Llama3 Full Rag - API with Ollama, LangChain and ChromaDB with Flask API and PDF upload

Get ready to dive into the world of RAG with Llama3! Learn how to set up an API using Ollama, LangChain, and ChromaDB, all while incorporating Flask and PDF uploads. Subscribe now for more exciting tutorials like this one!
Complete Llama3 PDF RAG (Retrieval Augemented Generation) API application. Python Flask API, Ollama, Llama3, LangChain and ChromaDB with PDF integration.

Complete system from start to finish as a Rest API for uploading PDF documents and asking questions againsts the document.

This video starts from teh basics of Ollama with Llama3 and build son your knowledge to create a complete end to end API solution.

Connect this to your UI for a ready to go system.

I've been building large scale systems fo over 15 years and wanted so share some of my experience on new Open Source Technologies.

Ollama and Llama3 combined with LangChain and ChromeDB are some game changers in teh AI field today.

Please follow me and check out my other vidoes on AI as well as Java Spring Boot Integrations.

#AI #Python #Programming

[lesptitsoiseaux]

We're about the same age. This is by far the best tutorial on the subject I've seen in a while. Thank you very much for your conscientiousness and dedication to quality! Cheers from Vancouver :)

[ExpertKNowledgeGroup]

Amazing step by step with complete explenation of what and why. Thanks!

[salamina_]

Very helpful content. Great tutorial on putting it all together in a RAG application. Thank you for taking the time to put this together and sharing it!

[Dani-cgyc]

Literally just what I was looking for. Thx so much for the video. It's difficult to find good information about doing projects with llama models, every use case is for openai. Again, thx a lot!!!!

[RobynLeSueur]

Very useful, criminally underviewed too.

[ruggerovecchio]

Congratulations, this is really an exhaustive explanation on how to setup the necessary architecture for exposing AI, LLM based services from a private cloud. Thank you for sharing!

[chidi]

This is awesome! Thank you very much for posting this!👏

[deathdefier]

I was looking for just this, thank you sir you're a wonderful human being! Thank you so much for this content! <3

[TokyoNeko]

Awesome with all of the latest LLM and APIs!

[raymondcswong]

Thank you very much! I learnt a lot following your step-by-step guidance! Especially how you solve the 'errors', cheers!

[erictidmore]

Dude do you sell any training. Excellent video

[singar]

Thank you for making this video. It was so helpful :)

[hebertgodoy]

Excellent. Thanks very much for sharing

[yusuf]

Thats way man, great tutorial. Thank you

[davidtindell]

Thank You Again. Perhaps a follow-on Vid where you make this a full Flask App with a responsive Web-GUI ?!?!?

[juliandarley]

thank you very much. i would add that adjusting the hyperparameters `k`, `score_threshold` and the `PromptTemplate` custom instruction can make a huge difference to the answer - by changing these i got the system to stop producing useless, inaccurate verbiage and give short, accurate, useful answers. it was like comparing a 1B early LLM with GPT4o.

[Dan-mmyd]

very useful vedio, thanks for sharing！

[utrkdfq]

nice starter tutorial that does not involve openai!

[raghavareddy]

Really loved can you add delete endpoint to delete from both pdf folder and chroma db

[Pekarnick]

Very good video, it helped me a lot with something I was looking for to integrate with a chatbot, but I had to adjust the search_kwargs a little to 3 because it got dizzy with the result. I would be happy to see how to delete added PDFs in Chroma, greetings and thank you very much for this content