| import streamlit as st |
| import pandas as pd |
| from transformers import pipeline |
|
|
| |
| llm = pipeline("text2text-generation", model="google/flan-t5-large") |
|
|
| SUPPLIER_FILE = "supplier_master.xlsx" |
| CUSTOMER_FILE = "customer_master.xlsx" |
|
|
| def fetch_supplier_master(): |
| return pd.read_excel(SUPPLIER_FILE) |
|
|
| def fetch_contractor_master(): |
| return pd.read_excel(CUSTOMER_FILE) |
|
|
| def structured_retrieval(query, supplier_df, contractor_df): |
| """Map queries to structured filters instead of raw string search.""" |
| query_lower = query.lower() |
| context = "" |
|
|
| |
| if "msa" in query_lower and "expired" in query_lower: |
| expired = supplier_df[supplier_df['Duration'].str.contains("Dec") == False] |
| if not expired.empty: |
| context += "Suppliers with expired MSA:\n" + expired.to_string(index=False) + "\n\n" |
| elif "msa" in query_lower: |
| active = supplier_df[supplier_df['MSA Exists'].str.lower() == "yes"] |
| if not active.empty: |
| context += "Suppliers with MSA:\n" + active.to_string(index=False) + "\n\n" |
|
|
| |
| if "top performer" in query_lower: |
| top = contractor_df[contractor_df['Performance Category'].str.lower() == "high"] |
| if not top.empty: |
| context += "Top performers:\n" + top.to_string(index=False) + "\n\n" |
| if "below par" in query_lower or "low performer" in query_lower: |
| low = contractor_df[contractor_df['Performance Category'].str.lower() == "low"] |
| if not low.empty: |
| context += "Below par performers:\n" + low.to_string(index=False) + "\n\n" |
|
|
| return context if context else "No relevant rows found." |
|
|
| def answer_query(query, context): |
| """LLM generates a consolidated answer based on retrieved context.""" |
| prompt = f"Leadership question: {query}\n\nRelevant data:\n{context}\n\nProvide a clear consolidated answer for leadership." |
| result = llm(prompt, max_length=256, do_sample=False) |
| return result[0]['generated_text'] |
|
|
| def main(): |
| st.title("Supplier & Contractor Agent") |
|
|
| supplier_data = fetch_supplier_master() |
| contractor_data = fetch_contractor_master() |
|
|
| st.subheader("Leadership Query Interface") |
| query = st.text_input("Enter your query about suppliers or contractors:") |
|
|
| if query: |
| st.info(f"Processing query: {query}") |
| context = structured_retrieval(query, supplier_data, contractor_data) |
| response = answer_query(query, context) |
| st.success("Consolidated Response:") |
| st.write(response) |
|
|
| st.subheader("Quick Performance Snapshot") |
| role_distribution = contractor_data.groupby('Role').size() |
| budget_utilization = contractor_data['Budget Approved'].str.replace('$','').str.replace('M','').astype(float).sum() |
|
|
| st.write("📊 Role Distribution", role_distribution) |
| st.write(f"💰 Overall Budget Utilization: ${budget_utilization}M") |
|
|
| if __name__ == "__main__": |
| main() |
|
|
