
+stat6371_agent = build_rag_agent("/content/drive/MyDrive/PDFs/ds_6371_syllabus Ver 7.pdf")
+ds6306_agent = build_rag_agent("/content/drive/MyDrive/PDFs/DDS_Syllabus_2025.pdf")
 
 # ✅ Load Hugging Face fine-tuned model for general statistics questions
 general_stat_agent = pipeline("text2text-generation", model="google/flan-t5-base")  # Replace with your model

requirements.txt

@@ -1,9 +1,11 @@
-openai 
-langchain 
-langchain-community 
-faiss-cpu 
-PyPDF2 
-transformers 
+openai
+langchain
+langchain-community
+langchain-openai
+faiss-cpu
+PyPDF2
 pypdf
+transformers
 gradio
-tiktoken
+tiktoken
+torch  # ✅ Required for HF pipeline