1.9 DSPy Question Answering Agent

"""DSPy Agent Example — Bindu Integration
=======================================
WHAT EXISTED BEFORE:
    Only Agno, CrewAI, LangChain examples existed.
    No DSPy integration existed anywhere in the repo.

WHAT IS NEW:
    - First DSPy example in the Bindu ecosystem
    - Uses DSPy Signatures for structured, typed prompting
    - Supports multi-turn conversation history
    - Works with any OpenAI-compatible model
"""

import dspy
from bindu.penguin.bindufy import bindufy

# Configure DSPy with your preferred LLM
lm = dspy.LM("openai/gpt-4o-mini")
dspy.configure(lm=lm)

# Define a DSPy Signature (typed prompt template)
class QASignature(dspy.Signature):
    """Answer the user's question clearly and concisely."""

    question: str = dspy.InputField(desc="The user's question")
    answer: str = dspy.OutputField(desc="A clear and concise answer")

# Build the DSPy program
qa_program = dspy.Predict(QASignature)

config = {
    "author": "varshayadav1722@gmail.com",
    "name": "dspy_agent",
    "description": "A DSPy-powered question answering agent",
    "deployment": {
        "url": "http://localhost:3773",
        "expose": True,
        "cors_origins": ["http://localhost:5173"]
    },
    "skills": ["skills/question-answering"]
}

def handler(messages: list[dict]) -> list[dict]:
    last_message = messages[-1]["content"]
    result = qa_program(question=last_message)
    return [{"role": "assistant", "content": result.answer}]

if __name__ == "__main__":
    bindufy(config, handler)

uv run examples/beginner/dspy-agent.py