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2218f3b 52e0b19 2218f3b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | from flask import Flask, request, jsonify
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
app = Flask(__name__)
# Load Hugging Face DialoGPT model
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
# Simulated new releases (could be replaced with TMDB API or scraped data)
latest_releases = [
{
"title": "Neon Drift",
"genre": "Sci-Fi | Netflix | April 10, 2025",
"description": "A futuristic racer enters a deadly tournament to save his sister from a megacorp."
},
{
"title": "The Forgotten Bloom",
"genre": "Drama | Prime Video | April 9, 2025",
"description": "A woman unearths family secrets while restoring her grandmother’s abandoned greenhouse."
},
{
"title": "Shadow Protocol",
"genre": "Action-Thriller | Disney+ | April 12, 2025",
"description": "An ex-agent is forced back into action to prevent a digital war between superpowers."
}
]
# Helper function to generate a reply
def generate_reply(user_input):
new_user_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
bot_input_ids = new_user_input_ids
chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
reply = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
return reply
@app.route("/chat", methods=["POST"])
def chat():
user_message = request.json.get("message", "").lower()
if "new" in user_message or "release" in user_message:
movie_list = "\n\n".join([
f"🎬 *{movie['title']}*\n{movie['genre']}\n_{movie['description']}_"
for movie in latest_releases
])
return jsonify({"response": f"Here are the latest releases:\n\n{movie_list}"})
elif any(title.lower() in user_message for title in [m["title"].lower() for m in latest_releases]):
movie = next(m for m in latest_releases if m["title"].lower() in user_message)
return jsonify({
"response": f"🎬 *{movie['title']}*\n{movie['genre']}\n\n_{movie['description']}_"
})
else:
reply = generate_reply(user_message)
return jsonify({"response": reply})
if __name__ == "__main__":
app.run(debug=True)
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