diff options
author | navanchauhan <navanchauhan@gmail.com> | 2022-05-22 11:40:41 -0600 |
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committer | navanchauhan <navanchauhan@gmail.com> | 2022-05-22 11:40:41 -0600 |
commit | 3c506e9c5d0408a1ba0fa637d467a2a8a821da1f (patch) | |
tree | c1b8d562b31272d8f5f4779940a1a6a742b1f695 /app.py | |
parent | 04e733f16889494d23cf3fedaf9f281ddc057fff (diff) |
added flask app
Diffstat (limited to 'app.py')
-rw-r--r-- | app.py | 163 |
1 files changed, 163 insertions, 0 deletions
@@ -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) |