curo1305
0d34867a69
- New `features/doc-service` FastAPI microservice: PDF upload, async text extraction (pdfplumber), AI classification via Anthropic/Ollama/ LM Studio, per-user categories, file download - Alembic migration isolated with `alembic_version_doc_service` table - Main backend: httpx proxy routers for /api/documents/* and /api/documents/categories/*, admin settings API at /api/settings/* - Runtime config in /config/doc_service_config.json (shared Docker volume); api_key masking on reads; atomic write with os.replace() - Frontend: DocumentsPage, DocumentAdminSettingsPage, updated AppsPage launcher hub, simplified Nav (removed Settings link), new routes - docker-compose: doc-service service, doc_data + app_config volumes, removed internal:true from backend-net for outbound AI API calls - Fix pre-commit hook: probe Docker socket path so git subprocess picks up Docker Desktop on macOS - Fix security_check.py: use sys.executable for bandit so venv python is used instead of system python Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
32 lines
1.0 KiB
Python
32 lines
1.0 KiB
Python
from abc import ABC, abstractmethod
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SYSTEM_PROMPT = (
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"You are a financial document analysis assistant. "
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"Given the text extracted from a PDF document, return ONLY a JSON object "
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"with no markdown, no code fences, and no explanation."
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)
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USER_PROMPT_TEMPLATE = """Analyze the following document text and return a JSON object with exactly these keys:
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document_type (one of: invoice, bill, receipt, order, expense, revenue, unknown),
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total_amount (string or null),
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currency (string or null),
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vendor_name (string or null),
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customer_name (string or null),
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billing_address (string or null),
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customer_address (string or null),
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invoice_number (string or null),
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invoice_date (string or null),
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due_date (string or null),
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tags (array of strings),
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line_items (array of objects, each with keys: description, amount).
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Document text:
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{text}"""
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class AIProvider(ABC):
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@abstractmethod
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async def classify_document(self, text: str) -> dict:
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"""Return structured extraction dict from document text."""
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...
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