Repository for bedrock implementation
This repo contains blogs + code samples around:
- Amazon Bedrock
- Agentic AI
- GenAI concepts
- Map Server integrations (coming soon)
blogs/→ Markdown articlescode/→ Hands-on projectsbedrock_setup/→ Hands-on to setup bedrock on cloud
- Blog 1: Introduction to Amazon Bedrock
- Blog 2: Agentic AI Overview
- Blog 3: Map Server Basics
- Blog 4: Retrieval-Augmented Generation (RAG)
- Blog 5: Bedrock vs OpenAI API
- Blog 6: Building an AI Travel Planner
- Blog 7: Security Risks in GenAI
- Blog 8: Bedrock Guardrails
- Blog 9: Multi-Agent Collaboration
- Blog 10: Building a GenAI API with FastAPI
- Blog 11: Agentic Autonomous Agent
- Blog 12: GenAI Text-to-SQL
- Blog 13: Building GenAI Pipelines
- Blog 14: Real-World Multi-Agent Workflows
- Blog 15: Enterprise Adoption of GenAI
- Blog 16: Building a GenAI Knowledge Base
- Blog 17: AI-Powered Data Visualization
- Blog 18: Generating Dashboards with GenAI
- Blog 19: Multi-Agent Systems in Finance
- Blog 20: AI for Fraud Detection
- Code 1: Bedrock Chatbot (Python + boto3)
- Code 2: Agentic Task Planner (Pure Python)
- Code 3: Simple Map Server (Flask)
- Code 4: RAG Demo (FAISS + Sentence Transformers)
- Code 5: Bedrock Summarizer (Python + boto3)
- Code 6: Travel Planner Agent (Pure Python)
- Code 7: Prompt Injection Test
- Code 8: Bedrock Guardrails Demo
- Code 9: Multi-Agent Demo
- Code 10: FastAPI GenAI API
- Code 11: Agentic Autonomous Agent
- Code 12: GenAI Text-to-SQL
- Code 13: GenAI Pipelines
- Code 14: Multi-Agent Workflows
- Code 15: Enterprise AI Summary Generator
- Code 16: GenAI Knowledge Base Demo
- Code 17: AI Data Visualization (Matplotlib)
- Code 18: AI Dashboard Generation (Plotly)
- Code 19: Multi-Agent Finance Simulation
- Code 20: AI Fraud Detection Demo
- Day 11–15: Map Server Integration, Advanced RAG, Bedrock Fine-Tuning
- Day 16–25: GenAI Security Case Studies, Multi-Agent Use Cases (Healthcare, Finance, Education)
- Day 26–40: Scaling GenAI Workflows, Hybrid Cloud Deployments, AI Observability
- Day 41–50+: Autonomous Multi-Agent Systems, Enterprise AI Best Practices