python
12 results
Web Data Extraction with Firecrawl and LLMs: The Modern Scraping Stack
Extract structured data from any website using Firecrawl and Claude, with working Python code for competitor pricing, job listings, and news aggregation.
Anthropic Batch API: Cut Your AI Costs 50% for High-Volume Workloads
Anthropic's Message Batches API processes async workloads at 50% off standard pricing. Complete Python implementation, hybrid architecture patterns, and failure handling.
What Is smolagents? HuggingFace's Lightweight Agent Library Explained
smolagents is HuggingFace's answer to complex agent frameworks — a minimal Python library that lets LLMs write and run code as their primary action mechanism.
Build a Python AI App in India: LangChain + Claude + AICredits.in (Full Tutorial)
Build a document Q&A app using RAG in Python with LangChain and Claude — pay for the API with UPI via AICredits.in. No international card needed. ~₹10 total.
Structured Outputs with Claude 4.6: JSON Schemas, Pydantic, and Reliable Extraction
Structured outputs are GA in Claude 4.6. Pass a JSON schema, get schema-valid JSON back — no retry logic needed. Three copy-paste patterns for Python developers.
Build an AI App in India Without a Dollar Account: LangChain + AICredits.in Tutorial
A complete tutorial for building a LangChain AI agent in India — GPT-4o and Claude via INR billing, UPI top-up, no international card required.
LangChain vs LangGraph: Which One Should You Use?
LangChain handles linear pipelines. LangGraph handles everything that needs loops, branching, or persistent state. Here's the exact decision framework — with code showing when each breaks and why.
Structured Output from AI APIs: JSON Every Time
How to reliably get JSON, typed objects, and formatted data from ChatGPT, Claude, and Gemini APIs. Covers response_format, tool use, Pydantic, and every technique that actually works in production.
LangGraph: Build Stateful AI Agents That Actually Work
LangGraph extends LangChain with graph-based agent architecture — nodes, edges, state, and cycles. Learn how to build reliable multi-step AI agents with real Python code examples.
