DSPy - using TGI for local model

dspy_tgi_mistral.py

# install DSPy: pip install dspy
import dspy

# This sets up the language model for DSPy in this case we are using mistral 7b through TGI (Text Generation Interface from HuggingFace)
mistral = dspy.HFClientTGI(model='mistralai/Mistral-7B-v0.1', port=8080, url='http://localhost')

# This sets the language model for DSPy.
dspy.settings.configure(lm=mistral)

# 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)