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Simple DSPY example of BasicQA
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# install DSPy: pip install dspy | |
import dspy | |
# This sets up the language model for DSPy in this case we are using GPT-3.5-turbo | |
turbo = dspy.OpenAI(model='gpt-3.5-turbo') | |
# This sets the language model for DSPy. This must be set or you get an error that is not helpful: | |
# --> temperature = lm.kwargs['temperature'] if temperature is None else temperature | |
# --> AttributeError: 'NoneType' object has no attribute 'kwargs' | |
dspy.settings.configure(lm=turbo) | |
# This is not required but it helps to understand what is happening | |
my_example = { | |
"question": "What system was final fantasy 1 made for?", | |
"answer": "NES", | |
} | |
# This is the signature for the predictor. It is a simple question and answer model. | |
class BasicQA(dspy.Signature): | |
"""Answer questions with short factoid answers.""" | |
question = dspy.InputField() | |
answer = dspy.OutputField(desc="often between 1 and 5 words") | |
# Define the predictor. | |
generate_answer = dspy.Predict(BasicQA) | |
# Call the predictor on a particular input. | |
pred = generate_answer(question=my_example['question']) | |
# Print the answer...profit :) | |
print(pred.answer) |
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