magiseek-v1-pro

MagiSeek-Pro-V1 — OpenCode serving template

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Overview

magiseek-v1-pro is a GGUF release for llama.cpp-compatible runtimes and local inference, published by groxaxo. It is intended for open-source evaluation, reproducible experimentation, and compatible local or hosted inference workflows. The wording below is deliberately limited to what can be verified from this repository's metadata and artifacts.

At a glance

What is included

• chat_template.jinja

Quick start

llama.cpp

Download a .gguf file that fits your available memory, then run it with a current llama.cpp build:

llama-cli \
  -m /path/to/model.gguf \
  -p "Write a concise technical summary."

For vision or any-to-any models, download the matching multimodal projection file when one is provided and follow the source model's modality-specific instructions.

Compatibility and responsible use

• Use a runtime that explicitly supports this format, architecture, and modality.
• Keep configuration, tokenizer, processor, projection, and weight files from the same revision together.
• Review the source model card and license before redistribution or deployment.
• Hardware needs depend on parameter count, context length, cache precision, quantization, and concurrency.
• Report reproducible issues with the runtime version, hardware, launch command, and a minimal example.

Quantization or conversion changes numerical behavior, memory use, and throughput relative to the source checkpoint; validate quality on your own workload.

Generated outputs may be inaccurate or unsuitable for a given use case. Users are responsible for testing behavior, applying appropriate safeguards, and complying with applicable licenses and laws.

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This repository contains the corrected llama.cpp chat template for the Magidonia/MagiSeek p5 Q6_K checkpoint. It is designed for OpenAI-compatible clients, especially OpenCode.

The template is important: the model emits Hermes-style <tool_call> JSON. Without this template, llama.cpp may return those calls as ordinary text instead of a structured OpenAI tool_calls response.

OpenCode / llama.cpp serving

llama-server \
  --model p5.Q6_K.gguf \
  --host 0.0.0.0 --port 12434 \
  -ngl all -c 60000 -fa on \
  --jinja --chat-template-file chat_template.jinja \
  --reasoning-format deepseek \
  -ctk q8_0 -ctv q8_0 \
  --repeat-penalty 1.15 --repeat-last-n 256 \
  --presence-penalty 0.1 -np 1

For agentic use, use a sampling temperature around 0.6–0.7. Avoid temperature: 0 for long tool-use sessions because deterministic decoding can repeat read-only commands.

OpenCode connection

Configure an OpenAI-compatible provider with:

Base URL: http://HOST:12434/v1
Model:    magidonia-p5-q6-coding

The live proxy may expose these variants:

• magidonia-p5-q6-instruct — normal responses
• magidonia-p5-q6-coding — tool use and reasoning
• magidonia-p5-q6-thinking — reasoning-focused responses

Tool calls should arrive as structured OpenAI tool_calls; reasoning should arrive in reasoning_content, not leak into ordinary response content.

Files

• chat_template.jinja — corrected OpenCode-compatible llama.cpp template.

This repository publishes the serving template and instructions; model weights are not duplicated here by this template-only upload.