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{
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"# 1) Import Required Libraries \n",
"\n",
"import requests\n",
"import gradio as gr\n",
"\n",
"# Deepseek only uses abstract summarization\n",
"# This tool use DeepSeek API Endpoint\n",
"\n",
"# 2) Define the DeepSeek API Endpoint\n",
"\n",
"OLLAMA_URL = \"http://localhost:11434/api/generate\"\n",
"\n",
"# 3) Define the Summarization Function which can retrieve Information\n",
"\n",
"def summarize_text(text):\n",
" payload = {\n",
" \"model\": \"deepseek-r1\", #Here you can load whatever the model you have in your ollama(ex:deepseek-r1:1.5b,7b,8b,14b) I used 7b model here \n",
" \"prompt\": f\"Summarize the following text in **5 bullet points**:\\n\\n{text}\", #The prompt is here for tell commands for the llm to act \n",
" \"stream\": False # Ensures the response is returned as a whole, not streamed\n",
" }\n",
"\n",
" response = requests.post(OLLAMA_URL, json=payload) #Send Requests to deepseekAPI\n",
"\n",
" if response.status_code == 200: #if server run correctly it return the result or it will give error\n",
" return response.json().get(\"response\", \"No summary generated.\")\n",
" else:\n",
" return f\"Error: {response.text}\"\n",
"\n",
"# 4) Create Gradio interface to design \n",
"interface = gr.Interface(\n",
" fn=summarize_text,\n",
" inputs=gr.Textbox(lines=10, placeholder=\"Enter text to summarize\"),\n",
" outputs=gr.Textbox(label=\"Summarized Text\"),\n",
" #theme='NoCrypt/miku', #Theme for the Interface I used Hatsune Miku from HF \n",
" title=\"AI-Powered Text Summarizer\",\n",
" description=\"Enter a long text and DeepSeek AI will generate a concise summary.\"\n",
")\n",
"\n",
"# Launch the web app\n",
"if __name__ == \"__main__\":\n",
" interface.launch()\n",
"\n",
"\n"
]
}
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