Duplicate from souljoy/chatPDF

Co-authored-by: 小爷毛毛-卓寿杰 <[email protected]>

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+title: ChatPDF
+emoji: 💻
+colorFrom: gray
+colorTo: yellow
+sdk: gradio
+sdk_version: 3.20.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+duplicated_from: souljoy/chatPDF
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import requests
+import json
+import gradio as gr
+# from concurrent.futures import ThreadPoolExecutor
+import pdfplumber
+import pandas as pd
+import time
+from cnocr import CnOcr
+from sentence_transformers import SentenceTransformer, models, util
+word_embedding_model = models.Transformer('uer/sbert-base-chinese-nli', do_lower_case=True)
+pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension(), pooling_mode='cls')
+embedder = SentenceTransformer(modules=[word_embedding_model, pooling_model])
+ocr = CnOcr()
+# chat_url = 'https://souljoy-my-api.hf.space/sale'
+chat_url = 'https://souljoy-my-api.hf.space/chatpdf'
+headers = {
+    'Content-Type': 'application/json',
+}
+# thread_pool_executor = ThreadPoolExecutor(max_workers=4)
+history_max_len = 500
+all_max_len = 3000
+
+
+def get_emb(text):
+    emb_url = 'https://souljoy-my-api.hf.space/embeddings'
+    data = {"content": text}
+    try:
+        result = requests.post(url=emb_url,
+                               data=json.dumps(data),
+                               headers=headers
+                               )
+        return result.json()['data'][0]['embedding']
+    except Exception as e:
+        print('data', data, 'result json', result.json())
+
+
+def doc_emb(doc: str):
+    texts = doc.split('\n')
+    # futures = []
+    emb_list = embedder.encode(texts)
+    # for text in texts:
+    #     futures.append(thread_pool_executor.submit(get_emb, text))
+    # 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(
+        value="""操作说明 step 3：PDF解析提交成功！ 🙋 可以开始对话啦~"""), gr.Chatbot.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()
+    query_embedding = embedder.encode([msg])
+    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_set, sub_doc_list = set(), []
+    for s_i in score_index:
+        doc = doc_text_list[s_i[1]]
+        if now_len + len(doc) > all_max_len:
+            break
+        index_set.add(s_i[1])
+        now_len += len(doc)
+        # 可能段落截断错误，所以把上下段也加入进来
+        if s_i[1] > 0 and s_i[1] -1 not in index_set:
+            doc = doc_text_list[s_i[1]-1]
+            if now_len + len(doc) > all_max_len:
+                break
+            index_set.add(s_i[1]-1)
+            now_len += len(doc)
+        if s_i[1] + 1 < len(doc_text_list) and s_i[1] + 1 not in index_set:
+            doc = doc_text_list[s_i[1]+1]
+            if now_len + len(doc) > all_max_len:
+                break
+            index_set.add(s_i[1]+1)
+            now_len += len(doc)
+
+    index_list = list(index_set)
+    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=chat_url,
+                           data=json.dumps(data),
+                           headers=headers
+                           )
+    res = result.json()['content']
+    bot.append([msg, res])
+    return bot[max(0, len(bot) - 3):]
+
+
+def up_file(files):
+    doc_text_list = []
+    for idx, file in enumerate(files):
+        print(file.name)
+        with pdfplumber.open(file.name) as pdf:
+            for i in range(len(pdf.pages)):
+                # 读取PDF文档第i+1页
+                page = pdf.pages[i]
+                res_list = page.extract_text().split('\n')[:-1]
+
+                for j in range(len(page.images)):
+                    # 获取图片的二进制流
+                    img = page.images[j]
+                    file_name = '{}-{}-{}.png'.format(str(time.time()), str(i), str(j))
+                    with open(file_name, mode='wb') as f:
+                        f.write(img['stream'].get_data())
+                    try:
+                        res = ocr.ocr(file_name)
+                    except Exception as e:
+                        res = []
+                    if len(res) > 0:
+                        res_list.append(' '.join([re['text'] for re in res]))
+
+                tables = page.extract_tables()
+                for table in tables:
+                    # 第一��当成表头：
+                    df = pd.DataFrame(table[1:], columns=table[0])
+                    try:
+                        records = json.loads(df.to_json(orient="records", force_ascii=False))
+                        for rec in records:
+                            res_list.append(json.dumps(rec, ensure_ascii=False))
+                    except Exception as e:
+                        res_list.append(str(df))
+
+                doc_text_list += res_list
+    doc_text_list = [str(text).strip() for text in doc_text_list if len(str(text).strip()) > 0]
+    print(doc_text_list)
+    return gr.Textbox.update(value='\n'.join(doc_text_list), visible=True), gr.Button.update(
+        visible=True), gr.Markdown.update(
+        value="操作说明 step 2：确认PDF解析结果（可修正），点击“提交解析结果”，随后进行对话")
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            file = gr.File(file_types=['.pdf'], label='点击上传PDF，进行解析(支持多文档、表格、OCR)', file_count='multiple')
+            doc_bu = gr.Button(value='提交解析结果', visible=False)
+            txt = gr.Textbox(label='PDF解析结果', visible=False)
+            doc_text_state = gr.State([])
+            doc_emb_state = gr.State([])
+        with gr.Column():
+            md = gr.Markdown("""操作说明 step 1：点击左侧区域，上传PDF，进行解析""")
+            chat_bot = gr.Chatbot(visible=False)
+            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)
+
+    file.change(up_file, [file], [txt, doc_bu, md])
+    doc_bu.click(doc_emb, [txt], [doc_text_state, doc_emb_state, msg_txt, chat_bu, md, chat_bot])
+    chat_bu.click(get_response, [msg_txt, chat_bot, doc_text_state, doc_emb_state], [chat_bot])
+
+if __name__ == "__main__":
+    demo.queue().launch()
+    # demo.queue().launch(share=False, server_name='172.22.2.54', server_port=9191)

requirements.txt

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+pdfplumber
+sentence_transformers
+cnocr