# awesome-generative-ai-guide | aishwaryanr | Knowledge Base | Instagit

A one stop repository for generative AI research updates, interview resources, notebooks and much more!

GitHub Stars: 27.8k

Repository: https://github.com/aishwaryanr/awesome-generative-ai-guide

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## Articles

### [How to Implement Knowledge Graphs for Advanced RAG Systems: A Complete Technical Guide](/aishwaryanr/awesome-generative-ai-guide/knowledge-graphs-advanced-rag-systems)

Implement knowledge graphs for advanced RAG systems by storing data as triples, querying subgraphs with Cypher in LangGraph, and prompting LLMs for verifiable, grounded outputs.

- Tags: how-to-guide
- Published: 2026-06-21

### [Best Practices for Red Teaming LLM Applications: A 7-Step Security Framework](/aishwaryanr/awesome-generative-ai-guide/red-teaming-llm-applications-best-practices)

Master red teaming LLM applications with a 7-step security framework. Discover prompt injection, memory poisoning, and tool exploitation vulnerabilities before deployment. Enhance your AI security now.

- Tags: best-practices
- Published: 2026-06-21

### [How to Build Multimodal RAG Systems with ColPali and Qwen-2: A Complete Implementation Guide](/aishwaryanr/awesome-generative-ai-guide/multimodal-rag-systems-colpali-qwen2)

Build multimodal RAG systems leveraging Qwen-2-VL and ColPali. Implement late-interaction retrieval with FAISS for visual and textual content. Get answers from combined data.

- Tags: how-to-guide
- Published: 2026-06-21

### [Key Techniques for Prompt Engineering with LLMs: From Chain-of-Thought to ReAct](/aishwaryanr/awesome-generative-ai-guide/prompt-engineering-techniques-llms)

Master key techniques for prompt engineering with LLMs like Chain-of-Thought and ReAct. Explore a five-layer architecture for advanced AI prompting and reasoning.

- Tags: deep-dive
- Published: 2026-06-21

### [Best Tools for LLM Fine-Tuning: Llama Factory vs Hugging Face PEFT](/aishwaryanr/awesome-generative-ai-guide/llm-finetuning-tools-llama-factory-huggingface-peft)

Discover the best tools for LLM fine-tuning comparing Llama Factory's rapid CLI prototyping with Hugging Face PEFT's granular Python control for efficient training.

- Tags: comparison
- Published: 2026-06-21

### [How to Fine-Tune DeepSeek Models on Custom Datasets: A Complete Guide](/aishwaryanr/awesome-generative-ai-guide/finetune-deepseek-models-custom-datasets)

Learn to fine-tune DeepSeek models on your custom datasets efficiently using JSONL data and PEFT/LoRA techniques. Adapt powerful AI models with minimal GPU memory.

- Tags: how-to-guide
- Published: 2026-06-21

### [Differences Between PEFT, LoRA, and QLoRA for Parameter-Efficient Fine-Tuning](/aishwaryanr/awesome-generative-ai-guide/peft-lora-qlora-differences)

Understand the differences between PEFT, LoRA, and QLoRA for parameter-efficient fine-tuning. Learn how LoRA uses low-rank matrices and QLoRA quantizes models for efficient memory use.

- Tags: deep-dive
- Published: 2026-06-21

### [How to Implement Voice Assistants Using Whisper and LLaVA: A Complete Multimodal Guide](/aishwaryanr/awesome-generative-ai-guide/voice-assistants-whisper-llava)

Build a voice assistant using Whisper and LLaVA. Transcribe speech with Whisper and enable multimodal understanding with LLaVA for advanced command processing. Get started today.

- Tags: how-to-guide
- Published: 2026-06-21

### [Security Considerations for Agentic AI Systems: OWASP Top 10 Defense Guide](/aishwaryanr/awesome-generative-ai-guide/security-considerations-agentic-ai-owasp)

Defend agentic AI systems against OWASP Top 10 risks like prompt injection. Learn about guardrails, permissions, and auditability for robust security.

- Tags: tutorial
- Published: 2026-06-21

### [How to Build a Production RAG App with Open-Source Models and Groq](/aishwaryanr/awesome-generative-ai-guide/production-rag-app-open-source-groq)

Build a production RAG app with open-source models and Groq. Learn a four-layer architecture for sub-millisecond inference using FastAPI and LangChain or LlamaIndex.

- Tags: how-to-guide
- Published: 2026-06-21

### [Best Practices for LLM Observability and Monitoring in Production](/aishwaryanr/awesome-generative-ai-guide/llm-observability-monitoring-production-best-practices)

Master LLM observability and monitoring in production. Implement trace IDs, comprehensive logging, expose metrics, and automate alerts for latency, cost, and hallucinations. Ensure robust LLM deployments.

- Tags: best-practices
- Published: 2026-06-21

### [How to Implement Text-to-Music Generation with Meta's MusicGen](/aishwaryanr/awesome-generative-ai-guide/text-to-music-generation-musicgen)

Learn to implement text-to-music generation with Meta's MusicGen. This guide explores the Audiocraft library for creating high-fidelity audio from text prompts.

- Tags: how-to-guide
- Published: 2026-06-21

### [Key Considerations for LLM Evaluation and Benchmarking in Production](/aishwaryanr/awesome-generative-ai-guide/llm-evaluation-benchmarking-production-considerations)

Discover key considerations for LLM evaluation and benchmarking in production. Optimize accuracy, reliability, safety, cost, and operational impact for your end-to-end system.

- Tags: best-practices
- Published: 2026-06-21

### [How to Fine-Tune Multimodal LLMs (IDEFICS and Qwen2-VL) for Visual Question Answering](/aishwaryanr/awesome-generative-ai-guide/finetune-multimodal-llms-idefics-qwen2-vl-vqa)

Learn to fine-tune IDEFICS and Qwen2-VL multimodal LLMs for Visual Question Answering. Master QLoRA, LoRA, prompt templates, and training techniques for VQA.

- Tags: tutorial
- Published: 2026-06-21

### [Best Vector Databases for RAG: FAISS, Weaviate, and Pinecone Compared](/aishwaryanr/awesome-generative-ai-guide/best-vector-databases-rag-faiss-weaviate-pinecone)

Compare top vector databases for RAG: FAISS for local prototyping, Weaviate for open-source hybrid search, and Pinecone for scalable production systems to choose the best fit.

- Tags: comparison
- Published: 2026-06-21

### [How to Use MCP Servers for AI Assistants with LangChain Tools: A Complete Implementation Guide](/aishwaryanr/awesome-generative-ai-guide/mcp-servers-ai-assistants-langchain-tools)

Implement AI assistants with LangChain tools using MCP servers. Discover how to expose tool schemas and execution endpoints for seamless external capability invocation, avoiding embedded logic.

- Tags: how-to-guide
- Published: 2026-06-21

### [Trade-offs Between Fine-Tuning, Prompting, and Training LLMs from Scratch](/aishwaryanr/awesome-generative-ai-guide/llm-finetuning-prompting-training-tradeoffs)

Explore the trade-offs between fine-tuning, prompting, and training LLMs from scratch. Understand compute costs, performance gains, and control for your generative AI projects.

- Tags: deep-dive
- Published: 2026-06-21

### [How to Build an Agentic RAG Pipeline with LangGraph and Map-Reduce](/aishwaryanr/awesome-generative-ai-guide/agentic-rag-pipeline-langgraph-map-reduce)

Learn to build an agentic RAG pipeline using LangGraph and map-reduce. Orchestrate parallel retrieval, aggregate results, and leverage LLMs for iterative search refinement. Unlock powerful AI agents.

- Tags: how-to-guide
- Published: 2026-06-21

### [How to Secure Agentic AI Systems Against Memory Poisoning: A Three-Pillar Defense](/aishwaryanr/awesome-generative-ai-guide/secure-agentic-ai-memory-poisoning)

Secure agentic AI systems against memory poisoning with a three-pillar defense: guardrails, permissions, and auditability. Prevent malicious entries and ensure safe future reasoning.

- Tags: best-practices
- Published: 2026-06-21

### [How to Implement Multi-Agent AI with CrewAI vs AutoGen in Production](/aishwaryanr/awesome-generative-ai-guide/multi-agent-ai-crewai-vs-autogen-production)

Implement multi-agent AI in production comparing CrewAI and AutoGen. Learn which framework suits deterministic or dynamic agent workflows for your needs.

- Tags: how-to-guide
- Published: 2026-06-21

### [When to Use QLoRA Versus Standard LoRA for Fine-Tuning LLMs](/aishwaryanr/awesome-generative-ai-guide/when-to-use-qlora-vs-standard-lora)

Decide between QLoRA and standard LoRA for LLM fine-tuning. Learn when to use QLoRA for large models on limited GPU memory vs. standard LoRA for maximum accuracy on full-precision models.

- Tags: deep-dive
- Published: 2026-06-21

### [QLoRA vs LoRA: How Quantized Low-Rank Adaptation Reduces Memory for LLM Fine-Tuning](/aishwaryanr/awesome-generative-ai-guide/qlora-vs-standard-lora-llm-finetuning)

Discover how QLoRA slashes LLM fine-tuning memory needs by 80% using 4-bit quantization. Fine-tune large models on consumer GPUs with minimal accuracy impact compared to standard LoRA.

- Tags: deep-dive
- Published: 2026-06-21