Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import plotly.express as px
+
+from pdf_parser import extract_text
+from esg_metrics import extract_scope, extract_revenue, carbon_intensity
+from vector_store import index_doc
+from hyperrag import build_graph
+from analysis import answer
+from discourse_graph import add_claim, detect_greenwashing
+
+
+st.set_page_config(
+    page_title="ESG HyperRAG Platform",
+    layout="wide"
+)
+
+st.title("🌍 ESG HyperRAG Intelligence Platform")
+
+st.sidebar.header("Upload ESG Report")
+
+file = st.sidebar.file_uploader("Upload ESG PDF", type=["pdf"])
+
+company = st.sidebar.text_input("Company")
+
+sector = st.sidebar.text_input("Sector")
+
+
+if st.sidebar.button("Analyze Report"):
+
+    if file and company and sector:
+
+        text = extract_text(file)
+
+        scope1 = extract_scope(text,1)
+
+        scope2 = extract_scope(text,2)
+
+        scope3 = extract_scope(text,3)
+
+        revenue = extract_revenue(text)
+
+        intensity = carbon_intensity(scope1, revenue)
+
+        index_doc(text,{
+            "company":company,
+            "sector":sector,
+            "scope1":scope1,
+            "scope2":scope2,
+            "scope3":scope3,
+            "revenue":revenue,
+            "carbon_intensity":intensity
+        })
+
+        build_graph([text])
+
+        add_claim(company,"low emissions",f"Scope1 {scope1}")
+
+        st.success("Report processed successfully")
+
+        df = pd.DataFrame({
+
+            "Scope":["Scope1","Scope2","Scope3"],
+
+            "Value":[scope1,scope2,scope3]
+
+        })
+
+        fig = px.bar(
+
+            df,
+
+            x="Scope",
+
+            y="Value",
+
+            color="Scope",
+
+            title="Emission Breakdown"
+
+        )
+
+        st.plotly_chart(fig,use_container_width=True)
+
+        st.metric("Carbon Intensity", intensity)
+
+
+st.header("🔎 HyperRAG ESG Query")
+
+query = st.text_input("Ask ESG question")
+
+if st.button("Run Query"):
+
+    result = answer(query)
+
+    st.text(result)
+
+
+st.header("🚨 Greenwashing Detection")
+
+if st.button("Check Greenwashing"):
+
+    issues = detect_greenwashing()
+
+    if issues:
+
+        st.error(f"Potential contradictions detected: {issues}")
+
+    else:
+
+        st.success("No contradictions detected")