Deep Research and Development

In our previous article , we established a foundational architecture for blockchain-enabled agents using LLMs. Now, we'll focus on optimizing two critical components - LLM Integration and Context Management - to create a more robust, production-ready system. Zero to Hero Enhanced LLM Integration with Langchain Our initial implementation used a basic LLamaModel setup. While functional, production environments demand more sophisticated capabilities. Let's enhance our implementation using Langchain with the Qwen2.5-7B-Instruct model: class OptimizedBlockchainLLM:     def __init__(self, model_config, web3_provider, context_manager):         # Initialize Qwen model through Langchain         self.llm = Qwen(             model_name="Qwen/Qwen2.5-7B-Instruct",             temperature=0.7,             max_tokens=2048,           ...