Ollama Python Library Released! How to implement Ollama RAG?

🌟 Welcome to an exciting journey where coding meets artificial intelligence! In today's tutorial, we delve into the world of Python and JavaScript, showcasing how effortlessly we can integrate Ollama into our applications. 🚀 Ollama Python Library and Ollama RAG Implementation.

🔍 What You'll Learn:

0:00 Introduction to Ollama integration in Python & JavaScript
0:34 Step-by-step guide to creating a RAG application using Ollama
1:02 Setting up your Python environment for Ollama
1:20 Implementing Ollama's chat function in Python
2:06 Utilizing multimodel capabilities with Ollama in your projects
3:30 Creating an Ollama RAG using various libraries and databases
6:02 Running the RAG chain and exploring its capabilities
7:15 Adding a user-friendly interface with Gradio

👨‍💻 Whether you're a beginner or an experienced developer, this tutorial offers valuable insights into leveraging Ollama for AI applications. We'll explore how to create a RAG (Retrieval-Augmented Generation) application, use Mistal Lang chain, and Chroma DB to enhance the functionality of your AI projects.

💡 Key Highlights:
Integrating Ollama in Python and JavaScript applications
Creating a responsive RAG application
Using Chroma DB for storing embeddings
Practical demonstration of a multimodal approach using Ollama
Building and running a RAG chain query
Developing a user interface with Gradio for interactive querying

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[hand-eye]

i have probably watch over 300 hours of content on programming and ai systems/open source projects and this is hands down one of the most clear, concise, and follow-able pieces of content i have ever seen on the topic. I leave this video well informed on the beginning of creating interfaces with ollama. Happily subbed and eagerly looking for more. Thank you! all that usefulness in 8mins! wow!

[cosmosuncle]

This is fantastic. It's amazing how fast technology is moving. The libraries already need updating 3 months later. The code works great but I had to roll back my installation of pydantic to version 1.8.2

[Enkumnu]

Thank you very much. Your content is very relevant. Help me a lot.

[rgm]

I just tried this and its amazing work!

[mbottambotta]

such a useful video, thank you! At 3:25 you show how ollama is able to generate embeddings using `ollama.embeddings()`. then, in the project, you revert to the langchain function. do you know if it's possible to use the ollama function for this?

[spdnova]

is there a way to use other settings than temperature? like max lengh response or like system prompt?

[krishnagupta-tich]

Fantastic Brother. Thanks for sharing ❤. Just one question, we have lots of open-source llm chatbot model. How do we know which one best opensource for general purpose questions answers bot?

[morespinach]

Any comparison of the various libraries now? For example, for finding contextual answers from our own diverse PDFs?

[mxmerce]

Thank you for the great video, it was very helpful. I'm embedding a large markdown instead of a website. I have a question for you, that may be a good video idea for you. Since Chromadb is persistent and reloading the vectors is an expensive process for large sources. What would be the best means to, using your video as an example, only reload a website if it does not already exist, or x amount of days has past since last embedding. How do you retrieve/update an existing entry? Thanks again!

[manueljan]

Thanks! Can you do a video on how LLM can update (write) a web form based on prompt data. This can be really useful to use LLM to update automatically company web tools and remove human effort for the data entry

[svb]

what is the performance like with cpu only?

[adventurelens]

Okay, now I think we're onto something with this. Not sure what yet, but I can feel it, haha!

[thrashassault]

Awesome content, i want to change to pdf version also

[atrocitus]

is there an option to stream the output?

[naveenpandey]

Can we give custom prompt and data like json format

[HyperUpscale]

@Mervin is going GOD MODE with this video 💥🔥

🤯 My mind can't comprehend how valuable this 8 minute video is 🤯

[halfbathbrewing]

I have run into problems using langchain Ollama embeddings and chromaDB before. If you do the same thing as in this video but use a PDF loader to load a large PDF. It comes back with bad results. I swapped out the embeddings for a hugging face embeddings model and everything started working.

[moresignal]

Quality content amongst a sea of copycats, clickbait and hyperbole. No fluff, just stuff. Well done!

[chukypedro]

What's the difference between this RAG video and building RAG with Langchain and using Ollama as the LLM. Is the inference speed same as using openai for RAG?

[madaebnana]

Excellent! I loved it .. wondering if that can be tweaked so instead retrieving data from URL, would be retrieving data from a database? my use case based on applying this scenario on ERP/CRM system where users can get quick and accurate insights in real-time. Thanks in advance .. keep it up the good work, mate! cheers