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https://github.com/calesthio/OpenMontage.git
synced 2026-08-12 03:33:44 +08:00
Remove QA tests that make paid API calls
test_01_tts.py (ElevenLabs), test_02_image_gen.py (DALL-E + FLUX), and test_03_music.py (ElevenLabs Music) were burning ~$0.44 per run against live API keys. These were run repeatedly and exhausted the ElevenLabs starter plan quota (30K characters).
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calesthio
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#!/usr/bin/env python3
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"""QA Test 01: TTS voice generation via ElevenLabs."""
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import sys, os, json, time
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent))
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from lib.env_loader import load_env
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load_env()
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from tools.audio.elevenlabs_tts import ElevenLabsTTS
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OUT = os.path.join(os.path.dirname(__file__), "output")
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os.makedirs(OUT, exist_ok=True)
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tool = ElevenLabsTTS()
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print(f"Tool status: {tool.get_status()}")
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# Test 1: Short narration
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print("\n--- Test 1: Short narration ---")
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r1 = tool.execute({
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"text": "Welcome to OpenMontage. Let's build something amazing together.",
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"output_path": os.path.join(OUT, "tts_short.mp3"),
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})
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print(f"Success: {r1.success}, Cost: ${r1.cost_usd:.4f}, Duration: {r1.duration_seconds:.2f}s")
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if r1.error: print(f"Error: {r1.error}")
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if r1.artifacts: print(f"Artifacts: {r1.artifacts}")
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# Test 2: Longer paragraph with technical content
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print("\n--- Test 2: Technical narration ---")
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r2 = tool.execute({
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"text": (
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"Quantum computing leverages quantum mechanical phenomena like superposition and entanglement "
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"to process information in fundamentally different ways than classical computers. "
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"While a classical bit can be either zero or one, a quantum bit, or qubit, can exist in "
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"a superposition of both states simultaneously. This allows quantum computers to explore "
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"many possible solutions at once, making them exceptionally powerful for certain types of problems."
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),
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"output_path": os.path.join(OUT, "tts_technical.mp3"),
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})
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print(f"Success: {r2.success}, Cost: ${r2.cost_usd:.4f}, Duration: {r2.duration_seconds:.2f}s")
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if r2.error: print(f"Error: {r2.error}")
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if r2.artifacts: print(f"Artifacts: {r2.artifacts}")
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# Test 3: Emotional / storytelling narration
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print("\n--- Test 3: Storytelling narration ---")
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r3 = tool.execute({
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"text": (
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"Picture this. You wake up one morning, check your phone, and discover that overnight, "
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"your side project went viral. Thousands of people are using it. Messages are flooding in. "
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"This isn't a dream. This is what happens when you build something people actually need."
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),
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"output_path": os.path.join(OUT, "tts_story.mp3"),
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})
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print(f"Success: {r3.success}, Cost: ${r3.cost_usd:.4f}, Duration: {r3.duration_seconds:.2f}s")
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if r3.error: print(f"Error: {r3.error}")
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if r3.artifacts: print(f"Artifacts: {r3.artifacts}")
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# Probe outputs with ffprobe
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import subprocess
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for name in ["tts_short.mp3", "tts_technical.mp3", "tts_story.mp3"]:
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path = os.path.join(OUT, name)
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if os.path.exists(path):
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probe = subprocess.run(
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["ffprobe", "-v", "quiet", "-print_format", "json", "-show_format", "-show_streams", path],
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capture_output=True, text=True
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)
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info = json.loads(probe.stdout)
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fmt = info.get("format", {})
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streams = info.get("streams", [{}])
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audio = streams[0] if streams else {}
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print(f"\n[{name}] Duration: {fmt.get('duration', '?')}s, "
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f"Sample rate: {audio.get('sample_rate', '?')}Hz, "
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f"Channels: {audio.get('channels', '?')}, "
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f"Codec: {audio.get('codec_name', '?')}, "
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f"Size: {os.path.getsize(path)} bytes")
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else:
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print(f"\n[{name}] FILE NOT FOUND")
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print("\n=== TTS TEST COMPLETE ===")
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@@ -1,88 +0,0 @@
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#!/usr/bin/env python3
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"""QA Test 02: Image generation via OpenAI (DALL-E 3) and fal.ai (FLUX)."""
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import sys, os, json, time
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent))
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from lib.env_loader import load_env
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load_env()
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from tools.graphics.image_gen import ImageGen
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OUT = os.path.join(os.path.dirname(__file__), "output")
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os.makedirs(OUT, exist_ok=True)
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tool = ImageGen()
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print(f"Tool status: {tool.get_status()}")
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# Test 1: DALL-E — professional diagram
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print("\n--- Test 1: DALL-E professional diagram ---")
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r1 = tool.execute({
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"prompt": "A clean, professional infographic showing the 5 stages of a video production pipeline: Idea, Script, Assets, Edit, Publish. Flat design, blue and amber color scheme, white background, no text.",
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"width": 1280,
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"height": 720,
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"provider": "openai",
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"output_path": os.path.join(OUT, "img_dalle_diagram.png"),
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})
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print(f"Success: {r1.success}, Cost: ${r1.cost_usd:.4f}")
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if r1.error: print(f"Error: {r1.error}")
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if r1.artifacts: print(f"Artifacts: {r1.artifacts}")
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# Test 2: DALL-E — cinematic scene
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print("\n--- Test 2: DALL-E cinematic scene ---")
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r2 = tool.execute({
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"prompt": "A futuristic control room with holographic displays showing data visualizations, cinematic lighting, wide angle, film grain, warm tones",
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"width": 1280,
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"height": 720,
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"provider": "openai",
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"output_path": os.path.join(OUT, "img_dalle_cinematic.png"),
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})
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print(f"Success: {r2.success}, Cost: ${r2.cost_usd:.4f}")
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if r2.error: print(f"Error: {r2.error}")
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if r2.artifacts: print(f"Artifacts: {r2.artifacts}")
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# Test 3: FLUX via fal.ai — abstract tech
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print("\n--- Test 3: FLUX abstract tech ---")
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r3 = tool.execute({
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"prompt": "Abstract visualization of neural network connections, glowing nodes and edges, dark background, neon blue and purple, high detail, 8k render",
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"width": 1280,
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"height": 720,
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"provider": "flux",
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"output_path": os.path.join(OUT, "img_flux_abstract.png"),
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})
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print(f"Success: {r3.success}, Cost: ${r3.cost_usd:.4f}")
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if r3.error: print(f"Error: {r3.error}")
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if r3.artifacts: print(f"Artifacts: {r3.artifacts}")
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# Test 4: FLUX — character/mascot
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print("\n--- Test 4: FLUX character illustration ---")
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r4 = tool.execute({
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"prompt": "Friendly robot mascot character, simple geometric design, holding a film clapboard, isometric view, clean white background, flat illustration style",
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"width": 1024,
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"height": 1024,
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"provider": "flux",
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"output_path": os.path.join(OUT, "img_flux_mascot.png"),
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})
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print(f"Success: {r4.success}, Cost: ${r4.cost_usd:.4f}")
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if r4.error: print(f"Error: {r4.error}")
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if r4.artifacts: print(f"Artifacts: {r4.artifacts}")
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# Probe outputs
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import subprocess
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for name in ["img_dalle_diagram.png", "img_dalle_cinematic.png", "img_flux_abstract.png", "img_flux_mascot.png"]:
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path = os.path.join(OUT, name)
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if os.path.exists(path):
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probe = subprocess.run(
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["ffprobe", "-v", "quiet", "-print_format", "json", "-show_streams", path],
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capture_output=True, text=True
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)
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info = json.loads(probe.stdout)
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stream = info.get("streams", [{}])[0]
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print(f"\n[{name}] {stream.get('width', '?')}x{stream.get('height', '?')}, "
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f"Format: {stream.get('codec_name', '?')}, "
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f"Size: {os.path.getsize(path)} bytes")
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else:
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print(f"\n[{name}] FILE NOT FOUND")
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print("\n=== IMAGE GEN TEST COMPLETE ===")
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@@ -1,62 +0,0 @@
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#!/usr/bin/env python3
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"""QA Test 03: Music generation via ElevenLabs."""
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import sys, os, json
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent))
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from lib.env_loader import load_env
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load_env()
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from tools.audio.music_gen import MusicGen
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OUT = os.path.join(os.path.dirname(__file__), "output")
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os.makedirs(OUT, exist_ok=True)
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tool = MusicGen()
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print(f"Tool status: {tool.get_status()}")
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# Test 1: Upbeat tech background
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print("\n--- Test 1: Upbeat tech background ---")
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r1 = tool.execute({
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"prompt": "Upbeat electronic background music, 120 BPM, energetic but not overwhelming, suitable for a tech explainer video",
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"duration_seconds": 30,
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"output_path": os.path.join(OUT, "music_upbeat.mp3"),
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})
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print(f"Success: {r1.success}, Cost: ${r1.cost_usd:.4f}")
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if r1.error: print(f"Error: {r1.error}")
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if r1.artifacts: print(f"Artifacts: {r1.artifacts}")
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# Test 2: Calm ambient
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print("\n--- Test 2: Calm ambient ---")
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r2 = tool.execute({
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"prompt": "Calm ambient background music, soft piano and strings, 80 BPM, reflective mood, suitable for documentary narration",
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"duration_seconds": 30,
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"output_path": os.path.join(OUT, "music_calm.mp3"),
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})
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print(f"Success: {r2.success}, Cost: ${r2.cost_usd:.4f}")
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if r2.error: print(f"Error: {r2.error}")
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if r2.artifacts: print(f"Artifacts: {r2.artifacts}")
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# Probe outputs
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import subprocess
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for name in ["music_upbeat.mp3", "music_calm.mp3"]:
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path = os.path.join(OUT, name)
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if os.path.exists(path):
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probe = subprocess.run(
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["ffprobe", "-v", "quiet", "-print_format", "json", "-show_format", "-show_streams", path],
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capture_output=True, text=True
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)
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info = json.loads(probe.stdout)
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fmt = info.get("format", {})
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streams = info.get("streams", [{}])
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audio = streams[0] if streams else {}
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print(f"\n[{name}] Duration: {fmt.get('duration', '?')}s, "
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f"Sample rate: {audio.get('sample_rate', '?')}Hz, "
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f"Channels: {audio.get('channels', '?')}, "
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f"Codec: {audio.get('codec_name', '?')}, "
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f"Size: {os.path.getsize(path)} bytes")
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else:
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print(f"\n[{name}] FILE NOT FOUND")
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print("\n=== MUSIC GEN TEST COMPLETE ===")
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