From System Prompts to DSPy Programs

This repo is an important step in moving from handcrafted system prompts to programmable, optimizable prompt pipelines with DSPy.

What changes with DSPy?

The key mindset shift in DSPy is this:

You don’t hand the model a huge “system prompt” as a raw string.
Instead, you translate the structure and intent of that prompt into a dspy.Signature in Python.
DSPy then builds the actual prompt for you.

So instead of:

• One giant system prompt written by hand
• Tweaking words and tone in the UI

you now have:

• A Python class that defines
  • Inputs (what context you give the model)
  • Outputs (what you expect back)
  • High-level behavior (inside the docstring)
• DSPy compiles this into a structured prompt automatically.

---

copywriter.py: crypto cpy engine

This demo implements a first version of CRYPTO COPY_ENGINE A specialized copywriter for crypto, DeFi, and blockchain products.

In copywriter.py example you can see how a classic “system prompt” becomes a structured class:

• The docstring describes the role and global rules.
• Each InputField describes one piece of context:
  • product_context, unique_edge, target_audience, etc.
• Each OutputField describes what we want back:
  • hook, main_post, cta, hashtags_or_tags, alt_version.

Installation and config:

• apt update
• apt install software-properties-common -y it runs on python 3.11
• apt install python3.11 python3.11-venv python3.11-dev -y

Py version & vnenv

• python3.11 --version
• python3.11 -m venv .venv
• source .venv/bin/activate
• python --version
• python -m pip install --upgrade pip setuptools wheel
• pip install dspy-ai

how to run:

chmod +x copywriter.py
python copywriter.py