Prompt Templates

Reusable prompt templates with variable interpolation and a registry

Blazen ships a lightweight prompt templating layer for reusing system prompts and user-message scaffolds across steps, agents, and workflows. Templates use {{variable}} placeholders, carry a chat role, and render into ChatMessage objects that plug straight into CompletionModel.complete().

Overview

PromptTemplate — a named template with a role (system / user / assistant), a template string, and the set of variables it needs.
PromptRegistry — a versioned collection of templates loadable from YAML or JSON files and indexed by name.

Basic usage

from blazen import PromptTemplate, ChatMessage

template = PromptTemplate(
    "Summarise the following {{doc_type}} in {{style}} style.",
    role="system",
    name="summariser",
)

message = template.render({"doc_type": "article", "style": "concise"})
print(message.content)
# -> "Summarise the following article in concise style."

import { PromptTemplate } from "blazen";

const template = new PromptTemplate(
  "Summarise the following {{doc_type}} in {{style}} style.",
  { role: "system", name: "summariser" },
);

const msg = template.render({ doc_type: "article", style: "concise" });
console.log(msg.content);

Pass the rendered ChatMessage straight into the model:

from blazen import CompletionModel, ChatMessage

model = CompletionModel.openai()
response = await model.complete([
    template.render({"doc_type": "article", "style": "concise"}),
    ChatMessage.user(document_text),
])

Registering templates

A PromptRegistry indexes named templates and supports version pinning. Use it when your application has more than a handful of prompts or when prompts are maintained by a separate team.

from blazen import PromptRegistry, PromptTemplate

registry = PromptRegistry()
registry.register("summariser", PromptTemplate(
    "Summarise the following {{doc_type}}.",
    role="system",
))
registry.register("translator", PromptTemplate(
    "Translate the following text into {{lang}}.",
    role="system",
))

msg = registry.render("summariser", {"doc_type": "meeting transcript"})

import { PromptRegistry, PromptTemplate } from "blazen";

const registry = new PromptRegistry();
registry.register(
  "summariser",
  new PromptTemplate("Summarise the following {{doc_type}}.", { role: "system" }),
);
registry.register(
  "translator",
  new PromptTemplate("Translate the following text into {{lang}}.", { role: "system" }),
);

const msg = registry.render("summariser", { doc_type: "meeting transcript" });

Loading from disk

YAML (or JSON) files let you keep prompts out of the codebase:

# prompts/summariser.yaml
name: summariser
version: "2"
role: system
template: |
  Summarise the following {{doc_type}} in {{style}} style.
  Limit your response to {{max_words}} words.

from blazen import PromptRegistry

registry = PromptRegistry.from_file("prompts/summariser.yaml")
# Or load every .yaml/.yml/.json file in a directory:
registry = PromptRegistry.from_dir("prompts")

const registry = PromptRegistry.fromFile("prompts/summariser.yaml");
// Or:
const dirRegistry = PromptRegistry.fromDir("prompts");

Variables

Templates extract variable names eagerly at construction time, so you can inspect them and validate inputs up-front:

tmpl = PromptTemplate("Hello {{name}}, welcome to {{place}}!")
tmpl.variables
# -> ["name", "place"]

const tmpl = new PromptTemplate("Hello {{name}}, welcome to {{place}}!");
console.log(tmpl.variables);
// -> ["name", "place"]