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Image Search

Visual image search using Google Lens via SerpAPI. Identify objects, landmarks, products, plants, animals, artwork, logos, or any visual entity from an image...
使用 SerpAPI 调用 Google Lens 进行视觉图片搜索,可识别图片中的物体、地标、产品、植物、动物、艺术作品、标志等视觉实体。
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内容创作 clawhub v1.0.0 1 版本 99895.3 Key: 需要
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概述

Image Search (Google Lens)

Identify anything from an image using Google Lens via SerpAPI.

Setup

Requires SERPAPI_KEY environment variable. Get a key at https://serpapi.com/ (100 free searches/month).

No pip dependencies needed — uses only Python stdlib (urllib, json, base64).

Usage

From CLI / Agent (exec tool)

# Search by image URL
python3 {baseDir}/scripts/lens_search.py "https://example.com/photo.jpg"

# Search by local file (auto-uploads to get a URL)
python3 {baseDir}/scripts/lens_search.py /path/to/image.png

# Refine with text query (e.g., find red version of a product)
python3 {baseDir}/scripts/lens_search.py "https://example.com/bag.jpg" --query "red"

# Product search (returns prices)
python3 {baseDir}/scripts/lens_search.py "https://example.com/sneakers.jpg" --type products

# Find exact matches (where this image appears online)
python3 {baseDir}/scripts/lens_search.py "https://example.com/photo.jpg" --type exact_matches

# Raw JSON output for programmatic use
python3 {baseDir}/scripts/lens_search.py "https://example.com/photo.jpg" --json

# Localized results (e.g., Japanese products with ¥ prices)
python3 {baseDir}/scripts/lens_search.py "https://example.com/laptop.jpg" --type products --country jp

Search Types

TypeUse CaseReturns
-------------------------
all (default)General identificationEntity name + visual matches + text
visual_matchesFind similar imagesVisually similar results with sources
exact_matchesFind image originPages containing this exact image
productsShopping / price lookupProducts with prices and buy links
about_this_imageImage provenanceMetadata about the image's origin

Output Format

The script outputs structured markdown:

## Identified Entity
- **Danny DeVito** — [link](https://...)

## Visual Matches (top 5)
- **Danny DeVito — Wikipedia** (Wikipedia) ✅ exact match
  https://en.wikipedia.org/wiki/Danny_DeVito
- ...

Use --json for raw SerpAPI response when you need thumbnails, image dimensions, or other metadata.

Agent Decision Guide

When a user sends an image:

  1. Already identified by vision model? If the main model confidently recognizes the entity, skip reverse search.
  2. Uncertain identification? Run lens_search.py to verify. Compare model's guess with Lens results.
  3. Need details beyond identification? First identify with Lens, then web_search for deeper info.
  4. Shopping intent? Use --type products to get prices and buy links directly.
  5. Local file from user? The script handles local files by auto-uploading to get a searchable URL.

Combining with Other Tools

Typical multi-tool workflow:

1. User sends image → "What building is this?"
2. reverse_image_search → identifies "Cologne Cathedral"
3. web_search("Cologne Cathedral history architecture") → detailed info
4. Compose answer combining visual match + web knowledge

Limitations

  • SerpAPI free tier: 100 searches/month. Paid plans from $50/month.
  • Local file upload uses freeimage.host (free) or imgbb (needs IMGBB_API_KEY).
  • Google Lens results vary by region; use --country for localized results.
  • Some niche/long-tail entities may not return useful visual matches.

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-30 04:50 安全 安全

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