LLM Engineering Practice

This repository contains practice of Large Language Models (LLMs), Prompt Engineering, LangChain, Retrieval-Augmented Generation (RAG), Vector Databases, FastAPI, GitHub APIs, Webhooks, Background Tasks, and Backend Development using Python.

Topics Covered

LLM Concepts

• What are Large Language Models (LLMs)
• Tokens and Tokenization
• How LLMs generate responses

API Integration

• API Calls
• Environment Variables (.env)
• Model Selection
• Response Handling

Prompt Engineering

• System Prompts
• Assistant Roles
• Temperature Control
• Few-Shot Prompting
• Structured JSON Output
• Prompt Design Best Practices

Token Management

• Token Usage Monitoring
• Prompt Tokens
• Completion Tokens
• Cost Awareness

LangChain Fundamentals

• ChatGroq
• PromptTemplate
• ChatPromptTemplate
• StrOutputParser
• Chains
• LCEL (LangChain Expression Language)
• invoke()
• batch()
• stream()

Memory Concepts

RAG Basics

• Document Loaders
• LangChain Documents
• page_content and metadata
• Text Chunking
• chunk_size
• chunk_overlap
• RecursiveCharacterTextSplitter

Embeddings

• Embedding Vectors
• Cosine Similarity
• Semantic Search
• Similarity Search
• HuggingFace Embeddings
• Sentence Transformer Embeddings

ChromaDB

• Vector Stores
• Similarity Search
• Retrievers
• Retrieval Process
• Collections
• PersistentClient
• Collection Management
• Vector Persistence
• add()
• query()
• update()
• Unique Document IDs
• Metadata Storage
• Metadata Retrieval

Complete RAG Pipeline

• Document → Chunking → Embeddings
• Embeddings → Vector Database
• Retrieved Context → LLM
• Context Injection
• Question Answering using RAG
• Interactive RAG Chatbot
• Retriever + LLM Pipeline
• Conversational Question Answering

FastAPI & Backend Development

• FastAPI Basics
• CRUD APIs
• Pydantic Schemas
• Request & Response Handling
• JWT Authentication
• Password Hashing
• SQLite
• PostgreSQL
• SQLAlchemy ORM
• Database Models
• Query Operations
• REST APIs

GitHub REST API

• Personal Access Tokens
• Authentication Headers
• Repository API
• Pull Request API
• Contributor Analytics
• JSON Response Handling

GitHub Webhooks

• Webhook Events
• Push Events
• Pull Request Events
• Event Payloads
• Event Headers
• ngrok Integration
• Real-Time Event Processing

Background Tasks

• FastAPI BackgroundTasks
• add_task()
• Asynchronous Processing
• Webhook Event Processing
• Event Logging

Event Storage & Analytics

• SQLite Event Database
• SQLAlchemy Models
• Database Sessions
• Event Storage
• Analytics APIs

---

Project Structure

AI-ENGINEERING/
│
├── groq-api/
│   ├── 01_api_call.py
│   ├── 02_system_prompt.py
│   ├── 03_assistant_role.py
│   ├── 04_temperature.py
│   ├── 05_json_output.py
│   ├── 06_few_shot_prompting.py
│   ├── 07_token_usage.py
│   ├── notes.md
│   └── requirements.txt
│
├── langchain-basics/
│   ├── 01_langchain.py
│   ├── 02_prompt_template.py
│   ├── 03_output_parser.py
│   ├── 04_chain.py
│   ├── 05_chat_prompt_template.py
│   ├── 06_batch.py
│   ├── 07_stream.py
│   └── notes.md
│
├── rag-basics/
│   ├── chroma_db/
│   ├── .env
│   ├── 01_document_loader.py
│   ├── 02_text_splitter.py
│   ├── 03_embeddings.py
│   ├── 04_similarity.py
│   ├── 05_chromadb.py
│   ├── 06_chromadb_search.py
│   ├── 07_retriever.py
│   ├── 08_rag_pipeline.py
│   ├── 09_rag_chatbot.py
│   ├── app.py
│   ├── notes.md
│   ├── notes.pdf
│   ├── notes.txt
│   ├── rag_chunks.py
│   └── requirements.txt
│
├── vector-db-practice/
│   ├── chroma_db/
│   ├── 01_document_loader.py
│   ├── 02_text_splitter.py
│   ├── 03_embeddings.py
│   ├── 04_chromadb.py
│   ├── 05_similarity_search.py
│   ├── 06_metadata_store.py
│   ├── 07_retriever.py
│   ├── 08_rag_pipeline.py
│   ├── 09_rag_chatbot.py
│   ├── app.py
│   ├── chunking.py
│   ├── notes.pdf
│   ├── persistent_db.py
│   └── requirements.txt
│
├── github-api/
│   ├── 01_repo_info_fetcher.py
│   ├── 02_pr_tracker.py
│   ├── 03_contributor_analytics.py
│   ├── 04_webhook_practice.py
│   ├── 05_background_tasks.py
│   ├── 06_webhook_background_task.py
│   ├── 07_event_logger.py
│   ├── 08_event_database.py
│   ├── 09_webhook_database.py
│   ├── 10_analytics_api.py
│   ├── database.py
│   ├── models.py
│   ├── requirements.txt
│   └── README.md
│
└── README.md

Technologies Used

• Python
• Groq API
• Llama Models
• LangChain
• ChromaDB
• Vector Databases
• Sentence Transformers
• HuggingFace Embeddings
• Prompt Engineering
• RAG Concepts
• Semantic Search
• Similarity Search
• Vector Embeddings
• Retrieval Systems
• LangChain Retrievers
• FastAPI
• SQLAlchemy
• SQLite
• PostgreSQL
• Redis
• Celery
• GitHub REST API
• GitHub Webhooks
• Background Tasks
• ngrok
• Environment Variables
• Git & GitHub