Upload 8 files

app.py

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+import streamlit as st
+import faiss
+import pickle
+from transformers import AutoTokenizer, HuggingFaceEndpoint
+import os
+
+st.title("Chatbot Interface")
+
+# User role input
+user_role = st.text_input("Enter your role (Sales, Marketing, HR)")
+
+query = st.text_input("Enter your query")
+
+dataset = st.selectbox("Select Dataset", ["Sales", "Marketing", "HR"])
+
+# Load Meta-Llama model using Hugging Face Endpoint
+temperature = 0.7
+max_new_tokens = 150
+llm = HuggingFaceEndpoint(
+    repo_id="meta-llama/Meta-Llama-3-8B-Instruct",
+    temperature=temperature,
+    max_new_tokens=max_new_tokens,
+    huggingfacehub_api_token=os.getenv("P_HF_TOKEN", "None"),
+)
+
+# Retrieve relevant data from vector database
+if query and dataset:
+    if user_role == dataset:  # Simple access control
+        index_file = f'vector_db_{dataset}.index'
+        metadata_file = f'metadata_{dataset}.pkl'
+        
+        if os.path.exists(index_file) and os.path.exists(metadata_file):
+            index = faiss.read_index(index_file)
+            with open(metadata_file, 'rb') as f:
+                metadata = pickle.load(f)
+            
+            # Load pre-trained model for embeddings
+            model = SentenceTransformer('all-MiniLM-L6-v2')
+            query_embedding = model.encode([query])
+            
+            # Search in the vector database
+            distances, indices = index.search(query_embedding, k=5)
+            
+            results = [metadata[i] for i in indices[0]]
+            st.write("Results:", results)
+            
+            # Use the retrieved data as context for LLM
+            context = " ".join(results)
+            response = llm(f"{context}\n\n{query}")
+            st.write("Chatbot:", response)
+        else:
+            st.write("No data found for the selected dataset.")
+    else:
+        st.write("Access denied: You do not have permission to access this dataset.")

metadata_HR.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6404ac6866a8bc54162bb4075a6769c032220f75c81dd9f30b870f6667c17372
+size 3036

metadata_Marketing.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6a4b72bdffc384e62cd66b61b00de6e9b738de97593c552691069e1c81877e08
+size 1639

metadata_Sales.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a702a2cceb2776d899dd7ae78633917f6956cef3adc71330feb5031cf932b7a0
+size 1390

requirements.txt

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+streamlit
+faiss-cpu
+sentence-transformers
+transformers
+huggingface-hub