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Explore the skillRAG Chatbot
umbertogriffo
RAG (Retrieval-augmented generation) ChatBot that provides answers based on contextual information extracted from a collection of Markdown files.
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Finde den passenden Skill für deine nächste Aufgabe mit Codex, Claude Code, Cursor und mehr.
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Explore the skillumbertogriffo
RAG (Retrieval-augmented generation) ChatBot that provides answers based on contextual information extracted from a collection of Markdown files.
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Explore the skillaws-samples
A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) us…
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Explore the skillcodefuse-ai
An intelligent assistant serving the entire software development lifecycle, powered by a Multi-Agent Framework, working with DevOps Toolkits, Code&Doc Repo RAG, etc.
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Explore the skillVatshayan
Chatbot system for Final Year Project. Chatbot made in Python using Natural Language Toolkit especially Machine Learning. Easy to Understand and Implement.
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Explore the skillOpenGVLab
Chatbot Arena meets multi-modality! Multi-Modality Arena allows you to benchmark vision-language models side-by-side while providing images as inputs. Supports MiniGPT-4…
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Explore the skilljasonacox
Setup and run a local LLM and Chatbot using consumer grade hardware.
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Explore the skillmemodb-io
User Profile-Based Long-Term Memory for AI Chatbot Applications.
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Explore the skillLambdaTest
Designs AI-powered API features, LLM tool/function definitions, MCP server tool schemas, natural language to API conversion, and agentic API workflows. Use whenever the…
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Construction d'agents de support client intelligents avec knowledge base, escalade et personnalisation. Se déclenche avec "agent support", "chatbot support", "customer s…
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Explore the skillContextJet-ai
Use this to measure and monitor the quality of a RAG (retrieval-augmented generation) pipeline - whether it retrieves the right context and answers faithfully. Trigger o…
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Explore the skillselvarajmurugesan90
Guides designing retrieval-augmented generation (RAG) pipelines: document chunking, embedding, indexing, retrieval, and grounding LLM output in retrieved content. Use wh…