Create app.py

app.py

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+import streamlit as st
+from tabulate import tabulate
+from eventbrite_scrapper import Eventbrite
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+import numpy as np
+
+# Initialize Eventbrite API Client
+client = Eventbrite()
+
+# Fetch events
+def fetch_events():
+    return client.search_events.get_results(
+        region="ca--los-angeles",  # Can change region
+        dt_start="2024-11-28",
+        dt_end="2024-12-25",
+        max_pages=4,
+    )
+
+# Define Event RAG Pipeline
+class EventbriteRAGPipeline:
+    def __init__(self, events, embedding_model='all-MiniLM-L6-v2'):
+        self.events = events
+        self.model = SentenceTransformer(embedding_model)
+        self.event_embeddings = self._compute_embeddings()
+
+    def _compute_embeddings(self):
+        def event_to_text(event):
+            return " ".join(filter(None, [event.name, event.short_description]))
+        return self.model.encode([event_to_text(event) for event in self.events])
+
+    def query_events(self, query, top_k=5):
+        query_embedding = self.model.encode(query).reshape(1, -1)
+        similarities = cosine_similarity(query_embedding, self.event_embeddings)[0]
+        top_indices = similarities.argsort()[-top_k:][::-1]
+        return [self.events[idx] for idx in top_indices]
+
+class EventEvaluator:
+    def __init__(self, pipeline):
+        self.pipeline = pipeline
+
+    def evaluate_query(self, query):
+        """Evaluate a single query and return results."""
+        top_events = self.pipeline.query_events(query)
+        results = []
+        for event in top_events:
+            result = {
+                "Event Name": event.name,
+                "Online Event": event.is_online_event,
+                "Start Time": event.start_datetime,
+                "Venue Address": event.primary_venue.address.address_1,
+                "Venue Name": event.primary_venue.name,
+                "Tickets URL": event.tickets_url,
+                "Language": event.language,
+                "Description": event.short_description,
+                "Categories": [tag.text for tag in event.tags_categories],
+            }
+            results.append(result)
+        return results
+
+# Streamlit UI
+st.title("Eventbrite Event Search")
+query = st.text_input("Enter event type (e.g., concerts, hackathons, conferences)")
+if st.button("Search"):
+    sample_events = fetch_events()
+    rag_pipeline = EventbriteRAGPipeline(sample_events)
+    evaluator = EventEvaluator(rag_pipeline)
+    results = evaluator.evaluate_query(query)
+    
+    if results:
+        table = [
+            [
+                result["Event Name"],
+                result["Online Event"],
+                result["Start Time"],
+                result["Venue Address"],
+                result["Venue Name"],
+                result["Description"],
+                result["Tickets URL"],
+                result["Language"],
+                result["Categories"],
+            ]
+            for result in results
+        ]
+        st.text(tabulate(table, headers=["Event Name", "Online Event", "Start Time", "Venue Address", "Venue Name", "Description", "Tickets URL", "Language", "Categories"], tablefmt="grid"))
+    else:
+        st.write("No results found.")