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| from GPT4KG import KnowledgeGraph | |
| import gradio as gr | |
| from PIL import Image | |
| def generate_graph(input_text,api_key,graph): | |
| if graph == []: | |
| kg = KnowledgeGraph(api_key) | |
| graph.append(kg) | |
| else: | |
| kg = graph[0] | |
| kg.learn(str(input_text)) | |
| img = kg.display_graph() | |
| graph[0] = kg | |
| return img,graph | |
| def answer_question(question,api_key,graph): | |
| if graph == []: | |
| kg = KnowledgeGraph(api_key) | |
| graph.append(kg) | |
| else: | |
| kg = graph[0] | |
| return kg.chat_qa(question) | |
| def clear_graph(api_key,graph): | |
| graph = [] | |
| kg = KnowledgeGraph(api_key) | |
| graph.append(kg) | |
| return graph,None#Image.new('RGB', (400, 100),(255, 255, 255)) | |
| title = "Associative Memory with GPT4KG" | |
| description = "Enter text to generate a semantically searchable knowledge graph:" | |
| with gr.Blocks() as demo: | |
| gr.Markdown(f"<h1><center>{title}</center></h1>") | |
| gr.Markdown(f"<h3><center>{description}</center></h3>") | |
| output_image = gr.Image(label="Knowledge Graph", type="pil") | |
| api_key = gr.Textbox(lines=1, label="OpenAI API Key") | |
| graph = gr.State([]) | |
| input_text = gr.Textbox(lines=5, label="Information to be added to graph") | |
| submit_btn = gr.Button("Add info to graph") | |
| submit_btn.click(fn=generate_graph, inputs=[input_text,api_key,graph], outputs=[output_image,graph]) | |
| question = gr.Textbox(lines=1, label="Question about the info in this graph") | |
| answer = gr.Textbox(lines=1, label="Answer") | |
| qa_btn = gr.Button("Ask question") | |
| qa_btn.click(fn=answer_question, inputs=[question,api_key,graph], outputs=[answer]) | |
| clear_btn = gr.Button("Clear graph") | |
| clear_btn.click(fn=clear_graph, inputs=[api_key,graph], outputs=[graph,output_image],api_name="clear") | |
| demo.launch() |