ReeceandClaude Opus 4.7
b32a3cf271
Resolution favours main for all conflicts (new orchestrator shape with artifacts/file_names/conversation_history/resume_with, WorkflowOutcome enum, RAG, ledger agent, deleted engine/config/.env.example). Re-wires our three form-fill agents (FormAnalyserAgent, FormFillerAgent, DocumentExtractorAgent) into the new app layout: - contracts/__init__.py: adds form-fill exports to __all__ - api/dependencies.py: adds get_form_analyser_agent / get_form_filler_agent / get_document_extractor_agent - api/app.py: instantiates the three agents in lifespan and registers form_fill_router - api/routes/__init__.py: exports form_fill_router - tests/test_stirling_api.py: imports and registers form-fill stubs - tests/test_stirling_contracts.py: adds back KnowledgeUpdateResponse discriminator test Form fill remains accessible via its own endpoints (/api/v1/form/ai/analyse, /fill-batch, /extract). Not wired as an orchestrator delegate — following main's pattern where orchestrator only routes pdf_edit/pdf_question/user_spec /math_auditor. Follow-ups still needed: - Thread conversation_history into form-fill agent prompts - Align form-fill response outcomes with WorkflowOutcome enum - Decide whether engine should return ToolOperationStep plans (main's new pattern per #6116) or keep returning fill values directly All 127 engine tests pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
109 lines
3.2 KiB
Python
109 lines
3.2 KiB
Python
from stirling.config import AppSettings
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from stirling.contracts import (
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AgentExecutionRequest,
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AgentSpec,
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AgentSpecStep,
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EditPlanResponse,
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ExecutionContext,
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ExtractedFileText,
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ExtractedTextArtifact,
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KnowledgeEntry,
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KnowledgeUpdateResponse,
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OrchestratorRequest,
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PdfQuestionAnswerResponse,
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PdfTextSelection,
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ToolOperationStep,
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)
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from stirling.models.tool_models import Angle, RotatePdfParams, ToolEndpoint
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def test_orchestrator_request_accepts_user_message() -> None:
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request = OrchestratorRequest(
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user_message="Rotate the PDF",
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file_names=["test.pdf"],
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artifacts=[
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ExtractedTextArtifact(
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files=[
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ExtractedFileText(
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file_name="test.pdf",
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pages=[PdfTextSelection(page_number=1, text="Hello")],
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)
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]
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)
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],
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)
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assert request.user_message == "Rotate the PDF"
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assert len(request.artifacts) == 1
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def test_agent_execution_request_uses_typed_agent_spec() -> None:
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steps: list[AgentSpecStep] = [
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ToolOperationStep(
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tool=ToolEndpoint.ROTATE_PDF,
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parameters=RotatePdfParams(angle=Angle(90)),
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)
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]
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request = AgentExecutionRequest(
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agent_spec=AgentSpec(
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name="Invoice cleanup",
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description="Normalise inbound invoices",
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objective="Prepare uploads for accounting review",
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steps=steps,
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),
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current_step_index=0,
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execution_context=ExecutionContext(input_files=["invoice.pdf"]),
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)
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assert request.agent_spec.steps[0].kind == "tool"
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def test_edit_plan_response_has_typed_steps() -> None:
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steps = [ToolOperationStep(tool=ToolEndpoint.ROTATE_PDF, parameters=RotatePdfParams(angle=Angle(90)))]
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response = EditPlanResponse(
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summary="Rotate the input PDF by 90 degrees.",
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steps=steps,
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)
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assert response.steps[0].tool == ToolEndpoint.ROTATE_PDF
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def test_pdf_question_answer_defaults_evidence_list() -> None:
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response = PdfQuestionAnswerResponse(answer="The invoice total is 120.00")
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assert response.evidence == []
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def test_knowledge_update_response_discriminator() -> None:
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update = KnowledgeUpdateResponse(
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proposed_entries=[KnowledgeEntry(key="name", value="John", source="CV")],
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message="Extracted.",
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)
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assert update.outcome == "knowledge_update"
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def test_app_settings_accepts_model_configuration() -> None:
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from pathlib import Path
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from stirling.config import RagBackend
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settings = AppSettings(
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smart_model_name="claude-sonnet-4-5-20250929",
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fast_model_name="claude-haiku-4-5-20251001",
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smart_model_max_tokens=8192,
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fast_model_max_tokens=2048,
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rag_backend=RagBackend.SQLITE,
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rag_embedding_model="voyageai:voyage-4",
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rag_store_path=Path(":memory:"),
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rag_pgvector_dsn="",
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rag_chunk_size=512,
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rag_chunk_overlap=64,
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rag_default_top_k=5,
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posthog_enabled=False,
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posthog_api_key="",
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posthog_host="https://eu.i.posthog.com",
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)
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assert settings.smart_model_name
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assert settings.fast_model_max_tokens == 2048
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