You should've added the context tbh. Classical NLP algo still can be relevant in many cases tho
CODE
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Paper2Code and DeepWiki: Tools for AI Research
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Paper2Code (
https://
arxiv.org/pdf/2504.17192) can help you understand papers.
DeepWiki (
https://
deepwiki.com) can help you understand code.
Two great tools for accelerating your research! -
Ryoma: AI Data Agent Framework for Natural Language Database Queries
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Ryoma: AI Data Agent Framework A framework leveraging LangChain agents to convert natural language into database queries, with built-in UI for interactive data exploration across multiple databases. Check out Ryoma on GitHub https://
github.com/project-ryoma/
ryoma
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RAG Implementation Guide: Building Production Systems with LangChain
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RAG Implementation Guide A developer guide showing how to build RAG systems with LangChain and LangSmith, featuring implementation workflows, monitoring tools, and optimization techniques for production deployment. Dive into RAG development today!
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Production-Ready FastAPI Template for LLM App Development
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FastAPI MCP Template A production-ready FastAPI template that streamlines LLM app development with LangGraph orchestration and MCP context management. Features native streaming and comprehensive monitoring. Check out the template https://
github.com/NicholasGoh/fa
stapi-mcp-langgraph-template
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Medical AI Assistant: Multi-Agent LangGraph Healthcare System
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Medical AI Assistant A multi-agent system powered by LangGraph that combines medical diagnosis, imaging analysis, and voice interaction for comprehensive healthcare support. Check it out!
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Level 4: Limited Autonomous Agents Self-Improving Capabilities
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Level 4: Limited Autonomous Agents.
A broadly-capable self-directed agent that operates on a loop. Still uses predefined workflows and tools but can adapt and create its own tools and skills as needed. This is a self-improving agent. Completes tasks but not always perfectly. -
Level 3 Reasoning Agents: Self-Directed AI Systems and Tools
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Level 3: Reasoning Agents.
Contains a self-directed agent where the agent works on a task, uses tools/skills, decides next steps, and decides if it is done on a loop. Includes today’s reasoning agents (e.g. GPT-o3) and AI code assistants (Replit, Lovable, Cursor, etc) -
Level 2 Workflow Agents: Multi-Prompt Chains and Tool Integration
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Level 2: Workflow Agents
May include a chain of multiple prompts and/or tool use. Common tools are docs, web search, and image generation, web scrapers, computer use, email, and chat apps. The agent workflow is pre-defined. -
MCP Adapter for LangChain: Connect Agents to 100+ Tools
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MCP Adapter for LangChain A powerful integration connecting LangChain agents to 100+ external tools via Composio's MCP servers. Includes automatic tool registration and OAuth flows for seamless agent development. Learn more: https://
composio.dev/blog/langchain
-mcp-adapter-a-step-by-step-guide-to-build-mcp-agents/
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