import gradio as gr
import os
import json
import requests
#Streaming endpoint
API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
#Huggingface provided GPT4 OpenAI API Key
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
#Inferenec function
def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENAI_API_KEY}"
}
print(f"system message is ^^ {system_msg}")
if system_msg.strip() == '':
initial_message = [{"role": "user", "content": f"{inputs}"},]
multi_turn_message = []
else:
initial_message= [{"role": "system", "content": system_msg},
{"role": "user", "content": f"{inputs}"},]
multi_turn_message = [{"role": "system", "content": system_msg},]
if chat_counter == 0 :
payload = {
"model": "gpt-3.5-turbo",
"messages": initial_message ,
"temperature" : 1.0,
"top_p":1.0,
"n" : 1,
"stream": True,
"presence_penalty":0,
"frequency_penalty":0,
}
print(f"chat_counter - {chat_counter}")
else: #if chat_counter != 0 :
messages=multi_turn_message # Of the type of - [{"role": "system", "content": system_msg},]
for data in chatbot:
user = {}
user["role"] = "user"
user["content"] = data[0]
assistant = {}
assistant["role"] = "assistant"
assistant["content"] = data[1]
messages.append(user)
messages.append(assistant)
temp = {}
temp["role"] = "user"
temp["content"] = inputs
messages.append(temp)
#messages
payload = {
"model": "gpt-3.5-turbo",
"messages": messages, # Of the type of [{"role": "user", "content": f"{inputs}"}],
"temperature" : temperature, #1.0,
"top_p": top_p, #1.0,
"n" : 1,
"stream": True,
"presence_penalty":0,
"frequency_penalty":0,}
chat_counter+=1
history.append(inputs)
print(f"Logging : payload is - {payload}")
# 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)
print(f"Logging : response code - {response}")
token_counter = 0
partial_words = ""
counter=0
for chunk in response.iter_lines():
#Skipping 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) > 12 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, response # resembles {chatbot: chat, state: history}
#Resetting to blank
def reset_textbox():
return gr.update(value='')
#to set a component as visible=False
def set_visible_false():
return gr.update(visible=False)
#to set a component as visible=True
def set_visible_true():
return gr.update(visible=True)
def gen_gradio_demo():
title = """π Swarm Intelligence Agents ππ
"""
#display message for themes feature
theme_addon_msg = """π he swarm of agents combines a huge number of parallel agents divided into roles, including examiners, QA, evaluators, managers, analytics, and googlers.
πThe agents use smart task decomposition and optimization processes to ensure accurate and efficient research on any topic.π¨
"""
#Using info to add additional information about System message in GPT4
system_msg_info = """Swarm pre-configured for best practices using whitelists of top internet resources'"""
#Modifying existing Gradio Theme
theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="green", neutral_hue="green",
text_size=gr.themes.sizes.text_lg)
with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 520px; overflow: auto;}""",
theme=theme) as demo:
gr.HTML(title)
gr.HTML("""π₯Using a swarm of automated agents, we can perform fast and accurate research on any topic. ππ. ππ₯³πYou don't need to spent tons of hours during reseachyπ""")
gr.HTML(theme_addon_msg)
gr.HTML('''
Duplicate the Space and run securely with your OpenAI API Key''')
with gr.Column(elem_id = "col_container"):
#GPT4 API Key is provided by Huggingface
with gr.Accordion(label="Swarm Setup:", open=False):
system_msg = gr.Textbox(label="Instruct the AI Assistant to set its beaviour", info = system_msg_info, value="")
accordion_msg = gr.HTML(value="π§ To set System message you will have to refresh the app", visible=False)
chatbot = gr.Chatbot(label='Swarm Intelligence Search', elem_id="chatbot")
inputs = gr.Textbox(placeholder= "Enter your search query here...", label= "Type an input and press Enter")
state = gr.State([])
with gr.Row():
with gr.Column(scale=7):
b1 = gr.Button().style(full_width=True)
with gr.Column(scale=3):
server_status_code = gr.Textbox(label="Status code from OpenAI server", )
#top_p, temperature
with gr.Accordion("Parameters", open=False):
top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
chat_counter = gr.Number(value=0, visible=False, precision=0)
#Event handling
inputs.submit( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],) #openai_api_key
b1.click( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],) #openai_api_key
inputs.submit(set_visible_false, [], [system_msg])
b1.click(set_visible_false, [], [system_msg])
inputs.submit(set_visible_true, [], [accordion_msg])
b1.click(set_visible_true, [], [accordion_msg])
b1.click(reset_textbox, [], [inputs])
inputs.submit(reset_textbox, [], [inputs])
return demo