Merge remote-tracking branch 'hub/main'

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README.md

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+---
+title: Smart
+emoji: 📈
+colorFrom: pink
+colorTo: red
+sdk: gradio
+sdk_version: 3.28.0
+app_file: app.py
+pinned: false
+license: other
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from glob import glob
+from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
+from langchain.chat_models import ChatOpenAI
+import gradio as gr
+import sys
+import os
+import zipfile
+
+
+
+OPENAI_API_KEY = os.getenv('token')
+
+
+
+def construct_index():
+    # extrair arquivos do zip
+    zip_path = "tema.zip"
+    try:
+        with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+            zip_ref.extractall(".")
+    except Exception as e:
+        print("Erro ao extrair o arquivo zip:", e)
+
+        
+    max_input_size = 3500
+    num_outputs = 512
+    max_chunk_overlap = 20
+    chunk_size_limit = 600
+
+    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
+
+    llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0.3, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
+
+    documents = SimpleDirectoryReader(".").load_data()
+
+    index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+
+    index.save_to_disk('index.json')
+
+    return index
+
+
+def chatbot(input_text):
+    index = GPTSimpleVectorIndex.load_from_disk('index.json')
+
+    # Ler e concatenar os documentos da pasta "docs" como o contexto relevante
+    documents = ""
+    for file_path in glob(os.path.join(".", "*.{txt,pdf}")):
+        with open(file_path, "r") as f:
+            documents += f.read() + " "
+    contexto = documents.strip()
+
+    # Combinar o contexto e a pergunta de entrada
+    with open('tema.txt', 'r') as f:
+        texto_prefixo = f.readline().strip()
+    texto_entrada = f"Dentro do assunto {texto_prefixo} me responda: {input_text}{contexto} se não for {texto_prefixo} não responda"
+    print(texto_entrada)
+      
+    response = index.query(texto_entrada, response_mode="compact")
+    return response.response
+
+
+description = """
+A IA foi treinada com materiais enviados e responde perguntas sobre o tema definido!
+"""
+
+iface = gr.Interface(fn=chatbot,
+                     inputs=gr.components.Textbox(lines=7, label="Como podemos te ajudar?"),
+                     outputs="text",
+                     description=description,                     
+                     title="Demonstração Chat OpenAI")
+
+
+index = construct_index()
+iface.launch(share=False)

pre-requirements.txt

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+openai
+gpt_index==0.4.24
+transformers
+PyPDF2
+PyCryptodome
+spacy
+gensim
+https://github.com/explosion/spacy-models/releases/download/pt_core_news_sm-3.5.0/pt_core_news_sm-3.5.0.tar.gz