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81da2d5 1706cd9 8c6b423 dd678c1 1706cd9 dd678c1 81da2d5 a822dca dd678c1 83e828a 81da2d5 8c6b423 81da2d5 dd678c1 1706cd9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 | from agent.models import EducationPptxInput, SlideOutline, SlideSpec
from agent.preview import outline_to_html, render_slide_images
from agent.prompts import fallback_outline, outline_looks_like_schema_echo, outline_max_tokens
from agent.runner import AgentRunner
from agent.tools.docx import create_docx, create_html_export
from agent.tools.pptx import create_pptx
def test_outline_max_tokens_scales_with_slide_count():
assert outline_max_tokens(5) == 750
assert outline_max_tokens(1) == 230
assert outline_max_tokens(20) == 1024
runner = AgentRunner()
raw = (
'{"title": "AI Agents", "slides": ['
'{"title": "Intro", "bullets": ["What is an agent?"]},'
'{"title": "Uses", "bullets": ["Automation"]}'
"]}"
)
outline = runner._parse_outline(raw, expected_slides=5)
assert len(outline.slides) == 5
assert outline.title == "AI Agents"
def test_parse_outline_trims_when_model_returns_too_many():
runner = AgentRunner()
raw = (
'{"title": "Topic", "slides": ['
'{"title": "A", "bullets": ["a"]},'
'{"title": "B", "bullets": ["b"]},'
'{"title": "C", "bullets": ["c"]},'
'{"title": "D", "bullets": ["d"]}'
"]}"
)
outline = runner._parse_outline(raw, expected_slides=3)
assert len(outline.slides) == 3
def test_extract_json_from_fenced_block():
raw = '```json\n{"title": "T", "slides": [{"title": "S", "bullets": ["a"]}]}\n```'
data = AgentRunner._extract_json(raw)
assert data["title"] == "T"
def test_extract_json_ignores_trailing_text():
raw = (
'{"title": "AI Agents", "slides": [{"title": "Intro", "bullets": ["a"]}]}\n'
"Here is a short explanation of the lesson outline."
)
data = AgentRunner._extract_json(raw)
assert data["title"] == "AI Agents"
def test_extract_json_ignores_duplicate_object():
first = '{"title": "First", "slides": [{"title": "A", "bullets": ["a"]}]}'
second = '{"title": "Second", "slides": [{"title": "B", "bullets": ["b"]}]}'
data = AgentRunner._extract_json(f"{first}\n{second}")
assert data["title"] == "First"
def test_extract_json_empty_raises():
import pytest
with pytest.raises(ValueError, match="empty output"):
AgentRunner._extract_json(" ")
def test_extract_json_after_thinking_block():
raw = (
"planning the lesson\n"
'{"title": "Agents", "slides": [{"title": "Intro", "bullets": ["What is an agent?"]}]}'
)
from inference.response_clean import strip_thinking_blocks
cleaned = strip_thinking_blocks(raw)
data = AgentRunner._extract_json(cleaned)
assert data["title"] == "Agents"
def test_parse_outline_or_error_empty():
runner = AgentRunner()
outline, err = runner._parse_outline_or_error("", 5, None)
assert outline is None
assert "empty" in err.lower()
def test_parse_outline_rejects_schema_echo():
runner = AgentRunner()
raw = (
'{"title": "string — presentation title", "slides": ['
'{"title": "string — slide heading", "bullets": ["string", "..."], '
'"speaker_note": "string — one sentence for the teacher"}'
"]}"
)
import pytest
with pytest.raises(ValueError, match="schema placeholders"):
runner._parse_outline(raw, expected_slides=5)
def test_outline_looks_like_schema_echo():
echo = SlideOutline(
title="string — presentation title",
slides=[SlideSpec(title="string — slide heading", bullets=["string", "..."])],
)
assert outline_looks_like_schema_echo(echo) is True
real = SlideOutline(
title="Small model finetuning",
slides=[SlideSpec(title="What is finetuning?", bullets=["Adapting a base model"])],
)
assert outline_looks_like_schema_echo(real) is False
def test_fallback_outline_slide_count():
req = EducationPptxInput(topic="ai agent", grade="6", slide_count=5)
outline = fallback_outline(req)
assert len(outline.slides) == 5
assert "ai agent" in outline.title.lower()
def test_create_pptx_writes_file(tmp_path, monkeypatch):
monkeypatch.setenv("AGENT_OUTPUTS_DIR", str(tmp_path))
outline = SlideOutline(
title="Photosynthesis",
slides=[
SlideSpec(title="What is it?", bullets=["Plants make food", "Uses sunlight"]),
SlideSpec(title="Why it matters", bullets=["Oxygen", "Food chain"]),
],
)
path = create_pptx(outline, run_id="test")
assert path.exists()
assert path.suffix == ".pptx"
def test_create_docx_writes_file(tmp_path, monkeypatch):
monkeypatch.setenv("AGENT_OUTPUTS_DIR", str(tmp_path))
outline = SlideOutline(
title="Photosynthesis",
slides=[SlideSpec(title="Intro", bullets=["Sunlight", "Chlorophyll"])],
)
path = create_docx(outline, run_id="test")
assert path.exists()
assert path.suffix == ".docx"
def test_outline_preview_and_images(tmp_path, monkeypatch):
monkeypatch.setenv("AGENT_OUTPUTS_DIR", str(tmp_path))
outline = SlideOutline(
title="Water Cycle",
slides=[SlideSpec(title="Evaporation", bullets=["Heat", "Vapor"])],
)
html = outline_to_html(outline)
assert "Water Cycle" in html
assert "Evaporation" in html
images = render_slide_images(outline, run_id="prev")
assert len(images) == 2
assert all(p.exists() for p in images)
def test_create_html_export(tmp_path, monkeypatch):
monkeypatch.setenv("AGENT_OUTPUTS_DIR", str(tmp_path))
outline = SlideOutline(
title="Fractions",
slides=[SlideSpec(title="Parts", bullets=["Half", "Quarter"])],
)
path = create_html_export(outline, run_id="html")
assert path.exists()
assert "Fractions" in path.read_text()
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