public-resources/gemini-api/SKILL.md

name, description

name	description
gemini-api	Use when needing to call Gemini LLM for text generation or Gemini LMM for image generation via the local network Master API at 192.168.1.5:10900. Supports chat completion and image generation with concurrency control.

Gemini API (Local Network)

Overview

Wraps the local Gemini Master API (192.168.1.5:10900) for LLM text and LMM image generation. Max concurrency = 2. Uses gemini_client.py helper script.

When to Use

• Need LLM text generation (chat/completion) via Gemini
• Need image generation via Gemini LMM
• Any task requiring Gemini model capabilities on the local network

Quick Reference

Capability	Endpoint	Model Options	Timeout
LLM Chat (sync)	/api/v1/llm/chat/sync	pro (default), flash	~200s
LMM Image (sync)	/api/v1/lmm/image/sync	nano-bananapro (default)	~350s

Usage

Helper Script

All calls go through ~/.claude/skills/gemini-api/gemini_client.py:

# LLM: text generation
python ~/.claude/skills/gemini-api/gemini_client.py chat "你的问题"

# LLM: with model selection
python ~/.claude/skills/gemini-api/gemini_client.py chat "你的问题" --model flash

# LMM: image generation (saves to file)
python ~/.claude/skills/gemini-api/gemini_client.py image --prompt "图片描述" --output result.png

# LMM: image + auto-remove Gemini watermark
python ~/.claude/skills/gemini-api/gemini_client.py image --prompt "图片描述" --output result.png --remove-watermark

# LMM: image from event data (JSON file)
python ~/.claude/skills/gemini-api/gemini_client.py image --event-data event.json --output result.png

# Batch: multiple requests with concurrency=2
python ~/.claude/skills/gemini-api/gemini_client.py batch requests.jsonl --output-dir ./results/
python ~/.claude/skills/gemini-api/gemini_client.py batch requests.jsonl --output-dir ./results/ --remove-watermark

Python API (recommended for agents)

When writing inline Python scripts (not via CLI), import the module directly:

import sys
sys.path.insert(0, r'C:\Users\ZhuanZ（无密码）\.claude\skills\gemini-api')
# Or on Linux/Mac: sys.path.insert(0, os.path.expanduser('~/.claude/skills/gemini-api'))
from gemini_client import image_sync, save_image_from_response, remove_watermark

# Generate image (always use base64 format)
resp = image_sync(prompt="your prompt here")

# Save to file
save_image_from_response(resp, "output.png")

# Remove watermark (optional)
remove_watermark("output.png")

# Or combine: generate + save + remove watermark in one flow
resp = image_sync(prompt="your prompt here")
save_image_from_response(resp, "output.png")
remove_watermark("output.png")  # overwrites in-place

Image Generation: Critical Notes

MUST use base64 format (NOT url)

The output_format="url" mode is broken — returned URLs consistently 404. The client defaults to base64 which works reliably.

# CORRECT — base64 (default, works)
resp = image_sync(prompt="...", output_format="base64")
save_image_from_response(resp, "out.png")

# WRONG — url download will fail with 404
resp = image_sync(prompt="...", output_format="url")
download_image_by_url(resp["result"]["image_url"], "out.png")  # 404!

Watermark Removal

Gemini nano-bananapro adds a small star/sparkle watermark in the bottom-right corner of every generated image. Use --remove-watermark (CLI) or remove_watermark() (Python) to clean it.

Requires: pip install opencv-python numpy (one-time setup).

from gemini_client import remove_watermark

# Remove watermark in-place
remove_watermark("image.png")

# Or save to a different file
remove_watermark("input.png", "clean.png")

# Custom region size (for non-standard watermark placement)
remove_watermark("input.png", region_w=300, region_h=250)

How it works: OpenCV cv2.inpaint with TELEA algorithm. Detects the watermark region by corner position, creates a mask, and fills in using surrounding pixels. Works well on both solid and complex backgrounds.

Constraints

• Concurrency: Max 2 simultaneous requests (enforced by helper script)
• API Key: Uses one key per request, rotated from pool of 3
• Rate Limit: 10 req/min, 400 req/hour (server-side)
• Proxy: Must bypass system proxy for 192.168.1.5
• Image format: Always use output_format="base64", not "url"
• Watermark deps: remove_watermark() needs opencv-python and numpy

Common Mistakes

Mistake	Consequence	Fix
Using output_format="url"	URL downloads return 404	Use "base64" (default)
Forgetting --noproxy '*' with curl	Request hangs (proxy intercepts LAN)	Always add --noproxy '*'
Using 127.0.0.1 instead of 192.168.1.5	Wrong host	Use 192.168.1.5
Calling download_image_by_url()	404 error	Use save_image_from_response()
Exceeding concurrency=2	Queuing delays, timeouts	Use batch mode
Not checking status field	Missing errors silently	Check resp.get("status") == "completed"
Forgetting watermark removal	Star logo in bottom-right	Add --remove-watermark or call remove_watermark()