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ZRZRING

low-hallucination-vision

by ZRZRING

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
VISION_MODELYesThe model identifier (e.g., mimo-vl-2.5)
VISION_API_KEYYesAPI key for the vision model
VISION_API_BASEYesThe base URL for the OpenAI-compatible API endpoint
VISION_TEMPERATURENoTemperature for model responses (lower = less hallucination)0.2
VISION_CONFIDENCE_THRESHOLDNoConfidence threshold below which claims are flagged as dubious0.6

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
analyze_imageA

Analyze an image with anti-hallucination safeguards.

Args:
    image_source: Local file path or http(s) URL of the image.
    mode: One of "general" | "ui_screenshot" | "ocr" | "detect".
        - general       structured subject/background/style description
        - ui_screenshot UI element inventory with bbox + confidence
        - ocr           text-only extraction (see ocr_extract for the dedicated tool)
        - detect        object detection with mandatory bbox
    prompt: Optional extra instructions (e.g. "focus on the top-right card").
    temperature: Sampling temperature, default 0.2 (low = less hallucination).

Returns:
    JSON string. Low-confidence claims are tagged with "_flag": "存疑".
ocr_extractA

Extract visible text from an image (OCR only, no scene description).

Args:
    image_source: Local file path or http(s) URL of the image.
    prompt: Optional extra instructions.
    temperature: Sampling temperature, default 0.2.

Returns:
    JSON: {"texts":[{"text","bbox","confidence"}], "overall_confidence"}.
    Unclear characters are dropped, never guessed.
detect_elementsA

Detect objects in an image with mandatory bounding boxes.

Conservative by design: prefers false negatives over false positives.

Args:
    image_source: Local file path or http(s) URL of the image.
    prompt: Optional extra instructions (e.g. "only people and vehicles").
    temperature: Sampling temperature, default 0.2.

Returns:
    JSON: {"objects":[{"label","bbox","confidence"}], "overall_confidence"}.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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