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from llama_index.core import SimpleDirectoryReader, GPTListIndex, GPTVectorStoreIndex, PromptHelper
from llama_index.core import StorageContext, load_index_from_storage
#from llama_index import LLMPredictor, PromptHelper
#from langchain.chat_models import ChatOpenAI
from langchain_community.embeddings import OpenAIEmbeddings
import gradio as gr
import os
import openai
from gradio.themes.utils import colors, fonts, sizes
#os.environ['OPENAI_API_KEY'] = api_key
messages = [
{"role": "system", "content": "follow the 4 instructions below for your outputs:"},
{"role": "system", "content": "1. make sure all expressions are compatible with Polish"},
{"role": "system", "content": "2. use Polish only for outputs"},
{"role": "system", "content": "3. if you cannot answer, reply that you do not have enough information"},
{"role": "system", "content": "4. do not make up any answer if you do know the answer"},
]
def construct_index(directory_path):
max_input_size = 4096
num_outputs = 512
max_chunk_overlap = 0.05
chunk_size_limit = 1000
temperature = 0.1
prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
# llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=temperature, model_name="gpt-3.5-turbo-instruct", max_tokens=num_outputs))
documents = SimpleDirectoryReader(directory_path).load_data()
#index = GPTVectorStoreIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
index = GPTVectorStoreIndex.from_documents(documents, urls=[
'https://trio.house/',
'https://trio.house/kontakt/',
'https://trio.house/o-nas/',
'https://trio.house/w-sprzedazy/',
'https://trio.house/dzialki/',
'https://trio.house/zainwestuj-z-nami/',
'https://trio.house/potrzebujesz-konsultacji-rynku-nieruchomosci/',
'https://trio.house/potrzebujesz-remontu/',
'https://trio.house/potrzebujesz-projektu-wnetrza/',
'https://trio.house/potrzebujesz-mebli-na-wymiar/',
'https://trio.house/potrzebujesz-kredytu-na-zakup-nieruchomosci/',
'https://trio.house/makroekonomia/',
'https://trio.house/rynek-nieruchomosci/',
'https://trio.house/2023/05/24/deweloperzy-buduja-coraz-mniej/',
'https://trio.house/2023/04/27/prognozy-na-2023-2025-co-nas-czeka/',
'https://trio.house/2023/04/18/wycinka-drzew-na-wlasnej-dzialce-w-2023/',
'https://trio.house/2023/04/03/lipiec-rozpoczynamy-juz-w-kwietniu/',
'https://trio.house/2023/04/03/zmiany-w-podatku-od-czynnosci-cywilnoprawnych/',
'https://trio.house/2023/03/23/czy-aby-napewno-najdrozsze-mieszkania-sa-w-stolicy/',
'https://trio.house/2023/06/15/rekomendacja-s-korzystniejsza-dla-bezpiecznego-kredytu-2/',
'https://trio.house/2023/07/20/warszawski-rynek-nieruchomosci-mieszkaniowych-na-6-biegu/',
'https://livesmarter.pl/najlepsze-lokaty-maj-2023/',
'https://www.money.pl/gospodarka/inflacja-maj-2023-r-finalny-odczyt-gus-6909186710817344a.html',
'https://ksiegowosc.infor.pl/wiadomosci/5754337,oprocentowanie-lokat-bankowych-i-kont-oszczednosciowych-2023-koniec-maja-poczatek-czerwca-tabela.html#:~:text=7%2C05%25%20%2D%20takie%20jest,proc.',
# ], llm_predictor=llm_predictor, prompt_helper=prompt_helper)
], prompt_helper=prompt_helper)
index.storage_context.persist('index.json')
return index
def chatbotCustom(input):
storage_context = StorageContext.from_defaults(persist_dir="index.json")
index = load_index_from_storage(storage_context)
query_engine = index.as_query_engine()
response = query_engine.query(input, similarity_top_k=5, response_mode="tree_summarize")
# response = index.query(input, similarity_top_k=5, response_mode="tree_summarize")
return response.response
#def chatbotGPT(input):
# if input:
# messages.append({"role": "user", "content": input})
# chat = openai.ChatCompletion.create(
# model="gpt-3.5-turbo-instruct", messages=messages
# )
# reply = chat.choices[0].message.content
# messages.append({"role": "assistant", "content": reply})
# return reply
def clear():
return None, None
theme = gr.themes.Default(font=[gr.themes.GoogleFont("Roboto"), "sans-serif", "sans-serif"], primary_hue="neutral", secondary_hue="neutral", neutral_hue="neutral").set(
button_primary_background_fill="#3FCCA5",
button_primary_background_fill_dark="#3FCCA5",
button_primary_text_color="#003F62",
body_background_fill="FFFFFF",
body_background_fill_dark="FFFFFF"
)
with gr.Blocks(theme=theme) as trioGPT:
inputs = gr.Textbox(lines=4, elem_id="inputs", label="Zadaj mi pytanie")#, elem_classes="textbox")
outputs = gr.Textbox(label="Odpowiedź", elem_id="outputs")#, elem_classes="textbox")
with gr.Row():
submit_btn = gr.Button("Wyślij", variant="primary")
clear_btn = gr.Button("Wyczyść")
submit_btn.click(chatbotCustom, inputs=inputs, outputs=outputs)
clear_btn.click(fn=clear, inputs=None, outputs=[inputs, outputs])
index = construct_index("data")
trioGPT.launch()#(share=True) |