How to build multi-hop reasoning with DSPy

pip install dspy openai

import os
import dspy
from openai import OpenAI

# Configure DSPy with OpenAI LLM
lm = dspy.LM("openai/gpt-4o-mini", api_key=os.environ["OPENAI_API_KEY"])
dspy.configure(lm=lm)

# Step 1: Extract key facts from text
class ExtractFacts(dspy.Signature):
    text: str = dspy.InputField()
    facts: str = dspy.OutputField()

# Step 2: Answer question using extracted facts
class AnswerQuestion(dspy.Signature):
    facts: str = dspy.InputField()
    question: str = dspy.InputField()
    answer: str = dspy.OutputField()

# Define the multi-hop reasoning chain
class MultiHopReasoning(dspy.ChainOfThought):
    extract_facts = ExtractFacts()
    answer_question = AnswerQuestion()

    def __call__(self, text: str, question: str) -> str:
        # Step 1: Extract facts
        facts_result = self.extract_facts(text=text)
        # Step 2: Answer question using facts
        answer_result = self.answer_question(facts=facts_result.facts, question=question)
        return answer_result.answer

# Instantiate the chain
chain = MultiHopReasoning()

# Example input
input_text = (
    "Marie Curie was a physicist and chemist who conducted pioneering research on radioactivity."
)
input_question = "What field did Marie Curie contribute to?"

# Run multi-hop reasoning
answer = chain(text=input_text, question=input_question)
print("Answer:", answer)

import asyncio

async def async_multi_hop():
    # Async version of the chain call
    answer = await chain.acall(text=input_text, question=input_question)
    print("Async answer:", answer)

asyncio.run(async_multi_hop())