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| """What an infographic says: a short, length-limited block of text the premade themes pour into their layout. | |
| Model output is never trusted for layout, so every field is stripped of markup and clamped here.""" | |
| import re | |
| from pydantic import BaseModel | |
| WIDTH, HEIGHT = 1600, 2260 | |
| # Characters per field: the themes are drawn so the longest allowed text still fits its box. | |
| LIMITS = {"title": 60, "subtitle": 110, "label": 34, "item_name": 22, "item_text": 120, "step_name": 14, | |
| "step_text": 78, "rule": 80, "note": 90} | |
| ITEMS = (3, 5) | |
| STEPS = (4, 8) | |
| NOTES = 3 | |
| class Entry(BaseModel): | |
| name: str | |
| text: str | |
| class InfographicContent(BaseModel): | |
| title: str | |
| subtitle: str | |
| items_label: str | |
| items: list[Entry] | |
| steps_label: str | |
| steps: list[Entry] | |
| rule: str | |
| notes: list[str] | |
| _TAGS = re.compile(r"<[^>]*>") | |
| _SPACE = re.compile(r"\s+") | |
| def _clip(text: object, limit: int) -> str: | |
| """Plain text of at most `limit` characters, cut at a word with an ellipsis when it was longer.""" | |
| s = _SPACE.sub(" ", _TAGS.sub(" ", str(text or ""))).replace("—", ",").replace("–", "-").strip() | |
| if len(s) <= limit: | |
| return s | |
| cut = s[: limit - 1].rsplit(" ", 1)[0].rstrip(" ,;:.-") or s[: limit - 1] | |
| return cut + "…" | |
| def _entries(raw: object, name_limit: int, text_limit: int, count: tuple[int, int]) -> list[dict]: | |
| out = [] | |
| for e in (raw if isinstance(raw, list) else []): | |
| e = e if isinstance(e, dict) else getattr(e, "__dict__", {}) | |
| name, text = _clip(e.get("name"), name_limit), _clip(e.get("text"), text_limit) | |
| if name and text: | |
| out.append({"name": name, "text": text}) | |
| return out[: count[1]] if len(out) >= count[0] else [] | |
| def clamp(raw: dict) -> dict | None: | |
| """The content in the shape the themes draw, or None when there is too little to draw (too few items or steps).""" | |
| if hasattr(raw, "model_dump"): | |
| raw = raw.model_dump() | |
| items = _entries(raw.get("items"), LIMITS["item_name"], LIMITS["item_text"], ITEMS) | |
| steps = _entries(raw.get("steps"), LIMITS["step_name"], LIMITS["step_text"], STEPS) | |
| title = _clip(raw.get("title"), LIMITS["title"]) | |
| if not items or not steps or not title: | |
| return None | |
| notes = [n for n in (_clip(n, LIMITS["note"]) for n in raw.get("notes") or []) if n][:NOTES] | |
| return {"title": title, "subtitle": _clip(raw.get("subtitle"), LIMITS["subtitle"]), | |
| "items_label": _clip(raw.get("items_label"), LIMITS["label"]) or "Key ideas", | |
| "items": items, | |
| "steps_label": _clip(raw.get("steps_label"), LIMITS["label"]) or "How it works", | |
| "steps": steps, "rule": _clip(raw.get("rule"), LIMITS["rule"]), "notes": notes} | |
| SAMPLE = { | |
| "title": "From Prompt to Production Agent", | |
| "subtitle": "Five engineering layers plus an eight step production request flow", | |
| "items_label": "The five layers", | |
| "items": [ | |
| {"name": "Prompt", "text": "Optimizes wording, examples, and format in a single request."}, | |
| {"name": "Context", "text": "Curates docs, history, tools, and memory before each model call."}, | |
| {"name": "Harness", "text": "Scaffolding around the model: tools, verification, and guardrails."}, | |
| {"name": "Loop", "text": "Runs reason, act and observe cycles until a stop condition is met."}, | |
| {"name": "Graph", "text": "Maps multi-agent systems as explicit nodes and edges."}, | |
| ], | |
| "steps_label": "Every request goes through", | |
| "steps": [ | |
| {"name": "Auth", "text": "Middleware checks identity, rate limits, and input guards."}, | |
| {"name": "Cache", "text": "Semantic cache returns answers for equivalent questions."}, | |
| {"name": "Safety", "text": "Scrub PII and detect prompt injection attacks."}, | |
| {"name": "Memory", "text": "Load session history with summarized context."}, | |
| {"name": "Retrieve", "text": "Fetch relevant docs and split complex queries."}, | |
| {"name": "Answer", "text": "Execute sub-queries in parallel with branching models."}, | |
| {"name": "Validate", "text": "Check output quality metrics before responding."}, | |
| {"name": "Save", "text": "Store results and log one full trace."}, | |
| ], | |
| "rule": "Most tasks only need the bottom layers; avoid complex graphs without cause.", | |
| "notes": ["Each layer builds on the one below it.", "Cache and middleware run outside the graph.", | |
| "Every request should produce a single end-to-end trace."], | |
| } | |
| # The longest text each field allows, with the most items and steps: what every theme must fit. | |
| STRESS = { | |
| "title": "W" * 4 + " Quarterly Review of Everything We Learned Here", "subtitle": "Long words here " * 7, | |
| "items_label": "The five very long layers", "steps_label": "Every request goes through", | |
| "items": [{"name": "Wide Name Here Now", "text": "Words that go on and on " * 6}] * 5, | |
| "steps": [{"name": "Validators", "text": "Words that go on and on " * 5}] * 8, | |
| "rule": "A very long rule that keeps going and going " * 3, "notes": ["A long note that keeps on going " * 4] * 3, | |
| } | |