0ef5fcb1c5
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501 lines
18 KiB
Python
501 lines
18 KiB
Python
"""Integration tests for Gemini countTokens endpoint with compression.
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These tests verify that the Gemini /v1beta/models/{model}:countTokens endpoint
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works correctly with compression enabled, properly counting tokens after
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compression is applied.
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Required environment variables:
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- GEMINI_API_KEY: For Gemini countTokens endpoint
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Run with:
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GEMINI_API_KEY=... pytest tests/test_proxy_count_tokens_integration.py -v
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"""
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import json
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import os
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import pytest
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# Skip entire module if no API key
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pytestmark = pytest.mark.skipif(
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not os.environ.get("GEMINI_API_KEY"), reason="GEMINI_API_KEY not set"
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)
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pytest.importorskip("fastapi")
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pytest.importorskip("httpx")
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from fastapi.testclient import TestClient # noqa: E402
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from headroom.proxy.server import ProxyConfig, create_app # noqa: E402
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# =============================================================================
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# Fixtures
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# =============================================================================
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@pytest.fixture
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def gemini_client_optimized():
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"""Create test client with optimization enabled for Gemini."""
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config = ProxyConfig(
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optimize=True, # Enable compression
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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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app = create_app(config)
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with TestClient(app) as client:
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yield client
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@pytest.fixture
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def gemini_client_passthrough():
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"""Create test client with optimization disabled (passthrough mode)."""
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config = ProxyConfig(
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optimize=False, # Disable compression
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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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app = create_app(config)
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with TestClient(app) as client:
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yield client
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@pytest.fixture
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def api_key():
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"""Get Gemini API key from environment."""
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return os.environ.get("GEMINI_API_KEY")
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def create_large_content(num_items: int = 50) -> list[dict]:
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"""Create Gemini-format contents with large compressible data."""
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# Create JSON data that can be compressed
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items = [
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{
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"id": i,
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"name": f"Product Item {i}",
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"description": f"This is a detailed description for product item {i}. "
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f"It includes various specifications and features.",
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"price": 99.99 + i * 0.5,
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"category": f"category_{i % 5}",
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"in_stock": i % 2 == 0,
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"metadata": {
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"sku": f"SKU-{i:05d}",
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"weight": f"{i * 0.1:.2f}kg",
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"dimensions": f"{10 + i}x{15 + i}x{5 + i}cm",
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},
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}
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for i in range(num_items)
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]
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large_json = json.dumps(items, indent=2)
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return [
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{
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"role": "user",
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"parts": [{"text": "I have product data to analyze."}],
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},
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{
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"role": "model",
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"parts": [{"text": f"Here is the product data:\n\n{large_json}"}],
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},
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{
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"role": "user",
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"parts": [{"text": "How many products are in stock?"}],
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},
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]
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def create_simple_content() -> list[dict]:
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"""Create simple Gemini-format contents for basic testing."""
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return [
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{
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"role": "user",
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"parts": [{"text": "What is 2 + 2?"}],
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}
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]
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# =============================================================================
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# Basic countTokens Tests
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# =============================================================================
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class TestGeminiCountTokensBasic:
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"""Test basic Gemini countTokens functionality."""
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def test_count_tokens_simple_content(self, gemini_client_optimized, api_key):
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"""Basic token counting works correctly."""
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": create_simple_content()},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify response format
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assert "totalTokens" in data
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assert isinstance(data["totalTokens"], int)
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assert data["totalTokens"] > 0
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def test_count_tokens_with_system_instruction(self, gemini_client_optimized, api_key):
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"""Token counting includes system instruction."""
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={
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"contents": create_simple_content(),
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"systemInstruction": {"parts": [{"text": "You are a helpful math assistant."}]},
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},
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)
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# Note: systemInstruction may not be supported by all models/versions
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# Accept both success and 400 (if not supported)
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assert response.status_code in [200, 400]
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if response.status_code == 200:
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data = response.json()
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assert "totalTokens" in data
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assert data["totalTokens"] > 0
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def test_count_tokens_multi_turn(self, gemini_client_optimized, api_key):
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"""Token counting for multi-turn conversation."""
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contents = [
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{"role": "user", "parts": [{"text": "Hello, my name is Alice."}]},
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{"role": "model", "parts": [{"text": "Nice to meet you, Alice!"}]},
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{"role": "user", "parts": [{"text": "What is my name?"}]},
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]
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": contents},
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)
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assert response.status_code == 200
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data = response.json()
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assert data["totalTokens"] > 0
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# =============================================================================
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# Compression Tests
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# =============================================================================
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class TestGeminiCountTokensCompression:
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"""Test that compression reduces token count."""
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def test_compression_reduces_token_count(
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self, gemini_client_optimized, gemini_client_passthrough, api_key
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):
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"""Verify compression reduces token count for large content.
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This test compares token counts between:
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- Passthrough mode (no compression)
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- Optimized mode (compression enabled)
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"""
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large_contents = create_large_content(num_items=40)
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# Get token count without compression
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passthrough_response = gemini_client_passthrough.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": large_contents},
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)
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assert passthrough_response.status_code == 200
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passthrough_tokens = passthrough_response.json()["totalTokens"]
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# Get token count with compression
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optimized_response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": large_contents},
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)
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assert optimized_response.status_code == 200
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optimized_tokens = optimized_response.json()["totalTokens"]
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# Compression should reduce token count (or at least not increase it)
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# Note: compression effect depends on content and may vary
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assert optimized_tokens <= passthrough_tokens * 1.1 # Allow 10% margin
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# For large content, we expect some savings
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if passthrough_tokens > 1000:
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assert optimized_tokens < passthrough_tokens, (
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f"Expected compression to reduce tokens from {passthrough_tokens} "
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f"but got {optimized_tokens}"
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)
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def test_compression_stats_tracked(self, gemini_client_optimized, api_key):
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"""Verify compression stats are tracked in proxy stats."""
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large_contents = create_large_content(num_items=30)
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# Make countTokens request with large content
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": large_contents},
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)
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assert response.status_code == 200
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# Check proxy stats
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stats_response = gemini_client_optimized.get("/stats")
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assert stats_response.status_code == 200
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stats = stats_response.json()
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# Verify Gemini requests are tracked
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assert stats["requests"]["total"] >= 1
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assert "gemini" in stats["requests"]["by_provider"]
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class TestGeminiCountTokensLargeContent:
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"""Test countTokens with large content that benefits from compression."""
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def test_very_large_json_content(self, gemini_client_optimized, api_key):
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"""Token counting handles very large JSON content."""
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large_contents = create_large_content(num_items=100)
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": large_contents},
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)
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assert response.status_code == 200
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data = response.json()
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assert "totalTokens" in data
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assert data["totalTokens"] > 0
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def test_repeated_data_compression(self, gemini_client_optimized, api_key):
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"""Content with repeated patterns compresses well."""
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# Create content with highly repetitive data
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repeated_items = [{"id": i, "status": "active", "type": "item"} for i in range(200)]
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repeated_json = json.dumps(repeated_items)
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contents = [
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{"role": "user", "parts": [{"text": "Analyze this data."}]},
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{"role": "model", "parts": [{"text": f"Data:\n{repeated_json}"}]},
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{"role": "user", "parts": [{"text": "Count the items."}]},
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]
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": contents},
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)
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assert response.status_code == 200
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data = response.json()
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assert data["totalTokens"] > 0
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def test_code_content_compression(self, gemini_client_optimized, api_key):
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"""Token counting handles code content."""
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code_sample = '''
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def calculate_statistics(data):
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"""Calculate statistics for the given data."""
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if not data:
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return {"count": 0, "sum": 0, "average": 0}
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count = len(data)
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total = sum(data)
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average = total / count
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return {
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"count": count,
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"sum": total,
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"average": average,
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"min": min(data),
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"max": max(data),
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}
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# Example usage
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numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
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result = calculate_statistics(numbers)
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print(result)
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'''
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contents = [
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{"role": "user", "parts": [{"text": "Can you explain this code?"}]},
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{
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"role": "model",
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"parts": [{"text": f"Here's the code:\n\n```python\n{code_sample}\n```"}],
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},
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{"role": "user", "parts": [{"text": "What does calculate_statistics return?"}]},
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]
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": contents},
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)
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assert response.status_code == 200
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data = response.json()
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assert data["totalTokens"] > 0
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# =============================================================================
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# Model Variant Tests
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# =============================================================================
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class TestGeminiCountTokensModels:
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"""Test countTokens with different Gemini models."""
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def test_gemini_flash_model(self, gemini_client_optimized, api_key):
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"""countTokens works with gemini-2.0-flash model."""
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
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json={"contents": create_simple_content()},
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)
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assert response.status_code == 200
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assert "totalTokens" in response.json()
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def test_gemini_flash_lite_model(self, gemini_client_optimized, api_key):
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"""countTokens works with gemini-2.0-flash-lite model."""
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response = gemini_client_optimized.post(
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f"/v1beta/models/gemini-2.0-flash-lite:countTokens?key={api_key}",
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json={"contents": create_simple_content()},
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)
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# Model may or may not be available
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assert response.status_code in [200, 404]
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if response.status_code == 200:
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assert "totalTokens" in response.json()
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# =============================================================================
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# Error Handling Tests
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# =============================================================================
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class TestGeminiCountTokensErrors:
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"""Test error handling for countTokens endpoint."""
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def test_invalid_api_key(self, gemini_client_optimized):
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"""Invalid API key returns authentication error."""
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response = gemini_client_optimized.post(
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"/v1beta/models/gemini-2.0-flash:countTokens?key=invalid-key-12345",
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json={"contents": create_simple_content()},
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)
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assert response.status_code in [400, 401, 403]
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def test_invalid_model(self, gemini_client_optimized, api_key):
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"""Invalid model name returns error."""
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response = gemini_client_optimized.post(
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f"/v1beta/models/nonexistent-model-xyz:countTokens?key={api_key}",
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json={"contents": create_simple_content()},
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)
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assert response.status_code >= 400
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def test_empty_contents(self, gemini_client_optimized, api_key):
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"""Empty contents may return error or zero tokens."""
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response = gemini_client_optimized.post(
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|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
json={"contents": []},
|
|
)
|
|
# May return error or success with 0 tokens
|
|
if response.status_code == 200:
|
|
data = response.json()
|
|
assert "totalTokens" in data
|
|
|
|
def test_invalid_json_body(self, gemini_client_optimized, api_key):
|
|
"""Invalid JSON body returns 400 error."""
|
|
response = gemini_client_optimized.post(
|
|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
headers={"Content-Type": "application/json"},
|
|
content=b"not valid json",
|
|
)
|
|
assert response.status_code == 400
|
|
|
|
def test_missing_contents_field(self, gemini_client_optimized, api_key):
|
|
"""Missing contents field handled gracefully."""
|
|
response = gemini_client_optimized.post(
|
|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
json={},
|
|
)
|
|
# May return error or handle empty contents
|
|
assert response.status_code in [200, 400]
|
|
|
|
|
|
# =============================================================================
|
|
# Stats Tracking Tests
|
|
# =============================================================================
|
|
|
|
|
|
class TestGeminiCountTokensStats:
|
|
"""Test proxy stats tracking for countTokens requests."""
|
|
|
|
def test_stats_track_gemini_provider(self, gemini_client_optimized, api_key):
|
|
"""Stats correctly track Gemini provider."""
|
|
# Clear stats by getting a fresh client
|
|
gemini_client_optimized.post(
|
|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
json={"contents": create_simple_content()},
|
|
)
|
|
|
|
stats = gemini_client_optimized.get("/stats").json()
|
|
assert "gemini" in stats["requests"]["by_provider"]
|
|
assert stats["requests"]["by_provider"]["gemini"] >= 1
|
|
|
|
def test_stats_track_model(self, gemini_client_optimized, api_key):
|
|
"""Stats correctly track model used."""
|
|
gemini_client_optimized.post(
|
|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
json={"contents": create_simple_content()},
|
|
)
|
|
|
|
stats = gemini_client_optimized.get("/stats").json()
|
|
# Model should be tracked in by_model
|
|
assert len(stats["requests"]["by_model"]) >= 1
|
|
|
|
def test_stats_track_tokens_saved(self, gemini_client_optimized, api_key):
|
|
"""Stats track tokens saved from compression."""
|
|
# Make request with large compressible content
|
|
large_contents = create_large_content(num_items=30)
|
|
gemini_client_optimized.post(
|
|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
json={"contents": large_contents},
|
|
)
|
|
|
|
stats = gemini_client_optimized.get("/stats").json()
|
|
# tokens.saved should be tracked (may be 0 if content wasn't compressed)
|
|
assert "tokens" in stats
|
|
assert "saved" in stats["tokens"]
|
|
|
|
|
|
# =============================================================================
|
|
# Integration Tests
|
|
# =============================================================================
|
|
|
|
|
|
class TestGeminiCountTokensIntegration:
|
|
"""Integration tests combining multiple features."""
|
|
|
|
def test_full_workflow(self, gemini_client_optimized, api_key):
|
|
"""Test complete workflow: count tokens, verify compression, check stats."""
|
|
# Step 1: Count tokens with large content
|
|
large_contents = create_large_content(num_items=35)
|
|
|
|
initial_stats = gemini_client_optimized.get("/stats").json()
|
|
initial_tokens_saved = initial_stats["tokens"]["saved"]
|
|
|
|
# Step 2: Make countTokens request
|
|
response = gemini_client_optimized.post(
|
|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
json={"contents": large_contents},
|
|
)
|
|
assert response.status_code == 200
|
|
token_count = response.json()["totalTokens"]
|
|
assert token_count > 0
|
|
|
|
# Step 3: Verify stats updated
|
|
updated_stats = gemini_client_optimized.get("/stats").json()
|
|
assert updated_stats["requests"]["total"] > initial_stats["requests"]["total"]
|
|
|
|
# Step 4: Verify tokens saved is tracked (may be negative for small overhead)
|
|
# Allow for some compression overhead
|
|
assert updated_stats["tokens"]["saved"] >= initial_tokens_saved - 100
|
|
|
|
def test_multiple_requests_accumulate_stats(self, gemini_client_optimized, api_key):
|
|
"""Multiple requests correctly accumulate stats."""
|
|
initial_stats = gemini_client_optimized.get("/stats").json()
|
|
initial_total = initial_stats["requests"]["total"]
|
|
|
|
# Make several requests
|
|
for _ in range(3):
|
|
gemini_client_optimized.post(
|
|
f"/v1beta/models/gemini-2.0-flash:countTokens?key={api_key}",
|
|
json={"contents": create_simple_content()},
|
|
)
|
|
|
|
updated_stats = gemini_client_optimized.get("/stats").json()
|
|
assert updated_stats["requests"]["total"] >= initial_total + 3
|