Merge pull request 'feat(pipeline): GenAIStep (spec §6.3, §7, §9.2)' (#14) from feat/step-genai into main

Assembles the prompt, picks the structured-output schema, calls the
injected GenAIClient, and maps any emitted segment_citations into
response.provenance. Reliability flags stay None here; ReliabilityStep
fills them in Task 2.7.

- System prompt = use_case.system_prompt + (provenance-on) the verbatim
  citation instruction from spec §9.2.
- User text = SegmentIndex.to_prompt_text([p1_l0] style) when provenance
  is on, else plain OCR flat text + texts joined.
- Response schema = UseCaseResponse directly, or a runtime
  create_model("ProvenanceWrappedResponse", result=(UCR, ...),
  segment_citations=(list[SegmentCitation], Field(default_factory=list)))
  when provenance is on.
- Model = request override -> use-case default.
- Failure modes: httpx / connection / timeout errors -> IX_002_000;
  pydantic.ValidationError -> IX_002_001.
- Writes ix_result.result + ix_result.meta_data (model_name +
  token_usage); builds response.provenance via
  map_segment_refs_to_provenance when provenance is on.

17 unit tests in tests/unit/test_genai_step.py cover validate
(ocr_only skip, empty -> IX_001_000, text-only, ocr-text path), process
happy path, system-prompt shape with/without citation instruction, user
text tagged vs. plain, response schema plain vs. wrapped, provenance
mapping, error mapping (IX_002_000 + IX_002_001), and model selection
(request override + use-case default).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/ix/pipeline/genai_step.py

@@ -0,0 +1,216 @@
+"""GenAIStep — assemble prompt, call LLM, map provenance (spec §6.3, §7, §9.2).
+
+Runs after :class:`~ix.pipeline.ocr_step.OCRStep`. Builds the chat-style
+``request_kwargs`` (messages + model name), picks the structured-output
+schema (plain ``UseCaseResponse`` or a runtime
+``ProvenanceWrappedResponse(result=..., segment_citations=...)`` when
+provenance is on), hands both to the injected :class:`GenAIClient`, and
+writes the parsed payload onto ``response_ix.ix_result``.
+
+When provenance is on, the LLM-emitted ``segment_citations`` flow into
+:func:`~ix.provenance.map_segment_refs_to_provenance` to build
+``response_ix.provenance``. The per-field reliability flags
+(``provenance_verified`` / ``text_agreement``) stay ``None`` here — they
+land in :class:`~ix.pipeline.reliability_step.ReliabilityStep`.
+
+Failure modes:
+
+* Network / timeout / non-2xx surfaced by the client → ``IX_002_000``.
+* :class:`pydantic.ValidationError` (structured output didn't match the
+  schema) → ``IX_002_001``.
+"""
+
+from __future__ import annotations
+
+from typing import Any, cast
+
+import httpx
+from pydantic import BaseModel, Field, ValidationError, create_model
+
+from ix.contracts import RequestIX, ResponseIX, SegmentCitation
+from ix.errors import IXErrorCode, IXException
+from ix.genai.client import GenAIClient
+from ix.pipeline.step import Step
+from ix.provenance import map_segment_refs_to_provenance
+from ix.segmentation import SegmentIndex
+
+# Verbatim from spec §9.2 (core-pipeline spec) — inserted after the
+# use-case system prompt when provenance is on.
+_CITATION_INSTRUCTION = (
+    "For each extracted field, you must also populate the `segment_citations` list.\n"
+    "Each entry maps one field to the document segments that were its source.\n"
+    "Set `field_path` to the dot-separated JSON path of the field "
+    "(e.g. 'result.invoice_number').\n"
+    "Use two separate segment ID lists:\n"
+    "- `value_segment_ids`: segment IDs whose text directly contains the extracted "
+    "value (e.g. ['p1_l4'] for the line containing 'INV-001').\n"
+    "- `context_segment_ids`: segment IDs for surrounding label or anchor text that "
+    "helped you identify the field but does not contain the value itself "
+    "(e.g. ['p1_l3'] for a label like 'Invoice Number:'). Leave empty if there is "
+    "no distinct label.\n"
+    "Only use segment IDs that appear in the document text.\n"
+    "Omit fields for which you cannot identify a source segment."
+)
+
+
+class GenAIStep(Step):
+    """LLM extraction + (optional) provenance mapping."""
+
+    def __init__(self, genai_client: GenAIClient) -> None:
+        self._client = genai_client
+
+    async def validate(self, request_ix: RequestIX, response_ix: ResponseIX) -> bool:
+        if request_ix.options.ocr.ocr_only:
+            return False
+
+        ctx = response_ix.context
+        ocr_text = (
+            response_ix.ocr_result.result.text
+            if response_ix.ocr_result is not None
+            else None
+        )
+        texts = list(getattr(ctx, "texts", []) or []) if ctx is not None else []
+
+        if not (ocr_text and ocr_text.strip()) and not texts:
+            raise IXException(IXErrorCode.IX_001_000)
+        return True
+
+    async def process(
+        self, request_ix: RequestIX, response_ix: ResponseIX
+    ) -> ResponseIX:
+        ctx = response_ix.context
+        assert ctx is not None, "SetupStep must populate response_ix.context"
+        use_case_request: Any = getattr(ctx, "use_case_request", None)
+        use_case_response_cls: type[BaseModel] = getattr(ctx, "use_case_response", None)
+        assert use_case_request is not None and use_case_response_cls is not None
+
+        opts = request_ix.options
+        provenance_on = opts.provenance.include_provenance
+
+        # 1. System prompt — use-case default + optional citation instruction.
+        system_prompt = use_case_request.system_prompt
+        if provenance_on:
+            system_prompt = f"{system_prompt}\n\n{_CITATION_INSTRUCTION}"
+
+        # 2. User text — segment-tagged when provenance is on, else plain OCR + texts.
+        user_text = self._build_user_text(response_ix, provenance_on)
+
+        # 3. Response schema — plain or wrapped.
+        response_schema = self._resolve_response_schema(
+            use_case_response_cls, provenance_on
+        )
+
+        # 4. Model selection — request override → use-case default.
+        model_name = (
+            opts.gen_ai.gen_ai_model_name
+            or getattr(use_case_request, "default_model", None)
+        )
+
+        request_kwargs = {
+            "model": model_name,
+            "messages": [
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_text},
+            ],
+        }
+
+        # 5. Call the backend, translate errors.
+        try:
+            result = await self._client.invoke(
+                request_kwargs=request_kwargs,
+                response_schema=response_schema,
+            )
+        except ValidationError as exc:
+            raise IXException(
+                IXErrorCode.IX_002_001,
+                detail=f"{use_case_response_cls.__name__}: {exc}",
+            ) from exc
+        except (httpx.HTTPError, ConnectionError, TimeoutError) as exc:
+            raise IXException(
+                IXErrorCode.IX_002_000,
+                detail=f"{model_name}: {exc.__class__.__name__}: {exc}",
+            ) from exc
+        except IXException:
+            raise
+
+        # 6. Split parsed output; write result + meta.
+        if provenance_on:
+            wrapped = result.parsed
+            extraction: BaseModel = wrapped.result
+            segment_citations: list[SegmentCitation] = list(
+                getattr(wrapped, "segment_citations", []) or []
+            )
+        else:
+            extraction = result.parsed
+            segment_citations = []
+
+        response_ix.ix_result.result = extraction.model_dump(mode="json")
+        response_ix.ix_result.meta_data = {
+            "model_name": result.model_name,
+            "token_usage": {
+                "prompt_tokens": result.usage.prompt_tokens,
+                "completion_tokens": result.usage.completion_tokens,
+            },
+        }
+
+        # 7. Provenance mapping — only the structural assembly. Reliability
+        # flags get written in ReliabilityStep.
+        if provenance_on:
+            seg_idx = cast(SegmentIndex, getattr(ctx, "segment_index", None))
+            if seg_idx is None:
+                # No OCR was run (text-only request); skip provenance.
+                response_ix.provenance = None
+            else:
+                response_ix.provenance = map_segment_refs_to_provenance(
+                    extraction_result={"result": response_ix.ix_result.result},
+                    segment_citations=segment_citations,
+                    segment_index=seg_idx,
+                    max_sources_per_field=opts.provenance.max_sources_per_field,
+                    min_confidence=0.0,
+                    include_bounding_boxes=True,
+                    source_type="value_and_context",
+                )
+
+        return response_ix
+
+    def _build_user_text(self, response_ix: ResponseIX, provenance_on: bool) -> str:
+        ctx = response_ix.context
+        assert ctx is not None
+        texts: list[str] = list(getattr(ctx, "texts", []) or [])
+        seg_idx: SegmentIndex | None = getattr(ctx, "segment_index", None)
+
+        if provenance_on and seg_idx is not None:
+            return seg_idx.to_prompt_text(context_texts=texts)
+
+        # Plain concat — OCR flat text + any extra paperless-style texts.
+        parts: list[str] = []
+        ocr_text = (
+            response_ix.ocr_result.result.text
+            if response_ix.ocr_result is not None
+            else None
+        )
+        if ocr_text:
+            parts.append(ocr_text)
+        parts.extend(texts)
+        return "\n\n".join(p for p in parts if p)
+
+    def _resolve_response_schema(
+        self,
+        use_case_response_cls: type[BaseModel],
+        provenance_on: bool,
+    ) -> type[BaseModel]:
+        if not provenance_on:
+            return use_case_response_cls
+        # Dynamic wrapper — one per call is fine; Pydantic caches the
+        # generated JSON schema internally.
+        return create_model(
+            "ProvenanceWrappedResponse",
+            result=(use_case_response_cls, ...),
+            segment_citations=(
+                list[SegmentCitation],
+                Field(default_factory=list),
+            ),
+        )
+
+
+__all__ = ["GenAIStep"]

tests/unit/test_genai_step.py

@@ -0,0 +1,378 @@
+"""Tests for :class:`ix.pipeline.genai_step.GenAIStep` (spec §6.3, §7, §9.2)."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import httpx
+import pytest
+from pydantic import BaseModel, ValidationError
+
+from ix.contracts import (
+    Context,
+    GenAIOptions,
+    Line,
+    OCRDetails,
+    OCROptions,
+    OCRResult,
+    Options,
+    Page,
+    ProvenanceData,
+    ProvenanceOptions,
+    RequestIX,
+    ResponseIX,
+    SegmentCitation,
+)
+from ix.contracts.response import _InternalContext
+from ix.errors import IXErrorCode, IXException
+from ix.genai import FakeGenAIClient, GenAIInvocationResult, GenAIUsage
+from ix.pipeline.genai_step import GenAIStep
+from ix.segmentation import PageMetadata, SegmentIndex
+from ix.use_cases.bank_statement_header import BankStatementHeader
+from ix.use_cases.bank_statement_header import Request as BankReq
+
+
+def _make_request(
+    *,
+    use_ocr: bool = True,
+    ocr_only: bool = False,
+    include_provenance: bool = True,
+    model_name: str | None = None,
+) -> RequestIX:
+    return RequestIX(
+        use_case="bank_statement_header",
+        ix_client_id="test",
+        request_id="r-1",
+        context=Context(files=[], texts=[]),
+        options=Options(
+            ocr=OCROptions(use_ocr=use_ocr, ocr_only=ocr_only),
+            gen_ai=GenAIOptions(gen_ai_model_name=model_name),
+            provenance=ProvenanceOptions(
+                include_provenance=include_provenance,
+                max_sources_per_field=5,
+            ),
+        ),
+    )
+
+
+def _ocr_with_lines(lines: list[str]) -> OCRResult:
+    return OCRResult(
+        result=OCRDetails(
+            text="\n".join(lines),
+            pages=[
+                Page(
+                    page_no=1,
+                    width=100.0,
+                    height=200.0,
+                    lines=[
+                        Line(text=t, bounding_box=[0, i * 10, 10, i * 10, 10, i * 10 + 5, 0, i * 10 + 5])
+                        for i, t in enumerate(lines)
+                    ],
+                )
+            ],
+        )
+    )
+
+
+def _response_with_segment_index(
+    lines: list[str], texts: list[str] | None = None
+) -> ResponseIX:
+    ocr = _ocr_with_lines(lines)
+    resp = ResponseIX(ocr_result=ocr)
+    seg_idx = SegmentIndex.build(
+        ocr_result=ocr,
+        granularity="line",
+        pages_metadata=[PageMetadata(file_index=0)],
+    )
+    resp.context = _InternalContext(
+        use_case_request=BankReq(),
+        use_case_response=BankStatementHeader,
+        segment_index=seg_idx,
+        texts=texts or [],
+        pages=ocr.result.pages,
+        page_metadata=[PageMetadata(file_index=0)],
+    )
+    return resp
+
+
+class CapturingClient:
+    """Records the request_kwargs + response_schema handed to invoke()."""
+
+    def __init__(self, parsed: Any) -> None:
+        self._parsed = parsed
+        self.request_kwargs: dict[str, Any] | None = None
+        self.response_schema: type[BaseModel] | None = None
+
+    async def invoke(
+        self,
+        request_kwargs: dict[str, Any],
+        response_schema: type[BaseModel],
+    ) -> GenAIInvocationResult:
+        self.request_kwargs = request_kwargs
+        self.response_schema = response_schema
+        return GenAIInvocationResult(
+            parsed=self._parsed,
+            usage=GenAIUsage(prompt_tokens=5, completion_tokens=7),
+            model_name="captured-model",
+        )
+
+
+class TestValidate:
+    async def test_ocr_only_skips(self) -> None:
+        step = GenAIStep(
+            genai_client=FakeGenAIClient(parsed=BankStatementHeader(bank_name="x", currency="EUR"))
+        )
+        req = _make_request(ocr_only=True)
+        resp = _response_with_segment_index(lines=["hello"])
+        assert await step.validate(req, resp) is False
+
+    async def test_empty_context_raises_IX_001_000(self) -> None:
+        step = GenAIStep(
+            genai_client=FakeGenAIClient(parsed=BankStatementHeader(bank_name="x", currency="EUR"))
+        )
+        req = _make_request()
+        resp = ResponseIX(ocr_result=OCRResult(result=OCRDetails(text="")))
+        resp.context = _InternalContext(
+            use_case_request=BankReq(),
+            use_case_response=BankStatementHeader,
+            texts=[],
+        )
+        with pytest.raises(IXException) as ei:
+            await step.validate(req, resp)
+        assert ei.value.code is IXErrorCode.IX_001_000
+
+    async def test_runs_when_texts_only(self) -> None:
+        step = GenAIStep(
+            genai_client=FakeGenAIClient(parsed=BankStatementHeader(bank_name="x", currency="EUR"))
+        )
+        req = _make_request()
+        resp = ResponseIX(ocr_result=OCRResult(result=OCRDetails(text="")))
+        resp.context = _InternalContext(
+            use_case_request=BankReq(),
+            use_case_response=BankStatementHeader,
+            texts=["some paperless text"],
+        )
+        assert await step.validate(req, resp) is True
+
+    async def test_runs_when_ocr_text_present(self) -> None:
+        step = GenAIStep(
+            genai_client=FakeGenAIClient(parsed=BankStatementHeader(bank_name="x", currency="EUR"))
+        )
+        req = _make_request()
+        resp = _response_with_segment_index(lines=["hello"])
+        assert await step.validate(req, resp) is True
+
+
+class TestProcessBasic:
+    async def test_writes_ix_result_and_meta(self) -> None:
+        parsed = BankStatementHeader(bank_name="DKB", currency="EUR")
+        client = CapturingClient(parsed=parsed)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["hello"])
+        resp = await step.process(req, resp)
+
+        assert resp.ix_result.result["bank_name"] == "DKB"
+        assert resp.ix_result.result["currency"] == "EUR"
+        assert resp.ix_result.meta_data["model_name"] == "captured-model"
+        assert resp.ix_result.meta_data["token_usage"]["prompt_tokens"] == 5
+        assert resp.ix_result.meta_data["token_usage"]["completion_tokens"] == 7
+
+
+class TestSystemPromptAssembly:
+    async def test_citation_instruction_appended_when_provenance_on(self) -> None:
+        parsed_wrapped: Any = _WrappedResponse(
+            result=BankStatementHeader(bank_name="DKB", currency="EUR"),
+            segment_citations=[],
+        )
+        client = CapturingClient(parsed=parsed_wrapped)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=True)
+        resp = _response_with_segment_index(lines=["hello"])
+        await step.process(req, resp)
+
+        messages = client.request_kwargs["messages"]  # type: ignore[index]
+        system = messages[0]["content"]
+        # Use-case system prompt is always there.
+        assert "extract header metadata" in system
+        # Citation instruction added.
+        assert "segment_citations" in system
+        assert "value_segment_ids" in system
+
+    async def test_citation_instruction_absent_when_provenance_off(self) -> None:
+        parsed = BankStatementHeader(bank_name="DKB", currency="EUR")
+        client = CapturingClient(parsed=parsed)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["hello"])
+        await step.process(req, resp)
+
+        messages = client.request_kwargs["messages"]  # type: ignore[index]
+        system = messages[0]["content"]
+        assert "segment_citations" not in system
+
+
+class TestUserTextFormat:
+    async def test_tagged_prompt_when_provenance_on(self) -> None:
+        parsed_wrapped: Any = _WrappedResponse(
+            result=BankStatementHeader(bank_name="DKB", currency="EUR"),
+            segment_citations=[],
+        )
+        client = CapturingClient(parsed=parsed_wrapped)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=True)
+        resp = _response_with_segment_index(lines=["alpha line", "beta line"])
+        await step.process(req, resp)
+
+        user_content = client.request_kwargs["messages"][1]["content"]  # type: ignore[index]
+        assert "[p1_l0] alpha line" in user_content
+        assert "[p1_l1] beta line" in user_content
+
+    async def test_plain_prompt_when_provenance_off(self) -> None:
+        parsed = BankStatementHeader(bank_name="DKB", currency="EUR")
+        client = CapturingClient(parsed=parsed)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["alpha line", "beta line"])
+        await step.process(req, resp)
+
+        user_content = client.request_kwargs["messages"][1]["content"]  # type: ignore[index]
+        assert "[p1_l0]" not in user_content
+        assert "alpha line" in user_content
+        assert "beta line" in user_content
+
+
+class TestResponseSchemaChoice:
+    async def test_plain_schema_when_provenance_off(self) -> None:
+        parsed = BankStatementHeader(bank_name="DKB", currency="EUR")
+        client = CapturingClient(parsed=parsed)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["hello"])
+        await step.process(req, resp)
+        assert client.response_schema is BankStatementHeader
+
+    async def test_wrapped_schema_when_provenance_on(self) -> None:
+        parsed_wrapped: Any = _WrappedResponse(
+            result=BankStatementHeader(bank_name="DKB", currency="EUR"),
+            segment_citations=[],
+        )
+        client = CapturingClient(parsed=parsed_wrapped)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=True)
+        resp = _response_with_segment_index(lines=["hello"])
+        await step.process(req, resp)
+        schema = client.response_schema
+        assert schema is not None
+        field_names = set(schema.model_fields.keys())
+        assert field_names == {"result", "segment_citations"}
+
+
+class TestProvenanceMapping:
+    async def test_provenance_populated_from_citations(self) -> None:
+        parsed_wrapped: Any = _WrappedResponse(
+            result=BankStatementHeader(bank_name="DKB", currency="EUR"),
+            segment_citations=[
+                SegmentCitation(
+                    field_path="result.bank_name",
+                    value_segment_ids=["p1_l0"],
+                    context_segment_ids=[],
+                ),
+            ],
+        )
+        client = CapturingClient(parsed=parsed_wrapped)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=True)
+        resp = _response_with_segment_index(lines=["DKB"])
+        resp = await step.process(req, resp)
+
+        assert isinstance(resp.provenance, ProvenanceData)
+        fields = resp.provenance.fields
+        assert "result.bank_name" in fields
+        fp = fields["result.bank_name"]
+        assert fp.value == "DKB"
+        assert len(fp.sources) == 1
+        assert fp.sources[0].segment_id == "p1_l0"
+        # Reliability flags are NOT set here — ReliabilityStep does that.
+        assert fp.provenance_verified is None
+        assert fp.text_agreement is None
+
+
+class TestErrorHandling:
+    async def test_network_error_maps_to_IX_002_000(self) -> None:
+        err = httpx.ConnectError("refused")
+        client = FakeGenAIClient(
+            parsed=BankStatementHeader(bank_name="x", currency="EUR"),
+            raise_on_call=err,
+        )
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["hello"])
+        with pytest.raises(IXException) as ei:
+            await step.process(req, resp)
+        assert ei.value.code is IXErrorCode.IX_002_000
+
+    async def test_timeout_maps_to_IX_002_000(self) -> None:
+        err = httpx.ReadTimeout("slow")
+        client = FakeGenAIClient(
+            parsed=BankStatementHeader(bank_name="x", currency="EUR"),
+            raise_on_call=err,
+        )
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["hello"])
+        with pytest.raises(IXException) as ei:
+            await step.process(req, resp)
+        assert ei.value.code is IXErrorCode.IX_002_000
+
+    async def test_validation_error_maps_to_IX_002_001(self) -> None:
+        class _M(BaseModel):
+            x: int
+
+        try:
+            _M(x="not-an-int")  # type: ignore[arg-type]
+        except ValidationError as err:
+            raise_err = err
+
+        client = FakeGenAIClient(
+            parsed=BankStatementHeader(bank_name="x", currency="EUR"),
+            raise_on_call=raise_err,
+        )
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["hello"])
+        with pytest.raises(IXException) as ei:
+            await step.process(req, resp)
+        assert ei.value.code is IXErrorCode.IX_002_001
+
+
+class TestModelSelection:
+    async def test_request_model_override_wins(self) -> None:
+        parsed = BankStatementHeader(bank_name="DKB", currency="EUR")
+        client = CapturingClient(parsed=parsed)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False, model_name="explicit-model")
+        resp = _response_with_segment_index(lines=["hello"])
+        await step.process(req, resp)
+        assert client.request_kwargs["model"] == "explicit-model"  # type: ignore[index]
+
+    async def test_falls_back_to_use_case_default(self) -> None:
+        parsed = BankStatementHeader(bank_name="DKB", currency="EUR")
+        client = CapturingClient(parsed=parsed)
+        step = GenAIStep(genai_client=client)
+        req = _make_request(include_provenance=False)
+        resp = _response_with_segment_index(lines=["hello"])
+        await step.process(req, resp)
+        # use-case default is gpt-oss:20b
+        assert client.request_kwargs["model"] == "gpt-oss:20b"  # type: ignore[index]
+
+
+# ----------------------------------------------------------------------------
+# Helpers
+
+
+class _WrappedResponse(BaseModel):
+    """Stand-in for the runtime-created ProvenanceWrappedResponse."""
+
+    result: BankStatementHeader
+    segment_citations: list[SegmentCitation] = []