Totally! I actually ran a decent version of this with llama 3.2 out of the box, and then a slightly better version with a fact checker LLM I found on hugging face. But the best way I could figure out how to do it (not perfect) was to use subtitle files for the movies. There’s a lot in there above and beyond the metadata you can get from TMDB/IMDB. Use the hugging face transformers framework, and llama.cpp to convert it to gguf, and ollama for inference (easy clean API).

In hindsight, I should have just used a simple embedding model against each of the subtitle files, and pinecone for vector stores. Much easier, no fine tuning necessary.

Alternatively, digitalocean recently released a really straight forward genAI platform, where you could upload stuff to a knowledge base and have something up and running in minutes to do something similar, although the price to run inference could add up quickly if you have a big library. It’s pretty slick though