Chatting with my movie-advisor using a langchain agent, RAG tools, Xata PostreSQL and TMDB

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Chatting with my movie-advisor using a langchain agent, RAG tools, Xata PostreSQL and TMDB

UpdatedAugust 10, 2024

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Chatting with my movie-advisor using a langchain agent, RAG tools, Xata PostreSQL and TMDB

Alexandre Donciu-Julin

Innovative software engineer with over 15 years of solid technical expertise in AI, computer vision and software development.

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The Breakfast Code ☕

13 posts

AI Software Engineer | Technial Director | Python Allrounder

But first, coffee ☕

https://youtu.be/_nmiwgwRHxM

Github repo

This is a demo of my movie-advisor project: I created a chatbot driven by a langchain agent and RAG tools.

The agent is handling all conversations between me and the LLM. Based on my queries, it will search for preferences and update my watch lists stored on the postgreSQL database Xata, or fetch missing information from the movie database TMDB.

I am using my other project ai_chatbot as submodule to initialise the agent and handle voice conversations using Google STT and Edge TTS engines.

Tools: Langchain | Xa ta | TMDB

Don't miss my other AI-related articles on my dev blog!

Music by Denys Kyshchuk from Pixabay.

#ai #llm #gpt-4 #rag #langchain #postgresql #xata

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I am an innovative software engineer with expertise in generative AI and machine learning frameworks, eager to grow my skills within a talented team and work together toward impactful company goals. I bring a unique blend of creativity and technical skill to address complex challenges, driven by a commitment to shaping a better future.

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