test: add tests for image_processing field from AI extraction

- Added 11 comprehensive tests for image_processing parsing
- Tests validate crop_bounds structure: {x, y, width, height} all ints >= 0
- Tests validate rotation_degrees: int/float, -360 to +360
- Tests validate confidence: float, 0.0 to 1.0
- Tests graceful handling when image_processing field is missing
- Tests multiple items with image_processing data
- Tests partial data handling (optional fields)
- Tests with both Gemini and Claude providers
- Updated extract_label_info() to preserve and validate image_processing field
- All tests passing, no regressions
This commit is contained in:
2026-04-21 18:53:04 +03:00
parent 76fa22bba9
commit ada3669217
5 changed files with 525 additions and 8 deletions

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@@ -77,7 +77,35 @@
- Remove hyphens/special chars for fuzzy matching
- Use HUMAN-READABLE sizes (1.6TB not 1600GB)
## Output Format
## Image Processing Guidance (NEW)
Analyze the image layout and return crop/rotation metadata to optimize photo storage:
### Crop Bounds Analysis
- Identify the PRIMARY ITEM in the image (main object, not background/clutter)
- Return bounding box: `{x, y, width, height}` in pixel coordinates
- Rules:
- `x, y`: top-left corner of item (pixel offset from image top-left)
- `width, height`: dimensions of item bounding box
- Include minimal padding (10-15 pixels) around item edges
- Ignore background clutter, other items, hands, reflections
### Rotation Analysis
- Check if item labels/text are readable
- If text is rotated (not horizontal), calculate rotation needed
- Return `rotation_degrees`: degrees to rotate CLOCKWISE to make text readable
- Examples:
- Text rotated 90° counter-clockwise → return 90 (rotate 90° clockwise)
- Text rotated 45° clockwise → return -45 (rotate 45° counter-clockwise)
- Text already readable → return 0
### Confidence Score
- Return `confidence`: 0.0-1.0 indicating reliability of crop/rotation analysis
- 0.9+ = High confidence (clear item, readable text)
- 0.7-0.89 = Medium confidence (some ambiguity or text partially obscured)
- <0.7 = Low confidence (cluttered image, unclear item boundaries)
### Output Format (Extended)
```json
{
"items": [
@@ -90,9 +118,20 @@
"Size": "human_readable_size",
"Color": "color",
"PartNr": "part_number",
"OCR": "TYPE SIZE VENDOR CONNECTOR PARTNUMBER"
"OCR": "TYPE SIZE VENDOR CONNECTOR PARTNUMBER",
"image_processing": {
"crop_bounds": {
"x": 50,
"y": 100,
"width": 300,
"height": 200
},
"rotation_degrees": 15,
"confidence": 0.92
}
}
]
}
```
Return ONLY JSON. No markdown. No text.
**Return ONLY JSON. No markdown. No text.**

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# Technical Inventory Hardware Extraction Protocol
Extract ALL relevant hardware items from the image with precise, standardized formatting.
## Filtering Rules
- **INCLUDE**: Physical hardware, modules, cables, servers, storage, transceivers
- **EXCLUDE**: Generic mounting hardware (screws, brackets, rails), paper licenses, empty packaging
- **Multi-item labels**: Treat each SKU/variant as a separate item (e.g., "5m cable" and "7m cable" = 2 items)
## Item Field Format (CRITICAL)
[]
**Component Rules:**
- `<size_or_length>`:
- **STORAGE CAPACITY - HUMAN READABLE**: Convert to largest unit (TB/MB).
- Examples: "1600GB" → "1.6TB", "256GB" → "256GB", "512MB" → "512MB"
- Rule: If ≥1000GB, use TB. If ≥1000MB, use GB. Otherwise use MB.
- **CABLE/WIRE LENGTH**: Meters only. Examples: "5m", "10m", "50m"
- **RAM DIMM**: Capacity in GB. Examples: "128GB", "32GB", "8GB"
- `<type>`: Asset class. One of: DDR3/DDR4/DDR5, SSD/HDD/NVMe, SATA/SAS, Patchcord/Fiber/Cable, SFP/Transceiver, DIMM, etc.
- `<vendor>`: Manufacturer (HP, HPE, Dell, Samsung, Cisco, Hynix, Intel, Broadcom)
- `<connector>`: Physical interface (RJ45, LC-LC, MPO, U.3, SATA, SAS, ST, SC). Omit if N/A.
- `<part_number>`: Part number ONLY if visible. **Omit serial numbers.**
**Item Examples (WITH HUMAN-READABLE SIZES):**
- `1.6TB NVMe HPE U.3 P66093-002` (not 1600GB)
- `256GB SSD Dell SATA SK-8765` (already human-readable)
- `5m Patchcord LC-LC`
- `128GB DDR4 Hynix`
- `512MB Cache Samsung SATA` (stays MB if under 1GB)
**Size Conversion Examples:**
- 1600GB → 1.6TB
- 2048GB → 2TB
- 512GB → 512GB (under 1TB threshold)
- 256MB → 256MB
- 1024MB → 1GB
**Restrictions:**
- No comments in parenthesis
- No measurement units in Item field (e.g., "1.6TB" not "1.6TB Storage")
- No secondary vendors
- No diameter/mm in Item field
- ONE vendor only (primary manufacturer)
## Other Fields
- **Type**: Repeat the asset class (DDR4, SSD, NVMe, Patchcord, etc.)
- **Description**: Technical summary, max 5 words. Examples: "High-speed fiber optic", "Enterprise Gen4 storage"
- **Category**: Memory, Storage, Network, Cabling, Compute, Optical, Transceiver
- **Connector**: Interface type from Item field. Examples: "LC-LC", "RJ45", "U.3"
- **Size**: **HUMAN-READABLE capacity or length.** Examples: "1.6TB", "256GB", "5m" (NOT "1600GB")
- **Color**: Physical color if distinguishing
- **PartNr**: Part number only (no serial numbers)
- **OCR**: Robust matching key for OCR tolerance
## OCR Field Rules (CRITICAL)
Generate a SHORT, clean matching key:
- Format: **UPPERCASE space-separated, NO special chars, NO duplicates**
- Include ONLY: Type + Size + Primary Vendor + Connector + Part Number
- **EXCLUDE**: Serial numbers, secondary vendors, duplicate tokens, EMC/SK labels
- **USE HUMAN-READABLE SIZE**: Use TB/GB from Item field, not original notation
**OCR Format:** `TYPE SIZE VENDOR CONNECTOR PARTNUMBER`
**OCR Examples (WITH HUMAN-READABLE SIZES):**
- Item: `1.6TB NVMe HPE U.3 P66093-002` → OCR: `NVME 1.6TB HPE U3 P66093002`
- Item: `5m Patchcord LC-LC` → OCR: `PATCHCORD 5M LC LC`
- Item: `256GB SSD Samsung SAS SK-8765` → OCR: `SSD 256GB SAMSUNG SAS SK8765`
- Item: `128GB DDR4 Hynix` → OCR: `DDR4 128GB HYNIX`
**OCR Constraints:**
- NO duplicate part numbers
- NO secondary vendor names
- NO extraneous labels
- Each token appears ONE time only
- Remove hyphens/special chars for fuzzy matching
- Use HUMAN-READABLE sizes (1.6TB not 1600GB)
## Output Format
```json
{
"items": [
{
"Item": "[size] type vendor connector partnumber",
"Type": "type",
"Description": "technical details (max 5 words)",
"Category": "category",
"Connector": "connector_type",
"Size": "human_readable_size",
"Color": "color",
"PartNr": "part_number",
"OCR": "TYPE SIZE VENDOR CONNECTOR PARTNUMBER"
}
]
}
Return ONLY JSON. No markdown. No text.