From 3c506e9c5d0408a1ba0fa637d467a2a8a821da1f Mon Sep 17 00:00:00 2001
From: navanchauhan <navanchauhan@gmail.com>
Date: Sun, 22 May 2022 11:40:41 -0600
Subject: added flask app

---
 app.py | 163 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 163 insertions(+)
 create mode 100644 app.py

(limited to 'app.py')

diff --git a/app.py b/app.py
new file mode 100644
index 0000000..fbd5c7d
--- /dev/null
+++ b/app.py
@@ -0,0 +1,163 @@
+from flask import Flask, render_template, request, url_for
+from database import *
+import pandas as pd
+from fuzzywuzzy import process, fuzz
+import os
+import pinecone
+
+PINECONE_KEY = os.getenv("PINECONE_API_DEFAULT")
+
+database_url = "sqlite:///jlm.db"
+
+engine, Session = init_db_stuff(database_url)
+
+df = pd.read_sql("Select * from movies", engine)
+movie_titles = df["title"].tolist()
+
+pinecone.init(api_key=PINECONE_KEY, environment="us-west1-gcp")
+index = pinecone.Index("movies")
+
+app = Flask(__name__, template_folder="./templates")
+
+def title2trakt_id(title: str, df=df):
+    #Matches Exact Title, Otherwise Returns None
+    records = df[df["title"].str.lower() == title.lower()]
+    if len(records) == 0:
+        return 0, None
+    elif len(records) == 1:
+        return 1, records.trakt_id.tolist()[0]
+    else:
+        return 2, records.trakt_id.tolist() 
+
+def get_vector_value(trakt_id: int):
+  fetch_response = index.fetch(ids=[str(trakt_id)])
+  return fetch_response["vectors"][str(trakt_id)]["values"]
+
+def query_vectors(vector: list, top_k: int = 20, include_values: bool = False, include_metada: bool = True):
+  query_response = index.query(
+      queries=[
+          (vector),
+      ],
+      top_k=top_k,
+      include_values=include_values,
+      include_metadata=include_metada
+  )
+  return query_response
+
+def query2ids(query_response):
+  trakt_ids = []
+  for match in query_response["results"][0]["matches"]:
+    trakt_ids.append(int(match["id"]))
+  return trakt_ids
+
+def get_deets_by_trakt_id(df, trakt_id: int):
+  df = df[df["trakt_id"]==trakt_id]
+  return {
+      "title": df.title.values[0],
+      "overview": df.overview.values[0],
+      "runtime": int(df.runtime.values[0]),
+      "year": int(df.year.values[0]),
+      "trakt_id": trakt_id,
+      "tagline": df.tagline.values[0]
+  }
+
+@app.route("/similar")
+def get_similar_titles():
+    trakt_id = request.args.get("trakt_id")
+    filterin = request.args.get("filter")
+
+    min_year = request.args.get("minYear")
+    if min_year == None:
+        min_year = 1900
+    else:
+        try:
+            min_year = int(min_year)
+        except TypeError:
+            min_year = 1900
+    max_year = request.args.get("maxYear")
+    if max_year == None:
+        max_year = 2021
+    else:
+        try:
+            max_year = int(max_year)
+        except TypeError:
+            max_year = 2021
+    minRuntime = request.args.get("minRuntime")
+    if minRuntime == None:
+        minRuntime = 70
+    else:
+        try:
+            minRuntime = int(minRuntime)
+        except TypeError:
+            minRuntime = 70
+    maxRuntime = request.args.get("maxRuntime")
+    if maxRuntime == None:
+        maxRuntime = 220
+    else:
+        try:
+            maxRuntime = int(maxRuntime)
+        except TypeError:
+            maxRuntime = 220
+    vector = get_vector_value(trakt_id)
+    movie_queries = query_vectors(vector, top_k = 69)
+    movie_ids = query2ids(movie_queries)
+    results = []
+    #for trakt_id in movie_ids:
+    #    deets = get_deets_by_trakt_id(df, trakt_id)
+    #    results.append(deets)
+    max_res = 30
+    cur_res = 0
+    for trakt_id in movie_ids:
+        if cur_res >= max_res:
+            break
+        deets = get_deets_by_trakt_id(df, trakt_id)
+        if ((deets["year"]>=min_year) and (deets["year"]<=max_year)) and ((deets["runtime"]>=minRuntime) and (deets["runtime"]<=maxRuntime)):
+            results.append(deets)
+            cur_res += 1
+    return render_template("show_results.html",deets=results)
+
+@app.route("/",methods=("GET","POST"))
+def find_similar_title():
+    if request.method == "GET":
+        return render_template("index.html")
+    elif request.method == "POST":
+        to_search_title = request.form["title"]
+        code, values = title2trakt_id(to_search_title)
+        print(f"Code {code} for {to_search_title}")
+        if code == 0:
+            search_results = process.extract(to_search_title, movie_titles, scorer=fuzz.token_sort_ratio)
+            to_search_titles = []
+            to_search_ids = []
+            results = []
+            for search_result in search_results:
+                search_title, score = search_result
+                to_search_titles.append(search_title)
+            for to_search in to_search_titles:
+                code, values = title2trakt_id(to_search)
+                if code == 1:
+                    to_search_ids.append(values)
+                else:
+                    for trakt_id in values:
+                        to_search_ids.append(trakt_id)
+            for trakt_id in to_search_ids:
+                deets = get_deets_by_trakt_id(df, int(trakt_id))
+                deets["trakt_id"] = trakt_id
+                results.append(deets)
+            return render_template("same_titles.html",deets=results)
+
+        elif code == 1:
+            vector = get_vector_value(values)
+            movie_queries = query_vectors(vector)
+            movie_ids = query2ids(movie_queries)
+            results = []
+            for trakt_id in movie_ids:
+                deets = get_deets_by_trakt_id(df, trakt_id)
+                results.append(deets)
+            return render_template("show_results.html",deets=results)
+        else:
+            results = []
+            for trakt_id in values:
+                deets = get_deets_by_trakt_id(df, int(trakt_id))
+                deets["trakt_id"] = trakt_id
+                results.append(deets)
+            return render_template("same_titles.html",deets=results)
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