Create app.py

app.py

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+import streamlit as st
+import spacy
+from spacy import displacy
+import json
+import subprocess
+subprocess.run(["python", "-m", "spacy", "download", "en_core_web_md"])
+
+    
+# Initialize spaCy
+nlp = spacy.load("en_core_web_md")
+
+# Define sample data
+data = {
+    "fruit": ["apple", "pear", "orange"],
+    "vegetable": ["broccoli", "spinach", "tomato"],
+    "meat": ['beef', 'pork', 'turkey', 'duck']
+}
+
+# Streamlit app
+st.title('Named Entity Recognition with spaCy')
+
+user_input = st.text_area("Enter text:", "")
+
+if st.button("Process"):
+    if user_input:
+        # Process the text
+        doc = nlp(user_input)
+        
+        # Visualization options
+        options = {
+            "colors": {"fruit": "darkorange", "vegetable": "limegreen", "meat": "salmon"},
+            "ents": ["fruit", "vegetable", "meat"],
+        }
+
+        # JSON serialization with only entity and type
+        result_dict = {'entities': []}
+        
+        for ent in doc.ents:
+            ent_data = {
+                'entity': ent.text,
+                'type': ent.label_
+            }
+            result_dict['entities'].append(ent_data)
+        
+        result_json = json.dumps(result_dict, indent=4)
+
+        # Display results
+        st.subheader("Named Entities")
+        html = displacy.render(doc, style="ent", page=True, minify=True)
+        st.write(html, unsafe_allow_html=True)
+        st.subheader("Entities in JSON format")
+        st.json(result_json)
+