Automate Finance Tasks: Build Fake OpenAI Server with llama CPP
- Authors
- Published on
- Published on
In this exhilarating episode by Nicholas Renotte, he delves into the thrilling world of setting up a counterfeit OpenAI server using llama CPP. Picture this: you're revving up your desktop computer, ready to unleash the power of AI on your terms, without being tethered to OpenAI's API. With llama CPP at the helm, you can harness the might of colossal language models like MixT and Llama, all without the need for a fancy GPU. It's like taking the wheel of a roaring sports car on a winding mountain road - pure freedom.
Renotte uncovers a hidden gem within the llama CPP library - a function that conjures up a server mirroring OpenAI's capabilities. This means you can seamlessly swap out OpenAI for llama CPP, injecting a dose of AI wizardry into your finance-related tasks. But hold onto your seat because the adrenaline-fueled journey doesn't stop there. Renotte raises the stakes, questioning whether this homegrown solution can match the speed and performance of the mighty GPT-4. He pushes the boundaries, exploring advanced techniques like function calling and multi-model integration, all while clocking in hours of intense experimentation and coding wizardry.
Buckle up as Renotte breaks down the process into five turbocharged steps, kicking off with the crucial task of firing up the server. The thrill intensifies as he guides you through cloning llama CPP, building the package, and installing essential Python libraries like OpenAI, Llama CP Python, and more. The excitement peaks as Renotte demonstrates how to start the server, choosing the model path and optimizing performance by offloading layers to a GPU for a speed boost that'll leave you breathless. And just when you think you've reached top gear, Renotte shifts into overdrive, showcasing how to craft a Python script to interact with the server, sending prompts and receiving lightning-fast responses - all with a dash of finance flair.
As the dust settles and the engine hums with newfound power, Renotte unveils the fruits of his labor. The Python script springs to life, engaging the fake OpenAI server in a riveting dialogue about finance metrics like return on investment. The server's response, a symphony of AI-generated insights, underscores the limitless possibilities of this DIY AI adventure. Renotte's journey is a testament to the thrill of pushing boundaries, embracing innovation, and steering your AI destiny with the wind in your sails.
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Watch How to Build a Fake OpenAI Server (so you can automate finance stuff) on Youtube
Viewer Reactions for How to Build a Fake OpenAI Server (so you can automate finance stuff)
Using the "—chat_format llama-2" flag when running the server
Building apps relying on LLMs
Working with open-source LLMs and deployment challenges
Setting up servers with llama-cpp-python[server] or llama-cpp
Creating AI for trading patterns
Incorporating Multi-Agent Systems in finance projects
Request for a bigger video on the topic
Difference between approaches vs using Langchain
Request for a hardcore function call video
Collaboration suggestions and making money with AI
Related Articles
Revolutionizing AI: Open-Source Model App Challenges OpenAI
Nicholas Renotte showcases the development of a cutting-edge large language model app, comparing it to OpenAI models. Through tests and comparisons, the video highlights the app's capabilities in tasks like Q&A, email writing, and poem generation. Exciting insights into the future of AI technology are revealed.
Revolutionizing Software: Building Auto GPT Model with Lang Chain
Discover how large language models like GPT are transforming software development. Learn how Lang chain simplifies leveraging these models with prompts, indexes, and agents. Follow Nicholas Renotte as he builds an Auto GPT model using Lang chain and Streamlit in a 15-minute tutorial.
Build AI Investment Banker: Streamlit & Annual Report Guide
Learn how to build an AI-powered investment banker using Streamlit and an annual report. Install dependencies, integrate personal documents, and leverage the power of Langchain and OpenAI for personalized financial insights. A thrilling tech journey awaits with just 45 lines of code.
Falcon 40b: The Ultimate Open-Source LLN Model Showdown
Nicholas Renotte explores Falcon 40b, a leading open-source LLN model, comparing it against competitors in a thrilling showdown. Falcon 40b shines with multilingual training, precise responses, and top-tier performance in tasks like Q&A and sentiment analysis. Don't miss this exciting dive into the world of AI technology!