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AI Agents

How to use Shieldstral as a local guardrail for your agent

Shieldstral is the 3B safety classifier Mistral released in August 2026: it answers yes or no to a policy written in plain language. Converted to GGUF Q8_0 with llama.cpp and served on a CPU, it blocked no legitimate one among the 100 Spanish and English prompts I prepared, but let 8 of 17 injections through.

AI Agents

How to use OpenCode with local models on llama.cpp and Ollama

OpenCode uses a local model when you declare an @ai-sdk/openai-compatible provider in opencode.json with the llama-server or Ollama URL and the model's context limit. Version 1.18.31 sends 7,516 tokens on its first turn, so the 4k context Ollama assigns by default without a large GPU is not enough: reserve 32k.

AI Agents

How to migrate self-hosted Langfuse from v3 to v4

To migrate Langfuse v3 to v4 with Docker Compose, first upgrade ClickHouse to 26.4 while still on v3, back up PostgreSQL and ClickHouse, start v4 in dual write mode, backfill the history and cut over to events_only once every SDK is compatible. I tested it with 45,931 traces and three Python SDK versions.

AI Agents

How to use DeepSeek Harness with a local model

DeepSeek Harness (dsh) is the open-source agent harness DeepSeek released in August 2026. It works with a local model if you declare an openai-completions provider in settings.yaml that points at llama-server, with a placeholder key and the real context size. With Qwen3.5-4B on CPU it left the tests green in 4 of 5 attempts, but slowly.

AI Agents

How to build an agent with Dify Agent and a local model

Dify Agent, the Linux-sandbox agent Dify introduced in 1.16, works with a local model once you install the Ollama plugin and switch on tool calling. With Dify 1.17.1 and Qwen3.5-4B on a CPU, the published agent returned correct figures in three out of three runs; Build mode finished none of its three sessions.

AI Agents

Engram: persistent memory for coding agents

Engram is a Go binary backed by SQLite and FTS5 that gives coding agents persistent memory over MCP. It stores decisions and conventions between sessions, syncs through git and needs no Node, Python or Docker. Its search is lexical rather than semantic, and that shapes what you should save.

AI Agents

Herdr: a terminal multiplexer for coding agents

Herdr is a Rust terminal multiplexer that runs your coding agents inside a background server. It marks every pane as working, blocked or idle, and that status rolls up to the workspace, so you can see at a glance which agent is waiting on you.