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| # ================================ | |
| # ChatVLD Futurista - Gradio 5.x | |
| # ================================ | |
| import os | |
| from pathlib import Path | |
| import requests | |
| import gradio as gr | |
| import time | |
| from langchain_groq import ChatGroq | |
| from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder | |
| from langchain_core.messages import AIMessage, HumanMessage | |
| from langchain_community.document_loaders import PyMuPDFLoader | |
| from langchain_text_splitters import RecursiveCharacterTextSplitter | |
| from langchain_huggingface import HuggingFaceEmbeddings | |
| from langchain_community.vectorstores import FAISS | |
| from langchain.chains import create_history_aware_retriever, create_retrieval_chain | |
| from langchain.chains.combine_documents import create_stuff_documents_chain | |
| # ================================ | |
| # API KEY | |
| # ================================ | |
| if "GROQ_API_KEY" not in os.environ: | |
| raise ValueError("❌ A variável de ambiente GROQ_API_KEY não está definida.") | |
| # ================================ | |
| # PDFs | |
| # ================================ | |
| pdf_urls = { | |
| "documento.pdf": "https://drive.google.com/uc?id=1hin1AVM6vh0adcqH0RBOmEXZrn_Ebfyk", | |
| "documento2.pdf": "https://drive.google.com/uc?id=1GVbPq8SDriIS5CQo0kT0EZEqwWwjGJmY" | |
| } | |
| for pdf_path, pdf_url in pdf_urls.items(): | |
| if not Path(pdf_path).exists(): | |
| r = requests.get(pdf_url) | |
| with open(pdf_path, "wb") as f: | |
| f.write(r.content) | |
| # ================================ | |
| # CONFIG | |
| # ================================ | |
| ID_MODEL = "deepseek-r1-distill-llama-70b" | |
| TEMPERATURE = 0.7 | |
| FAISS_INDEX_PATH = "index_faiss" | |
| # ================================ | |
| # FUNÇÕES | |
| # ================================ | |
| def load_llm(model_id, temperature): | |
| return ChatGroq( | |
| model=model_id, | |
| temperature=temperature, | |
| groq_api_key=os.environ["GROQ_API_KEY"], | |
| max_tokens=None, | |
| timeout=None, | |
| max_retries=2, | |
| ) | |
| def extract_text_pdf(file_path): | |
| loader = PyMuPDFLoader(file_path) | |
| docs = loader.load() | |
| return "\n".join([page.page_content for page in docs]) | |
| def config_retriever(pdf_files): | |
| embeddings = HuggingFaceEmbeddings(model_name="BAAI/bge-m3") | |
| if Path(FAISS_INDEX_PATH).exists(): | |
| vectorstore = FAISS.load_local(FAISS_INDEX_PATH, embeddings, allow_dangerous_deserialization=True) | |
| else: | |
| all_texts = "" | |
| for file_path in pdf_files: | |
| all_texts += extract_text_pdf(file_path) + "\n" | |
| text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200) | |
| chunks = text_splitter.split_text(all_texts) | |
| vectorstore = FAISS.from_texts(chunks, embeddings) | |
| vectorstore.save_local(FAISS_INDEX_PATH) | |
| return vectorstore.as_retriever(search_type='mmr', search_kwargs={'k': 3, 'fetch_k': 4}) | |
| def config_rag_chain(llm, retriever): | |
| context_q_prompt = ChatPromptTemplate.from_messages([ | |
| ("system","Dada a conversa e a pergunta, formule uma pergunta independente."), | |
| MessagesPlaceholder("chat_history"), | |
| ("human", "Pergunta: {input}"), | |
| ]) | |
| hist_aware_retriever = create_history_aware_retriever( | |
| llm=llm, | |
| retriever=retriever, | |
| prompt=context_q_prompt | |
| ) | |
| system_prompt = """Você é um assistente virtual futurista da empresa VLD. Responda de forma clara e objetiva em português. Se não souber, diga que não sabe.""" | |
| qa_prompt = ChatPromptTemplate.from_messages([ | |
| ("system", system_prompt), | |
| MessagesPlaceholder("chat_history"), | |
| ("human", "Pergunta: {input}\n\nContexto: {context}"), | |
| ]) | |
| qa_chain = create_stuff_documents_chain(llm, qa_prompt) | |
| return create_retrieval_chain(hist_aware_retriever, qa_chain) | |
| llm = load_llm(ID_MODEL, TEMPERATURE) | |
| retriever_instance = config_retriever(list(pdf_urls.keys())) | |
| rag_chain = config_rag_chain(llm, retriever_instance) | |
| chat_history = [AIMessage(content="🚀 Olá, sou o seu suporte virtual futurista! Como posso te ajudar?")] | |
| def responder(pergunta): | |
| chat_history.append(HumanMessage(content=pergunta)) | |
| try: | |
| resposta = rag_chain.invoke({"input": pergunta, "chat_history": chat_history})["answer"] | |
| resposta = resposta.split("</think>")[-1].strip() if "</think>" in resposta else resposta.strip() | |
| except Exception as e: | |
| resposta = f"❌ Erro: {str(e)}" | |
| chat_history.append(AIMessage(content=resposta)) | |
| return resposta | |
| # ================================ | |
| # CSS FUTURISTA | |
| # ================================ | |
| custom_css = """ | |
| .gradio-chatbot { background-color: #f8f9fa; color: #111; } | |
| .gradio-textbox textarea { background-color: #1c1c1c; color: #fff; border-radius: 8px; border: 1px solid #333; padding: 8px; } | |
| .gradio-button, .gradio-button:active { background: linear-gradient(to right, #00c6ff, #0072ff); color: #fff; border: none; border-radius: 8px; } | |
| /* 🎇 Estilo futurista para o título principal */ | |
| #titulo-principal { | |
| text-align: center; | |
| font-size: 32px; | |
| font-weight: bold; | |
| background: linear-gradient(90deg, #00c6ff, #8a2be2, #ff0080, #00c6ff); | |
| -webkit-background-clip: text; | |
| -webkit-text-fill-color: transparent; | |
| animation: brilho 5s linear infinite; | |
| margin-bottom: 20px; | |
| } | |
| @keyframes brilho { | |
| 0% { background-position: 0% 50%; } | |
| 50% { background-position: 100% 50%; } | |
| 100% { background-position: 0% 50%; } | |
| } | |
| """ | |
| # ================================ | |
| # INTERFACE GRADIO 5.x | |
| # ================================ | |
| with gr.Blocks(css=custom_css, theme="soft") as iface: | |
| # TÍTULO PRINCIPAL | |
| gr.Markdown("🛸 SUPORTE AUTOMATIZADO", elem_id="titulo-principal") | |
| with gr.Tabs(): | |
| # ==================== | |
| # Aba Chat Futurista | |
| # ==================== | |
| with gr.TabItem("💭 ChatVLD"): | |
| gr.Markdown("""🤖 **Olá!** | |
| Sou o suporte para as impressoras **Codeline SS5632** e **LINX 7900**. | |
| Em que posso ajudar?""") | |
| chatbot = gr.Chatbot(type="messages") | |
| with gr.Row(): | |
| txt = gr.Textbox( | |
| placeholder="Diz o que tu quer macho...", | |
| show_label=False, | |
| lines=2 | |
| ) | |
| submit_btn = gr.Button("🚀 Arrocha") | |
| with gr.Row(): | |
| clear_btn = gr.Button("🧹 Barrer a prosa") | |
| new_chat_btn = gr.Button("✨ Nova prosa") | |
| def enviar(msg, history): | |
| history.append({"role": "user", "content": msg}) | |
| yield history, "" | |
| history.append({"role": "assistant", "content": "🤖 Digitando..."}) | |
| yield history, "" | |
| resposta = responder(msg) | |
| history[-1] = {"role": "assistant", "content": resposta} | |
| yield history, "" | |
| def limpar(): | |
| chat_history.clear() | |
| return [], "" | |
| def novo_chat(): | |
| chat_history.clear() | |
| chat_history.append(AIMessage(content="🤖 Novo chat iniciado. Como posso te ajudar?")) | |
| return [{"role": "assistant", "content": "🤖 Novo chat iniciado. Como posso te ajudar?"}], "" | |
| txt.submit(enviar, [txt, chatbot], [chatbot, txt]) | |
| submit_btn.click(enviar, [txt, chatbot], [chatbot, txt]) | |
| clear_btn.click(limpar, outputs=[chatbot, txt]) | |
| new_chat_btn.click(novo_chat, outputs=[chatbot, txt]) | |
| # ==================== | |
| # Aba VALID NODE com botão fixo | |
| # ==================== | |
| with gr.TabItem("🌐 VALIDNODE"): | |
| gr.Markdown("### Acesse o VALID NODE clicando no botão abaixo:") | |
| gr.HTML( | |
| '<button onclick="window.open(\'https://172.17.200.97\', \'_blank\')" ' | |
| 'style="background: linear-gradient(to right, #00c6ff, #0072ff); ' | |
| 'color: #fff; border: none; border-radius: 8px; padding: 10px 20px; ' | |
| 'font-size: 16px; cursor: pointer;">🖥️ VALIDeNODE</button>' | |
| ) | |
| iface.launch() |