Invoice Number: {INVOICE_NUMBER}
" + f"Customer: {CUSTOMER}
" + f"Total Amount: ${TOTAL_AMOUNT}
" + f"Due Date: {DUE_DATE}
" + "" + ) + return body.encode("utf-8") + + +def make_pdf() -> bytes: + from reportlab.pdfgen import canvas + + buf = io.BytesIO() + c = canvas.Canvas(buf) + c.setFont("Helvetica", 14) + y = 800 + for line in INVOICE_TEXT.splitlines(): + c.drawString(72, y, line) + y -= 24 + c.save() + return buf.getvalue() + + +def make_docx() -> bytes: + from docx import Document + + doc = Document() + doc.add_heading("Invoice", level=1) + for line in INVOICE_TEXT.splitlines(): + doc.add_paragraph(line) + buf = io.BytesIO() + doc.save(buf) + return buf.getvalue() + + +def make_xlsx() -> bytes: + from openpyxl import Workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws.title = "Invoice" + ws.append(["field", "value"]) + ws.append(["invoice_number", INVOICE_NUMBER]) + ws.append(["customer", CUSTOMER]) + ws.append(["total_amount", TOTAL_AMOUNT]) + ws.append(["due_date", DUE_DATE]) + buf = io.BytesIO() + wb.save(buf) + return buf.getvalue() + + +def _make_image(fmt: str) -> bytes: + """Render the invoice text into an image so the model has to OCR it.""" + from PIL import Image, ImageDraw, ImageFont + + width, height = 640, 360 + img = Image.new("RGB", (width, height), color="white") + draw = ImageDraw.Draw(img) + try: + font = ImageFont.truetype("DejaVuSans.ttf", 22) + except OSError: + font = ImageFont.load_default() + y = 40 + for line in INVOICE_TEXT.splitlines(): + draw.text((40, y), line, fill="black", font=font) + y += 40 + buf = io.BytesIO() + save_kwargs: dict[str, Any] = {"format": fmt.upper()} + if fmt.lower() in ("jpg", "jpeg"): + save_kwargs["format"] = "JPEG" + save_kwargs["quality"] = 95 + img.save(buf, **save_kwargs) + return buf.getvalue() + + +def make_png() -> bytes: + return _make_image("PNG") + + +def make_jpg() -> bytes: + return _make_image("JPEG") + + +def make_gif() -> bytes: + return _make_image("GIF") + + +def make_webp() -> bytes: + return _make_image("WEBP") + + +GENERATORS = { + "txt": (make_txt, "text/plain"), + "md": (make_md, "text/markdown"), + "csv": (make_csv, "text/csv"), + "html": (make_html, "text/html"), + "pdf": (make_pdf, "application/pdf"), + "docx": (make_docx, "application/vnd.openxmlformats-officedocument.wordprocessingml.document"), + "xlsx": (make_xlsx, "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"), + "png": (make_png, "image/png"), + "jpg": (make_jpg, "image/jpeg"), + "gif": (make_gif, "image/gif"), + "webp": (make_webp, "image/webp"), +} + +TEXT_LIKE_FORMATS = {"txt", "md", "csv", "html"} +IMAGE_FORMATS = {"png", "jpg", "gif", "webp"} +PDF_FORMATS = {"pdf"} +OFFICE_FORMATS = {"docx", "xlsx"} + + +def fixture_path(fmt: str) -> Path: + return FIXTURES_DIR / f"invoice.{fmt}" + + +def load_fixture(fmt: str) -> bytes: + """Read the committed fixture for ``fmt`` from ``tests/langchain/fixtures/files``.""" + return fixture_path(fmt).read_bytes() + + +def regenerate_fixtures() -> None: + """Re-generate every committed fixture file. Run via ``python -m tests.langchain.file_fixtures``.""" + FIXTURES_DIR.mkdir(parents=True, exist_ok=True) + for fmt, (generator, _) in GENERATORS.items(): + fixture_path(fmt).write_bytes(generator()) + + +def extract_text_for_office(fmt: str, data: bytes) -> str: + """Return readable text extracted from a docx/xlsx blob. + + Most LLM providers don't accept raw Office binaries as content blocks, so + we pre-extract on the client side and send the result as plain text. + """ + buf = io.BytesIO(data) + if fmt == "docx": + from docx import Document + + doc = Document(buf) + return "\n".join(p.text for p in doc.paragraphs if p.text) + if fmt == "xlsx": + from openpyxl import load_workbook + + wb = load_workbook(buf, read_only=True, data_only=True) + lines: list[str] = [] + for ws in wb.worksheets: + for row in ws.iter_rows(values_only=True): + lines.append(",".join("" if v is None else str(v) for v in row)) + return "\n".join(lines) + raise ValueError(f"extract_text_for_office does not handle {fmt!r}") + + +def build_human_content_block(fmt: str, data: bytes) -> list[dict[str, Any]]: + """Return the LangChain HumanMessage content blocks for a generated file. + + - text-like formats are sent inline as a fenced code block in a text block + - images go through the standard ``image`` block (base64) + - pdf goes through the standard ``file`` block (base64) + - docx/xlsx are pre-extracted to text and sent as a text block + """ + prompt = "Extract the invoice number, customer, and total amount from the attached file." + if fmt in TEXT_LIKE_FORMATS: + text = data.decode("utf-8") + return [ + {"type": "text", "text": f"{prompt}\n\n```{fmt}\n{text}\n```"}, + ] + if fmt in OFFICE_FORMATS: + text = extract_text_for_office(fmt, data) + return [ + {"type": "text", "text": f"{prompt}\n\n```{fmt}\n{text}\n```"}, + ] + if fmt in PDF_FORMATS: + return [ + {"type": "text", "text": prompt}, + { + "type": "file", + "base64": base64.b64encode(data).decode("ascii"), + "mime_type": "application/pdf", + }, + ] + if fmt in IMAGE_FORMATS: + mime = GENERATORS[fmt][1] + return [ + {"type": "text", "text": prompt}, + { + "type": "image", + "base64": base64.b64encode(data).decode("ascii"), + "mime_type": mime, + }, + ] + raise ValueError(f"Unsupported fixture format: {fmt!r}") + + +if __name__ == "__main__": + regenerate_fixtures() + print(f"Wrote {len(GENERATORS)} fixtures to {FIXTURES_DIR}") diff --git a/tests/langchain/fixtures/files/invoice.csv b/tests/langchain/fixtures/files/invoice.csv new file mode 100644 index 0000000..0c44e3a --- /dev/null +++ b/tests/langchain/fixtures/files/invoice.csv @@ -0,0 +1,5 @@ +field,value +invoice_number,INV-7421 +customer,Acme Corp +total_amount,4200 +due_date,2026-03-15 diff --git a/tests/langchain/fixtures/files/invoice.docx b/tests/langchain/fixtures/files/invoice.docx new file mode 100644 index 0000000..d8b4c64 Binary files /dev/null and b/tests/langchain/fixtures/files/invoice.docx differ diff --git a/tests/langchain/fixtures/files/invoice.gif b/tests/langchain/fixtures/files/invoice.gif new file mode 100644 index 0000000..6c169a3 Binary files /dev/null and b/tests/langchain/fixtures/files/invoice.gif differ diff --git a/tests/langchain/fixtures/files/invoice.html b/tests/langchain/fixtures/files/invoice.html new file mode 100644 index 0000000..dc4ee7f --- /dev/null +++ b/tests/langchain/fixtures/files/invoice.html @@ -0,0 +1 @@ +Invoice Number: INV-7421
Customer: Acme Corp
Total Amount: $4200
Due Date: 2026-03-15
\ No newline at end of file diff --git a/tests/langchain/fixtures/files/invoice.jpg b/tests/langchain/fixtures/files/invoice.jpg new file mode 100644 index 0000000..d7de9e1 Binary files /dev/null and b/tests/langchain/fixtures/files/invoice.jpg differ diff --git a/tests/langchain/fixtures/files/invoice.md b/tests/langchain/fixtures/files/invoice.md new file mode 100644 index 0000000..c0ee17b --- /dev/null +++ b/tests/langchain/fixtures/files/invoice.md @@ -0,0 +1,6 @@ +# Invoice + +- **Invoice Number:** INV-7421 +- **Customer:** Acme Corp +- **Total Amount:** $4200 +- **Due Date:** 2026-03-15 diff --git a/tests/langchain/fixtures/files/invoice.pdf b/tests/langchain/fixtures/files/invoice.pdf new file mode 100644 index 0000000..c709eed Binary files /dev/null and b/tests/langchain/fixtures/files/invoice.pdf differ diff --git a/tests/langchain/fixtures/files/invoice.png b/tests/langchain/fixtures/files/invoice.png new file mode 100644 index 0000000..ea8d9a8 Binary files /dev/null and b/tests/langchain/fixtures/files/invoice.png differ diff --git a/tests/langchain/fixtures/files/invoice.txt b/tests/langchain/fixtures/files/invoice.txt new file mode 100644 index 0000000..3b6da86 --- /dev/null +++ b/tests/langchain/fixtures/files/invoice.txt @@ -0,0 +1,4 @@ +Invoice Number: INV-7421 +Customer: Acme Corp +Total Amount: $4200 +Due Date: 2026-03-15 diff --git a/tests/langchain/fixtures/files/invoice.webp b/tests/langchain/fixtures/files/invoice.webp new file mode 100644 index 0000000..d3af360 Binary files /dev/null and b/tests/langchain/fixtures/files/invoice.webp differ diff --git a/tests/langchain/fixtures/files/invoice.xlsx b/tests/langchain/fixtures/files/invoice.xlsx new file mode 100644 index 0000000..8f1f21e Binary files /dev/null and b/tests/langchain/fixtures/files/invoice.xlsx differ diff --git a/tests/langchain/integration_tests.py b/tests/langchain/integration_tests.py new file mode 100644 index 0000000..6398dba --- /dev/null +++ b/tests/langchain/integration_tests.py @@ -0,0 +1,228 @@ +"""Shared base class for the per-provider LangChain integration tests. + +`UiPathChatModelIntegrationTests` consolidates the overrides that every +provider's `ChatModelIntegrationTests` subclass previously duplicated: + +- `setup_models` autouse fixture (reads the provider-local `completions_config`) +- `chat_model_class` / `chat_model_params` properties +- `supports_*` property defaults (all `True`; override in a subclass to disable) +- The `test_stream` / `test_astream` overrides that parametrize on + ``output_version`` and assert `chunk_position == "last"` +- The `test_parallel_and_sequential_tool_calling[_async]` methods, with a + ``_bind_parallel_and_sequential`` hook that providers override to switch + between the OpenAI dialect (``parallel_tool_calls``) and the Anthropic + dialect (``disable_parallel_tool_use``) +- The new `test_file_inputs[_async]` matrix, parameterized over every format in + `tests.langchain.file_fixtures.GENERATORS` (txt/md/csv/html, pdf, docx/xlsx, + png/jpg/gif/webp). Each test asks the model for structured output and + asserts the embedded invoice payload round-trips. + +Subclasses should still declare a `skip_on_specific_configs` fixture for +provider-specific skips, and override `supports_*` properties or +`_bind_parallel_and_sequential` where the defaults don't apply. +""" + +from __future__ import annotations + +from collections.abc import Iterable +from typing import Any, cast + +import pytest +from langchain_core.language_models.chat_models import BaseChatModel +from langchain_core.messages import AIMessageChunk, HumanMessage +from langchain_core.runnables import Runnable +from langchain_tests.integration_tests import ChatModelIntegrationTests + +from tests.langchain.file_fixtures import ( + CUSTOMER, + GENERATORS, + INVOICE_NUMBER, + TOTAL_AMOUNT, + InvoiceInfo, + build_human_content_block, + load_fixture, +) +from tests.langchain.utils import search_accommodation, search_attractions, search_flights + +_PARALLEL_TOOL_PROMPT = ( + "I want to plan a trip to Paris from New York. " + "I need to find flights for March 15th, accommodation from March 15th to March 20th, " + "and things to do there.", + "Search for accomodations, flights and attractions in parallel. " + "Don't repeat the same tool call.", +) + +_FILE_INPUT_FORMATS = sorted(GENERATORS.keys()) + + +def _assert_invoice(result: Any) -> None: + assert isinstance(result, InvoiceInfo), f"Unexpected result type: {type(result)!r}" + assert result.invoice_number.upper().replace(" ", "") == INVOICE_NUMBER, ( + f"Got invoice_number={result.invoice_number!r}, expected {INVOICE_NUMBER!r}" + ) + assert CUSTOMER.lower() in result.customer.lower(), ( + f"Got customer={result.customer!r}, expected to contain {CUSTOMER!r}" + ) + assert abs(result.total_amount - TOTAL_AMOUNT) < 0.01, ( + f"Got total_amount={result.total_amount!r}, expected ≈ {TOTAL_AMOUNT}" + ) + + +class UiPathChatModelIntegrationTests(ChatModelIntegrationTests): + @pytest.fixture(autouse=True) + def setup_models(self, completions_config: tuple[type[BaseChatModel], dict[str, Any]]) -> None: + self._completions_class, self.completions_kwargs = completions_config + + @pytest.fixture(autouse=True) + def skip_framework_irrelevant(self, request: pytest.FixtureRequest) -> None: + if request.node.originalname in ( + "test_no_overrides_DO_NOT_OVERRIDE", + "test_unicode_tool_call_integration", + ): + pytest.skip(f"Skipping {request.node.originalname}: not relevant") + + @property + def chat_model_class(self) -> type[BaseChatModel]: + return self._completions_class + + @property + def chat_model_params(self) -> dict[str, Any]: + return self.completions_kwargs + + @property + def supports_image_inputs(self) -> bool: + return True + + @property + def supports_image_tool_message(self) -> bool: + return True + + @property + def supports_image_urls(self) -> bool: + return True + + @property + def supports_pdf_inputs(self) -> bool: + return True + + @property + def supports_pdf_tool_message(self) -> bool: + return True + + @pytest.mark.parametrize("model", [{}, {"output_version": "v1"}], indirect=True) + def test_stream(self, model: BaseChatModel) -> None: + chunks: list[AIMessageChunk] = [] + full: AIMessageChunk | None = None + for chunk in model.stream("Hello"): + assert chunk is not None + assert isinstance(chunk, AIMessageChunk) + assert isinstance(chunk.content, str | list) + chunks.append(chunk) + full = chunk if full is None else full + chunk + assert len(chunks) > 0 + assert isinstance(full, AIMessageChunk) + assert full.content + text_blocks = [block for block in full.content_blocks if block["type"] == "text"] + assert len(text_blocks) == 1 + + last_chunk = chunks[-1] + assert last_chunk.chunk_position == "last", ( + f"Final chunk must have chunk_position='last', got {last_chunk.chunk_position!r}" + ) + + @pytest.mark.parametrize("model", [{}, {"output_version": "v1"}], indirect=True) + async def test_astream(self, model: BaseChatModel) -> None: + chunks: list[AIMessageChunk] = [] + full: AIMessageChunk | None = None + async for chunk in model.astream("Hello"): + assert chunk is not None + assert isinstance(chunk, AIMessageChunk) + assert isinstance(chunk.content, str | list) + chunks.append(chunk) + full = chunk if full is None else full + chunk + assert len(chunks) > 0 + assert isinstance(full, AIMessageChunk) + assert full.content + text_blocks = [block for block in full.content_blocks if block["type"] == "text"] + assert len(text_blocks) == 1 + + last_chunk = chunks[-1] + assert last_chunk.chunk_position == "last", ( + f"Final chunk must have chunk_position='last', got {last_chunk.chunk_position!r}" + ) + + def _bind_parallel_and_sequential( + self, model: BaseChatModel, tools: Iterable[Any] + ) -> tuple[Runnable, Runnable]: + """Return ``(parallel_model, sequential_model)`` for the parallel test. + + Default is the OpenAI dialect (``parallel_tool_calls`` kwarg). Providers + on the Anthropic dialect override to use ``disable_parallel_tool_use`` + inside ``tool_choice``. + """ + tools_list = list(tools) + return ( + model.bind_tools(tools_list, tool_choice="any", parallel_tool_calls=True), + model.bind_tools(tools_list, tool_choice="any", parallel_tool_calls=False), + ) + + def test_parallel_and_sequential_tool_calling(self, model: BaseChatModel) -> None: + tools = [search_accommodation, search_flights, search_attractions] + parallel, sequential = self._bind_parallel_and_sequential(model, tools) + + parallel_response = parallel.invoke(_PARALLEL_TOOL_PROMPT) + sequential_response = sequential.invoke(_PARALLEL_TOOL_PROMPT) + + assert parallel_response.tool_calls is not None + assert sequential_response.tool_calls is not None + assert len(parallel_response.tool_calls) == len(tools), ( + f"Expected multiple different tools to be called in parallel, " + f"got: {parallel_response.tool_calls}" + ) + assert len(sequential_response.tool_calls) == 1, ( + f"Expected only one tool to be called in sequential mode, " + f"got: {sequential_response.tool_calls}" + ) + + async def test_parallel_and_sequential_tool_calling_async(self, model: BaseChatModel) -> None: + tools = [search_accommodation, search_flights, search_attractions] + parallel, sequential = self._bind_parallel_and_sequential(model, tools) + + parallel_response = await parallel.ainvoke(_PARALLEL_TOOL_PROMPT) + sequential_response = await sequential.ainvoke(_PARALLEL_TOOL_PROMPT) + + assert parallel_response.tool_calls is not None + assert sequential_response.tool_calls is not None + assert len(parallel_response.tool_calls) == len(tools), ( + f"Expected multiple different tools to be called in parallel, " + f"got: {parallel_response.tool_calls}" + ) + assert len(sequential_response.tool_calls) == 1, ( + f"Expected only one tool to be called in sequential mode, " + f"got: {sequential_response.tool_calls}" + ) + + def _build_file_input_structured_model(self) -> Runnable: + model = self._completions_class(**self.completions_kwargs) + return model.with_structured_output(InvoiceInfo) + + def _build_human_message(self, fmt: str) -> HumanMessage: + # `HumanMessage.content` is typed against `list[str | dict[Unknown, Unknown]]`; + # langchain happily accepts our concrete `list[dict[str, Any]]` at runtime + # but pyright can't widen across the invariant `list`, so cast. + blocks = cast(list[Any], build_human_content_block(fmt, load_fixture(fmt))) + return HumanMessage(content=blocks) + + @pytest.mark.parametrize("fmt", _FILE_INPUT_FORMATS) + def test_file_inputs(self, fmt: str) -> None: + """Round-trip a generated ``fmt`` file through the model via structured output.""" + result = self._build_file_input_structured_model().invoke([self._build_human_message(fmt)]) + _assert_invoice(result) + + @pytest.mark.parametrize("fmt", _FILE_INPUT_FORMATS) + async def test_file_inputs_async(self, fmt: str) -> None: + """Async path mirrors `test_file_inputs` for every supported format.""" + result = await self._build_file_input_structured_model().ainvoke( + [self._build_human_message(fmt)] + ) + _assert_invoice(result) diff --git a/uv.lock b/uv.lock index 3de86ec..87debb1 100644 --- a/uv.lock +++ b/uv.lock @@ -673,6 +673,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/a7/5f/ed01f9a3cdffbd5a008556fc7b2a08ddb1cc6ace7effa7340604b1d16699/docstring_parser-0.18.0-py3-none-any.whl", hash = "sha256:b3fcbed555c47d8479be0796ef7e19c2670d428d72e96da63f3a40122860374b", size = 22484, upload-time = "2026-04-14T04:09:18.638Z" }, ] +[[package]] +name = "et-xmlfile" +version = "2.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/d3/38/af70d7ab1ae9d4da450eeec1fa3918940a5fafb9055e934af8d6eb0c2313/et_xmlfile-2.0.0.tar.gz", hash = "sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54", size = 17234, upload-time = "2024-10-25T17:25:40.039Z" } +wheels = [ + { url = 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