News & guides
JetBrains LLM Setup: Custom Endpoints in IntelliJ IDEs
How to run a model of your choosing inside IntelliJ, PyCharm or GoLand — what the bundled assistant will and will not do, and the plugin route that does.
· 8 min read
JSON Schema for Tool Calls: What Providers Actually Support
Which JSON Schema features survive the trip to a model, why strict mode changes the rules, and how to write tool parameter schemas that validate and get used correctly.
· 9 min read
Kilo Code Setup Guide: Custom Endpoints and Profiles
Configure Kilo Code against your own OpenAI-compatible endpoint, set the model metadata it cannot infer, and assign different models per mode with profiles.
· 8 min read
LlamaIndex Setup on a Custom OpenAI-Compatible Endpoint
Configure LlamaIndex against a non-OpenAI base URL, split the LLM from the embedding model, and avoid the defaults that silently call OpenAI anyway.
· 9 min read
LLM Classification: Fix the Taxonomy Before the Model
Most classification failures are label definition failures. How to design a taxonomy, handle abstention and imbalance, and check the model beats a cheap baseline.
· 9 min readLLM Data Extraction: Design the Schema Before the Prompt
Extraction failures are usually schema failures. How to model absent, ambiguous and multi-valued fields, attach provenance, and validate what comes back.
· 9 min readLLM Summarisation: Omission Hurts More Than Invention
Summaries fail by leaving things out, not by making things up. How to control what gets kept, pick a chunking strategy, and evaluate faithfulness cheaply.
· 9 min readLLM Translation: Placeholders, Glossaries and Register
Machine translation is solved enough. What breaks in software localisation is interpolation syntax, terminology drift and missing context, not language quality.
· 9 min read
LLM-Powered Search: The Model Is Not the Retriever
Adding a model to search usually means query rewriting and reranking, not generation. Where each stage helps, what it costs in latency, and how it fails.
· 9 min readLogging LLM Requests Safely Without Building a Liability
The fields that make a model request debuggable are mostly not the fields that make it risky. How to log traffic that stays useful and minimal by default.
· 9 min read
Neovim LLM Setup: Adapters, Keys and Custom Endpoints
Wire a Neovim LLM plugin to your own OpenAI-compatible endpoint — how adapters are shaped, where the key should come from, and why streaming often looks broken.
· 8 min readOpenAI Node SDK Setup Against a Custom Base URL
Configure the official Node client for any OpenAI-compatible endpoint: retries, timeouts, abort signals, streaming, typed errors and the runtime traps in serverless.
· 9 min readReady to try it?
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