2025 Master Langchain and Ollama - Chatbot, RAG and Agents

🎓 2025 Master Langchain and Ollama - Chatbot, RAG and Agents: A Comprehensive Course

Course Overview:

Embark on a journey to master the integration of Langchain and Ollama, powerful tools for building AI applications. This course is tailored to provide you with a deep dive into setting up, automating, and deploying real-world AI solutions. Whether you're a developer, data scientist, or an AI enthusiast, this practical guide will equip you with hands-on skills and experience to build and manage robust AI applications.

What You Will Learn:

🔹 Ollama & Langchain Setup

• Complete the setup and installation of Ollama and Langchain.
• Configure base URLs and handle direct API calls.
• Establish an environment for efficient integration between Ollama and Langchain.

🔹 Prompt Engineering

• Understand how to craft AI, human, and system message prompts.
• Utilize AIPromptTemplate, Human, System, and ChatMessagePromptTemplate to tailor responses.
• Control the model's behavior with the invoke method.

🔹 Chains for Workflow Automation

• Build flexible workflows using Sequential, Parallel, and Router Chains.
• Implement custom chains and explore Chain Runnables for enhanced automation.
• Apply Langchain's chaining capabilities to real-world workflows.

🔹 Output Parsing

• Format data with parsers like JSON, CSV, Markdown, and Pydantic.
• Parse structured output and manage date-time output for organized data handling.

🔹 Chat Message Memory

• Use BaseChatMessageHistory and InMemoryChatMessageHistory to manage chat sessions.
• Create chat applications with memory features to improve user experience.

🔹 Build and Deploy Chatbots

• Construct a chatbot application using Streamlit.
• Maintain chat history and handle user inputs efficiently within the chatbot.

🔹 Document Loaders and Retrievals

• Work with loaders for various data formats like web pages, PDFs, and HTML.
• Retrieve and summarize documents, convert text data, and utilize vector stores.

🔹 Vector Stores and Retrievals

• Integrate vector stores such as FAISS and Chroma for document retrieval.
• Reload retrievers, index documents, and enhance the accuracy of document retrieval.

🔹 Tool Calling and Custom Agents

• Set up tools for popular services like Tavily Search, PubMed, Wikipedia, etc.
• Design custom tools that can be integrated with Langchain Agents to execute step-by-step instructions.

🔹 Real-World Integrations

• Execute text-based queries on MySQL databases.
• Parse LinkedIn Profiles and Job Resumes using Large Language Models (LLM).
• Deploy LLAMA with Ollama on AWS cloud platform.

Who This Course Is For:

This course is designed for:

• Developers and data scientists interested in leveraging Langchain and Ollama for AI applications.
• AI enthusiasts aiming to automate workflows or create document retrieval systems.
• Professionals looking to build end-to-end chatbots or deploy AI applications on AWS.
• Learners with basic Python knowledge seeking practical experience in real-world AI tool usage.

By completing this course, you will have the skills to build, deploy, and manage AI-powered applications, including chatbots, document retrievers, and more, ready for production use. 🚀

Join us on this educational adventure and unlock the potential of Langchain and Ollama today! 🌟