AI Agents, RAG, and LLMs just had their biggest week.
And the releases are mind-blowing.
Here's everything you need to know:
1. DeepSeek V3 Base model shows impressive performance
→ 671B parameter Mixture-of-Experts model
→ 37B parameters activated per token
→ Outperforms Claude 3.5 Sonnet, GPT-4, and Llama 3
2. OASIS launches social media simulator
→ Model up to 1 million AI agent interactions
→ Study behavior across Twitter and Reddit
→ Analyze information spread and group dynamics
3. Cheshire Cat AI is an opensource framework for production AI agents
→ Built with Docker at its core
→ Process documents and connect to external APIs
→ Supports both commercial and open-source LLMs
4. Humanloop releases comprehensive RAG evaluation suite
→ Automated evaluations through code or UI
→ Human feedback collection capabilities
→ Real-time performance monitoring
5. Hercules emerges as first opensource testing agent
→ Converts Gherkin steps to end-to-end tests
→ No coding skills required
→ Handles complex testing automation
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Build a personal health and fitness AI Agent using Google Gemini in less than 50 lines of Python Code (step-by-step instructions):
For easy viewing, follow this blog post with step-by-step code instructions.
Alternatively, continue reading for detailed code instructions and steps.
Qwen QwQ-32B can reason as good as OpenAI o1 mini (in most of the cases).
Best part? You can run this locally with an UI in less than 10 lines of Python Code (100% free and without internet).
1. Pull Qwen QwQ-32B from @ollama locally on your computer.
Build a local ChatGPT Clone with memory using Llama 3.1 and vector databases (100% free and without internet):
For easy viewing, follow this blog post with step-by-step code instructions.
Alternatively, continue reading for detailed code instructions and steps.
Build an AI Finance Agent with web access using xAI Grok in just 20 lines of Python Code (step-by-step instructions):
For easy viewing, follow this blog post with step-by-step code instructions.
Alternatively, continue reading for detailed code instructions and steps.
Build a team of AI Agents to create an AI financial analyst with web access using GPT-4o in just 20 lines of Python Code (step-by-step instructions):
For easy viewing, follow this blog post with step-by-step code instructions.
Alternatively, continue reading for detailed code instructions and steps.
Build an AI RAG agent with web access using GPT-4o in just 15 lines of Python Code (step-by-step instructions):
For easy viewing, follow this blog post with step-by-step code instructions.
Alternatively, continue reading for detailed code instructions and steps.
Finetune Llama 3.2 for free in just 30 lines of Python Code (step-by-step instructions):
For easy viewing, follow this blog post with step-by-step code instructions.
Alternatively, continue reading for detailed code instructions and steps.