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import yaml
import gradio as gr
from typing import List
from llm_client import PalmClient
from pinecone_index import PinceconeIndex
SYSTEM_MESSAGE = 'Give a precise answer to the question based on only the \
context and evidence and do not be verbose.'
TOP_K = 2
def format_prompt(question: str, evidence: List[str]):
evidence_string = ''
for i, ev in enumerate(evidence):
evidence_string.join(f'\n Evidence {i+1}: {ev}')
content = f"{SYSTEM_MESSAGE} \
\n ### Question:{question} \
\n ### Evidence: {evidence_string} \
\n ### Response:"
return content
if __name__ == '__main__':
config_path = 'config.yml'
with open('config.yml', 'r') as file:
config = yaml.safe_load(file)
print(config)
data_path = config['paths']['data_path']
project = config['paths']['project']
index_name = config['pinecone']['index-name']
embedding_model = config['sentence-transformers']['model-name']
embedding_dimension = config['sentence-transformers'][
'embedding-dimension']
index = PinceconeIndex(index_name, embedding_model)
index.connect_index(embedding_dimension, False)
palm_client = PalmClient()
def get_answer(question: str):
evidence = index.query(question, top_k=TOP_K)
prompt_with_evidence = format_prompt(question, evidence)
print(prompt_with_evidence)
response = palm_client.generate_text(prompt_with_evidence)
final_output = [response] + evidence
return final_output
context_outputs = [gr.Textbox(label=f'Evidence {i+1}')
for i in range(TOP_K)]
result_output = [gr.Textbox(label='Answer')]
gradio_outputs = result_output + context_outputs
gradio_inputs = gr.Textbox(placeholder="Enter your question...")
demo = gr.Interface(
fn=get_answer,
inputs=gradio_inputs,
# outputs=[gr.Textbox(label=f'Document {i+1}') for i in range(TOP_K)],
outputs=gradio_outputs,
title="GT Student Code of Conduct Bot",
description="Get LLM-powered answers to questions about the \
Georgia Tech Student Code of Conduct. The evidences are exerpts\
from the Code of Conduct."
)
demo.launch()
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