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import openai
import os
import gradio as gr
import json
from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv())
openai.api_key = os.getenv('OPENAI_API_KEY')
def get_completion(prompt, model="gpt-3.5-turbo"):
messages = [{"role": "user", "content": prompt}]
response = openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=0, # this is the degree of randomness of the model's output
)
return response.choices[0].message["content"]
def greet(input):
prompt = f"""
Recommend complementary shop combinations which match well with the shop(s) described in the following text, which is delimited by triple backticks. Rank by synergy: \
Text: ```{input}```
"""
response = get_completion(prompt)
return response
#iface = gr.Interface(fn=greet, inputs="text", outputs="text")
#iface.launch()
#iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Text to find entities", lines=2)], outputs=[gr.HighlightedText(label="Text with entities")], title="NER with dslim/bert-base-NER", description="Find entities using the `dslim/bert-base-NER` model under the hood!", allow_flagging="never", examples=["My name is Andrew and I live in California", "My name is Poli and work at HuggingFace"])
iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Co-Retailing Business")], outputs="text")
iface.launch()
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