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import os
from gpt_index import SimpleDirectoryReader, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
import gradio as gr
import openai
API_URL = "https://api.openai.com/v1/chat/completions"
openai.api_key = os.environ["OPENAI_API_KEY"]
top_p_chatgpt = 1.0
temperature_chatgpt = 1.0
def predict_chatgpt(inputs,chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):
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)
#os.environ['OPENAI_API_KEY'] = openai.api_key
chat_counter_chatgpt += 1
history.append("You asked: " + inputs)
# load index from disk
index = GPTSimpleVectorIndex.load_from_disk('PLIndex.json')
# query the index
result = index.query(inputs)
response = result.response.split()
token_counter = 0
partial_words = ""
counter = 0
for chunk in response:
partial_words=partial_words+" "+chunk
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 PLCoversationalAI:
with gr.Row():
with gr.Column(scale=14):
with gr.Box():
with gr.Row():
with gr.Column(scale=13):
inputs = gr.Textbox(label="Ask anything about Productization Labs ⤵️ Try : Who is Gopala" )
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="Productization Labs Conversational AI")
chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
inputs.submit(reset_textbox, [], [inputs])
b1.click( predict_chatgpt,
[ inputs, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt],
[chatbot_chatgpt, state_chatgpt],)
b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
PLCoversationalAI.queue(concurrency_count=16).launch(height= 2500, debug=True)
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