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import gradio as gr
import json, openai, os, time
from openai import OpenAI
_client, _assistant, _thread = None, None, None
def show_json(str, obj):
print(f"=> {str}\n{json.loads(obj.model_dump_json())}")
def init_client():
global _client, _assistant, _thread
_client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
_assistant = _client.beta.assistants.create(
name="Math Tutor",
instructions="You are a personal math tutor. Answer questions briefly, in a sentence or less.",
model="gpt-4-1106-preview",
)
#show_json("assistant", _assistant)
_thread = _client.beta.threads.create()
#show_json("thread", _thread)
def wait_on_run(run):
global _client, _thread
while run.status == "queued" or run.status == "in_progress":
run = _client.beta.threads.runs.retrieve(
thread_id=_thread.id,
run_id=run.id,
)
time.sleep(0.25)
return run
def extract_content_values(data):
content_values = []
for item in data.data:
for content in item.content:
if content.type == 'text':
content_values.append(content.text.value)
return content_values
def chat(message, msg2, history):
global _client, _assistant, _thread
if _client == None:
init_client()
message = _client.beta.threads.messages.create(
role="user",
thread_id=_thread.id,
content=message,
)
#show_json("message", message)
run = _client.beta.threads.runs.create(
assistant_id=_assistant.id,
thread_id=_thread.id,
)
#show_json("run", run)
run = wait_on_run(run)
show_json("run", run)
messages = _client.beta.threads.messages.list(
thread_id=_thread.id
)
show_json("messages", messages)
return extract_content_values(messages)[0]
def vote(data: gr.LikeData):
print(data)
if data.liked:
print("You upvoted this response: " + data.value["value"])
else:
print("You downvoted this response: " + data.value["value"])
"""
gr.ChatInterface(
chat,
chatbot=gr.Chatbot(height=300),
textbox=gr.Textbox(placeholder="Question", container=False, scale=7),
title="Math Tutor",
description="Ask Math Tutor any question",
theme="soft",
examples=["I need to solve the equation '3x + 13 = 11'. Can you help me?"],
cache_examples=True,
retry_btn=None,
undo_btn=None,
clear_btn="Clear",
#multimodal=True,
#additional_inputs=[
# gr.Textbox("sk-", label="OpenAI API Key", type = "password"),
#],
).launch()
"""
with gr.Blocks() as demo:
chatbot = gr.Chatbot(placeholder="<strong>Math Tutor</strong><br>Ask Me Anything")
chatbot.like(vote, None, None)
gr.ChatInterface(fn=chat, chatbot=chatbot)
demo.launch() |