Create app.py

app.py

@@ -0,0 +1,55 @@
+# app.py
+import streamlit as st
+import spacy
+from neo4j import GraphDatabase
+import matplotlib.pyplot as plt
+import networkx as nx
+
+# Neo4j credentials
+uri = "neo4j+s://ff701b1c.databases.neo4j.io"
+username = "neo4j"
+password = "your_neo4j_password_here"
+
+# Connect to Neo4j
+driver = GraphDatabase.driver(uri, auth=(username, password))
+
+def extract_triples(text):
+    nlp = spacy.load("en_core_web_sm")
+    doc = nlp(text)
+    triples = []
+    for sent in doc.sents:
+        subjects = [tok for tok in sent if "subj" in tok.dep_]
+        verbs = [tok for tok in sent if tok.pos_ == "VERB"]
+        objects = [tok for tok in sent if "obj" in tok.dep_]
+        for subj in subjects:
+            for verb in verbs:
+                for obj in objects:
+                    triples.append((subj.text, verb.lemma_, obj.text))
+    return triples
+
+def show_graph(triples):
+    G = nx.DiGraph()
+    for s, p, o in triples:
+        G.add_node(s)
+        G.add_node(o)
+        G.add_edge(s, o, label=p)
+    pos = nx.spring_layout(G)
+    plt.figure(figsize=(10, 8))
+    nx.draw(G, pos, with_labels=True, node_color='skyblue', node_size=2000, font_size=10)
+    nx.draw_networkx_edge_labels(G, pos, edge_labels={(u,v):d['label'] for u,v,d in G.edges(data=True)})
+    st.pyplot(plt)
+
+# === Streamlit UI ===
+st.title("🧠 Knowledge Graph Generator")
+
+text_input = st.text_area("Paste your text here", height=200)
+
+if st.button("Generate Graph"):
+    if text_input:
+        triples = extract_triples(text_input)
+        st.write("### Extracted Triples")
+        for t in triples:
+            st.write("🔗", t)
+        show_graph(triples)
+    else:
+        st.warning("Please enter some text.")