import requests import json import gradio as gr from concurrent.futures import ThreadPoolExecutor from sentence_transformers import util url = 'https://souljoy-my-api.hf.space/qa_maker' headers = { 'Content-Type': 'application/json', } thread_pool_executor = ThreadPoolExecutor(max_workers=16) history_max_len = 500 all_max_len = 2000 def get_emb(text): emb_url = 'https://souljoy-my-api.hf.space/embeddings' data = {"content": text} result = requests.post(url=emb_url, data=json.dumps(data), headers=headers ) return result.json()['data'][0]['embedding'] def doc_emb(doc: str): texts = doc.split('\n') futures = [] for text in texts: futures.append(thread_pool_executor.submit(get_emb, text)) emb_list = [] for f in futures: emb_list.append(f.result()) print('\n'.join(texts)) return texts, emb_list, gr.Textbox.update(visible=True), gr.Button.update(visible=True), gr.Markdown.update( visible=True) def get_response(msg, bot, doc_text_list, doc_embeddings): future = thread_pool_executor.submit(get_emb, msg) now_len = len(msg) req_json = {'question': msg} his_bg = -1 for i in range(len(bot) - 1, -1, -1): if now_len + len(bot[i][0]) + len(bot[i][1]) > history_max_len: break now_len += len(bot[i][0]) + len(bot[i][1]) his_bg = i req_json['history'] = [] if his_bg == -1 else bot[his_bg:] query_embedding = future.result() cos_scores = util.cos_sim(query_embedding, doc_embeddings)[0] score_index = [[score, index] for score, index in zip(cos_scores, [i for i in range(len(cos_scores))])] score_index.sort(key=lambda x: x[0], reverse=True) print('score_index:\n', score_index) index_list, sub_doc_list = [], [] for s_i in score_index: doc = doc_text_list[s_i[1]] if now_len + len(doc) > all_max_len: break index_list.append(s_i[1]) now_len += len(doc) index_list.sort() for i in index_list: sub_doc_list.append(doc_text_list[i]) req_json['doc'] = '' if len(sub_doc_list) == 0 else '\n'.join(sub_doc_list) data = {"content": json.dumps(req_json)} print('data:\n', req_json) result = requests.post(url='https://souljoy-my-api.hf.space/chatpdf', data=json.dumps(data), headers=headers ) res = result.json()['content'] bot.append([msg, res]) return bot[max(0, len(bot) - 3):], gr.Markdown.update(visible=False) def up_file(files): for idx, file in enumerate(files): print(file.name) return gr.Button.update(visible=True) with gr.Blocks() as demo: with gr.Row(): with gr.Column(): file = gr.File(file_types=['.pdf'], label='上传PDF') txt = gr.Textbox(label='PDF解析结果', visible=False) doc_bu = gr.Button(value='提交', visible=False) md = gr.Markdown("""#### 文档提交成功 🙋 """, visible=False) doc_text_state = gr.State([]) doc_emb_state = gr.State([]) with gr.Column(): chat_bot = gr.Chatbot() msg_txt = gr.Textbox(label='消息框', placeholder='输入消息,点击发送', visible=False) chat_bu = gr.Button(value='发送', visible=False) doc_bu.click(doc_emb, [txt], [doc_text_state, doc_emb_state, msg_txt, chat_bu, md]) chat_bu.click(get_response, [msg_txt, chat_bot, doc_text_state, doc_emb_state], [chat_bot, md]) file.change(up_file, [file], [doc_bu]) if __name__ == "__main__": demo.queue().launch() # demo.queue().launch(share=False, server_name='172.22.2.54', server_port=9191)