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import os
import gradio as gr
import json
import requests
import openai
try:
openai.api_key = os.environ["OPENAI_API_KEY"]
except KeyError:
error_message = "System is at capacity right now.Please try again later"
print(error_message)
def chatbot(input):
return error_message
else:
messages = [
{"role": "system", "content": "My AI Assistant"},
]
#Streaming endpoint for OPENAI ChatGPT
API_URL = "https://api.openai.com/v1/chat/completions"
top_p_chatgpt = 1.0
temperature_chatgpt = 1.0
#Predict function for CHATGPT
def chatbot(inputs, chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):
#Define payload and header for chatgpt API
payload = {
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": f"{inputs}"}],
"temperature" : 1.0,
"top_p":1.0,
"n" : 1,
"stream": True,
"presence_penalty":0,
"frequency_penalty":0,
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {openai.api_key}"
}
#Handling the different roles for ChatGPT
if chat_counter_chatgpt != 0 :
messages=[]
for data in chatbot_chatgpt:
temp1 = {}
temp1["role"] = "user"
temp1["content"] = data[0]
temp2 = {}
temp2["role"] = "assistant"
temp2["content"] = data[1]
messages.append(temp1)
messages.append(temp2)
temp3 = {}
temp3["role"] = "user"
temp3["content"] = inputs
messages.append(temp3)
payload = {
"model": "gpt-3.5-turbo",
"messages": messages, #[{"role": "user", "content": f"{inputs}"}],
"temperature" : temperature_chatgpt, #1.0,
"top_p": top_p_chatgpt, #1.0,
"n" : 1,
"stream": True,
"presence_penalty":0,
"frequency_penalty":0,
}
chat_counter_chatgpt+=1
history.append("You asked: "+ inputs)
# make a POST request to the API endpoint using the requests.post method, passing in stream=True
response = requests.post(API_URL, headers=headers, json=payload, stream=True)
token_counter = 0
partial_words = ""
counter=0
for chunk in response.iter_lines():
#Skipping the first chunk
if counter == 0:
counter+=1
continue
# check whether each line is non-empty
if chunk.decode() :
chunk = chunk.decode()
# decode each line as response data is in bytes
if len(chunk) > 13 and "content" in json.loads(chunk[6:])['choices'][0]["delta"]:
partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
if token_counter == 0:
history.append(" " + partial_words)
else:
history[-1] = partial_words
chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] # convert to tuples of list
token_counter+=1
yield chat, history, chat_counter_chatgpt # this resembles {chatbot: chat, state: history}
def reset_textbox():
return gr.update(value="")
def reset_chat(chatbot, state):
return None, []
with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
#chatgpt {height: 400px; overflow: auto;}} """, theme=gr.themes.Default(primary_hue="slate") ) as demo:
with gr.Row():
with gr.Column(scale=14):
with gr.Box():
with gr.Row():
with gr.Column(scale=13):
inputs = gr.Textbox(label="Ask me anything ⤵️ Try: Value of pi" )
with gr.Column(scale=1):
b1 = gr.Button('Submit', elem_id = 'submit').style(full_width=True)
b2 = gr.Button('Clear', elem_id = 'clear').style(full_width=True)
state_chatgpt = gr.State([])
with gr.Box():
with gr.Row():
chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label=''My ChatGPT Turbo")
chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
inputs.submit(reset_textbox, [], [inputs])
b1.click( chatbot,
[ inputs, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt],
[chatbot_chatgpt, state_chatgpt],)
b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
demo.queue(concurrency_count=16).launch(height= 2500, debug=True)
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