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#!git clone https://github.com/sudipmondal1310/Internship.git | |
#!pip install llama-index==0.5.6 | |
#!pip install langchain==0.0.148 | |
from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper, ServiceContext | |
from langchain import OpenAI | |
import sys | |
import os | |
from IPython.display import Markdown, display | |
import time | |
import random | |
import gradio as gr | |
def construct_index(directory_path): | |
# set maximum input size | |
max_input_size = 4096 | |
# set number of output tokens | |
num_outputs = 2000 | |
# set maximum chunk overlap | |
max_chunk_overlap = 20 | |
# set chunk size limit | |
chunk_size_limit = 600 | |
# define prompt helper | |
prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit) | |
# define LLM | |
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="text-davinci-003", max_tokens=num_outputs)) | |
documents = SimpleDirectoryReader(directory_path).load_data() | |
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper) | |
index = GPTSimpleVectorIndex.from_documents(documents, service_context=service_context) | |
index.save_to_disk('index.json') | |
return index | |
def ask_ai_new(query): | |
index = GPTSimpleVectorIndex.load_from_disk('index.json') | |
while True: | |
#query = input("What do you want to ask? ") | |
response = index.query(query) | |
response = Markdown(f"<b>{response.response}</b>") | |
print(response) | |
return response.data | |
os.environ["OPENAI_API_KEY"]="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" | |
construct_index("Data") | |
#pip install gradio | |
with gr.Blocks() as demo: | |
chatbot = gr.Chatbot() | |
query = gr.inputs.Textbox(label="Enter your message here") | |
clear = gr.Button("Clear") | |
def user(user_message, history): | |
return "", history + [[user_message, None]] | |
def bot(history): | |
bot_message = ask_ai_new(history[-1][0]) | |
print(bot_message) | |
history[-1][1] = "" | |
for character in bot_message: | |
history[-1][1] += character | |
time.sleep(0.05) | |
yield history | |
query.submit(user, [query, chatbot], [query, chatbot], queue=False).then( | |
bot, chatbot, chatbot | |
) | |
clear.click(lambda: None, None, chatbot, queue=False) | |
demo.queue() | |
demo.launch() | |