fix: Restore all files lost during destructive rebase
A previous `git pull --rebase origin main` dropped 177 local commits,
losing 3400+ files across admin-v2, backend, studio-v2, website,
klausur-service, and many other services. The partial restore attempt
(660295e2) only recovered some files.
This commit restores all missing files from pre-rebase ref 98933f5e
while preserving post-rebase additions (night-scheduler, night-mode UI,
NightModeWidget dashboard integration).
Restored features include:
- AI Module Sidebar (FAB), OCR Labeling, OCR Compare
- GPU Dashboard, RAG Pipeline, Magic Help
- Klausur-Korrektur (8 files), Abitur-Archiv (5+ files)
- Companion, Zeugnisse-Crawler, Screen Flow
- Full backend, studio-v2, website, klausur-service
- All compliance SDKs, agent-core, voice-service
- CI/CD configs, documentation, scripts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
299
backend/claude_vision.py
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299
backend/claude_vision.py
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"""
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Claude Vision API Integration for Worksheet Analysis
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Uses Anthropic's Claude 3.5 Sonnet for superior OCR and layout understanding.
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"""
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import os
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import base64
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import json
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from pathlib import Path
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from typing import Dict, Optional
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import logging
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logger = logging.getLogger(__name__)
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# Try to import Anthropic SDK
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try:
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from anthropic import Anthropic
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ANTHROPIC_AVAILABLE = True
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except ImportError:
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ANTHROPIC_AVAILABLE = False
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logger.warning("Anthropic SDK not installed. Run: pip install anthropic")
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def _get_anthropic_api_key() -> str:
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"""Get Anthropic API key from environment variable"""
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api_key = os.getenv("ANTHROPIC_API_KEY")
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if not api_key:
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raise RuntimeError(
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"ANTHROPIC_API_KEY ist nicht gesetzt. "
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"Bitte API-Schlüssel als Umgebungsvariable setzen:\n"
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"export ANTHROPIC_API_KEY='sk-ant-api03-...'"
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)
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return api_key
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def _encode_image_to_base64(image_path: Path) -> tuple[str, str]:
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"""
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Encode image to base64 for Claude API.
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Returns:
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(base64_string, media_type)
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"""
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image_bytes = image_path.read_bytes()
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image_b64 = base64.standard_b64encode(image_bytes).decode("utf-8")
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# Determine media type from extension
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ext = image_path.suffix.lower()
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media_type_map = {
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'.jpg': 'image/jpeg',
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'.jpeg': 'image/jpeg',
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'.png': 'image/png',
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'.gif': 'image/gif',
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'.webp': 'image/webp'
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}
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media_type = media_type_map.get(ext, 'image/jpeg')
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return image_b64, media_type
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def analyze_worksheet_with_claude(
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image_path: Path,
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max_tokens: int = 2500,
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model: str = "claude-3-5-sonnet-20241022"
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) -> Dict:
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"""
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Analyze worksheet using Claude Vision API.
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Args:
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image_path: Path to worksheet image
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max_tokens: Maximum tokens in response (default 2500)
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model: Claude model to use (default: Claude 3.5 Sonnet)
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Returns:
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Analysis dict with same structure as OpenAI version
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Raises:
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RuntimeError: If API key not set or SDK not installed
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Exception: If API call fails
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"""
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if not ANTHROPIC_AVAILABLE:
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raise RuntimeError("Anthropic SDK nicht installiert. Run: pip install anthropic")
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if not image_path.exists():
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raise FileNotFoundError(f"Image not found: {image_path}")
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# Get API key
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api_key = _get_anthropic_api_key()
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# Initialize Anthropic client
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client = Anthropic(api_key=api_key)
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# Encode image
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image_b64, media_type = _encode_image_to_base64(image_path)
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# System prompt (instructions)
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system_prompt = """Du bist ein Experte für die Analyse von Schul-Arbeitsblättern.
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Deine Aufgabe ist es, das Arbeitsblatt detailliert zu analysieren und strukturierte Informationen zu extrahieren:
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1. **Gedruckter Text**: Erkenne den VOLLSTÄNDIGEN gedruckten Text inklusive durchgestrichener Wörter
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2. **Handschrift**: Identifiziere alle handschriftlichen Eintragungen (Schülerantworten, Korrekturen, Notizen)
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3. **Layout**: Bestimme räumliche Positionen aller Elemente (Bounding Boxes in Pixeln)
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4. **Diagramme**: Erkenne gedruckte Illustrationen, Grafiken, Diagramme
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5. **Farben**: Klassifiziere Handschrift nach Farbe (blau/schwarz/rot/Bleistift)
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WICHTIG: Gib deine Antwort als gültiges JSON zurück, nicht als Markdown Code Block!"""
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# User prompt with JSON schema
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user_prompt = """Analysiere dieses Arbeitsblatt und gib ein JSON mit folgendem Aufbau zurück:
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{
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"title": string | null,
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"subject": string | null,
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"grade_level": string | null,
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"instructions": string | null,
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"canonical_text": string | null,
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"printed_blocks": [
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{
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"id": string,
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"role": "title" | "instructions" | "body" | "other",
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"text": string
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}
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],
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"layout": {
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"page_structure": {
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"has_diagram": boolean,
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"orientation": "portrait" | "landscape"
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},
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"text_regions": [
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{
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"id": string,
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"type": "title" | "paragraph" | "list" | "instruction",
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"text": string,
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"bounding_box": {"x": int, "y": int, "width": int, "height": int},
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"font_characteristics": {
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"is_bold": boolean,
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"approximate_size": "large" | "medium" | "small"
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}
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}
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],
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"diagram_elements": [
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{
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"id": string,
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"type": "illustration" | "chart" | "graph" | "shape",
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"description": string,
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"bounding_box": {"x": int, "y": int, "width": int, "height": int},
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"preserve": boolean
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}
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]
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},
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"handwriting_regions": [
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{
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"id": string,
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"text": string,
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"type": "student_answer" | "correction" | "note" | "drawing",
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"bounding_box": {"x": int, "y": int, "width": int, "height": int},
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"color_hint": "blue" | "black" | "red" | "pencil" | "unknown"
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}
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],
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"handwritten_annotations": [
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{
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"text": string,
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"approx_location": string
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}
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],
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"struck_through_words": [
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{
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"text": string,
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"context": string
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}
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],
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"tasks": [
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{
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"id": string,
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"type": "cloze" | "mcq" | "short_answer" | "math" | "other",
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"description": string,
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"text_with_gaps": string | null,
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"gaps": [
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{
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"id": string,
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"solution": string,
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"position_hint": string
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}
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]
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}
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]
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}
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WICHTIGE HINWEISE:
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- "canonical_text" enthält den KORRIGIERTEN gedruckten Text OHNE Handschrift und OHNE durchgestrichene Wörter
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- "struck_through_words" enthält alle durchgestrichenen Wörter mit Kontext
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- Bounding Boxes sind ungefähre Pixel-Positionen (x, y von oben links, width/height in Pixeln)
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- "layout.text_regions" sollte alle gedruckten Textbereiche mit genauen Positionen enthalten
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- "handwriting_regions" sollte alle handschriftlichen Bereiche mit Farb-Hinweisen enthalten
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- Setze "preserve": true für Diagramm-Elemente die erhalten bleiben sollen
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- Durchgestrichene Wörter NUR in "struck_through_words", NICHT in "canonical_text"
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Gib NUR das JSON zurück, ohne Code-Block-Marker!"""
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try:
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logger.info(f"Calling Claude API for analysis of {image_path.name}")
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# Call Claude API
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response = client.messages.create(
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model=model,
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max_tokens=max_tokens,
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system=system_prompt,
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "image",
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"source": {
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"type": "base64",
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"media_type": media_type,
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"data": image_b64,
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},
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},
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{
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"type": "text",
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"text": user_prompt
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}
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],
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}
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],
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)
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# Extract text from response
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if not response.content:
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raise RuntimeError("Empty response from Claude API")
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# Get first text block
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text_content = None
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for block in response.content:
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if block.type == "text":
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text_content = block.text
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break
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if not text_content:
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raise RuntimeError("No text content in Claude response")
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logger.info(f"Received response from Claude ({len(text_content)} chars)")
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# Parse JSON
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# Claude might wrap JSON in ```json ... ```, remove if present
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text_content = text_content.strip()
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if text_content.startswith("```json"):
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text_content = text_content[7:]
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if text_content.startswith("```"):
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text_content = text_content[3:]
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if text_content.endswith("```"):
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text_content = text_content[:-3]
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text_content = text_content.strip()
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try:
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analysis_data = json.loads(text_content)
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except json.JSONDecodeError as e:
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logger.error(f"Failed to parse Claude JSON response: {e}")
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logger.error(f"Response text: {text_content[:500]}...")
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raise RuntimeError(f"Invalid JSON from Claude: {e}\nContent: {text_content[:200]}...") from e
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logger.info("Successfully parsed Claude analysis")
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return analysis_data
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except Exception as e:
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logger.error(f"Claude API call failed: {e}")
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raise
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def test_claude_connection() -> bool:
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"""
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Test if Claude API is accessible with current credentials.
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Returns:
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True if connection successful, False otherwise
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"""
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if not ANTHROPIC_AVAILABLE:
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logger.error("Anthropic SDK not installed")
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return False
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try:
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api_key = _get_anthropic_api_key()
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client = Anthropic(api_key=api_key)
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# Simple test call
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response = client.messages.create(
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model="claude-3-5-sonnet-20241022",
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max_tokens=10,
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messages=[{"role": "user", "content": "Test"}]
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)
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logger.info("✅ Claude API connection successful")
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return True
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except Exception as e:
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logger.error(f"❌ Claude API connection failed: {e}")
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return False
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Block a user