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import gradio as gr | |
import logging, os, sys, threading | |
from custom_utils import ( | |
connect_to_database, | |
inference, | |
rag_ingestion, | |
rag_retrieval_naive, | |
rag_retrieval_advanced, | |
rag_inference | |
) | |
lock = threading.Lock() | |
RAG_INGESTION = False | |
RAG_OFF = "Off" | |
RAG_NAIVE = "Naive RAG" | |
RAG_ADVANCED = "Advanced RAG" | |
logging.basicConfig(stream = sys.stdout, level = logging.INFO) | |
logging.getLogger().addHandler(logging.StreamHandler(stream = sys.stdout)) | |
def invoke(openai_api_key, | |
prompt, | |
accomodates, | |
bedrooms, | |
rag_option): | |
if not openai_api_key: | |
raise gr.Error("OpenAI API Key is required.") | |
if not prompt: | |
raise gr.Error("Prompt is required.") | |
if not rag_option: | |
raise gr.Error("Retrieval-Augmented Generation is required.") | |
with lock: | |
db, collection = connect_to_database() | |
inference_result = "" | |
try: | |
if (RAG_INGESTION): | |
return rag_ingestion(collection) | |
elif rag_option == RAG_OFF: | |
inference_result = inference( | |
openai_api_key, | |
prompt | |
) | |
elif rag_option == RAG_NAIVE: | |
retrieval_result = rag_retrieval_naive( | |
openai_api_key, | |
prompt, | |
accomodates, | |
bedrooms, | |
db, | |
collection | |
) | |
inference_result = rag_inference( | |
openai_api_key, | |
prompt, | |
retrieval_result | |
) | |
elif rag_option == RAG_ADVANCED: | |
retrieval_result = rag_retrieval_advanced( | |
openai_api_key, | |
prompt, | |
accomodates, | |
bedrooms, | |
db, | |
collection | |
) | |
inference_result = rag_inference( | |
openai_api_key, | |
prompt, | |
retrieval_result | |
) | |
except Exception as e: | |
raise gr.Error(e) | |
print("###") | |
print(inference_result) | |
print("###") | |
return inference_result | |
gr.close_all() | |
demo = gr.Interface( | |
fn = invoke, | |
inputs = [gr.Textbox(label = "OpenAI API Key", type = "password", lines = 1), | |
gr.Textbox(label = "Prompt", value = os.environ["PROMPT"], lines = 1), | |
gr.Number(label = "Accomodates", value = 2), | |
gr.Number(label = "Bedrooms", value = 1), | |
gr.Radio([RAG_OFF, RAG_NAIVE, RAG_ADVANCED], label = "Retrieval-Augmented Generation", value = RAG_ADVANCED)], | |
outputs = [gr.Markdown(label = "Completion", value = os.environ["COMPLETION"], line_breaks = True, sanitize_html = False)], | |
title = "Context-Aware Reasoning Application", | |
description = os.environ["DESCRIPTION"] | |
) | |
demo.launch() |