cleaned with black
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801289d123
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26
app.py
26
app.py
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@ -19,6 +19,7 @@ index = pinecone.Index("movies")
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app = Flask(__name__, template_folder="./templates")
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def title2trakt_id(title: str, df=df):
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# Matches Exact Title, Otherwise Returns None
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records = df[df["title"].str.lower() == title.lower()]
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@ -29,27 +30,36 @@ def title2trakt_id(title: str, df=df):
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else:
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return 2, records.trakt_id.tolist()
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def get_vector_value(trakt_id: int):
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fetch_response = index.fetch(ids=[str(trakt_id)])
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return fetch_response["vectors"][str(trakt_id)]["values"]
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def query_vectors(vector: list, top_k: int = 20, include_values: bool = False, include_metada: bool = True):
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def query_vectors(
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vector: list,
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top_k: int = 20,
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include_values: bool = False,
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include_metada: bool = True,
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):
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query_response = index.query(
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queries=[
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(vector),
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],
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top_k=top_k,
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include_values=include_values,
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include_metadata=include_metada
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include_metadata=include_metada,
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)
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return query_response
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def query2ids(query_response):
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trakt_ids = []
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for match in query_response["results"][0]["matches"]:
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trakt_ids.append(int(match["id"]))
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return trakt_ids
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def get_deets_by_trakt_id(df, trakt_id: int):
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df = df[df["trakt_id"] == trakt_id]
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return {
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@ -58,9 +68,10 @@ def get_deets_by_trakt_id(df, trakt_id: int):
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"runtime": int(df.runtime.values[0]),
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"year": int(df.year.values[0]),
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"trakt_id": trakt_id,
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"tagline": df.tagline.values[0]
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"tagline": df.tagline.values[0],
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}
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@app.route("/similar")
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def get_similar_titles():
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trakt_id = request.args.get("trakt_id")
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@ -111,11 +122,14 @@ def get_similar_titles():
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if cur_res >= max_res:
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break
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deets = get_deets_by_trakt_id(df, trakt_id)
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if ((deets["year"]>=min_year) and (deets["year"]<=max_year)) and ((deets["runtime"]>=minRuntime) and (deets["runtime"]<=maxRuntime)):
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if ((deets["year"] >= min_year) and (deets["year"] <= max_year)) and (
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(deets["runtime"] >= minRuntime) and (deets["runtime"] <= maxRuntime)
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):
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results.append(deets)
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cur_res += 1
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return render_template("show_results.html", deets=results)
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@app.route("/", methods=("GET", "POST"))
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def find_similar_title():
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if request.method == "GET":
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@ -125,7 +139,9 @@ def find_similar_title():
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code, values = title2trakt_id(to_search_title)
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print(f"Code {code} for {to_search_title}")
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if code == 0:
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search_results = process.extract(to_search_title, movie_titles, scorer=fuzz.token_sort_ratio)
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search_results = process.extract(
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to_search_title, movie_titles, scorer=fuzz.token_sort_ratio
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)
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to_search_titles = []
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to_search_ids = []
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results = []
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@ -25,15 +25,17 @@ movies_table = Table(
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Column("votes", Integer),
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Column("comment_count", Integer),
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Column("tagline", String),
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Column("embeddings", PickleType)
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Column("embeddings", PickleType),
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)
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def init_db_stuff(database_url: str):
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engine = create_engine(database_url)
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meta.create_all(engine)
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Session = sessionmaker(bind=engine)
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return engine, Session
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"""
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movie = {
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"title": movie["movie"]["title"],
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15
db2pc.py
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db2pc.py
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@ -20,7 +20,15 @@ model = SentenceTransformer("paraphrase-multilingual-MiniLM-L12-v2")
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batch_size = 32
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df = pd.read_sql("Select * from movies", engine)
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df["combined_text"] = df["title"] + ": " + df["overview"].fillna('') + " - " + df["tagline"].fillna('') + " Genres:- " + df["genres"].fillna('')
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df["combined_text"] = (
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df["title"]
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+ ": "
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+ df["overview"].fillna("")
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+ " - "
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+ df["tagline"].fillna("")
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+ " Genres:- "
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+ df["genres"].fillna("")
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)
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print(f'Length of Combined Text: {len(df["combined_text"].tolist())}')
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@ -30,8 +38,5 @@ for x in tqdm(range(0,len(df),batch_size)):
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sentences = df["combined_text"][x : x + batch_size].tolist()
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embeddings = model.encode(sentences)
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for idx, value in enumerate(trakt_ids):
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to_send.append(
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(
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str(value), embeddings[idx].tolist()
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))
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to_send.append((str(value), embeddings[idx].tolist()))
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index.upsert(to_send)
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26
main.py
26
main.py
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@ -25,7 +25,7 @@ database_url = "sqlite:///jlm.db"
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headers = {
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"Content-Type": "application/json",
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"trakt-api-version": "2",
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"trakt-api-key": trakt_id
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"trakt-api-key": trakt_id,
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}
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params = {
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@ -34,7 +34,7 @@ params = {
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"page": page,
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"extended": extended,
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"limit": limit,
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"languages": languages
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"languages": languages,
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}
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@ -53,12 +53,11 @@ def create_movie_dict(movie: dict):
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"rating": int(m["rating"]),
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"votes": int(m["votes"]),
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"comment_count": int(m["comment_count"]),
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"tagline": m["tagline"]
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"tagline": m["tagline"],
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}
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return movie_dict
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params["limit"] = 1
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res = requests.get(f"{api_base}/search/movie", headers=headers, params=params)
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total_items = res.headers["x-pagination-item-count"]
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@ -111,11 +110,20 @@ for page in tqdm(range(1,max_requests+10)):
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for movie in movies:
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with conn.begin() as trans:
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stmt = insert(movies_table).values(
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trakt_id=movie["trakt_id"], title=movie["title"], genres=" ".join(movie["genres"]),
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language=movie["language"], year=movie["year"], released=movie["released"],
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runtime=movie["runtime"], country=movie["country"], overview=movie["overview"],
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rating=movie["rating"], votes=movie["votes"], comment_count=movie["comment_count"],
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tagline=movie["tagline"])
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trakt_id=movie["trakt_id"],
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title=movie["title"],
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genres=" ".join(movie["genres"]),
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language=movie["language"],
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year=movie["year"],
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released=movie["released"],
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runtime=movie["runtime"],
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country=movie["country"],
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overview=movie["overview"],
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rating=movie["rating"],
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votes=movie["votes"],
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comment_count=movie["comment_count"],
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tagline=movie["tagline"],
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)
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try:
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result = conn.execute(stmt)
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trans.commit()
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@ -10,7 +10,9 @@ from sqlalchemy import func
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movie_name = "Forrest Gump"
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with engine.connect() as conn:
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movie_deets = select(movies_table).filter(func.lower(movies_table.columns.title)==func.lower(movie_name))
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movie_deets = select(movies_table).filter(
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func.lower(movies_table.columns.title) == func.lower(movie_name)
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)
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result = conn.execute(movie_deets)
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for row in result:
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print(row)
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