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.env.txt

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+OPENROUTER_API_KEY=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

chatbot.py

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+# -*- coding: utf-8 -*-
+"""chatbot
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1ZBbgzg8TvtDp13fmfvJolHegnlAiN70C
+"""
+
+OPENROUTER_API_KEY= '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'
+
+!pip install python-dotenv
+
+!pip install langchain-community --quiet
+
+!pip install -U langchain langchain-community --quiet
+
+!pip install gradio --quiet
+
+!pip install -U langchain-openai --quiet
+
+import os
+from dotenv import load_dotenv
+from langchain_openai import ChatOpenAI
+import gradio as gr
+
+# Carrega a chave do .env
+load_dotenv()
+api_key = os.getenv("OPENROUTER_API_KEY")
+# Verifica se a chave está disponível
+if not api_key:
+    raise ValueError("❌ Variável OPENROUTER_API_KEY não encontrada.")
+
+# Define as variáveis que o LangChain espera
+os.environ["OPENAI_API_KEY"] = api_key
+os.environ["OPENAI_API_BASE"] = "https://openrouter.ai/api/v1"
+
+# Instancia o modelo
+llm = ChatOpenAI(
+    model="deepseek/deepseek-r1:free",
+    temperature=0.5
+)
+
+# Função simples sem histórico
+def responder(mensagem):
+    try:
+        resposta = llm.invoke(mensagem)
+        return resposta.content
+    except Exception as e:
+        import traceback
+        return f"❌ Erro:\n{traceback.format_exc()}"
+
+# Interface Gradio simples
+app = gr.Interface(
+    fn=responder,
+    inputs=gr.Textbox(placeholder="Digite sua pergunta aqui", label="Mensagem"),
+    outputs=gr.Textbox(label="Resposta do Chatbot"),
+    title="Meu Primeiro Chatbot com IA Generativa",
+    description="Teste do modelo DeepSeek via OpenRouter com retorno direto.",
+)
+
+app.launch(share=True)