Build the fastest AI Chatbot using Groq Chat: Insane LLM Speed 🔥

In this detailed tutorial, I guide you through the exciting process of building one of the fastest AI chatbots using Groq Chat, powered by the revolutionary Tensor Streaming Processor (TSP) technology developed by Groq. This technology enables unparalleled processing speeds for machine learning workloads, especially for complex Natural Language Processing (NLP) tasks. Groq Chat, built atop this cutting-edge hardware, stands out by providing real-time responses to natural language queries, making it an exceptional tool for a myriad of applications including customer service, technical support, and sales.

Throughout this video, I delve into how to utilize Streamlit to create a user-friendly interface for interacting with Groq Chat. By integrating a Large Language Model, Mixtral 8x7b, and leveraging LangChain for advanced functionalities, I showcase the process of developing a chatbot that not only understands and responds to user queries with incredible speed but also handles a vast volume of interactions simultaneously without breaking a sweat.

Whether you're aiming to enhance customer engagement, provide swift technical support, or boost your sales efforts through real-time interactions, this tutorial equips you with the knowledge to leverage the power of Groq's TSP technology.

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[brendancoram]

Amazing, thanks so much for posting along with the resources.

[jorgerios]

This is what I was waiting for, thank you sir!

[tintintintin]

good job, brother! yur channel is amazing!

[jorgerios]

My contribution to newcomers based on my experience. Put a comma in line 20 after 'Choose a model'. In line 21 write 'mixtral' without the capital "M" or the model would not be recognized. At least this is what worked for me after struggling a bit.

[criticalnodecapital]

Man you are the best in teaching. I’m proficient in langraph.

[hassubalti]

great sir... please make video to create custom dataset of question answer .. you said you will make a video.

[devadriptajadhav]

Thankyou so much! Can you make some chatbot using Groq with RAG?

[kakashi_vladivostok]

Is your "network url" working on other device like mobile?

[farhanachowdhury]

how to use groq for this.. I'm not finding any groq method for embeddings

[parkersettle]

@AIAnytime anyway you can help me set up function calling for a project I am working on?

[drlordbasil]

I'm always using too many TPM, but adding timers work for me. Love the guide<3
I can't wait for their unlimited/paid API to come out which will be HUGE.

[khalidkifayat]

Nice one.
question was this is locally installed, how to move it to production OR give it as a client project to client.
Thanks

[asmitamondal]

Is this an api that can be used freely? A few months ago you created a prompt to ppt using oneapi. Is oneapi free to use the way you used it in that video? And is this free to use too?

[muhammadatif]

How can we train it on particular data, such as when a company has its information and wants to convert that into a chatbot? Can we do it with this?

[chitranshtiwari]

sir i wanted to make web app using medical bot as you shown in your medical bot video but models are large upto 3-4 gb so how can i provide such facility in web app

[patrykh]

can you add pdf reader to that project?

[wmhyceo]

please tell me how to stream response using ollama in rag app.

this without using rag and it successfully stream the response:
response = ollama.chat(model='llama2', messages=[ {'role': 'user', 'content': 'your_question', }, ])


and this using rag but it not stream the response:
ollama = Ollama(model="llama2")
qachain=RetrievalQA.from_chain_type(ollama,
qachain.invoke({"query": your_question})