Python is the standard language for building GenAI applications. This guide covers Python for Generative AI training in Hyderabad — the specific libraries, frameworks and patterns you need.
Python Foundation
You need solid Python before GenAI: functions, classes, async/await, type hints, error handling, package management. See our Python training for foundation.
Core GenAI Libraries
- openai — OpenAI SDK
- anthropic — Claude SDK
- google-generativeai — Gemini SDK
- langchain + langchain-community — orchestration
- langgraph — agent workflows
- llama-index — RAG framework
- chromadb, pinecone-client, weaviate-client — vector databases
- sentence-transformers — embeddings
- tiktoken — token counting
- pydantic — structured output validation
Building RAG in Python
End-to-end: document loading (unstructured, pypdf), chunking, embedding, vector DB storage, retrieval, prompt construction, LLM call, response formatting. FastAPI for serving.
Building Agents in Python
LangChain agents, LangGraph state machines, MCP tool integration. See Agentic AI training.
Real-Time Python GenAI Projects
- PDF Q&A app with FastAPI + Streamlit
- Multi-provider LLM comparison tool
- Structured extraction API
- Multi-agent research assistant
- Voice-to-text-to-LLM pipeline
- Cost-tracking wrapper around OpenAI API
Cloud Soft Solutions offers hands-on training in AI, GenAI, Agentic AI, ML, Deep Learning, Python, AWS, Azure, DevOps and Cyber Security — with real-time projects.
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❓ Frequently Asked Questions
Python or JavaScript for GenAI?
Python is the standard.
LangChain necessary?
Optional but valuable.
OpenAI or Claude API?
Both — real engineers know both.
Free API options?
Ollama for local models.
About Cloud Soft Solutions
Hyderabad-based technology training in AI, GenAI, Agentic AI, Enterprise AI, AWS, Azure, DevOps, Machine Learning, Deep Learning, Python and Cyber Security. Classroom (Ameerpet) + live online.