From 6239f300bf0dcfe9fd2b1fbdfafd17dd92e68ff6 Mon Sep 17 00:00:00 2001 From: Mengqin Shen Date: Thu, 5 Feb 2026 10:26:46 -0800 Subject: [PATCH 1/3] feat(py): web GUI for Model Performance Tool --- py/model_performance_report.md | 68 + py/pyproject.toml | 2 +- py/samples/sample-test/README.md | 23 + py/samples/sample-test/pyproject.toml | 26 + .../sample-test/run_single_model_test.py | 163 ++ py/samples/sample-test/server.py | 167 ++ py/samples/sample-test/static/index.html | 90 + py/samples/sample-test/static/script.js | 246 +++ py/samples/sample-test/static/style.css | 301 +++ .../sample-test/test_model_performance.py | 428 ++++ py/samples/sample-test/uv.lock | 1807 +++++++++++++++++ 11 files changed, 3320 insertions(+), 1 deletion(-) create mode 100644 py/model_performance_report.md create mode 100644 py/samples/sample-test/README.md create mode 100644 py/samples/sample-test/pyproject.toml create mode 100644 py/samples/sample-test/run_single_model_test.py create mode 100644 py/samples/sample-test/server.py create mode 100644 py/samples/sample-test/static/index.html create mode 100644 py/samples/sample-test/static/script.js create mode 100644 py/samples/sample-test/static/style.css create mode 100644 py/samples/sample-test/test_model_performance.py create mode 100644 py/samples/sample-test/uv.lock diff --git a/py/model_performance_report.md b/py/model_performance_report.md new file mode 100644 index 0000000000..f508c18403 --- /dev/null +++ b/py/model_performance_report.md @@ -0,0 +1,68 @@ +# Model Performance Test Report + +## Summary + +- **Total Tests**: 8 +- **Passed**: 8 +- **Failed**: 0 +- **Success Rate**: 100.0% + +## Detailed Results + +### googleai/gemini-2.0-flash + +#### Config: `{}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.602s +- **Response**: Aye, 5 doubloons plus 3 more... that be 8 doubloons in total! + + +#### Config: `{"temperature": 0.0}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.832s +- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers! + + +#### Config: `{"temperature": 2.0}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.565s +- **Response**: Arrr, 5 doubloons plus 3 doubloons be equal to 8 doubloons! + + +#### Config: `{"temperature": 1.0}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.662s +- **Response**: Aye, 5 doubloons plus 3 doubloons be 8 doubloons in total! Shiver me timbers! + + +#### Config: `{"topP": 0.0}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.774s +- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers, that be a fine haul o' doubloons! + + +#### Config: `{"topP": 1.0}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.651s +- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers! + + +#### Config: `{"topP": 0.5}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.752s +- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers, that be a fine bit o' arithmetic! + + +#### Config: `{"safetySettings": []}` + +- **Status**: ✅ SUCCESS +- **Timing**: 1.562s +- **Response**: Aye, 5 doubloons plus 3 doubloons be 8 doubloons, me hearty! + diff --git a/py/pyproject.toml b/py/pyproject.toml index e53e516295..d7fafcf6a8 100644 --- a/py/pyproject.toml +++ b/py/pyproject.toml @@ -188,7 +188,7 @@ genkit-plugin-vertex-ai = { workspace = true } genkit-plugin-xai = { workspace = true } [tool.uv.workspace] -exclude = ["*/shared", "testapps/*"] +exclude = ["*/shared", "testapps/*", "samples/sample-test"] members = ["packages/*", "plugins/*", "samples/*"] diff --git a/py/samples/sample-test/README.md b/py/samples/sample-test/README.md new file mode 100644 index 0000000000..031098f098 --- /dev/null +++ b/py/samples/sample-test/README.md @@ -0,0 +1,23 @@ +# Model Performance Testing Tool + +A tool to test model performance across different models and configuration variations. + +## Setup + +1. Ensure you have `uv` installed. +2. Set your API keys (e.g., `GOOGLE_GENAI_API_KEY`). + +## Usage + +Run the tool: + +```bash +uv run test_model_performance.py --models googleai/gemini-2.0-flash +``` + +## Features + +- **Model Discovery**: Automatically finds registered models. +- **Config Discovery**: Inspects model schema to find parameters. +- **Variations**: Tests min, max, midpoint, and default values. +- **Report**: Generates a Markdown report with pass/fail stats and detailed results. diff --git a/py/samples/sample-test/pyproject.toml b/py/samples/sample-test/pyproject.toml new file mode 100644 index 0000000000..03d71e63cf --- /dev/null +++ b/py/samples/sample-test/pyproject.toml @@ -0,0 +1,26 @@ +# Copyright 2026 Google LLC +# SPDX-License-Identifier: Apache-2.0 + +[project] +name = "sample-test" +version = "0.1.0" +description = "Model Performance Testing Tool" +readme = "README.md" +requires-python = ">=3.10" +dependencies = [ + "genkit", + "genkit-plugin-google-genai", + "fastapi", + "uvicorn", +] + +[build-system] +build-backend = "hatchling.build" +requires = ["hatchling"] + +[tool.hatch.build.targets.wheel] +packages = ["test_model_performance.py", "run_single_model_test.py"] + +[tool.uv.sources] +genkit = { path = "../../packages/genkit", editable = true } +genkit-plugin-google-genai = { path = "../../plugins/google-genai", editable = true } diff --git a/py/samples/sample-test/run_single_model_test.py b/py/samples/sample-test/run_single_model_test.py new file mode 100644 index 0000000000..dbb8db3e5e --- /dev/null +++ b/py/samples/sample-test/run_single_model_test.py @@ -0,0 +1,163 @@ +#!/usr/bin/env python3 +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Helper script to run a single model test in isolation. + +This script is called by test_model_performance.py to execute each model+config +test in a separate subprocess, avoiding state pollution and enabling timeout handling. + +Usage: + python run_single_model_test.py --config --user-prompt --system-prompt + +Output: + JSON object with 'success', 'response', 'error', 'timing' fields +""" + +import argparse +import json +import sys +import time +from typing import Any + + +async def run_model_test( + model_name: str, + config: dict[str, Any], + user_prompt: str, + system_prompt: str | None = None, +) -> dict[str, Any]: + """Run a single model test and return result. + + Args: + model_name: Name of the model to test + config: Configuration dictionary for the model + user_prompt: User prompt to send + system_prompt: Optional system prompt + + Returns: + Dict with 'success', 'response', 'error', 'timing' fields + """ + result: dict[str, Any] = { + "success": False, + "response": None, + "error": None, + "timing": 0.0, + } + + try: + # Import Genkit + from genkit import Genkit + from genkit.plugins.google_genai import GoogleAI, VertexAI + from genkit.core.typing import Message, TextPart + + plugins = [] + try: + plugins.append(GoogleAI()) + except Exception: + pass + try: + plugins.append(VertexAI()) + except Exception: + pass + + # Initialize Genkit + ai = Genkit(plugins=plugins) + + # Build the prompt + messages = [] + if system_prompt: + messages.append(Message( + role='system', + content=[TextPart(text=system_prompt)] + )) + messages.append(Message( + role='user', + content=[TextPart(text=user_prompt)] + )) + + # Start timing + start_time = time.time() + + # Run generation + response = await ai.generate( + model=model_name, + messages=messages, + config=config, + ) + + # Calculate timing + elapsed = time.time() - start_time + + # Extract response text + response_text = response.text if hasattr(response, 'text') else str(response) + + result["success"] = True + result["response"] = response_text + result["timing"] = round(elapsed, 3) + + except Exception as e: + import traceback + result["error"] = f"{type(e).__name__}: {e}\n{traceback.format_exc()}" + + return result + + +def main() -> None: + """Run a single model test and output JSON result.""" + parser = argparse.ArgumentParser(description='Run a single model test.') + parser.add_argument('model_name', type=str, help='Name of the model to test') + parser.add_argument('--config', type=str, default='{}', help='JSON string of model config') + parser.add_argument('--user-prompt', type=str, required=True, help='User prompt text') + parser.add_argument('--system-prompt', type=str, default=None, help='System prompt text') + args = parser.parse_args() + + # Suppress verbose logging + import logging + logging.basicConfig(level=logging.ERROR) + logging.getLogger('genkit').setLevel(logging.ERROR) + logging.getLogger('google').setLevel(logging.ERROR) + + # Override input() to prevent blocking + import builtins + builtins.input = lambda prompt="": "dummy_value" + + result: dict[str, Any] = {"success": False, "response": None, "error": "Unknown initialization error", "timing": 0.0} + + try: + # Parse config + config = json.loads(args.config) + + # Run test in async context + import asyncio + result = asyncio.run(run_model_test( + args.model_name, + config, + args.user_prompt, + args.system_prompt, + )) + + except Exception as e: + result = {"success": False, "response": None, "error": f"Initialization failed: {e}", "timing": 0.0} + + # Output JSON result with markers + print("---JSON_RESULT_START---") + print(json.dumps(result)) + print("---JSON_RESULT_END---") + + +if __name__ == "__main__": + main() diff --git a/py/samples/sample-test/server.py b/py/samples/sample-test/server.py new file mode 100644 index 0000000000..3dbc3a7b29 --- /dev/null +++ b/py/samples/sample-test/server.py @@ -0,0 +1,167 @@ +#!/usr/bin/env python3 +# Copyright 2026 Google LLC +# SPDX-License-Identifier: Apache-2.0 + +"""FastAPI backend for Model Performance Tool.""" + +from fastapi import FastAPI, HTTPException +from fastapi.staticfiles import StaticFiles +from fastapi.middleware.cors import CORSMiddleware +from pydantic import BaseModel +import asyncio +from typing import Any, List, Dict +import logging +from pathlib import Path + +# Import tool logic +from test_model_performance import discover_models, run_model_test, parse_config_schema + +app = FastAPI(title="Model Performance Tool") + +# CORS for local dev +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +# --- Data Models --- + +class Scenario(BaseModel): + id: str + name: str + description: str + system_prompt: str + user_prompt: str + +class TestRequest(BaseModel): + model: str + config: Dict[str, Any] + scenario_id: str + user_prompt: str + system_prompt: str + +class TestResult(BaseModel): + success: bool + response: str | None + error: str | None + timing: float + +# --- Scenarios --- + +SCENARIOS = [ + Scenario( + id="basic_math", + name="Basic Logic & Math", + description="Tests reasoning capabilities with simple math problems.", + system_prompt="You are a helpful math assistant.", + user_prompt="What is 15 * 7? Explain step by step." + ), + Scenario( + id="creative_writing", + name="Creative Writing", + description="Tests creativity and tone adherence.", + system_prompt="You are a pirate bard.", + user_prompt="Write a short poem about the ocean." + ), + Scenario( + id="code_gen", + name="Code Generation", + description="Tests code generation capabilities.", + system_prompt="You are an expert Python developer.", + user_prompt="Write a function to calculate the Fibonacci sequence." + ), + Scenario( + id="image_gen", + name="Image Generation", + description="Tests image generation models (Vertex AI only).", + system_prompt="", + user_prompt="A futuristic cityscape at sunset, neon lights, cyberpunk style." + ) +] + +# --- Endpoints --- + +@app.get("/api/scenarios", response_model=List[Scenario]) +async def get_scenarios(): + return SCENARIOS + +@app.get("/api/models") +async def get_models(scenario: str | None = None): + try: + models = await discover_models() + + # Simple filtering logic based on scenario + filtered_models = [] + for name, info in models.items(): + # For specific scenarios, we might want to filter models if possible + # But currently we don't have enough metadata to distinguish text vs image clearly + # except by name convention or inspecting supported actions deeper. + # For now, we return all models and let the user choose. + + # Extract config schema for UI + config_schema = info.get('customOptions', {}) + params = parse_config_schema(config_schema) + + filtered_models.append({ + "name": name, + "info": info, + "params": params + }) + + return filtered_models + except Exception as e: + logging.error(f"Error discovering models: {e}") + raise HTTPException(status_code=500, detail=str(e)) + +@app.post("/api/run", response_model=TestResult) +async def run_test(request: TestRequest): + try: + script_path = Path(__file__).parent / "run_single_model_test.py" + + # Run test in thread pool to not block async loop (subprocess call inside) + result = await asyncio.to_thread( + lambda: asyncio.run(run_wrapper( + request.model, + request.config, + request.user_prompt, + request.system_prompt, + script_path + )) + ) + + return TestResult( + success=result.get("success", False), + response=str(result.get("response")) if result.get("response") else None, + error=result.get("error"), + timing=result.get("timing", 0.0) + ) + + except Exception as e: + logging.error(f"Error running test: {e}") + raise HTTPException(status_code=500, detail=str(e)) + +# Wrapper to run async run_model_test inside the thread +async def run_wrapper(model, config, user_prompt, system_prompt, script_path): + # run_model_test in test_model_performance is synchronous (uses subprocess.run) + # We need to call it directly. Wait, run_model_test in test_model_performance IS synchronous wrapper around subprocess. + # So we don't need asyncio.run inside the lambda unless run_model_test was async. + # Checking test_model_performance.py... run_model_test is synchronous. + + return run_model_test( + model, + config, + user_prompt, + system_prompt, + script_path + ) + + +# Mount static files (Frontend) +app.mount("/", StaticFiles(directory="samples/sample-test/static", html=True), name="static") + +if __name__ == "__main__": + import uvicorn + uvicorn.run(app, host="0.0.0.0", port=8000) diff --git a/py/samples/sample-test/static/index.html b/py/samples/sample-test/static/index.html new file mode 100644 index 0000000000..8d59787d0e --- /dev/null +++ b/py/samples/sample-test/static/index.html @@ -0,0 +1,90 @@ + + + + + + Genkit Model Performance + + + + + + +
+ + + + +
+
+

Select a Sample

+
+ 0 Models +
+
+ +
+ +
+
+

Model Selection

+
+ + +
+ +
+ +
+ +
+ + +
+ +
+ + +
+ + +
+
+ + +
+
+

Results

+ +
+ +
+
+ Select a model and run test to see results. +
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+
+
+
+
+ + + diff --git a/py/samples/sample-test/static/script.js b/py/samples/sample-test/static/script.js new file mode 100644 index 0000000000..007384c00f --- /dev/null +++ b/py/samples/sample-test/static/script.js @@ -0,0 +1,246 @@ +const API_BASE = '/api'; + +// State +let currentState = { + scenarios: [], + models: [], + selectedScenarioId: null, + selectedModel: null, + stats: { pass: 0, fail: 0 } +}; + +// DOM Elements +const els = { + samplesList: document.getElementById('samples-list'), + currentScenarioTitle: document.getElementById('current-scenario-title'), + modelCount: document.getElementById('model-count'), + modelSelect: document.getElementById('model-select'), + paramConfig: document.getElementById('param-config'), + systemPrompt: document.getElementById('system-prompt'), + userPrompt: document.getElementById('user-prompt'), + runBtn: document.getElementById('run-btn'), + resultsList: document.getElementById('results-list'), + statsBar: document.getElementById('stats-bar'), + passCount: document.getElementById('pass-count'), + failCount: document.getElementById('fail-count') +}; + +// Init +async function init() { + try { + const scenarios = await fetchAPI('/scenarios'); + currentState.scenarios = scenarios; + renderScenariosList(); + + // Select first by default + if (scenarios.length > 0) { + selectScenario(scenarios[0].id); + } + } catch (e) { + console.error('Failed to init:', e); + els.samplesList.innerHTML = ``; + } +} + +// Actions +async function selectScenario(id) { + currentState.selectedScenarioId = id; + const scenario = currentState.scenarios.find(s => s.id === id); + + // Update UI + document.querySelectorAll('.nav-item').forEach(el => { + el.classList.toggle('active', el.dataset.id === id); + }); + + els.currentScenarioTitle.textContent = scenario.name; + els.systemPrompt.value = scenario.system_prompt; + els.userPrompt.value = scenario.user_prompt; + + await loadModels(id); +} + +async function loadModels(scenarioId) { + els.modelSelect.innerHTML = ''; + els.modelSelect.disabled = true; + + try { + const models = await fetchAPI(`/models?scenario=${scenarioId}`); + currentState.models = models; + + els.modelCount.textContent = `${models.length} Models`; + + // Render Select + els.modelSelect.innerHTML = models.length ? + models.map(m => ``).join('') : + ''; + + els.modelSelect.disabled = false; + + // Trigger select change to load params + if (models.length > 0) { + handleModelChange(models[0].name); + } else { + els.paramConfig.innerHTML = ''; + } + } catch (e) { + console.error('Failed to load models:', e); + els.modelSelect.innerHTML = ''; + } +} + +function handleModelChange(modelName) { + const model = currentState.models.find(m => m.name === modelName); + currentState.selectedModel = model; + + renderParams(model.params); +} + +function renderParams(params) { + if (!params || Object.keys(params).length === 0) { + els.paramConfig.innerHTML = '
No configurable parameters
'; + return; + } + + let html = '

Configuration

'; + + for (const [key, config] of Object.entries(params)) { + html += `
+ `; + + if (config.enum) { + html += ``; + } else if (config.type === 'boolean') { + html += ``; + } else if (config.type === 'number') { + const min = config.minimum !== undefined ? `min="${config.minimum}"` : ''; + const max = config.maximum !== undefined ? `max="${config.maximum}"` : ''; + const step = (config.maximum - config.minimum) <= 1 ? '0.1' : '1'; + const val = config.default !== undefined ? config.default : + (config.minimum !== undefined ? config.minimum : 0); + + html += ``; + } else { + // Default text + html += ``; + } + + html += `
`; + } + + els.paramConfig.innerHTML = html; +} + +async function runTest() { + if (!currentState.selectedModel) return; + + els.runBtn.disabled = true; + els.runBtn.textContent = 'Running...'; + + // Collect Config + const config = {}; + document.querySelectorAll('.config-input').forEach(input => { + const key = input.dataset.key; + const type = input.dataset.type; + let value = input.value; + + if (type === 'number') value = parseFloat(value); + if (type === 'boolean') value = value === 'true'; + + config[key] = value; + }); + + try { + const result = await fetchAPI('/run', 'POST', { + model: currentState.selectedModel.name, + config: config, + scenario_id: currentState.selectedScenarioId, + user_prompt: els.userPrompt.value, + system_prompt: els.systemPrompt.value + }); + + addResultCard(result); + updateStats(result.success); + + } catch (e) { + console.error(e); + addResultCard({ success: false, error: e.message, timing: 0 }); + updateStats(false); + } finally { + els.runBtn.disabled = false; + els.runBtn.textContent = 'Run Test'; + } +} + +// Helpers +async function fetchAPI(endpoint, method = 'GET', body = null) { + const options = { + method, + headers: { + 'Content-Type': 'application/json' + } + }; + if (body) options.body = JSON.stringify(body); + + const res = await fetch(API_BASE + endpoint, options); + if (!res.ok) throw new Error(`API Error: ${res.statusText}`); + return await res.json(); +} + +function renderScenariosList() { + els.samplesList.innerHTML = currentState.scenarios.map(s => + `` + ).join(''); +} + +function addResultCard(result) { + const card = document.createElement('div'); + card.className = `result-card ${result.success ? 'success' : 'error'}`; + + card.innerHTML = ` +
+ ${currentState.selectedModel.name} + ${result.timing}s +
+
${result.success ? escapeHtml(result.response) : result.error}
+ `; + + els.resultsList.prepend(card); + + // Clear empty state + const empty = els.resultsList.querySelector('.empty-state'); + if (empty) empty.remove(); +} + +function updateStats(success) { + if (success) currentState.stats.pass++; + else currentState.stats.fail++; + + els.passCount.textContent = currentState.stats.pass; + els.failCount.textContent = currentState.stats.fail; + els.statsBar.classList.remove('hidden'); +} + +function escapeHtml(text) { + if (!text) return ''; + return text.replace(/&/g, "&") + .replace(//g, ">") + .replace(/"/g, """) + .replace(/'/g, "'"); +} + +// Event Listeners +els.modelSelect.addEventListener('change', (e) => handleModelChange(e.target.value)); +els.runBtn.addEventListener('click', runTest); + +// Start +init(); diff --git a/py/samples/sample-test/static/style.css b/py/samples/sample-test/static/style.css new file mode 100644 index 0000000000..606376e9fe --- /dev/null +++ b/py/samples/sample-test/static/style.css @@ -0,0 +1,301 @@ +:root { + --bg-dark: #0f1115; + --bg-panel: #181b21; + --bg-card: #20242c; + --border: #2d323b; + --text-primary: #e0e4eb; + --text-secondary: #949ba6; + --accent: #6e5bf1; + --accent-hover: #5a4bd4; + --success: #22c55e; + --error: #ef4444; +} + +* { + box-sizing: border-box; + margin: 0; + padding: 0; +} + +body { + font-family: 'Inter', sans-serif; + background-color: var(--bg-dark); + color: var(--text-primary); + line-height: 1.5; + height: 100vh; + overflow: hidden; +} + +.app-container { + display: grid; + grid-template-columns: 280px 1fr; + height: 100vh; +} + +/* Sidebar */ +.sidebar { + background-color: var(--bg-panel); + border-right: 1px solid var(--border); + padding: 1.5rem; + display: flex; + flex-direction: column; +} + +.brand { + display: flex; + align-items: center; + gap: 0.75rem; + margin-bottom: 2.5rem; +} + +.logo-icon { + width: 32px; + height: 32px; + background: linear-gradient(135deg, var(--accent), #a78bfa); + border-radius: 8px; + display: flex; + align-items: center; + justify-content: center; + font-weight: 700; + font-size: 1.2rem; + color: white; +} + +.brand h1 { + font-size: 1.25rem; + font-weight: 600; +} + +.section-title { + font-size: 0.75rem; + text-transform: uppercase; + color: var(--text-secondary); + letter-spacing: 0.05em; + margin-bottom: 1rem; + font-weight: 600; +} + +.nav-list { + display: flex; + flex-direction: column; + gap: 0.5rem; +} + +.nav-item { + padding: 0.75rem 1rem; + border-radius: 8px; + cursor: pointer; + transition: all 0.2s ease; + color: var(--text-secondary); + font-size: 0.9rem; + font-weight: 500; +} + +.nav-item:hover { + color: var(--text-primary); + background-color: rgba(255,255,255,0.05); +} + +.nav-item.active { + background-color: rgba(110, 91, 241, 0.15); + color: var(--accent); +} + +/* Main Content */ +.main-content { + display: flex; + flex-direction: column; + height: 100vh; + overflow: hidden; +} + +.top-bar { + height: 70px; + border-bottom: 1px solid var(--border); + padding: 0 2rem; + display: flex; + align-items: center; + justify-content: space-between; + background-color: rgba(15, 17, 21, 0.8); + backdrop-filter: blur(12px); +} + +.top-bar h2 { + font-size: 1.1rem; + font-weight: 600; +} + +.badge { + background-color: var(--bg-card); + border: 1px solid var(--border); + padding: 0.25rem 0.75rem; + border-radius: 20px; + font-size: 0.8rem; + color: var(--text-secondary); +} + +/* Grid Layout */ +.content-grid { + flex: 1; + display: grid; + grid-template-columns: 400px 1fr; + gap: 2rem; + padding: 2rem; + overflow: hidden; +} + +/* Panels */ +.config-panel { + overflow-y: auto; +} + +.results-panel { + display: flex; + flex-direction: column; + height: 100%; + overflow: hidden; + background-color: var(--bg-card); + border: 1px solid var(--border); + border-radius: 12px; +} + +/* Cards */ +.card { + background-color: var(--bg-card); + border: 1px solid var(--border); + border-radius: 12px; + padding: 1.5rem; +} + +.card h3 { + margin-bottom: 1.5rem; + font-size: 1rem; + font-weight: 600; +} + +/* Forms */ +.form-group { + margin-bottom: 1.25rem; +} + +.form-group label { + display: block; + margin-bottom: 0.5rem; + font-size: 0.85rem; + color: var(--text-secondary); +} + +select, textarea, input { + width: 100%; + background-color: var(--bg-dark); + border: 1px solid var(--border); + color: var(--text-primary); + padding: 0.75rem; + border-radius: 8px; + font-family: inherit; + font-size: 0.9rem; + transition: border-color 0.2s; + outline: none; +} + +select:focus, textarea:focus, input:focus { + border-color: var(--accent); +} + +textarea { + resize: vertical; +} + +.btn-primary { + width: 100%; + background-color: var(--accent); + color: white; + border: none; + padding: 0.85rem; + border-radius: 8px; + font-weight: 600; + cursor: pointer; + transition: background-color 0.2s; + margin-top: 1rem; +} + +.btn-primary:hover { + background-color: var(--accent-hover); +} + +.btn-primary:disabled { + opacity: 0.6; + cursor: wait; +} + +/* Results */ +.results-header { + padding: 1.5rem; + border-bottom: 1px solid var(--border); + display: flex; + justify-content: space-between; + align-items: center; +} + +.results-list { + flex: 1; + overflow-y: auto; + padding: 1.5rem; + display: flex; + flex-direction: column; + gap: 1rem; +} + +.empty-state { + text-align: center; + color: var(--text-secondary); + margin-top: 3rem; +} + +.result-card { + background-color: var(--bg-panel); + border: 1px solid var(--border); + border-radius: 8px; + padding: 1rem; + border-left: 4px solid var(--border); +} + +.result-card.success { + border-left-color: var(--success); +} + +.result-card.error { + border-left-color: var(--error); +} + +.result-meta { + display: flex; + justify-content: space-between; + margin-bottom: 0.75rem; + font-size: 0.85rem; + color: var(--text-secondary); +} + +.result-content { + background-color: var(--bg-dark); + padding: 0.75rem; + border-radius: 6px; + font-family: monospace; + font-size: 0.9rem; + white-space: pre-wrap; + max-height: 200px; + overflow-y: auto; +} + +.stat-item { + font-size: 0.9rem; + font-weight: 500; + margin-left: 1rem; +} + +.stat-item.success { color: var(--success); } +.stat-item.error { color: var(--error); } + +.hidden { + display: none; +} diff --git a/py/samples/sample-test/test_model_performance.py b/py/samples/sample-test/test_model_performance.py new file mode 100644 index 0000000000..6df832b2e4 --- /dev/null +++ b/py/samples/sample-test/test_model_performance.py @@ -0,0 +1,428 @@ +#!/usr/bin/env python3 +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Tool to test model performance with dynamic configuration variations. + +Usage: + python test_model_performance.py [--models model1,model2] [--output report.md] + +Example: + python test_model_performance.py --models googleai/gemini-2.0-flash +""" + +import argparse +import builtins +import importlib.util +import json +import subprocess +import sys +from collections.abc import Callable +from pathlib import Path +from typing import Any + +# Mock input to prevent blocking +builtins.input = lambda prompt="": "dummy_value" + + +async def discover_models() -> dict[str, Any]: + """Discover all available models from Genkit registry. + + Returns: + Dict mapping model names to model info + """ + # Import Genkit + from genkit import Genkit + from genkit.plugins.google_genai import GoogleAI, VertexAI + + plugins = [] + # Initialize with GoogleAI plugin + try: + plugins.append(GoogleAI()) + except Exception as e: + print(f"Warning: Failed to initialize GoogleAI plugin: {e}") + + # Initialize with VertexAI plugin + try: + plugins.append(VertexAI()) + except Exception as e: + # print(f"Warning: Failed to initialize VertexAI plugin: {e}") + pass + + ai = Genkit(plugins=plugins) + + registry = ai.registry + + # Get all model actions via list_actions (which queries plugins) + from genkit.core.action import ActionKind + actions = await registry.list_actions(allowed_kinds=[ActionKind.MODEL]) + + model_info = {} + for meta in actions: + # Extract model info using metadata + info = meta.metadata.get('model', {}) + model_info[meta.name] = info + + return model_info + + +def parse_config_schema(schema: dict[str, Any]) -> dict[str, dict[str, Any]]: + """Parse JSON schema to extract configuration parameters. + + Args: + schema: JSON schema dict + + Returns: + Dict mapping parameter names to their schema info + """ + if not schema or 'properties' not in schema: + return {} + + params = {} + for param_name, param_schema in schema['properties'].items(): + params[param_name] = { + 'type': param_schema.get('type'), + 'minimum': param_schema.get('minimum'), + 'maximum': param_schema.get('maximum'), + 'default': param_schema.get('default'), + 'enum': param_schema.get('enum'), + 'items': param_schema.get('items'), + } + + return params + + +def generate_config_variations(params: dict[str, dict[str, Any]]) -> list[dict[str, Any]]: + """Generate configuration variations for testing. + + Args: + params: Parameter schema info from parse_config_schema + + Returns: + List of config dicts to test + """ + variations = [] + + # Start with baseline (all defaults or empty) + baseline = {} + variations.append(baseline.copy()) + + # Generate variations for each parameter + for param_name, param_info in params.items(): + param_type = param_info['type'] + + if param_type == 'number': + # Numeric parameters + minimum = param_info.get('minimum', 0.0) + maximum = param_info.get('maximum', 1.0) + default = param_info.get('default') + + # Test min, max, midpoint + test_values = [minimum, maximum] + if minimum < maximum: + midpoint = (minimum + maximum) / 2 + test_values.append(midpoint) + if default is not None and default not in test_values: + test_values.append(default) + + for value in test_values: + config = baseline.copy() + config[param_name] = value + variations.append(config) + + elif param_type == 'boolean': + # Boolean parameters + for value in [True, False]: + config = baseline.copy() + config[param_name] = value + variations.append(config) + + elif param_type == 'string': + # String parameters + enum_values = param_info.get('enum') + if enum_values: + for value in enum_values: + config = baseline.copy() + config[param_name] = value + variations.append(config) + + elif param_type == 'array': + # Array parameters + config = baseline.copy() + config[param_name] = [] + variations.append(config) + + # Add sample array value + items_schema = param_info.get('items', {}) + if items_schema.get('type') == 'string': + config = baseline.copy() + config[param_name] = ["STOP"] + variations.append(config) + + return variations + + +def run_model_test( + model_name: str, + config: dict[str, Any], + user_prompt: str, + system_prompt: str | None, + helper_script: Path, + timeout: int = 60, +) -> dict[str, Any]: + """Run a single model test via subprocess. + + Args: + model_name: Model to test + config: Configuration dict + user_prompt: User prompt + system_prompt: System prompt + helper_script: Path to run_single_model_test.py + timeout: Timeout in seconds + + Returns: + Test result dict + """ + cmd = [ + "uv", "run", + "run_single_model_test.py", + model_name, + "--config", json.dumps(config), + "--user-prompt", user_prompt, + ] + + if system_prompt: + cmd.extend(["--system-prompt", system_prompt]) + + try: + result_proc = subprocess.run( # noqa: S603 - cmd constructed from trusted paths + cmd, + capture_output=True, + text=True, + timeout=timeout, + cwd=helper_script.parent, # Run from script directory (samples/sample-test) + ) + + # Parse JSON output + stdout = result_proc.stdout + if "---JSON_RESULT_START---" in stdout and "---JSON_RESULT_END---" in stdout: + json_str = stdout.split("---JSON_RESULT_START---")[1].split("---JSON_RESULT_END---")[0].strip() + return json.loads(json_str) + else: + return json.loads(stdout) + + except subprocess.TimeoutExpired: + return { + "success": False, + "response": None, + "error": f"Test timed out after {timeout}s", + "timing": timeout, + } + except Exception as e: + return { + "success": False, + "response": None, + "error": f"Subprocess failed: {e}", + "timing": 0.0, + } + + +def generate_report( + results: list[dict[str, Any]], + output_file: str, +) -> None: + """Generate markdown report from test results. + + Args: + results: List of test result dicts + output_file: Output file path + """ + total_tests = len(results) + passed = sum(1 for r in results if r['result']['success']) + failed = total_tests - passed + success_rate = (passed / total_tests * 100) if total_tests > 0 else 0 + + lines = [] + lines.append("# Model Performance Test Report") + lines.append("") + lines.append("## Summary") + lines.append("") + lines.append(f"- **Total Tests**: {total_tests}") + lines.append(f"- **Passed**: {passed}") + lines.append(f"- **Failed**: {failed}") + lines.append(f"- **Success Rate**: {success_rate:.1f}%") + lines.append("") + + # Failed tests summary + if failed > 0: + lines.append("## Failed Tests") + lines.append("") + for test in results: + if not test['result']['success']: + config_str = json.dumps(test['config'], sort_keys=True) + error = test['result']['error'] + # Truncate long errors + if len(error) > 200: + error = error[:200] + "..." + lines.append(f"- **{test['model']}** (config: `{config_str}`)") + lines.append(f" - Error: {error}") + lines.append("") + + # Detailed results + lines.append("## Detailed Results") + lines.append("") + + # Group by model + models = {} + for test in results: + model_name = test['model'] + if model_name not in models: + models[model_name] = [] + models[model_name].append(test) + + for model_name, model_tests in models.items(): + lines.append(f"### {model_name}") + lines.append("") + + for test in model_tests: + config_str = json.dumps(test['config'], sort_keys=True) if test['config'] else "{}" + status = "✅ SUCCESS" if test['result']['success'] else "❌ FAILED" + timing = test['result']['timing'] + + lines.append(f"#### Config: `{config_str}`") + lines.append("") + lines.append(f"- **Status**: {status}") + lines.append(f"- **Timing**: {timing}s") + + if test['result']['success']: + response = test['result']['response'] + # Truncate long responses + if len(response) > 500: + response = response[:500] + "..." + lines.append(f"- **Response**: {response}") + else: + error = test['result']['error'] + if len(error) > 500: + error = error[:500] + "..." + lines.append(f"- **Error**: {error}") + + lines.append("") + + # Write report + with open(output_file, 'w') as f: + f.write('\n'.join(lines)) + + +def main() -> None: # noqa: ASYNC240, ASYNC230 - test script, blocking I/O acceptable + """Test model performance with dynamic configuration variations.""" + parser = argparse.ArgumentParser(description='Test model performance.') + parser.add_argument('--models', type=str, default=None, help='Comma-separated list of models to test') + parser.add_argument('--output', type=str, default='model_performance_report.md', help='Output report file') + parser.add_argument('--user-prompt', type=str, default='what is 5 +3?', help='User prompt for testing') + parser.add_argument('--system-prompt', type=str, default='pirate', help='System prompt for testing') + args = parser.parse_args() + + # Suppress verbose logging + import logging + logging.basicConfig(level=logging.WARNING) + logging.getLogger('genkit').setLevel(logging.WARNING) + logging.getLogger('google').setLevel(logging.WARNING) + + import asyncio + + print("Discovering models...") + all_models = asyncio.run(discover_models()) + + print(f"Discovered models: {list(all_models.keys())}") + + # Filter models if specified + if args.models: + model_names = [m.strip() for m in args.models.split(',')] + models_to_test = {k: v for k, v in all_models.items() if k in model_names} + else: + models_to_test = all_models + + print(f"Found {len(models_to_test)} models to test") + + if not models_to_test: + print("No models to test. Exiting.") + return + + # Get helper script path + script_dir = Path(__file__).parent + helper_script = script_dir / "run_single_model_test.py" + + # Run tests + all_results = [] + for model_name, model_info in models_to_test.items(): + print(f"\nTesting {model_name}...") + + # Parse config schema + config_schema = model_info.get('customOptions', {}) + params = parse_config_schema(config_schema) + + print(f" Found {len(params)} configurable parameters") + + # Generate variations + variations = generate_config_variations(params) + print(f" Generated {len(variations)} config variations") + + # Run tests + for i, config in enumerate(variations, 1): + print(f" Testing variation {i}/{len(variations)}...", end=' ') + # Flush stdout to ensure progress is visible + sys.stdout.flush() + + result = run_model_test( + model_name, + config, + args.user_prompt, + args.system_prompt, + helper_script, + ) + + all_results.append({ + 'model': model_name, + 'config': config, + 'result': result, + }) + + 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100644 --- a/py/samples/sample-test/pyproject.toml +++ b/py/samples/sample-test/pyproject.toml @@ -10,6 +10,14 @@ requires-python = ">=3.10" dependencies = [ "genkit", "genkit-plugin-google-genai", + "genkit-plugin-vertex-ai", + "genkit-plugin-google-cloud", + "genkit-plugin-amazon-bedrock", + "genkit-plugin-anthropic", + "genkit-plugin-deepseek", + "genkit-plugin-xai", + "genkit-plugin-ollama", + "genkit-plugin-mistral", "fastapi", "uvicorn", ] @@ -24,3 +32,11 @@ packages = ["test_model_performance.py", "run_single_model_test.py"] [tool.uv.sources] genkit = { path = "../../packages/genkit", editable = true } genkit-plugin-google-genai = { path = "../../plugins/google-genai", editable = true } +genkit-plugin-vertex-ai = { path = "../../plugins/vertex-ai", editable = true } +genkit-plugin-google-cloud = { path = "../../plugins/google-cloud", editable = true } +genkit-plugin-amazon-bedrock = { path = "../../plugins/amazon-bedrock", editable = true } +genkit-plugin-anthropic = { path = "../../plugins/anthropic", editable = true } +genkit-plugin-deepseek = { path = "../../plugins/deepseek", editable = true } +genkit-plugin-xai = { path = "../../plugins/xai", editable = true } +genkit-plugin-ollama = { path = "../../plugins/ollama", editable = true } +genkit-plugin-mistral = { path = "../../plugins/mistral", editable = true } diff --git a/py/samples/sample-test/server.py b/py/samples/sample-test/server.py index 3dbc3a7b29..e9a2b6934e 100644 --- a/py/samples/sample-test/server.py +++ b/py/samples/sample-test/server.py @@ -7,6 +7,7 @@ from fastapi import FastAPI, HTTPException from fastapi.staticfiles import StaticFiles from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import HTMLResponse from pydantic import BaseModel import asyncio from typing import Any, List, Dict @@ -49,73 +50,122 @@ class TestResult(BaseModel): error: str | None timing: float -# --- Scenarios --- - -SCENARIOS = [ - Scenario( - id="basic_math", - name="Basic Logic & Math", - description="Tests reasoning capabilities with simple math problems.", - system_prompt="You are a helpful math assistant.", - user_prompt="What is 15 * 7? Explain step by step." - ), - Scenario( - id="creative_writing", - name="Creative Writing", - description="Tests creativity and tone adherence.", - system_prompt="You are a pirate bard.", - user_prompt="Write a short poem about the ocean." - ), - Scenario( - id="code_gen", - name="Code Generation", - description="Tests code generation capabilities.", - system_prompt="You are an expert Python developer.", - user_prompt="Write a function to calculate the Fibonacci sequence." - ), - Scenario( - id="image_gen", - name="Image Generation", - description="Tests image generation models (Vertex AI only).", - system_prompt="", - user_prompt="A futuristic cityscape at sunset, neon lights, cyberpunk style." - ) -] +# --- Scenarios Discovery --- + +async def discover_scenarios() -> List[Scenario]: + samples_dir = Path(__file__).parent.parent + scenarios = [] + + if not samples_dir.exists(): + return scenarios + + # Iterate through sample directories + for item in sorted(samples_dir.iterdir()): + if item.is_dir() and not item.name.startswith(('.', '_')): + # Try to read metadata from pyproject.toml + pyproject_path = item / "pyproject.toml" + name = item.name + description = "Genkit sample project" + + if pyproject_path.exists(): + try: + import tomllib # type: ignore + with open(pyproject_path, "rb") as f: + data = tomllib.load(f) + project = data.get("project", {}) + name = project.get("name", name) + description = project.get("description", description) + except Exception: + pass + + scenarios.append(Scenario( + id=item.name, + name=name, + description=description, + system_prompt="You are a pirate.", + user_prompt="what is 5 + 3?" + )) + + return scenarios + +# We'll fetch SCENARIOS dynamically in the endpoint # --- Endpoints --- +from fastapi.responses import HTMLResponse, JSONResponse + +@app.get("/", response_class=HTMLResponse) +async def root(): + logging.info("Root path accessed") + static_dir = Path(__file__).parent / "static" + index_path = static_dir / "index.html" + if not index_path.exists(): + logging.error(f"index.html not found at {index_path}") + return HTMLResponse(content="index.html not found", status_code=404) + return HTMLResponse(content=index_path.read_text()) + +@app.get("/health") +async def health_check(): + return {"status": "ok", "message": "Server is running"} + @app.get("/api/scenarios", response_model=List[Scenario]) async def get_scenarios(): - return SCENARIOS + return await discover_scenarios() @app.get("/api/models") -async def get_models(scenario: str | None = None): +async def get_models(sample: str | None = None): + """Get models available for a specific sample. + + Args: + sample: Sample name to discover models for (e.g., 'google-genai-hello') + + Returns: + List of models with numbering, info, and parsed parameters + """ try: - models = await discover_models() + # Import the discovery function + from test_model_performance import discover_models_for_sample, parse_config_schema + + if sample: + logging.info(f"Discovering models for sample: {sample}") + models = await discover_models_for_sample(sample) + else: + logging.info("Discovering all models") + from test_model_performance import discover_models + models = await discover_models() - # Simple filtering logic based on scenario + logging.info(f"Found {len(models)} models: {list(models.keys())}") + + # Build numbered model list filtered_models = [] - for name, info in models.items(): - # For specific scenarios, we might want to filter models if possible - # But currently we don't have enough metadata to distinguish text vs image clearly - # except by name convention or inspecting supported actions deeper. - # For now, we return all models and let the user choose. - + for idx, (name, info) in enumerate(models.items(), start=1): + # Validate model name + if not name or not isinstance(name, str): + logging.warning(f"Invalid model name at index {idx}: {name}") + continue + # Extract config schema for UI - config_schema = info.get('customOptions', {}) + config_schema = info.get('customOptions', {}) if isinstance(info, dict) else {} params = parse_config_schema(config_schema) - filtered_models.append({ + model_entry = { + "number": idx, "name": name, - "info": info, + "display_name": f"{idx}. {name}", + "info": info if isinstance(info, dict) else {}, "params": params - }) + } + logging.debug(f"Model entry: {model_entry['display_name']}") + filtered_models.append(model_entry) + + logging.info(f"Returning {len(filtered_models)} filtered models") return filtered_models except Exception as e: - logging.error(f"Error discovering models: {e}") + logging.error(f"Error discovering models: {e}", exc_info=True) raise HTTPException(status_code=500, detail=str(e)) + @app.post("/api/run", response_model=TestResult) async def run_test(request: TestRequest): try: @@ -143,6 +193,88 @@ async def run_test(request: TestRequest): logging.error(f"Error running test: {e}") raise HTTPException(status_code=500, detail=str(e)) + +class ComprehensiveTestRequest(BaseModel): + sample: str + model: str + user_prompt: str + system_prompt: str + + +class ComprehensiveTestResult(BaseModel): + total_tests: int + passed: int + failed: int + results: List[Dict[str, Any]] + + +@app.post("/api/run-comprehensive", response_model=ComprehensiveTestResult) +async def run_comprehensive_test(request: ComprehensiveTestRequest): + """Run comprehensive test with all parameter variations. + + Tests all config parameter variations: + 1. First test with all defaults ({}) + 2. Then vary one parameter at a time + """ + try: + from test_model_performance import ( + discover_models_for_sample, + parse_config_schema, + generate_config_variations, + run_model_test + ) + + # Get model info + models = await discover_models_for_sample(request.sample) + if request.model not in models: + raise HTTPException(status_code=404, detail=f"Model {request.model} not found in sample {request.sample}") + + model_info = models[request.model] + config_schema = model_info.get('customOptions', {}) + params = parse_config_schema(config_schema) + + # Generate variations + variations = generate_config_variations(params) + + # Run all tests + script_path = Path(__file__).parent / "run_single_model_test.py" + all_results = [] + + for config in variations: + result = await asyncio.to_thread( + run_model_test, + request.model, + config, + request.user_prompt, + request.system_prompt, + script_path + ) + + all_results.append({ + "config": config, + "success": result.get("success", False), + "response": result.get("response"), + "error": result.get("error"), + "timing": result.get("timing", 0.0) + }) + + # Calculate stats + passed = sum(1 for r in all_results if r["success"]) + failed = len(all_results) - passed + + return ComprehensiveTestResult( + total_tests=len(all_results), + passed=passed, + failed=failed, + results=all_results + ) + + except HTTPException: + raise + except Exception as e: + logging.error(f"Error running comprehensive test: {e}") + raise HTTPException(status_code=500, detail=str(e)) + # Wrapper to run async run_model_test inside the thread async def run_wrapper(model, config, user_prompt, system_prompt, script_path): # run_model_test in test_model_performance is synchronous (uses subprocess.run) @@ -158,10 +290,10 @@ async def run_wrapper(model, config, user_prompt, system_prompt, script_path): script_path ) - -# Mount static files (Frontend) -app.mount("/", StaticFiles(directory="samples/sample-test/static", html=True), name="static") +# Mount static files (CSS, JS, etc.) under /static/ +STATIC_DIR = Path(__file__).parent / "static" +app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static") if __name__ == "__main__": import uvicorn - uvicorn.run(app, host="0.0.0.0", port=8000) + uvicorn.run(app, host="127.0.0.1", port=8000) diff --git a/py/samples/sample-test/static/index.html b/py/samples/sample-test/static/index.html index 8d59787d0e..a165a8436c 100644 --- a/py/samples/sample-test/static/index.html +++ b/py/samples/sample-test/static/index.html @@ -1,5 +1,6 @@ + @@ -7,28 +8,19 @@ - + +
- - -
-

Select a Sample

+
+
G
+

Genkit Model Config Test

+
+

Model Performance Testing

0 Models
@@ -38,17 +30,21 @@

Select a Sample

-

Model Selection

+

Test Configuration

+ +
+ + +
+
- -
- -
@@ -63,6 +59,10 @@

Model Selection

+ +
@@ -75,7 +75,7 @@

Results

Fail: 0
- +
Select a model and run test to see results. @@ -85,6 +85,7 @@

Results

- + - + + \ No newline at end of file diff --git a/py/samples/sample-test/static/script.js b/py/samples/sample-test/static/script.js index 007384c00f..ed22bbe696 100644 --- a/py/samples/sample-test/static/script.js +++ b/py/samples/sample-test/static/script.js @@ -11,7 +11,7 @@ let currentState = { // DOM Elements const els = { - samplesList: document.getElementById('samples-list'), + sampleSelect: document.getElementById('sample-select'), currentScenarioTitle: document.getElementById('current-scenario-title'), modelCount: document.getElementById('model-count'), modelSelect: document.getElementById('model-select'), @@ -30,15 +30,15 @@ async function init() { try { const scenarios = await fetchAPI('/scenarios'); currentState.scenarios = scenarios; - renderScenariosList(); + renderScenariosDropdown(); - // Select first by default - if (scenarios.length > 0) { - selectScenario(scenarios[0].id); - } + // Don't auto-select - let user choose + // Leave model dropdown empty until sample is selected + els.modelSelect.innerHTML = ''; + els.modelSelect.disabled = true; } catch (e) { console.error('Failed to init:', e); - els.samplesList.innerHTML = ``; + if (els.sampleSelect) els.sampleSelect.innerHTML = ``; } } @@ -47,11 +47,7 @@ async function selectScenario(id) { currentState.selectedScenarioId = id; const scenario = currentState.scenarios.find(s => s.id === id); - // Update UI - document.querySelectorAll('.nav-item').forEach(el => { - el.classList.toggle('active', el.dataset.id === id); - }); - + // Update UI title els.currentScenarioTitle.textContent = scenario.name; els.systemPrompt.value = scenario.system_prompt; els.userPrompt.value = scenario.user_prompt; @@ -64,14 +60,26 @@ async function loadModels(scenarioId) { els.modelSelect.disabled = true; try { - const models = await fetchAPI(`/models?scenario=${scenarioId}`); + // Pass sample parameter to get sample-specific models + const models = await fetchAPI(`/models?sample=${scenarioId}`); + + // Debug logging + console.log('Received models:', models); + console.log('First model:', models[0]); + currentState.models = models; els.modelCount.textContent = `${models.length} Models`; - // Render Select + // Render Select with numbered display names els.modelSelect.innerHTML = models.length ? - models.map(m => ``).join('') : + models.map(m => { + // Fallback if display_name or name is undefined + const displayName = m.display_name || m.name || 'Unknown Model'; + const modelName = m.name || ''; + console.log('Rendering model:', modelName, displayName); + return ``; + }).join('') : ''; els.modelSelect.disabled = false; @@ -80,7 +88,9 @@ async function loadModels(scenarioId) { if (models.length > 0) { handleModelChange(models[0].name); } else { - els.paramConfig.innerHTML = ''; + if (els.paramConfig) { + els.paramConfig.innerHTML = ''; + } } } catch (e) { console.error('Failed to load models:', e); @@ -91,50 +101,6 @@ async function loadModels(scenarioId) { function handleModelChange(modelName) { const model = currentState.models.find(m => m.name === modelName); currentState.selectedModel = model; - - renderParams(model.params); -} - -function renderParams(params) { - if (!params || Object.keys(params).length === 0) { - els.paramConfig.innerHTML = '
No configurable parameters
'; - return; - } - - let html = '

Configuration

'; - - for (const [key, config] of Object.entries(params)) { - html += `
- `; - - if (config.enum) { - html += ``; - } else if (config.type === 'boolean') { - html += ``; - } else if (config.type === 'number') { - const min = config.minimum !== undefined ? `min="${config.minimum}"` : ''; - const max = config.maximum !== undefined ? `max="${config.maximum}"` : ''; - const step = (config.maximum - config.minimum) <= 1 ? '0.1' : '1'; - const val = config.default !== undefined ? config.default : - (config.minimum !== undefined ? config.minimum : 0); - - html += ``; - } else { - // Default text - html += ``; - } - - html += `
`; - } - - els.paramConfig.innerHTML = html; } async function runTest() { @@ -143,18 +109,8 @@ async function runTest() { els.runBtn.disabled = true; els.runBtn.textContent = 'Running...'; - // Collect Config + // Send empty config as we removed the inputs const config = {}; - document.querySelectorAll('.config-input').forEach(input => { - const key = input.dataset.key; - const type = input.dataset.type; - let value = input.value; - - if (type === 'number') value = parseFloat(value); - if (type === 'boolean') value = value === 'true'; - - config[key] = value; - }); try { const result = await fetchAPI('/run', 'POST', { @@ -178,6 +134,81 @@ async function runTest() { } } +async function runComprehensiveTest() { + if (!currentState.selectedModel || !currentState.selectedScenarioId) return; + + const comprehensiveBtn = document.getElementById('run-comprehensive-btn'); + comprehensiveBtn.disabled = true; + comprehensiveBtn.textContent = 'Running comprehensive test...'; + + // Clear previous results + els.resultsList.innerHTML = '
Running comprehensive test...
'; + + try { + const result = await fetchAPI('/run-comprehensive', 'POST', { + sample: currentState.selectedScenarioId, + model: currentState.selectedModel.name, + user_prompt: els.userPrompt.value, + system_prompt: els.systemPrompt.value + }); + + // Clear loading message + els.resultsList.innerHTML = ''; + + // Add summary card + const summaryCard = document.createElement('div'); + summaryCard.className = 'result-card summary'; + summaryCard.innerHTML = ` +

Comprehensive Test Summary

+
+
Total Tests: ${result.total_tests}
+
Passed: ${result.passed}
+
Failed: ${result.failed}
+
Success Rate: ${((result.passed / result.total_tests) * 100).toFixed(1)}%
+
+ `; + els.resultsList.appendChild(summaryCard); + + // Add individual test results + result.results.forEach((testResult, idx) => { + const card = document.createElement('div'); + card.className = `result-card ${testResult.success ? 'success' : 'error'}`; + + const configStr = JSON.stringify(testResult.config); + const configDisplay = configStr === '{}' ? 'Default (all parameters at default)' : configStr; + + card.innerHTML = ` +
+ Test ${idx + 1} + Config: ${escapeHtml(configDisplay)} + ${testResult.timing}s +
+
+ ${testResult.success ? escapeHtml(testResult.response || 'No response') : escapeHtml(testResult.error || 'Unknown error')} +
+ `; + + els.resultsList.appendChild(card); + }); + + // Update global stats + currentState.stats.pass += result.passed; + currentState.stats.fail += result.failed; + els.passCount.textContent = currentState.stats.pass; + els.failCount.textContent = currentState.stats.fail; + els.statsBar.classList.remove('hidden'); + + } catch (e) { + console.error(e); + els.resultsList.innerHTML = `
+
Error running comprehensive test: ${escapeHtml(e.message)}
+
`; + } finally { + comprehensiveBtn.disabled = false; + comprehensiveBtn.textContent = 'Run Comprehensive Test'; + } +} + // Helpers async function fetchAPI(endpoint, method = 'GET', body = null) { const options = { @@ -193,12 +224,12 @@ async function fetchAPI(endpoint, method = 'GET', body = null) { return await res.json(); } -function renderScenariosList() { - els.samplesList.innerHTML = currentState.scenarios.map(s => - `` - ).join(''); +function renderScenariosDropdown() { + const options = ['']; + options.push(...currentState.scenarios.map(s => + `` + )); + els.sampleSelect.innerHTML = options.join(''); } function addResultCard(result) { @@ -239,8 +270,10 @@ function escapeHtml(text) { } // Event Listeners +els.sampleSelect.addEventListener('change', (e) => selectScenario(e.target.value)); els.modelSelect.addEventListener('change', (e) => handleModelChange(e.target.value)); els.runBtn.addEventListener('click', runTest); +document.getElementById('run-comprehensive-btn').addEventListener('click', runComprehensiveTest); // Start init(); diff --git a/py/samples/sample-test/static/style.css b/py/samples/sample-test/static/style.css index 606376e9fe..12b2451454 100644 --- a/py/samples/sample-test/static/style.css +++ b/py/samples/sample-test/static/style.css @@ -1,14 +1,33 @@ :root { - --bg-dark: #0f1115; - --bg-panel: #181b21; - --bg-card: #20242c; - --border: #2d323b; - --text-primary: #e0e4eb; - --text-secondary: #949ba6; - --accent: #6e5bf1; - --accent-hover: #5a4bd4; - --success: #22c55e; - --error: #ef4444; + /* Safari-style Light Theme */ + --bg-app: #F5F5F7; + /* Light gray background */ + --bg-header: rgba(255, 255, 255, 0.72); + /* Glassy white */ + --bg-card: #FFFFFF; + /* Pure white cards */ + --bg-input: #E8E8ED; + /* Light gray inputs */ + + --text-primary: #1D1D1F; + /* Almost black */ + --text-secondary: #86868B; + /* Gray text */ + + --accent: #0071E3; + /* Apple Blue */ + --accent-hover: #0077ED; + + --border: rgba(0, 0, 0, 0.1); + /* Subtle border */ + --shadow-card: 0 4px 24px rgba(0, 0, 0, 0.04); + + --radius-card: 18px; + --radius-input: 10px; + --radius-btn: 10px; + + --success: #34C759; + --error: #FF3B30; } * { @@ -18,284 +37,343 @@ } body { - font-family: 'Inter', sans-serif; - background-color: var(--bg-dark); + font-family: -apple-system, BlinkMacSystemFont, "SF Pro Text", "Segoe UI", Roboto, Helvetica, Arial, sans-serif; + background-color: var(--bg-app); color: var(--text-primary); line-height: 1.5; height: 100vh; overflow: hidden; + -webkit-font-smoothing: antialiased; } .app-container { - display: grid; - grid-template-columns: 280px 1fr; + display: flex; + flex-direction: column; height: 100vh; } -/* Sidebar */ -.sidebar { - background-color: var(--bg-panel); - border-right: 1px solid var(--border); - padding: 1.5rem; +/* Header / Top Bar */ +.top-bar { + height: 60px; + padding: 0 24px; display: flex; - flex-direction: column; + align-items: center; + justify-content: space-between; + background-color: var(--bg-header); + backdrop-filter: blur(20px); + -webkit-backdrop-filter: blur(20px); + border-bottom: 1px solid var(--border); + position: sticky; + top: 0; + z-index: 100; } .brand { display: flex; align-items: center; - gap: 0.75rem; - margin-bottom: 2.5rem; + gap: 12px; } .logo-icon { - width: 32px; - height: 32px; - background: linear-gradient(135deg, var(--accent), #a78bfa); + width: 28px; + height: 28px; + background: linear-gradient(135deg, var(--accent), #42a1ff); border-radius: 8px; display: flex; align-items: center; justify-content: center; font-weight: 700; - font-size: 1.2rem; + font-size: 14px; color: white; + box-shadow: 0 2px 8px rgba(0, 113, 227, 0.3); } .brand h1 { - font-size: 1.25rem; + font-size: 17px; font-weight: 600; + color: var(--text-primary); } -.section-title { - font-size: 0.75rem; - text-transform: uppercase; +#current-scenario-title { + font-size: 15px; + font-weight: 500; color: var(--text-secondary); - letter-spacing: 0.05em; - margin-bottom: 1rem; - font-weight: 600; -} - -.nav-list { - display: flex; - flex-direction: column; - gap: 0.5rem; } -.nav-item { - padding: 0.75rem 1rem; - border-radius: 8px; - cursor: pointer; - transition: all 0.2s ease; - color: var(--text-secondary); - font-size: 0.9rem; +.badge { + background-color: rgba(0, 0, 0, 0.05); + padding: 4px 12px; + border-radius: 20px; + font-size: 12px; font-weight: 500; + color: var(--text-secondary); } -.nav-item:hover { - color: var(--text-primary); - background-color: rgba(255,255,255,0.05); -} - -.nav-item.active { - background-color: rgba(110, 91, 241, 0.15); - color: var(--accent); -} - -/* Main Content */ +/* Main Layout */ .main-content { - display: flex; - flex-direction: column; - height: 100vh; + flex: 1; overflow: hidden; + position: relative; } -.top-bar { - height: 70px; - border-bottom: 1px solid var(--border); - padding: 0 2rem; - display: flex; - align-items: center; - justify-content: space-between; - background-color: rgba(15, 17, 21, 0.8); - backdrop-filter: blur(12px); -} - -.top-bar h2 { - font-size: 1.1rem; - font-weight: 600; -} - -.badge { - background-color: var(--bg-card); - border: 1px solid var(--border); - padding: 0.25rem 0.75rem; - border-radius: 20px; - font-size: 0.8rem; - color: var(--text-secondary); -} - -/* Grid Layout */ .content-grid { - flex: 1; display: grid; - grid-template-columns: 400px 1fr; - gap: 2rem; - padding: 2rem; - overflow: hidden; + grid-template-columns: 480px 1fr; + /* Fixed sidebar width */ + gap: 24px; + padding: 24px; + height: 100%; + max-width: 1600px; + margin: 0 auto; } /* Panels */ .config-panel { overflow-y: auto; + padding-bottom: 24px; } .results-panel { + background-color: var(--bg-card); + border-radius: var(--radius-card); + box-shadow: var(--shadow-card); display: flex; flex-direction: column; - height: 100%; overflow: hidden; - background-color: var(--bg-card); + height: 100%; border: 1px solid var(--border); - border-radius: 12px; } /* Cards */ .card { background-color: var(--bg-card); + border-radius: var(--radius-card); + padding: 24px; + box-shadow: var(--shadow-card); border: 1px solid var(--border); - border-radius: 12px; - padding: 1.5rem; + margin-bottom: 24px; } -.card h3 { - margin-bottom: 1.5rem; - font-size: 1rem; +.card h3, +.results-header h3 { + font-size: 15px; font-weight: 600; + color: var(--text-secondary); + text-transform: uppercase; + letter-spacing: 0.5px; + margin-bottom: 16px; } /* Forms */ .form-group { - margin-bottom: 1.25rem; + margin-bottom: 20px; } .form-group label { display: block; - margin-bottom: 0.5rem; - font-size: 0.85rem; - color: var(--text-secondary); + margin-bottom: 8px; + font-size: 13px; + font-weight: 500; + color: var(--text-primary); } -select, textarea, input { +select, +textarea, +input { width: 100%; - background-color: var(--bg-dark); - border: 1px solid var(--border); + background-color: var(--bg-input); + border: 1px solid transparent; color: var(--text-primary); - padding: 0.75rem; - border-radius: 8px; + padding: 10px 12px; + border-radius: var(--radius-input); font-family: inherit; - font-size: 0.9rem; - transition: border-color 0.2s; + font-size: 15px; + transition: all 0.2s ease; outline: none; } -select:focus, textarea:focus, input:focus { +select:hover, +textarea:hover, +input:hover { + background-color: #E0E0E5; +} + +select:focus, +textarea:focus, +input:focus { + background-color: #FFFFFF; border-color: var(--accent); + box-shadow: 0 0 0 3px rgba(0, 113, 227, 0.15); } textarea { resize: vertical; + min-height: 80px; } +/* Custom Select Arrow */ +select { + appearance: none; + -webkit-appearance: none; + background-image: url("data:image/svg+xml;charset=UTF-8,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='none' stroke='%2386868B' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'%3e%3cpolyline points='6 9 12 15 18 9'%3e%3c/polyline%3e%3c/svg%3e"); + background-repeat: no-repeat; + background-position: right 12px center; + background-size: 16px; + padding-right: 40px; +} + +/* Buttons */ .btn-primary { width: 100%; background-color: var(--accent); color: white; border: none; - padding: 0.85rem; - border-radius: 8px; + padding: 12px; + border-radius: var(--radius-btn); + font-size: 15px; font-weight: 600; cursor: pointer; - transition: background-color 0.2s; - margin-top: 1rem; + transition: all 0.2s ease; + box-shadow: 0 2px 6px rgba(0, 113, 227, 0.2); + margin-top: 8px; } .btn-primary:hover { background-color: var(--accent-hover); + transform: scale(1.01); } -.btn-primary:disabled { - opacity: 0.6; - cursor: wait; +.btn-primary:active { + transform: scale(0.99); } -/* Results */ +.btn-secondary { + width: 100%; + background-color: rgba(0, 113, 227, 0.08); + /* Hint of blue */ + color: var(--accent); + border: none; + padding: 12px; + border-radius: var(--radius-btn); + font-size: 15px; + font-weight: 600; + cursor: pointer; + transition: all 0.2s ease; + margin-top: 12px; +} + +.btn-secondary:hover { + background-color: rgba(0, 113, 227, 0.15); +} + +/* Results Panel Styling */ .results-header { - padding: 1.5rem; + padding: 20px 24px; border-bottom: 1px solid var(--border); display: flex; justify-content: space-between; align-items: center; + background-color: rgba(255, 255, 255, 0.8); + backdrop-filter: blur(10px); } .results-list { flex: 1; overflow-y: auto; - padding: 1.5rem; + padding: 24px; display: flex; flex-direction: column; - gap: 1rem; -} - -.empty-state { - text-align: center; - color: var(--text-secondary); - margin-top: 3rem; + gap: 16px; } +/* Result Cards - Cleaner Look */ .result-card { - background-color: var(--bg-panel); + background-color: white; + border-radius: 12px; + padding: 20px; border: 1px solid var(--border); - border-radius: 8px; - padding: 1rem; - border-left: 4px solid var(--border); -} - -.result-card.success { - border-left-color: var(--success); + box-shadow: 0 2px 8px rgba(0, 0, 0, 0.02); + transition: transform 0.2s; } -.result-card.error { - border-left-color: var(--error); +.result-card:hover { + transform: translateY(-1px); + box-shadow: 0 4px 12px rgba(0, 0, 0, 0.06); } -.result-meta { +.result-header { display: flex; justify-content: space-between; - margin-bottom: 0.75rem; - font-size: 0.85rem; - color: var(--text-secondary); + align-items: center; + margin-bottom: 12px; +} + +.model-name { + font-weight: 600; + font-size: 16px; + color: var(--text-primary); +} + +/* Status Badges */ +.status { + font-size: 12px; + font-weight: 600; + padding: 4px 10px; + border-radius: 20px; + text-transform: uppercase; + letter-spacing: 0.5px; } -.result-content { - background-color: var(--bg-dark); - padding: 0.75rem; - border-radius: 6px; - font-family: monospace; - font-size: 0.9rem; +.status.success { + background-color: rgba(52, 199, 89, 0.1); + color: var(--success); +} + +.status.failure { + background-color: rgba(255, 59, 48, 0.1); + color: var(--error); +} + +/* Output Text */ +.output-text { + font-family: 'SF Mono', 'Menlo', monospace; + font-size: 13px; + background-color: #F5F5F7; + padding: 16px; + border-radius: 10px; + color: #424245; white-space: pre-wrap; - max-height: 200px; - overflow-y: auto; + border: 1px solid rgba(0, 0, 0, 0.05); } -.stat-item { - font-size: 0.9rem; - font-weight: 500; - margin-left: 1rem; +.error-text { + color: var(--error); + background-color: rgba(255, 59, 48, 0.05); } -.stat-item.success { color: var(--success); } -.stat-item.error { color: var(--error); } +/* Empty State */ +.empty-state { + text-align: center; + color: var(--text-secondary); + margin-top: 60px; + font-size: 16px; +} + +/* Scrollbars */ +::-webkit-scrollbar { + width: 8px; + height: 8px; +} -.hidden { - display: none; +::-webkit-scrollbar-track { + background: transparent; } + +::-webkit-scrollbar-thumb { + background: #D1D1D6; + border-radius: 4px; +} + +::-webkit-scrollbar-thumb:hover { + background: #8E8E93; +} \ No newline at end of file diff --git a/py/samples/sample-test/test_model_performance.py b/py/samples/sample-test/test_model_performance.py index 6df832b2e4..743caf7ebe 100644 --- a/py/samples/sample-test/test_model_performance.py +++ b/py/samples/sample-test/test_model_performance.py @@ -79,6 +79,159 @@ async def discover_models() -> dict[str, Any]: return model_info +async def discover_models_for_sample(sample_name: str) -> dict[str, Any]: + """Discover models used by a specific sample. + + Args: + sample_name: Name of the sample directory (e.g., 'google-genai-hello') + + Returns: + Dict mapping model names to model info for models used by this sample + """ + from pathlib import Path + import importlib.util + import sys + import logging + + logger = logging.getLogger(__name__) + + # Find the sample directory + samples_dir = Path(__file__).parent.parent + sample_dir = samples_dir / sample_name + + if not sample_dir.exists(): + logger.warning(f"Sample directory not found: {sample_dir}") + return {} + + # Look for main.py in common locations + main_file = None + search_paths = [ + sample_dir / 'main.py', + sample_dir / 'src' / 'main.py', # Some samples have src/ subdirectory + sample_dir / 'server.py', + sample_dir / 'app.py', + ] + + for candidate_path in search_paths: + if candidate_path.exists(): + main_file = candidate_path + break + + if not main_file: + logger.warning(f"No main file found for sample {sample_name}") + # Fall back to all models + return await discover_models() + + try: + # Mock input() to prevent blocking on API key prompts + import builtins + import os + original_input = builtins.input + builtins.input = lambda prompt="": "" # Return empty string for all inputs + + # Mock common API key environment variables if not set + env_vars_to_mock = { + 'ANTHROPIC_API_KEY': 'mock-key', + 'OPENAI_API_KEY': 'mock-key', + 'GOOGLE_API_KEY': 'mock-key', + 'GEMINI_API_KEY': 'mock-key', + } + original_env_vars = {} + for key, value in env_vars_to_mock.items(): + if key not in os.environ: + original_env_vars[key] = None + os.environ[key] = value + else: + original_env_vars[key] = os.environ[key] + + try: + # Dynamically import the sample module + module_name = f"sample_{sample_name.replace('-', '_')}" + spec = importlib.util.spec_from_file_location(module_name, main_file) + if spec is None or spec.loader is None: + logger.warning(f"Could not load spec for {main_file}") + return await discover_models() + + module = importlib.util.module_from_spec(spec) + + # Add to sys.modules before executing + old_module = sys.modules.get(module_name) + sys.modules[module_name] = module + + try: + # Execute the module to initialize Genkit + logger.info(f"Loading sample module from {main_file}") + spec.loader.exec_module(module) + + # Get the Genkit instance if available + if hasattr(module, 'ai'): + ai = module.ai + registry = ai.registry + + # Get all model actions + from genkit.core.action import ActionKind + actions = await registry.list_actions(allowed_kinds=[ActionKind.MODEL]) + + model_info = {} + for meta in actions: + info = meta.metadata.get('model', {}) + model_info[meta.name] = info + + logger.info(f"Discovered {len(model_info)} models for sample {sample_name}: {list(model_info.keys())}") + return model_info + else: + logger.warning(f"Sample {sample_name} has no 'ai' attribute") + + finally: + # Restore old module if it existed + if old_module is not None: + sys.modules[module_name] = old_module + elif module_name in sys.modules: + del sys.modules[module_name] + + finally: + # Restore original input function + builtins.input = original_input + + # Restore original environment variables + for key, original_value in original_env_vars.items(): + if original_value is None: + os.environ.pop(key, None) + else: + os.environ[key] = original_value + + except ModuleNotFoundError as e: + error_msg = str(e) + logger.warning(f"Sample {sample_name} missing module: {e}") + + # Heuristic: If it's a Google sample, falling back to default/global models (Gemini) is usually safe/helpful + is_google_sample = 'google' in sample_name or 'gemini' in sample_name or 'vertex' in sample_name + + if is_google_sample: + logger.info(f"Google sample {sample_name} failed to load, falling back to default models") + return await discover_models() + + # For non-Google samples (e.g. Bedrock), strict failure is better than showing Gemini + if 'genkit.plugins.' in error_msg: + return {} + + # For other import errors, return empty + return {} + + except Exception as e: + logger.error(f"Failed to load sample {sample_name}: {e}", exc_info=True) + + # Checking sample name again for fallback + if 'google' in sample_name or 'gemini' in sample_name or 'vertex' in sample_name: + logger.info(f"Google sample {sample_name} failed, falling back to default models") + return await discover_models() + + return {} # Return empty for other failures + + + + + def parse_config_schema(schema: dict[str, Any]) -> dict[str, dict[str, Any]]: """Parse JSON schema to extract configuration parameters. @@ -108,6 +261,10 @@ def parse_config_schema(schema: dict[str, Any]) -> dict[str, dict[str, Any]]: def generate_config_variations(params: dict[str, dict[str, Any]]) -> list[dict[str, Any]]: """Generate configuration variations for testing. + Strategy: + 1. First test: All parameters at default (empty config {}) + 2. Subsequent tests: Vary ONE parameter at a time, keeping others at default + Args: params: Parameter schema info from parse_config_schema @@ -116,61 +273,49 @@ def generate_config_variations(params: dict[str, dict[str, Any]]) -> list[dict[s """ variations = [] - # Start with baseline (all defaults or empty) - baseline = {} - variations.append(baseline.copy()) + # Test 1: Always start with all defaults (empty config) + variations.append({}) - # Generate variations for each parameter + # Subsequent tests: Vary one parameter at a time for param_name, param_info in params.items(): param_type = param_info['type'] if param_type == 'number': - # Numeric parameters + # Numeric parameters: test min, midpoint, max individually minimum = param_info.get('minimum', 0.0) maximum = param_info.get('maximum', 1.0) - default = param_info.get('default') - # Test min, max, midpoint - test_values = [minimum, maximum] + # Test minimum + variations.append({param_name: minimum}) + + # Test midpoint (only if range exists) if minimum < maximum: midpoint = (minimum + maximum) / 2 - test_values.append(midpoint) - if default is not None and default not in test_values: - test_values.append(default) + variations.append({param_name: midpoint}) - for value in test_values: - config = baseline.copy() - config[param_name] = value - variations.append(config) + # Test maximum + variations.append({param_name: maximum}) elif param_type == 'boolean': - # Boolean parameters - for value in [True, False]: - config = baseline.copy() - config[param_name] = value - variations.append(config) + # Boolean parameters: test true, then false + variations.append({param_name: True}) + variations.append({param_name: False}) elif param_type == 'string': - # String parameters + # String parameters: test each enum value individually enum_values = param_info.get('enum') if enum_values: for value in enum_values: - config = baseline.copy() - config[param_name] = value - variations.append(config) + variations.append({param_name: value}) elif param_type == 'array': - # Array parameters - config = baseline.copy() - config[param_name] = [] - variations.append(config) + # Array parameters: test empty array, then sample value + variations.append({param_name: []}) - # Add sample array value + # Add sample array value if items are strings items_schema = param_info.get('items', {}) if items_schema.get('type') == 'string': - config = baseline.copy() - config[param_name] = ["STOP"] - variations.append(config) + variations.append({param_name: ["STOP"]}) return variations diff --git a/py/samples/sample-test/uv.lock b/py/samples/sample-test/uv.lock index e5587c5072..b390bdd183 100644 --- a/py/samples/sample-test/uv.lock +++ b/py/samples/sample-test/uv.lock @@ -17,6 +17,148 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/bc/8a/340a1555ae33d7354dbca4faa54948d76d89a27ceef032c8c3bc661d003e/aiofiles-25.1.0-py3-none-any.whl", hash = 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8b3f305d311ceff4143439f8fba976918f41fa89 Mon Sep 17 00:00:00 2001 From: Mengqin Shen Date: Fri, 6 Feb 2026 21:34:09 -0800 Subject: [PATCH 3/3] fix(py): extend comprehensive test metric --- py/pyproject.toml | 1 - py/samples/sample-test/pyproject.toml | 3 + py/samples/sample-test/server.py | 6 +- py/samples/sample-test/static/script.js | 3 + .../sample-test/test_model_performance.py | 93 +++-- py/samples/sample-test/uv.lock | 377 ++++++++++++++++++ 6 files changed, 455 insertions(+), 28 deletions(-) diff --git a/py/pyproject.toml b/py/pyproject.toml index d3292c34c1..6d718aef8d 100644 --- a/py/pyproject.toml +++ b/py/pyproject.toml @@ -190,7 +190,6 @@ genkit-plugin-vertex-ai = { workspace = true } genkit-plugin-xai = { workspace = true } [tool.uv.workspace] -exclude = ["*/shared", "testapps/*", "samples/sample-test"] exclude = ["*/shared", "samples/sample-test", "testapps/*"] members = ["packages/*", "plugins/*", "samples/*"] diff --git a/py/samples/sample-test/pyproject.toml b/py/samples/sample-test/pyproject.toml index 167ee20bd8..fd55850ca7 100644 --- a/py/samples/sample-test/pyproject.toml +++ b/py/samples/sample-test/pyproject.toml @@ -18,8 +18,10 @@ dependencies = [ "genkit-plugin-xai", "genkit-plugin-ollama", "genkit-plugin-mistral", + "genkit-plugin-evaluators", "fastapi", "uvicorn", + "datamodel-code-generator", ] [build-system] @@ -40,3 +42,4 @@ genkit-plugin-deepseek = { path = "../../plugins/deepseek", editable = true } genkit-plugin-xai = { path = "../../plugins/xai", editable = true } genkit-plugin-ollama = { path = "../../plugins/ollama", editable = true } genkit-plugin-mistral = { path = "../../plugins/mistral", editable = true } +genkit-plugin-evaluators = { path = "../../plugins/evaluators", editable = true } diff --git a/py/samples/sample-test/server.py b/py/samples/sample-test/server.py index e9a2b6934e..29b69b2fb5 100644 --- a/py/samples/sample-test/server.py +++ b/py/samples/sample-test/server.py @@ -272,8 +272,10 @@ async def run_comprehensive_test(request: ComprehensiveTestRequest): except HTTPException: raise except Exception as e: - logging.error(f"Error running comprehensive test: {e}") - raise HTTPException(status_code=500, detail=str(e)) + logging.error(f"Error running comprehensive test: {e}", exc_info=True) + import traceback + traceback.print_exc() + raise HTTPException(status_code=500, detail=f"Internal Server Error: {str(e)}") # Wrapper to run async run_model_test inside the thread async def run_wrapper(model, config, user_prompt, system_prompt, script_path): diff --git a/py/samples/sample-test/static/script.js b/py/samples/sample-test/static/script.js index ed22bbe696..b0f14cff85 100644 --- a/py/samples/sample-test/static/script.js +++ b/py/samples/sample-test/static/script.js @@ -109,6 +109,9 @@ async function runTest() { els.runBtn.disabled = true; els.runBtn.textContent = 'Running...'; + // Clear previous results (including comprehensive test summary) + els.resultsList.innerHTML = ''; + // Send empty config as we removed the inputs const config = {}; diff --git a/py/samples/sample-test/test_model_performance.py b/py/samples/sample-test/test_model_performance.py index 743caf7ebe..9637e70817 100644 --- a/py/samples/sample-test/test_model_performance.py +++ b/py/samples/sample-test/test_model_performance.py @@ -246,24 +246,52 @@ def parse_config_schema(schema: dict[str, Any]) -> dict[str, dict[str, Any]]: params = {} for param_name, param_schema in schema['properties'].items(): + # Handle 'anyOf' schemas (common in Gemini for nullable types) + # e.g., "maxOutputTokens": { "anyOf": [{ "type": "integer" }, { "type": "null" }] } + eff_schema = param_schema + if 'type' not in eff_schema and 'anyOf' in eff_schema: + for option in eff_schema['anyOf']: + if option.get('type') and option.get('type') != 'null': + # Found the real type definition + eff_schema = option + break + + # If still no type, skip or look deeper (but simple type extraction is usually enough) + # Some fields like 'stopSequences' might be array of strings, so we need to check items too. + + param_type = eff_schema.get('type') + if not param_type and 'items' in eff_schema: + # Array type might be inferred if items is present, or check if type is 'array' + pass + params[param_name] = { - 'type': param_schema.get('type'), - 'minimum': param_schema.get('minimum'), - 'maximum': param_schema.get('maximum'), - 'default': param_schema.get('default'), - 'enum': param_schema.get('enum'), - 'items': param_schema.get('items'), + 'type': param_type, + 'minimum': eff_schema.get('minimum'), + 'maximum': eff_schema.get('maximum'), + 'default': param_schema.get('default'), # Default usually at top level + 'enum': eff_schema.get('enum'), + 'items': eff_schema.get('items'), } return params + return variations + + def generate_config_variations(params: dict[str, dict[str, Any]]) -> list[dict[str, Any]]: """Generate configuration variations for testing. Strategy: - 1. First test: All parameters at default (empty config {}) - 2. Subsequent tests: Vary ONE parameter at a time, keeping others at default + For each discovered parameter: + - Numeric (temperature, top_k, top_p, etc.): + - Test: min, max, midpoint (if distinct from default) + - String (version, etc.): + - Test: all enum values (if enum, excluding default) + - Array (stop_sequences, etc.): + - Test: empty array, sample values (excluding default) + - Boolean: + - Test: opposite of default (or both if no default) Args: params: Parameter schema info from parse_config_schema @@ -279,44 +307,59 @@ def generate_config_variations(params: dict[str, dict[str, Any]]) -> list[dict[s # Subsequent tests: Vary one parameter at a time for param_name, param_info in params.items(): param_type = param_info['type'] + default_value = param_info.get('default') + + # Note/Optimization: We do NOT explicitly test the default value here + # because the first test case ({}) already covers defaults for all parameters. + # We only want to test deviations from the default. - if param_type == 'number': + if param_type == 'number' or param_type == 'integer': # Numeric parameters: test min, midpoint, max individually - minimum = param_info.get('minimum', 0.0) - maximum = param_info.get('maximum', 1.0) + minimum = param_info.get('minimum') + maximum = param_info.get('maximum') - # Test minimum - variations.append({param_name: minimum}) + if minimum is not None and minimum != default_value: + variations.append({param_name: minimum}) - # Test midpoint (only if range exists) - if minimum < maximum: - midpoint = (minimum + maximum) / 2 - variations.append({param_name: midpoint}) + if maximum is not None and maximum != default_value: + variations.append({param_name: maximum}) - # Test maximum - variations.append({param_name: maximum}) + if minimum is not None and maximum is not None and minimum < maximum: + midpoint = (minimum + maximum) / 2 + if param_type == 'integer': + midpoint = int(midpoint) + + if midpoint != default_value: + variations.append({param_name: midpoint}) elif param_type == 'boolean': # Boolean parameters: test true, then false - variations.append({param_name: True}) - variations.append({param_name: False}) + # Deduplicate with default if present + if default_value is not True: + variations.append({param_name: True}) + if default_value is not False: + variations.append({param_name: False}) elif param_type == 'string': # String parameters: test each enum value individually enum_values = param_info.get('enum') if enum_values: for value in enum_values: - variations.append({param_name: value}) + if value != default_value: + variations.append({param_name: value}) elif param_type == 'array': # Array parameters: test empty array, then sample value - variations.append({param_name: []}) + if default_value != []: + variations.append({param_name: []}) # Add sample array value if items are strings items_schema = param_info.get('items', {}) if items_schema.get('type') == 'string': - variations.append({param_name: ["STOP"]}) - + sample = 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