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## Description Two related content-loss bugs in the Gemini `contents[]` <-> `messages[]` compression round-trip. Both drop or misplace real user content that entries with **non-text** parts should carry through untouched. They share the same theme (non-text preservation), so they're bundled here as two commits. ### 1. Google batch handler restores preserved entries by the wrong index (`handlers/batch.py`) The `batchGenerateContent` handler restored preserved (non-text) entries with the raw-index loop that commit #836 (`_rebuild_gemini_contents`) replaced in the three non-batch Gemini handlers: ```python for orig_idx, original_content in preserved_contents.items(): if orig_idx < len(optimized_contents): optimized_contents[orig_idx] = original_content ``` `preserved_indices` are indices into the **original** `contents[]`, but `optimized_contents` is a **shorter** list (text-less entries produce no message). Indexing `optimized_contents` by `orig_idx` overwrites the wrong entry and drops any preserved entry whose original index is past the optimized length. For: ```python [user text, model functionCall, user functionResponse, model text] ``` the batch was forwarded to Google as **two** entries: the model's answer overwritten by the functionCall, and the functionResponse dropped. Unlike `gemini.py` there is no `if optimized_messages != messages` gate, so it runs on every mixed batch item. **Fix:** use the shared `_rebuild_gemini_contents` interleaving helper. ### 2. Code-execution parts not detected as non-text (`handlers/gemini.py`) `_has_non_text_parts` only recognized `inlineData`/`fileData`/`functionCall`/`functionResponse`. Gemini's code-execution feature emits `executableCode` and `codeExecutionResult` parts, echoed back in `contents[]` on later turns. Because they weren't detected: - a mixed `text`+`executableCode` entry lost its code payload (only the text survived the round-trip); - a text-less `executableCode`+`codeExecutionResult` entry was treated as a phantom in `_rebuild_gemini_contents` — it consumed the next optimized message, dropping the whole code turn and shifting a following user turn into the model's role slot (corrupting role alternation). **Fix:** add both keys to the non-text detection so those entries are preserved verbatim. Closes: no issue filed — both found while auditing the Gemini contents<->messages round-trip. ## Type of Change - [x] Bug fix (non-breaking change that fixes an issue) ## Changes Made - `headroom/proxy/handlers/batch.py`: use `_rebuild_gemini_contents` instead of the raw-index restore loop. - `headroom/proxy/handlers/gemini.py`: recognize `executableCode` / `codeExecutionResult` in `_has_non_text_parts`. - `tests/test_proxy_handlers_batch.py`: add `test_handle_google_batch_create_preserves_functioncall_response_order`, driving the handler with the **real** Gemini converters (the existing batch tests stub them, which hid the bug); mix `GeminiHandlerMixin` into the shared `DummyBatchHandler` so `_rebuild_gemini_contents` is available. - `tests/test_google_multimodal.py`: extend the parametrized `test_each_non_text_key_detected` to the two new keys, and add `test_code_execution_entry_survives`. ## Testing - [x] New regression tests added (`tests/test_proxy_handlers_batch.py`, `tests/test_google_multimodal.py`) - [x] Linting/formatting clean — run with the CI-pinned `ruff==0.15.17` - [ ] Full `pytest` deferred to CI (local-OOM reason below). ```text $ uvx ruff@0.15.17 check headroom/proxy/handlers/batch.py headroom/proxy/handlers/gemini.py \ tests/test_proxy_handlers_batch.py tests/test_google_multimodal.py All checks passed! ``` ## Real Behavior Proof - Environment: Windows 11, Python 3.10, headroom from this branch. Importing `headroom` pulls in the torch/transformers stack and a full `pytest` gets OOM-killed on this box, so I verified the interleaving/detection with dependency-free scripts (replicating the Gemini converters, the old loop, and `_rebuild_gemini_contents`) and left the full pytest to CI. - Exact command / steps: ran two standalone scripts. Script 1 rebuilds a Gemini batch request with `preserved_indices` holding a `functionCall`/`functionResponse` pair and compares the old raw-index loop against `_rebuild_gemini_contents`. Script 2 feeds a `codeExecutionResult` entry through `_has_non_text_parts` and the preserve path with and without the two new allowlist keys. Also ran `uvx ruff@0.15.17 check` on the changed files and tests. - Observed result: the old batch loop drops the `functionResponse` and overwrites the answer (4 parts collapse to 2); `_rebuild_gemini_contents` keeps all 4. Without the new keys the code-execution entry is dropped/shifted (2 parts, code absent); with them it survives intact (3 parts, code present). Lint clean. See the two blocks below. Batch fix (bug #1): ```text preserved_indices: [1, 2] OLD result parts: ['text', 'functionCall'] len 2 NEW result parts: ['text', 'functionCall', 'functionResponse', 'text'] len 4 GEMINI BATCH REBUILD FIX VERIFIED (old drops response + overwrites answer; new keeps all 4) ``` Code-execution fix (bug #2): ```text (b) OLD len=2 NEW len=3 (a) OLD has code=False NEW has code=True GEMINI CODE-EXECUTION PRESERVE FIX VERIFIED (old drops/shifts; new keeps intact) ``` - Not tested: a live Google/Gemini round-trip (handlers stubbed, as the existing tests do). Full local `pytest` deferred to CI (OOM, per above). ## Review Readiness - [x] I have performed a self-review - [x] This PR is ready for human review ## Checklist - [x] My code follows the project's style guidelines - [x] I have performed a self-review of my code - [x] I have commented my code, particularly in hard-to-understand areas - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes — ran lint + standalone logic checks; full pytest deferred to CI (local OOM, disclosed above) - [x] I have updated the CHANGELOG.md if applicable ## Additional Notes - Two small behavioral changes (one loop -> shared helper, two keys added to an allowlist) plus regression tests; no new dependencies. Both complete/extend the non-text preservation the non-batch handlers already do (the #836 line). - @JerrettDavis tagging you since you reviewed the recent Gemini fixes. Both of these drop content (functionResponse/images on batch; code-execution on the normal round-trip), so they seemed worth surfacing together. Thanks. --------- Co-authored-by: Tejas Chopra <chopratejas@gmail.com>
739 lines
28 KiB
Python
739 lines
28 KiB
Python
"""Tests for Google multimodal content preservation in the proxy.
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Tests verify that:
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1. _has_non_text_parts correctly detects non-text parts (images, files, function calls/responses)
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2. _gemini_contents_to_messages returns preserved indices correctly
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3. The preservation flow works end-to-end with real Gemini format structures
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Uses REAL Google Gemini API format structures without any mocking.
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"""
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import pytest
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pytest.importorskip("fastapi")
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pytest.importorskip("httpx")
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from headroom.proxy.server import HeadroomProxy, ProxyConfig
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@pytest.fixture
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def proxy():
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"""Create a minimal HeadroomProxy instance for testing helper methods."""
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config = ProxyConfig(
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optimize=False,
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cache_enabled=False,
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rate_limit_enabled=False,
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cost_tracking_enabled=False,
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)
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return HeadroomProxy(config)
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# =============================================================================
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# Test data: Real Google Gemini API format structures
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# =============================================================================
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# Text-only content
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TEXT_ONLY_CONTENT = {"role": "user", "parts": [{"text": "Hello, world!"}]}
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# Content with inline image (base64 encoded)
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IMAGE_INLINE_CONTENT = {
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"role": "user",
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"parts": [
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{"text": "What's in this image?"},
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{"inlineData": {"mimeType": "image/jpeg", "data": "base64encodedimagedata..."}},
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],
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}
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# Content with only inline image (no text)
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IMAGE_ONLY_CONTENT = {
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"role": "user",
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"parts": [
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{"inlineData": {"mimeType": "image/png", "data": "iVBORw0KGgoAAAANSUhEUgAAAAEAAAAB"}},
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],
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}
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# Content with file reference (Google Cloud Storage)
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FILE_DATA_CONTENT = {
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"role": "user",
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"parts": [
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{"text": "Summarize this document"},
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{"fileData": {"mimeType": "application/pdf", "fileUri": "gs://bucket/document.pdf"}},
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],
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}
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# Content with function call (model response)
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FUNCTION_CALL_CONTENT = {
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"role": "model",
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"parts": [{"functionCall": {"name": "get_weather", "args": {"location": "NYC"}}}],
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}
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# Content with function call and text
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FUNCTION_CALL_WITH_TEXT_CONTENT = {
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"role": "model",
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"parts": [
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{"text": "Let me check the weather for you."},
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{"functionCall": {"name": "get_weather", "args": {"location": "San Francisco"}}},
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],
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}
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# Content with function response (user provides)
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FUNCTION_RESPONSE_CONTENT = {
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"role": "user",
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"parts": [
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{
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"functionResponse": {
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"name": "get_weather",
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"response": {"temperature": 72, "condition": "sunny"},
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}
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}
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],
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}
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# Content with multiple images
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MULTI_IMAGE_CONTENT = {
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"role": "user",
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"parts": [
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{"text": "Compare these two images"},
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{"inlineData": {"mimeType": "image/jpeg", "data": "firstimagebase64..."}},
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{"inlineData": {"mimeType": "image/jpeg", "data": "secondimagebase64..."}},
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],
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}
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# Model response with only text
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MODEL_TEXT_CONTENT = {
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"role": "model",
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"parts": [{"text": "Hello! How can I help you today?"}],
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}
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# Empty parts list
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EMPTY_PARTS_CONTENT = {"role": "user", "parts": []}
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# Content with mixed media types
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MIXED_MEDIA_CONTENT = {
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"role": "user",
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"parts": [
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{"text": "Analyze this image and document"},
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{"inlineData": {"mimeType": "image/png", "data": "imagedata..."}},
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{"fileData": {"mimeType": "application/pdf", "fileUri": "gs://bucket/file.pdf"}},
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],
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}
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# =============================================================================
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# Tests for _has_non_text_parts
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# =============================================================================
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class TestHasNonTextParts:
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"""Test _has_non_text_parts correctly detects non-text content types."""
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def test_text_only_returns_false(self, proxy):
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"""Content with only text parts returns False."""
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assert proxy._has_non_text_parts(TEXT_ONLY_CONTENT) is False
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def test_model_text_only_returns_false(self, proxy):
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"""Model response with only text returns False."""
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assert proxy._has_non_text_parts(MODEL_TEXT_CONTENT) is False
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def test_empty_parts_returns_false(self, proxy):
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"""Content with empty parts list returns False."""
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assert proxy._has_non_text_parts(EMPTY_PARTS_CONTENT) is False
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def test_inline_data_returns_true(self, proxy):
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"""Content with inlineData (images) returns True."""
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assert proxy._has_non_text_parts(IMAGE_INLINE_CONTENT) is True
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def test_inline_data_only_returns_true(self, proxy):
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"""Content with only inlineData (no text) returns True."""
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assert proxy._has_non_text_parts(IMAGE_ONLY_CONTENT) is True
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def test_file_data_returns_true(self, proxy):
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"""Content with fileData returns True."""
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assert proxy._has_non_text_parts(FILE_DATA_CONTENT) is True
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def test_function_call_returns_true(self, proxy):
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"""Content with functionCall returns True."""
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assert proxy._has_non_text_parts(FUNCTION_CALL_CONTENT) is True
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def test_function_call_with_text_returns_true(self, proxy):
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"""Content with functionCall and text returns True."""
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assert proxy._has_non_text_parts(FUNCTION_CALL_WITH_TEXT_CONTENT) is True
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def test_function_response_returns_true(self, proxy):
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"""Content with functionResponse returns True."""
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assert proxy._has_non_text_parts(FUNCTION_RESPONSE_CONTENT) is True
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def test_multiple_images_returns_true(self, proxy):
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"""Content with multiple images returns True."""
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assert proxy._has_non_text_parts(MULTI_IMAGE_CONTENT) is True
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def test_mixed_media_returns_true(self, proxy):
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"""Content with mixed media types returns True."""
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assert proxy._has_non_text_parts(MIXED_MEDIA_CONTENT) is True
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@pytest.mark.parametrize(
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"non_text_key",
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[
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"inlineData",
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"fileData",
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"functionCall",
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"functionResponse",
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# Gemini code-execution parts, echoed back in contents[] on later
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# turns; previously not detected, so they were dropped on round-trip.
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"executableCode",
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"codeExecutionResult",
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],
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)
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def test_each_non_text_key_detected(self, proxy, non_text_key):
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"""Each non-text part type is correctly detected."""
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content = {"role": "user", "parts": [{non_text_key: {"dummy": "data"}}]}
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assert proxy._has_non_text_parts(content) is True
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def test_content_without_parts_key(self, proxy):
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"""Content missing 'parts' key returns False (graceful handling)."""
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content = {"role": "user"}
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assert proxy._has_non_text_parts(content) is False
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# =============================================================================
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# Tests for _gemini_contents_to_messages preserved indices
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# =============================================================================
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class TestGeminiContentsToMessagesPreservedIndices:
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"""Test _gemini_contents_to_messages returns correct preserved indices."""
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def test_pure_text_returns_empty_set(self, proxy):
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"""Pure text content returns empty preserved_indices set."""
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contents = [
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TEXT_ONLY_CONTENT,
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MODEL_TEXT_CONTENT,
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{"role": "user", "parts": [{"text": "Another question"}]},
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]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == set()
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assert len(messages) == 3
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def test_single_image_content_preserves_index(self, proxy):
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"""Single content with image preserves its index."""
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contents = [IMAGE_INLINE_CONTENT]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == {0}
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assert len(messages) == 1
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def test_image_at_beginning_preserves_correct_index(self, proxy):
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"""Image at beginning of conversation preserves index 0."""
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contents = [
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IMAGE_INLINE_CONTENT, # index 0 - has image
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MODEL_TEXT_CONTENT, # index 1 - text only
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{"role": "user", "parts": [{"text": "Follow up"}]}, # index 2 - text only
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]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == {0}
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assert len(messages) == 3
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def test_image_at_middle_preserves_correct_index(self, proxy):
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"""Image in middle of conversation preserves correct index."""
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contents = [
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TEXT_ONLY_CONTENT, # index 0 - text only
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IMAGE_INLINE_CONTENT, # index 1 - has image
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MODEL_TEXT_CONTENT, # index 2 - text only
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]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == {1}
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assert len(messages) == 3
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def test_image_at_end_preserves_correct_index(self, proxy):
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"""Image at end of conversation preserves correct index."""
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contents = [
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TEXT_ONLY_CONTENT, # index 0 - text only
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MODEL_TEXT_CONTENT, # index 1 - text only
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IMAGE_INLINE_CONTENT, # index 2 - has image
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]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == {2}
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assert len(messages) == 3
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def test_multiple_images_preserves_all_indices(self, proxy):
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"""Multiple contents with images preserve all their indices."""
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contents = [
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IMAGE_INLINE_CONTENT, # index 0 - has image
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MODEL_TEXT_CONTENT, # index 1 - text only
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FILE_DATA_CONTENT, # index 2 - has file
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{"role": "model", "parts": [{"text": "Response"}]}, # index 3 - text only
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MULTI_IMAGE_CONTENT, # index 4 - has multiple images
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]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == {0, 2, 4}
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assert len(messages) == 5
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def test_function_call_preserves_index(self, proxy):
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"""Content with function call preserves its index."""
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contents = [
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TEXT_ONLY_CONTENT, # index 0
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FUNCTION_CALL_CONTENT, # index 1 - has function call
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FUNCTION_RESPONSE_CONTENT, # index 2 - has function response
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]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == {1, 2}
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def test_all_non_text_preserves_all(self, proxy):
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"""Conversation with all non-text content preserves all indices."""
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contents = [
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IMAGE_INLINE_CONTENT, # index 0
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FUNCTION_CALL_CONTENT, # index 1
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FUNCTION_RESPONSE_CONTENT, # index 2
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FILE_DATA_CONTENT, # index 3
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]
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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assert preserved_indices == {0, 1, 2, 3}
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def test_with_system_instruction(self, proxy):
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"""System instruction does not affect content indexing."""
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contents = [
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TEXT_ONLY_CONTENT, # index 0
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IMAGE_INLINE_CONTENT, # index 1
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]
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system_instruction = {"parts": [{"text": "You are a helpful assistant."}]}
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messages, preserved_indices = proxy._gemini_contents_to_messages(
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contents, system_instruction
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)
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# preserved_indices should reference content indices, not message indices
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assert preserved_indices == {1}
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# Messages should include system + 2 content messages
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assert len(messages) == 3
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assert messages[0]["role"] == "system"
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def test_empty_contents_returns_empty_set(self, proxy):
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"""Empty contents list returns empty preserved_indices."""
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messages, preserved_indices = proxy._gemini_contents_to_messages([])
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assert preserved_indices == set()
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assert messages == []
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# =============================================================================
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# Tests for message conversion correctness
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# =============================================================================
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class TestGeminiContentsToMessagesConversion:
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"""Test that _gemini_contents_to_messages correctly converts content."""
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def test_role_mapping_user(self, proxy):
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"""User role is preserved."""
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contents = [{"role": "user", "parts": [{"text": "Hello"}]}]
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messages, _ = proxy._gemini_contents_to_messages(contents)
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assert messages[0]["role"] == "user"
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assert messages[0]["content"] == "Hello"
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def test_role_mapping_model_to_assistant(self, proxy):
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"""Model role is mapped to assistant."""
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contents = [{"role": "model", "parts": [{"text": "Hi there"}]}]
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messages, _ = proxy._gemini_contents_to_messages(contents)
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assert messages[0]["role"] == "assistant"
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assert messages[0]["content"] == "Hi there"
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def test_multiple_text_parts_joined(self, proxy):
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"""Multiple text parts in one content are joined."""
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contents = [
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{
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"role": "user",
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"parts": [
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{"text": "First part."},
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{"text": "Second part."},
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],
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}
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]
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messages, _ = proxy._gemini_contents_to_messages(contents)
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assert messages[0]["content"] == "First part.\nSecond part."
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def test_text_extracted_from_mixed_content(self, proxy):
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"""Text is extracted from content with mixed parts."""
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contents = [IMAGE_INLINE_CONTENT] # Has text + inlineData
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messages, _ = proxy._gemini_contents_to_messages(contents)
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assert messages[0]["content"] == "What's in this image?"
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def test_content_with_only_non_text_creates_empty_message(self, proxy):
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"""Content with only non-text parts creates no message (no text to extract)."""
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contents = [FUNCTION_CALL_CONTENT] # Has only functionCall, no text
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messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
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# The index should still be preserved
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assert preserved_indices == {0}
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# But no message is created since there's no text
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assert messages == []
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def test_system_instruction_becomes_system_message(self, proxy):
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"""System instruction is converted to system message."""
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contents = [TEXT_ONLY_CONTENT]
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system_instruction = {"parts": [{"text": "Be concise."}]}
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messages, _ = proxy._gemini_contents_to_messages(contents, system_instruction)
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assert messages[0]["role"] == "system"
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assert messages[0]["content"] == "Be concise."
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assert messages[1]["role"] == "user"
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# =============================================================================
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# Tests for realistic conversation flows
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# =============================================================================
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|
|
|
|
class TestRealisticConversationFlows:
|
|
"""Test preservation with realistic conversation patterns."""
|
|
|
|
def test_image_analysis_conversation(self, proxy):
|
|
"""Realistic image analysis conversation preserves image content."""
|
|
contents = [
|
|
# User sends an image for analysis
|
|
{
|
|
"role": "user",
|
|
"parts": [
|
|
{"text": "What objects can you see in this photo?"},
|
|
{
|
|
"inlineData": {
|
|
"mimeType": "image/jpeg",
|
|
"data": "base64encodedphoto...",
|
|
}
|
|
},
|
|
],
|
|
},
|
|
# Model responds with analysis
|
|
{
|
|
"role": "model",
|
|
"parts": [
|
|
{
|
|
"text": "I can see a cat sitting on a windowsill. "
|
|
"The window overlooks a garden with flowers."
|
|
}
|
|
],
|
|
},
|
|
# User asks follow-up
|
|
{
|
|
"role": "user",
|
|
"parts": [{"text": "What color is the cat?"}],
|
|
},
|
|
]
|
|
|
|
messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
|
|
|
|
# Only the first content (with image) should be preserved
|
|
assert preserved_indices == {0}
|
|
assert len(messages) == 3
|
|
|
|
def test_function_calling_conversation(self, proxy):
|
|
"""Realistic function calling conversation preserves function content."""
|
|
contents = [
|
|
# User asks about weather
|
|
{"role": "user", "parts": [{"text": "What's the weather in Paris?"}]},
|
|
# Model calls weather function
|
|
{
|
|
"role": "model",
|
|
"parts": [{"functionCall": {"name": "get_weather", "args": {"city": "Paris"}}}],
|
|
},
|
|
# User provides function response
|
|
{
|
|
"role": "user",
|
|
"parts": [
|
|
{
|
|
"functionResponse": {
|
|
"name": "get_weather",
|
|
"response": {"temp_c": 18, "condition": "partly cloudy"},
|
|
}
|
|
}
|
|
],
|
|
},
|
|
# Model provides final answer
|
|
{
|
|
"role": "model",
|
|
"parts": [{"text": "The weather in Paris is 18C and partly cloudy."}],
|
|
},
|
|
# User asks another question
|
|
{"role": "user", "parts": [{"text": "Should I bring an umbrella?"}]},
|
|
]
|
|
|
|
messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
|
|
|
|
# Function call (index 1) and function response (index 2) should be preserved
|
|
assert preserved_indices == {1, 2}
|
|
|
|
def test_multi_modal_document_analysis(self, proxy):
|
|
"""Multi-modal document analysis with images and files."""
|
|
contents = [
|
|
# User provides document
|
|
{
|
|
"role": "user",
|
|
"parts": [
|
|
{"text": "Please review this contract"},
|
|
{
|
|
"fileData": {
|
|
"mimeType": "application/pdf",
|
|
"fileUri": "gs://contracts/agreement.pdf",
|
|
}
|
|
},
|
|
],
|
|
},
|
|
# Model asks for clarification
|
|
{
|
|
"role": "model",
|
|
"parts": [
|
|
{
|
|
"text": "I've reviewed the contract. Do you want me to highlight specific sections?"
|
|
}
|
|
],
|
|
},
|
|
# User provides screenshot of specific section
|
|
{
|
|
"role": "user",
|
|
"parts": [
|
|
{"text": "Yes, please explain this clause:"},
|
|
{
|
|
"inlineData": {
|
|
"mimeType": "image/png",
|
|
"data": "screenshotbase64...",
|
|
}
|
|
},
|
|
],
|
|
},
|
|
# Model explains
|
|
{
|
|
"role": "model",
|
|
"parts": [{"text": "This clause specifies the termination conditions..."}],
|
|
},
|
|
]
|
|
|
|
messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
|
|
|
|
# First content (PDF) and third content (screenshot) should be preserved
|
|
assert preserved_indices == {0, 2}
|
|
assert len(messages) == 4
|
|
|
|
def test_conversation_with_no_preservation_needed(self, proxy):
|
|
"""Pure text conversation needs no preservation."""
|
|
contents = [
|
|
{"role": "user", "parts": [{"text": "What is machine learning?"}]},
|
|
{
|
|
"role": "model",
|
|
"parts": [
|
|
{
|
|
"text": "Machine learning is a subset of AI that enables "
|
|
"computers to learn from data."
|
|
}
|
|
],
|
|
},
|
|
{"role": "user", "parts": [{"text": "Can you give an example?"}]},
|
|
{
|
|
"role": "model",
|
|
"parts": [
|
|
{"text": "Sure! Email spam filters use machine learning to classify messages."}
|
|
],
|
|
},
|
|
{"role": "user", "parts": [{"text": "Thanks!"}]},
|
|
]
|
|
|
|
messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
|
|
|
|
assert preserved_indices == set()
|
|
assert len(messages) == 5
|
|
|
|
|
|
# =============================================================================
|
|
# Parametrized tests for comprehensive coverage
|
|
# =============================================================================
|
|
|
|
|
|
class TestParametrizedNonTextDetection:
|
|
"""Parametrized tests for non-text part detection."""
|
|
|
|
@pytest.mark.parametrize(
|
|
"content,expected",
|
|
[
|
|
(TEXT_ONLY_CONTENT, False),
|
|
(MODEL_TEXT_CONTENT, False),
|
|
(EMPTY_PARTS_CONTENT, False),
|
|
(IMAGE_INLINE_CONTENT, True),
|
|
(IMAGE_ONLY_CONTENT, True),
|
|
(FILE_DATA_CONTENT, True),
|
|
(FUNCTION_CALL_CONTENT, True),
|
|
(FUNCTION_CALL_WITH_TEXT_CONTENT, True),
|
|
(FUNCTION_RESPONSE_CONTENT, True),
|
|
(MULTI_IMAGE_CONTENT, True),
|
|
(MIXED_MEDIA_CONTENT, True),
|
|
],
|
|
ids=[
|
|
"text_only",
|
|
"model_text",
|
|
"empty_parts",
|
|
"image_inline",
|
|
"image_only",
|
|
"file_data",
|
|
"function_call",
|
|
"function_call_with_text",
|
|
"function_response",
|
|
"multi_image",
|
|
"mixed_media",
|
|
],
|
|
)
|
|
def test_non_text_detection(self, proxy, content, expected):
|
|
"""Parametrized test for _has_non_text_parts."""
|
|
assert proxy._has_non_text_parts(content) is expected
|
|
|
|
|
|
class TestParametrizedPreservation:
|
|
"""Parametrized tests for index preservation."""
|
|
|
|
@pytest.mark.parametrize(
|
|
"contents,expected_indices",
|
|
[
|
|
# Single text
|
|
([TEXT_ONLY_CONTENT], set()),
|
|
# Single image
|
|
([IMAGE_INLINE_CONTENT], {0}),
|
|
# Text then image
|
|
([TEXT_ONLY_CONTENT, IMAGE_INLINE_CONTENT], {1}),
|
|
# Image then text
|
|
([IMAGE_INLINE_CONTENT, TEXT_ONLY_CONTENT], {0}),
|
|
# All images
|
|
([IMAGE_INLINE_CONTENT, FILE_DATA_CONTENT], {0, 1}),
|
|
# Mixed throughout
|
|
(
|
|
[TEXT_ONLY_CONTENT, IMAGE_INLINE_CONTENT, MODEL_TEXT_CONTENT, FILE_DATA_CONTENT],
|
|
{1, 3},
|
|
),
|
|
# Function call sequence
|
|
(
|
|
[TEXT_ONLY_CONTENT, FUNCTION_CALL_CONTENT, FUNCTION_RESPONSE_CONTENT],
|
|
{1, 2},
|
|
),
|
|
],
|
|
ids=[
|
|
"single_text",
|
|
"single_image",
|
|
"text_then_image",
|
|
"image_then_text",
|
|
"all_images",
|
|
"mixed_throughout",
|
|
"function_call_sequence",
|
|
],
|
|
)
|
|
def test_preserved_indices(self, proxy, contents, expected_indices):
|
|
"""Parametrized test for preserved indices."""
|
|
_, preserved_indices = proxy._gemini_contents_to_messages(contents)
|
|
assert preserved_indices == expected_indices
|
|
|
|
|
|
# =============================================================================
|
|
# Tests for _rebuild_gemini_contents
|
|
# =============================================================================
|
|
|
|
|
|
class TestRebuildGeminiContents:
|
|
"""_rebuild_gemini_contents must re-insert preserved entries at their original positions."""
|
|
|
|
def _round_trip(self, proxy, contents):
|
|
"""Simulate the full compression round-trip for a given contents list.
|
|
|
|
Mimics what the handler does: convert → strip system msg → convert back → rebuild.
|
|
"""
|
|
messages, preserved_indices = proxy._gemini_contents_to_messages(contents)
|
|
preserved_contents = {idx: contents[idx] for idx in preserved_indices}
|
|
optimized_contents, _ = proxy._messages_to_gemini_contents(messages)
|
|
return proxy._rebuild_gemini_contents(
|
|
contents, preserved_indices, preserved_contents, optimized_contents
|
|
)
|
|
|
|
def test_text_only_unchanged(self, proxy):
|
|
"""Text-only round-trip should produce identical contents."""
|
|
contents = [TEXT_ONLY_CONTENT, MODEL_TEXT_CONTENT]
|
|
result = self._round_trip(proxy, contents)
|
|
assert len(result) == 2
|
|
assert result[0]["parts"][0]["text"] == "Hello, world!"
|
|
assert result[1]["parts"][0]["text"] == "Hello! How can I help you today?"
|
|
|
|
def test_code_execution_entry_survives(self, proxy):
|
|
"""A text-less code-execution entry (executableCode + codeExecutionResult)
|
|
between two text turns must survive the round-trip at its position, and
|
|
not shift a neighboring turn. Before the fix it was not detected as
|
|
non-text, so it was dropped and the following user turn was misplaced."""
|
|
code_entry = {
|
|
"role": "model",
|
|
"parts": [
|
|
{"executableCode": {"language": "PYTHON", "code": "x = 1"}},
|
|
{"codeExecutionResult": {"outcome": "OUTCOME_OK", "output": "1"}},
|
|
],
|
|
}
|
|
contents = [
|
|
{"role": "user", "parts": [{"text": "Question 1"}]},
|
|
code_entry,
|
|
{"role": "user", "parts": [{"text": "Question 2"}]},
|
|
]
|
|
|
|
result = self._round_trip(proxy, contents)
|
|
|
|
assert len(result) == 3
|
|
assert result[1] == code_entry # preserved verbatim, in place
|
|
assert result[2]["parts"][0]["text"] == "Question 2"
|
|
|
|
def test_function_call_sequence_preserved(self, proxy):
|
|
"""functionCall and functionResponse entries must survive and appear at correct positions."""
|
|
contents = [
|
|
TEXT_ONLY_CONTENT, # idx 0: text
|
|
FUNCTION_CALL_CONTENT, # idx 1: functionCall only — no text → preserved
|
|
FUNCTION_RESPONSE_CONTENT, # idx 2: functionResponse only — no text → preserved
|
|
MODEL_TEXT_CONTENT, # idx 3: text
|
|
]
|
|
result = self._round_trip(proxy, contents)
|
|
|
|
assert len(result) == 4, f"Expected 4 entries, got {len(result)}: {result}"
|
|
# Position 0: original text
|
|
assert result[0]["parts"][0].get("text") == "Hello, world!"
|
|
# Position 1: functionCall preserved exactly
|
|
assert "functionCall" in result[1]["parts"][0], "functionCall missing at position 1"
|
|
assert result[1]["parts"][0]["functionCall"]["name"] == "get_weather"
|
|
# Position 2: functionResponse preserved exactly
|
|
assert "functionResponse" in result[2]["parts"][0], "functionResponse missing at position 2"
|
|
# Position 3: text preserved
|
|
assert result[3]["parts"][0].get("text") == "Hello! How can I help you today?"
|
|
|
|
def test_function_call_at_start(self, proxy):
|
|
"""Preserved entry at idx=0 must not overwrite idx=0 of optimized_contents."""
|
|
contents = [
|
|
FUNCTION_CALL_CONTENT, # idx 0: no text → preserved
|
|
TEXT_ONLY_CONTENT, # idx 1: text
|
|
]
|
|
result = self._round_trip(proxy, contents)
|
|
|
|
assert len(result) == 2
|
|
assert "functionCall" in result[0]["parts"][0]
|
|
assert result[1]["parts"][0].get("text") == "Hello, world!"
|
|
|
|
def test_hybrid_entry_uses_original(self, proxy):
|
|
"""Entry with both text and functionCall keeps the original (with functionCall intact)."""
|
|
contents = [
|
|
TEXT_ONLY_CONTENT,
|
|
FUNCTION_CALL_WITH_TEXT_CONTENT, # idx 1: has both text and functionCall → preserved
|
|
MODEL_TEXT_CONTENT,
|
|
]
|
|
result = self._round_trip(proxy, contents)
|
|
|
|
assert len(result) == 3
|
|
# Hybrid entry must come back as the original (functionCall retained)
|
|
hybrid = result[1]
|
|
part_keys = {k for p in hybrid["parts"] for k in p}
|
|
assert "functionCall" in part_keys, "functionCall lost from hybrid entry"
|