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authornavanchauhan <navanchauhan@gmail.com>2022-05-22 11:40:41 -0600
committernavanchauhan <navanchauhan@gmail.com>2022-05-22 11:40:41 -0600
commit3c506e9c5d0408a1ba0fa637d467a2a8a821da1f (patch)
treec1b8d562b31272d8f5f4779940a1a6a742b1f695 /app.py
parent04e733f16889494d23cf3fedaf9f281ddc057fff (diff)
added flask app
Diffstat (limited to 'app.py')
-rw-r--r--app.py163
1 files changed, 163 insertions, 0 deletions
diff --git a/app.py b/app.py
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index 0000000..fbd5c7d
--- /dev/null
+++ b/app.py
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+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)