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appbf.py

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+from flask import Flask, render_template, request, jsonify, Response
+import requests
+import json
+import logging
+import re
+from flask import request, jsonify, Response, stream_with_context
+import subprocess
+
+
+
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', encoding='utf-8')
+logger = logging.getLogger(__name__)
+app = Flask(__name__)
+
+def generate_content(messages, model, api_key, url):
+    payload = json.dumps({
+        "model": model,
+        "messages": messages,
+        "stream": True
+    })
+    headers = {
+        'Accept': 'application/json',
+        'Authorization': api_key,
+        'Content-Type': 'application/json'
+    }
+
+    decoded_payload = json.loads(payload)
+    logger.info(f"Request payload: {json.dumps(decoded_payload, ensure_ascii=False)}")
+
+    response = requests.post(url, headers=headers, data=payload, stream=True)
+
+    content = ""
+    for line in response.iter_lines():
+        if line:
+            decoded_line = line.decode('utf-8')
+            if "data: " in decoded_line:
+                data_str = decoded_line[6:]
+                if data_str.strip() == "[DONE]":
+                    break
+                try:
+                    data = json.loads(data_str)
+                    if "choices" in data:
+                        delta = data["choices"][0]["delta"]
+                        if "content" in delta:
+                            content_str = delta["content"]
+                            content += content_str
+                            yield content_str
+                except json.JSONDecodeError as e:
+                    logger.error(f"JSON decode error: {e}")
+            elif "error" in decoded_line:
+                error_data = json.loads(decoded_line)
+                logger.error(f"Error: {error_data}")
+                break
+
+def write_to_file(file_path, outline, generated_content):
+    with open(file_path, 'w', encoding='utf-8') as file:
+        for part, content in zip(outline, generated_content):
+            file.write(part + "\n")
+            if content:
+                file.write(content.strip() + "\n\n")
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/generate_outline', methods=['POST'])
+def generate_outline():
+    data = request.get_json()
+    outline_model = data['outline_model']
+    url = (data['proxy_url'] or "https://api.openai.com/v1") + "/chat/completions"
+    api_key = data['api_key']
+    title = data['title']
+    doc_type = data['doc_type']
+    notice = data['notice']
+
+    system_prompt = ""
+    doc_type_name = ""
+    if doc_type == "1":
+        system_prompt = "You are ChatGPT, a large language model by OpenAI, and you are good at writing academic papers."
+        doc_type_name = "论文"
+    elif doc_type == "2":
+        system_prompt = "You are ChatGPT, a large language model by OpenAI, and you are good at writing reports."
+        doc_type_name = "报告"
+    elif doc_type == "3":
+        system_prompt = "You are ChatGPT, a large language model by OpenAI. From now on, you need to play the role of a writer. You are good at writing articles."
+        doc_type_name = "文章"
+
+    outline_prompt = f'我想写一个题目是"{title}"的{doc_type_name},下面是具体要求:{notice}\n请你帮我列出一个详细具体的大纲,大纲需要列出各个标题,只能用Markdown中的#和##来区分标题的层级(例如#大标题1\n##小标题1\n##小标题2\n#大标题2\n##小标题3\n##小标题4\n##小标题5\n以此类推,标题数量不固定\n注意:有且仅有大纲中绝对禁止出现"###"的组合,大纲中只能通过#和##进行标题层次的划分,之后的输出待定)。你的输出仅可包含示例中的内容,无需任何其他的解释说明'
+    retry_prompt = '前文已经要求过你不能输出###了,你误解了我的意思,请你直接重新生成新的outline,直接输出outline即可,无需道歉和其他任何解释'
+
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": outline_prompt}
+    ]
+    outline = "".join(list(generate_content(messages, outline_model, api_key, url)))
+
+    if re.search(r'###', outline):
+        temp_outline = outline
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": outline_prompt},
+            {"role": "assistant", "content": temp_outline},
+            {"role": "user", "content": retry_prompt}
+        ]
+        outline = "".join(list(generate_content(messages, outline_model, api_key, url)))
+
+    return jsonify({"outline": outline})
+
+is_paused = False
+@app.route('/generate_key_words', methods=['POST'])
+def generate_key_words():
+    data = request.get_json()
+    key_word_model = data['key_word_model']
+    api_key = data['api_key']
+    url = (data['proxy_url'] or "https://api.openai.com/v1") + "/chat/completions" 
+    outline = data['outline']
+
+    result = subprocess.run(['python', 'key_words.py', key_word_model, api_key, url, outline], capture_output=True, text=True)
+    search_key_word = result.stdout.strip()
+
+    return jsonify({"search_key_word": search_key_word})
+@app.route('/search', methods=['POST'])
+def search():
+    data = request.get_json()
+    selected_key_words = data['selected_key_words']
+    bing_api_key = data['bing_api_key']
+    proxy_url = data['proxy_url'] 
+    api_key =data['api_key']
+
+    print(f"Received selected key words: {', '.join(selected_key_words)}")
+    print(f"Received Bing API key: {bing_api_key}")
+
+    cmd = ['python', 'search.py', ','.join(selected_key_words), bing_api_key, api_key,proxy_url]
+    print(f"Running command: {' '.join(cmd)}")
+
+    result = subprocess.run(cmd, capture_output=True, text=True, encoding='utf-8')
+    search_result = result.stdout.strip()
+    error_output = result.stderr.strip()
+
+    print("Output from search.py:")
+    print(search_result)
+
+    if error_output:
+        print("Error output from search.py:")
+        print(error_output)
+
+    return jsonify({"search_result": search_result})
+
+@app.route('/qa', methods=['POST'])
+def qa():
+    data = request.get_json()
+    search_result = data['search_result']
+    api_key = data['api_key']
+    api_url_base = data['proxy_url']  
+
+    import qa
+    qa_result = qa.main(search_result, api_key, api_url_base)
+    return jsonify({"qa_result": qa_result})
+
+
+@app.route('/pause', methods=['POST'])
+def pause():
+    global is_paused
+    is_paused = True
+    return jsonify({"message": "Generation paused"})
+
+@app.route('/resume', methods=['POST'])
+def resume():
+    global is_paused
+    is_paused = False
+    return jsonify({"message": "Generation resumed"})
+
+
+@app.route('/generate_content', methods=['POST'])
+def generate_article_content():
+    global is_paused
+    is_paused = False
+
+    data = request.get_json()
+    expand_outline = data['expand_outline']
+    optimize_token = data['optimize_token']
+    outline = data['outline']
+    content_model = data['content_model']
+    api_key = data['api_key']
+    url = (data['proxy_url'] or "https://api.openai.com/v1") + "/chat/completions"
+    doc_type = data['doc_type']
+    top_k = int(data['top_k'])
+    similarity_threshold = float(data['similarity_threshold'])
+
+    system_prompt = ""
+    if doc_type == "1":
+        system_prompt = "You are ChatGPT, a large language model by OpenAI, and you are good at writing academic papers."
+    elif doc_type == "2":
+        system_prompt = "You are ChatGPT, a large language model by OpenAI, and you are good at writing reports."
+    elif doc_type == "3":
+        system_prompt = "You are ChatGPT, a large language model by OpenAI. From now on, you need to play the role of a writer. You are good at writing articles."
+
+    outline_parts = [part for part in outline.split("\n") if part.strip()]
+    
+
+    def generate():
+        messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "assistant", "content": outline}
+        ]
+        for part in outline_parts:
+            if is_paused:
+                        break
+            if part.startswith("##"):
+                search_queries = [part[2:].strip()]  
+                from getcsv import search_dataset
+
+                search_results = search_dataset(search_queries, top_k=top_k, similarity_threshold=similarity_threshold)
+                
+                # 提取匹配到的QA
+                matched_qa = ""
+                for result in search_results:
+                    question = result['question']
+                    answer = result['answer']
+                    matched_qa += f"Question: {question}\nAnswer: {answer}\n\n"
+            
+
+                if expand_outline.lower() == 'n':
+                    article_prompt = f'参考之前的整体大纲,以及已经生成的内容,为"{part}"部分扩写内容。在扩写中,严禁出现下一级小标题,要求语言通俗易懂,不要过于死板,善于使用各种修辞手法。在每次输出的开头注明小标题是哪个(要用##放到小标题前面)(不要输出其他小标题和其他小标题的内容),结尾必须换2行\n将以下内容作为你本次生成的知识库:\n{matched_qa}'
+                else:
+                    article_prompt = f'参考之前的整体大纲,以及已经生成的内容,为"{part}"部分扩写内容。你需要在##小标题的基础上再扩充###小小标题,要求语言通俗易懂,不要过于死板,善于使用各种修辞手法。在每次输出的开头注明小标题是哪个(要用##放到小标题前面),结尾必须换2行\n将以下内容作为你本次生成的知识库:\n{matched_qa}'
+                if optimize_token.lower() == 'y':
+                    messages = messages[:2]
+                messages.append({"role": "user", "content": article_prompt})
+                article_content = ""
+                for chunk in generate_content(messages, content_model, api_key, url):
+                    # if is_paused:
+                    #     break
+                    article_content += chunk
+                    yield chunk
+                if optimize_token.lower() == 'n':
+                    messages.append({"role": "assistant", "content": article_content})
+            else:
+                yield "\n\n"
+
+    return Response(stream_with_context(generate()), mimetype='text/plain')
+
+@app.route('/write_to_file', methods=['POST'])
+def write_to_file():
+    data = request.get_json()
+    title = data['title']
+    content = data['content']
+
+    file_path = f"{title}.txt"
+    with open(file_path, 'w', encoding='utf-8') as file:
+        file.write(content)
+
+    return jsonify({"message": "Content written to file successfully."})
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0')

emb.py

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+import requests
+import json
+import logging
+from typing import List, Tuple
+import pandas as pd
+import uuid
+
+# 设置日志记录
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# OpenAI API配置
+API_KEY = ""
+API_URL = ""
+MODEL = "text-embedding-ada-002"
+proxies = {
+    "http": "http://127.0.0.1:10808",
+    "https": "http://127.0.0.1:10808"
+}
+
+def generate_embeddings_from_qa_pairs(qa_pairs: List[Tuple[str, str]], api_key, api_url_base):
+    global API_KEY, API_URL
+    API_KEY = api_key
+    API_URL = f"{api_url_base}/embeddings"
+
+    df = process_qa_pairs(qa_pairs)
+    random_filename = f"output/qa_embeddings_{uuid.uuid4().hex}.csv"
+    df.to_csv(random_filename, index=False)
+    print(f"Embeddings saved to {random_filename}")
+    print(df)
+    
+def generate_embeddings(text: str) -> List[float]:
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {API_KEY}"
+    }
+
+    data = {
+        "input": text,
+        "model": MODEL
+    }
+
+    try:
+        response = requests.post(API_URL, headers=headers, json=data)
+        response.raise_for_status()
+        embedding = response.json()["data"][0]["embedding"]
+    except requests.exceptions.RequestException as e:
+        logging.error(f"OpenAI API request failed: {e}")
+        return []
+
+    return embedding
+
+def process_qa_pairs(qa_pairs: List[Tuple[str, str]]) -> pd.DataFrame:
+    data = []
+    for q, a in qa_pairs:
+        combined_text = f"Question: {q}\nAnswer: {a}"
+        embedding = generate_embeddings(combined_text)
+        data.append({"Question": q, "Answer": a, "Combined_Text": combined_text, "Embedding": embedding})
+    
+    df = pd.DataFrame(data)
+    return df
+
+if __name__ == "__main__":
+    qa_pairs = [
+        ("秦始皇在中国历史的地位如何？", "秦始皇在中国历史上具有极其重要的地位,他建立了第一个中央集权国家,也是中国第一位称皇帝的君主。他在十年时间里兼并六国,结束了春秋战国五百年分裂局面,使天下归于一统。他成功的把原本七零八散的地域文明重新整合在一起,成为中国此后两千多年封建文明的基石。统一的疆域、统一的文明、统一的法制和中央集权,使中华民族以一个整体骄傲的屹立在世界东方。"),
+        ("秦始皇在世界历史上的地位如何？", "秦始皇在世界史上也具有一定的地位。他建立了中国历史上第一个大一统的中央集权国家,结束了兵荒马乱的战国时代。他的统一疆域、统一文明、统一法制和中央集权的成就,使得中华民族以一个整体骄傲的屹立在世界东方。"),
+        ("Minecraft是什么类型的游戏？", "《我的世界》（Minecraft）是一款沙盒类电子游戏。")
+    ]
+
+    df = process_qa_pairs(qa_pairs)
+    random_filename = f"output/qa_embeddings_{uuid.uuid4().hex}.csv"
+    df.to_csv(random_filename, index=False)
+    print(f"Embeddings saved to {random_filename}")
+    print(df)

getcsv.py

@@ -0,0 +1,129 @@
+import requests
+import logging
+from typing import List, Tuple
+import pandas as pd
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.metrics.pairwise import cosine_similarity
+from typing import List, Tuple, Dict
+
+# 设置日志记录
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# OpenAI API配置
+API_KEY = "sk-u0S4iYA2kJmaDNBgBc48D2A6Fa904fF0B6E19dF0F6A39717"
+API_URL = "https://api.ltcld.cn/v1/embeddings"
+MODEL = "text-embedding-ada-002"
+
+def generate_embeddings(text: str) -> List[float]:
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {API_KEY}"
+    }
+
+    data = {
+        "input": text,
+        "model": MODEL
+    }
+
+    try:
+        response = requests.post(API_URL, headers=headers, json=data)
+        response.raise_for_status()
+        embedding = response.json()["data"][0]["embedding"]
+    except requests.exceptions.RequestException as e:
+        logging.error(f"OpenAI API request failed: {e}")
+        return []
+
+    return embedding
+
+def rerank_results(query: str, documents: List[str]) -> List[Tuple[str, float]]:
+    vectorizer = TfidfVectorizer()
+    
+    tfidf_matrix = vectorizer.fit_transform(documents)
+    
+    query_vector = vectorizer.transform([query])
+    
+    similarity_scores = cosine_similarity(query_vector, tfidf_matrix).flatten()
+    
+    reranked_results = list(zip(documents, similarity_scores))
+    
+    reranked_results.sort(key=lambda x: x[1], reverse=True)
+    
+    return reranked_results
+
+def search_dataset(queries: List[str], top_k: int = 5, similarity_threshold: float = 0.5) -> List[dict]:
+    results = []
+    
+    for query in queries:
+        query_embedding = generate_embeddings(query)
+        
+        embeddings = df['Embedding'].tolist()
+        similarity_scores = cosine_similarity([query_embedding], embeddings)[0]
+        df['Similarity'] = similarity_scores
+        
+        print(f"Similarity scores for query '{query}': {similarity_scores}")
+        
+        top_results = df.sort_values('Similarity', ascending=False).head(top_k)
+        
+        print(f"Top {top_k} results for query '{query}':")
+        print(top_results)
+        
+        query_results = []
+        for _, row in top_results.iterrows():
+            if row['Similarity'] >= similarity_threshold:
+                query_results.append({
+                    'question': row['Question'],
+                    'answer': row['Answer'],
+                    'similarity': row['Similarity']
+                })
+        
+        print(f"Filtered results for query '{query}': {query_results}")
+        
+        results.append(query_results)
+    
+    merged_results = []
+    for query_results in results:
+        merged_results.extend(query_results)
+    
+    print(f"Merged results: {merged_results}")
+    
+    for query in queries:
+        documents = [result['question'] + ' ' + result['answer'] for result in merged_results]
+        reranked_results = rerank_results(query, documents)
+        
+        final_results = []
+        for doc, score in reranked_results:
+            for result in merged_results:
+                if doc == result['question'] + ' ' + result['answer']:
+                    result['score'] = score
+                    final_results.append(result)
+                    break
+    
+    unique_results = []
+    seen_questions = set()
+    seen_answers = set()
+    for result in final_results:
+        if result['question'] not in seen_questions and result['answer'] not in seen_answers:
+            unique_results.append(result)
+            seen_questions.add(result['question'])
+            seen_answers.add(result['answer'])
+    
+    print(f"Unique results: {unique_results}")
+    
+    filtered_results = [result for result in unique_results if result['similarity'] >= similarity_threshold]    
+    print(f"Filtered results: {filtered_results}")
+    
+    return filtered_results
+df = pd.read_csv('output/qa_embeddings.csv')
+
+df['Embedding'] = df['Embedding'].apply(eval)
+
+# search_queries = ["原神","minecraft"]
+# search_results = search_dataset(search_queries, top_k=1, similarity_threshold=0.5)
+
+# for i, result in enumerate(search_results):
+#     print(f"Search Result {i+1}:")
+#     print(f"Question: {result['question']}")
+#     print(f"Answer: {result['answer']}")
+#     print(f"Similarity: {result['similarity']}")
+#     print(f"Rerank Score: {result['score']}")
+#     print("----------------------------------------------------")

key_words.py

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+import json
+import requests
+import sys
+
+def generate_key_words(key_word_model, api_key, url, outline):
+    messages = [
+        {"role": "system", "content": "你现在正在生成一篇论文,我将提供给你一份大纲,为了论文的准确真实性,你需要根据论文要求和大纲进行相关数据以及资料的搜索,现在,请你列出你需要进行搜索的关键句。由我来代替你上网进行搜索。注意:你的回复应当有且仅有你列出的搜索关键句,多个关键句之间用英文逗号隔开,不得输出其他任何解释。示例输出:关键句1,关键句2,关键句3"},
+        {"role": "user", "content": f"大纲为:{outline}"}
+    ]
+
+    payload = json.dumps({
+        "model": key_word_model,
+        "messages": messages
+    })
+    headers = {
+        'Accept': 'application/json',
+        'Authorization': api_key,
+        'Content-Type': 'application/json'
+    }
+
+    response = requests.post(url, headers=headers, data=payload)
+    response_data = response.json()
+
+    if 'choices' in response_data:
+        search_key_word = response_data['choices'][0]['message']['content']
+        print(search_key_word)
+    else:
+        print("Error: Unable to generate search keywords.")
+
+if __name__ == "__main__":
+    key_word_model = sys.argv[1]
+    api_key = sys.argv[2]
+    url = sys.argv[3]
+    outline = sys.argv[4]
+
+    generate_key_words(key_word_model, api_key, url, outline)

output/11.csv

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+Question,Answer,Combined_Text,Embedding
+秦始皇在中国历史的地位如何？,"秦始皇在中国历史上具有极其重要的地位,他建立了第一个中央集权国家,也是中国第一位称皇帝的君主。他在十年时间里兼并六国,结束了春秋战国五百年分裂局面,使天下归于一统。他成功的把原本七零八散的地域文明重新整合在一起,成为中国此后两千多年封建文明的基石。统一的疆域、统一的文明、统一的法制和中央集权,使中华民族以一个整体骄傲的屹立在世界东方。","Question: 秦始皇在中国历史的地位如何？
+Answer: 秦始皇在中国历史上具有极其重要的地位,他建立了第一个中央集权国家,也是中国第一位称皇帝的君主。他在十年时间里兼并六国,结束了春秋战国五百年分裂局面,使天下归于一统。他成功的把原本七零八散的地域文明重新整合在一起,成为中国此后两千多年封建文明的基石。统一的疆域、统一的文明、统一的法制和中央集权,使中华民族以一个整体骄傲的屹立在世界东方。","[0.007234594, -0.0042884815, 0.0012923528, -0.013952892, -0.017605685, -0.0030945477, -0.023207493, -0.0044724117, -0.024588585, 0.0029574065, 0.014688614, 0.01817361, -0.007931593, 0.017554056, -0.0067312056, 0.010590516, 0.016869964, -0.012313654, 0.009796712, 0.0042207176, -0.008338176, -0.03126171, -0.016005168, 0.001521459, -0.009635369, 0.031158447, 0.03046145, -0.003572121, 0.0077960654, -0.031829633, -0.0099516, 0.0131332725, -0.01717974, -0.005124235, -0.011642469, 0.0015133918, -0.014004522, -0.013333337, -0.008460796, -0.011500487, 0.005214587, 0.022858994, -0.00792514, 0.02842208, -0.0044562775, -0.0013165541, 0.0008978706, -0.033791557, -0.0064666043, 0.00254921, 0.008002584, 0.040425956, -0.023543086, -0.010861572, -0.025621176, -0.028809302, -0.03807681, 0.00948048, -0.022691198, -0.020484034, 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+秦始皇在世界历史上的地位如何？,"秦始皇在世界史上也具有一定的地位。他建立了中国历史上第一个大一统的中央集权国家,结束了兵荒马乱的战国时代。他的统一疆域、统一文明、统一法制和中央集权的成就,使得中华民族以一个整体骄傲的屹立在世界东方。","Question: 秦始皇在世界历史上的地位如何？
+Answer: 秦始皇在世界史上也具有一定的地位。他建立了中国历史上第一个大一统的中央集权国家,结束了兵荒马乱的战国时代。他的统一疆域、统一文明、统一法制和中央集权的成就,使得中华民族以一个整体骄傲的屹立在世界东方。","[0.018476626, -0.0092511615, 0.009996395, -0.014030929, -0.018528022, -0.0053547523, -0.025222264, 0.0026340114, -0.027984764, 0.005242325, 0.0070475866, 0.014557731, -0.0076900283, 0.019144766, -0.00618029, 0.021123486, 0.019607324, -0.010998604, 0.015688429, -0.0028235316, -0.0067199413, -0.030605927, -0.01247622, 0.0011804868, 0.0010351343, 0.019260405, 0.027959067, -0.0076900283, 0.013902441, -0.020840812, -0.0065657552, 0.01612529, -0.0171018, -0.0030387496, -0.010690232, 0.0027014678, -0.009443894, -0.017191742, -0.00084802316, -0.0132086035, 0.009373226, 0.029192556, -0.0026243748, 0.029629415, -0.009919302, -0.0024589458, 0.006668546, -0.034948833, -0.003196148, 0.0061931387, 0.015765522, 0.03656779, -0.0215218, -0.01142904, -0.026468601, -0.024862498, -0.036336508, 0.014416394, -0.014930347, -0.0104268305, 0.0070283134, 0.027111044, -0.025016684, -0.0026998615, 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+Minecraft是什么类型的游戏？,《我的世界》（Minecraft）是一款沙盒类电子游戏。,"Question: Minecraft是什么类型的游戏？
+Answer: 《我的世界》（Minecraft）是一款沙盒类电子游戏。","[-0.00040432002, -0.021055095, 0.013438331, -0.027286993, -0.03085174, -0.0034172854, -0.025927773, -0.02546615, -0.01415641, -0.02582519, 0.012989532, 0.024671134, -0.012374036, -0.019542001, -0.0048983227, 0.021016626, 0.016426051, 0.0005465733, 0.026876662, -0.0069243307, -0.007725758, 0.039366104, 0.0095850695, -0.022568189, -0.006523617, 0.007668055, 0.005273391, -0.016182417, 0.0035294853, 0.008790053, 0.014720614, -0.007879632, -0.0023610045, -0.015656682, -0.0042764153, 0.012194516, -0.007475713, -0.010694244, 0.0014577961, -0.0028338465, 0.02600471, 0.034365196, -0.0014369589, 0.007853987, -0.019516354, 0.022452785, -0.0052124825, -0.04390539, -0.027671678, 0.0016717771, 0.0094632525, 0.02641504, -0.00062230823, -0.01592596, -0.0027697324, -0.02238867, -0.012047053, 0.011367443, 0.028466694, -0.020708878, 0.0023610045, 0.03180063, -0.036391206, -0.003773119, -0.006097258, 0.013098526, 0.009399138, -0.009758177, 0.0061902236, 0.007623175, 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-0.021452602, -0.021324374, -0.014284638, -0.011367443]"

output/qa_embeddings.csv

@@ -0,0 +1 @@
+

qa.py

@@ -0,0 +1,96 @@
+import re
+import sys
+import requests
+import logging
+from typing import List, Tuple
+from emb import generate_embeddings_from_qa_pairs
+
+# 设置日志记录
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# OpenAI API配置
+API_URL = ""
+API_KEY = ""
+MODEL = "gpt-3.5-turbo"
+
+# 问答提示模板
+Prompt_AgentQA = {
+    "description": "<Context></Context> 标记中是一段文本,学习和分析它,并整理学习成果:\n- 提出问题并给出每个问题的答案。\n- 你的拆分整理不得包含除了文本以外的知识内容,你的所有答案都只能从文本中获取\n- 答案需详细完整,尽可能保留原文描述。\n- 答案可以包含普通文字、链接、代码、表格、公示、媒体链接等 Markdown 元素。\n- 最多提出 40 个问题。\n",
+    "fixedText": "请按以下格式整理学习成果:\n<Context>\n文本\n</Context>\nQ1: 问题。\nA1: 答案。\nQ2:\nA2:\n\n------\n\n我们开始吧!\n\n<Context>\n{{{(text)}}}\n</Context>\n"
+}
+
+def replace_variable(text: str, obj: dict) -> str:
+    for key, val in obj.items():
+        if isinstance(val, (str, int)):
+            text = text.replace(f"{{{{({key})}}}}", str(val))
+    return text or ''
+
+def generate_qa(text: str) -> List[Tuple[str, str]]:
+    system_prompt = f"{Prompt_AgentQA['description']}"
+    user_prompt = f"{replace_variable(Prompt_AgentQA['fixedText'], {'text': text})}"
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {API_KEY}"
+    }
+
+    data = {
+        "model": MODEL,
+        "messages": [
+        {
+            "role": "system",
+            "content": system_prompt
+        },
+        {
+            "role": "user",
+            "content": user_prompt
+        }
+    ],
+        "temperature": 0.3,
+        "stream": False
+    }
+
+    try:
+        response = requests.post(API_URL, headers=headers, json=data)
+        response.raise_for_status()
+        answer = response.json()["choices"][0]["message"]["content"]
+    except requests.exceptions.RequestException as e:
+        logging.error(f"OpenAI API request failed: {e}")
+        return []
+
+    return format_split_text(answer, text)
+
+def format_split_text(text: str, raw_text: str) -> List[Tuple[str, str]]:
+    text = text.replace(r"\\n", "\n")  
+    regex = r"Q\d+:(\s*)(.*)(\s*)A\d+:(\s*)([\s\S]*?)(?=Q\d|$)"  # 匹配Q和A的正则表达式
+    matches = re.findall(regex, text)
+
+    result = []
+    for match in matches:
+        q = match[1].strip()
+        a = match[4].strip()
+        if q:
+            result.append((q, a))
+
+    # 如果结果为空,直接将原文本拆分为块
+    if not result:
+        chunks = [raw_text[i:i+512] for i in range(0, len(raw_text), 512)]
+        result = [(chunk, '') for chunk in chunks]
+
+    return result
+
+def main(text, api_key, api_url_base):
+    global API_KEY, API_URL
+    API_KEY = api_key
+    API_URL = f"{api_url_base}/chat/completions"
+
+    qa_pairs = generate_qa(text)
+    generate_embeddings_from_qa_pairs(qa_pairs, api_key, api_url_base)
+    return qa_pairs
+
+if __name__ == "__main__":
+    text = sys.argv[1]  # 从命令行获取搜索结果作为text变量
+    api_key = sys.argv[2]
+    api_url_base = sys.argv[3]
+    main(text, api_key, api_url_base)
+    
+

requirements.txt

@@ -0,0 +1,193 @@
+aiofiles==23.2.1
+aiohttp==3.9.3
+aiosignal==1.3.1
+altgraph==0.17.4
+annotated-types==0.6.0
+anthropic==0.18.1
+anyio==3.7.1
+arxiv==2.1.0
+async-timeout==4.0.3
+asyncio==3.4.3
+attrs==23.2.0
+Babel==2.14.0
+bce-python-sdk==0.9.6
+beautifulsoup4==4.12.3
+bidict==0.23.1
+blinker==1.7.0
+Brotli==1.1.0
+cachetools==5.3.3
+certifi==2023.7.22
+cffi==1.16.0
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+colorlog==6.8.2
+contourpy==1.2.0
+cssselect==1.2.0
+cssselect2==0.7.0
+curl_cffi==0.6.2
+cycler==0.12.1
+dataclasses-json==0.6.4
+datasets==2.18.0
+dill==0.3.4
+distro==1.8.0
+docopt==0.6.2
+docx==0.2.4
+duckduckgo_search==5.1.0
+exceptiongroup==1.1.3
+fastapi==0.110.0
+feedfinder2==0.0.4
+feedparser==6.0.10
+filelock==3.13.1
+Flask==3.0.2
+flask-babel==4.0.0
+Flask-SocketIO==5.3.6
+fonttools==4.50.0
+frozenlist==1.4.1
+fsspec==2024.2.0
+func_timeout==4.3.5
+future==1.0.0
+google==3.0.0
+google-ai-generativelanguage==0.4.0
+google-api-core==2.18.0
+google-auth==2.29.0
+google-generativeai==0.4.1
+googleapis-common-protos==1.63.0
+greenlet==3.0.3
+grpcio==1.62.1
+grpcio-status==1.62.1
+h11==0.14.0
+html5lib==1.1
+htmldocx==0.0.6
+httpcore==1.0.2
+httpx==0.25.1
+huggingface-hub==0.21.3
+idna==3.4
+itsdangerous==2.1.2
+jieba==0.42.1
+jieba3k==0.35.1
+Jinja2==3.1.3
+joblib==1.3.2
+jsonpatch==1.33
+jsonpointer==2.4
+kiwisolver==1.4.5
+langchain==0.1.13
+langchain-community==0.0.30
+langchain-core==0.1.37
+langchain-google-genai==1.0.1
+langchain-openai==0.1.1
+langchain-text-splitters==0.0.1
+langsmith==0.1.35
+loguru==0.7.2
+lxml==5.1.0
+Markdown==3.6
+markdown-it-py==3.0.0
+markdown2==2.4.13
+MarkupSafe==2.1.5
+marshmallow==3.21.1
+matplotlib==3.8.3
+md2pdf==1.0.1
+mdurl==0.1.2
+mistune==3.0.2
+multidict==6.0.5
+multiprocess==0.70.12.2
+mypy-extensions==1.0.0
+newspaper3k==0.2.8
+nltk==3.8.1
+numpy==1.26.4
+onnx==1.16.0
+openai==1.14.3
+orjson==3.10.0
+outcome==1.3.0.post0
+packaging==23.2
+paddle2onnx==1.0.6
+paddlefsl==1.1.0
+paddlenlp==2.6.1
+pandas==2.2.1
+pefile==2023.2.7
+pillow==10.2.0
+playwright==1.42.0
+plotly==5.20.0
+proto-plus==1.23.0
+protobuf==3.20.2
+psutil==5.9.8
+pyarrow==15.0.2
+pyarrow-hotfix==0.6
+pyasn1==0.6.0
+pyasn1_modules==0.4.0
+pycparser==2.21
+pycryptodome==3.20.0
+pydantic==2.4.2
+pydantic_core==2.10.1
+pydyf==0.9.0
+pyee==11.0.1
+Pygments==2.17.2
+pyinstaller==6.5.0
+pyinstaller-hooks-contrib==2024.3
+PyMuPDF==1.24.0
+PyMuPDFb==1.24.0
+pyparsing==3.1.2
+pypdf==4.1.0
+pyperclip==1.8.2
+pyphen==0.14.0
+PySocks==1.7.1
+python-dateutil==2.9.0.post0
+python-docx==1.1.0
+python-dotenv==1.0.1
+python-engineio==4.9.0
+python-multipart==0.0.9
+python-socketio==5.11.2
+pytz==2024.1
+pywin32-ctypes==0.2.2
+PyYAML==6.0.1
+rarfile==4.1
+regex==2023.12.25
+requests==2.31.0
+requests-file==2.0.0
+rich==13.7.1
+rsa==4.9
+safetensors==0.4.2
+scikit-learn==1.4.1.post1
+scipy==1.12.0
+selenium==4.18.1
+sentencepiece==0.2.0
+seqeval==1.2.2
+sgmllib3k==1.0.0
+shellingham==1.5.4
+simple-websocket==1.0.0
+six==1.16.0
+smsactivate==1.5
+sniffio==1.3.0
+sortedcontainers==2.4.0
+soupsieve==2.5
+SQLAlchemy==2.0.29
+starlette==0.36.3
+tavily-python==0.3.1
+tenacity==8.2.3
+threadpoolctl==3.4.0
+tiktoken==0.5.2
+tinycss2==1.2.1
+tinysegmenter==0.3
+tldextract==5.1.2
+tokenizers==0.15.2
+tqdm==4.66.1
+trio==0.24.0
+trio-websocket==0.11.1
+typer==0.12.0
+typer-cli==0.12.0
+typer-slim==0.12.0
+typing-inspect==0.9.0
+typing_extensions==4.10.0
+tzdata==2024.1
+urllib3==2.2.1
+uvicorn==0.29.0
+visualdl==2.5.3
+weasyprint==61.2
+webdriver-manager==4.0.1
+webencodings==0.5.1
+Werkzeug==3.0.1
+win32-setctime==1.1.0
+wsproto==1.2.0
+xxhash==3.4.1
+yarl==1.9.4
+zopfli==0.2.3

search.py

@@ -0,0 +1,53 @@
+import requests
+import json
+import sys
+import sys
+import io
+import sys
+sys.stdout.reconfigure(encoding='utf-8')
+
+def search_bing(key_word, bing_api_key):
+    headers = {
+        "Ocp-Apim-Subscription-Key": bing_api_key,
+        "X-MSEdge-ClientID": "00B4230B74496E7A13CC2C1475056FF4",
+        "X-MSEdge-ClientIP": "11.22.33.44",
+        "X-Search-Location": "lat:55;long:-111;re:22",
+        "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/29.0.1547.65 Safari/537.36"
+    }
+    url = "https://api.bing.microsoft.com/v7.0/search"
+    params = {"q": key_word, "mkt": "zh-CN", "count": "2"}
+
+    proxies = {
+        "http": "http://127.0.0.1:10809",
+        "https": "http://127.0.0.1:10809"
+    }
+
+    response = requests.get(url, headers=headers, params=params, proxies=proxies)
+    json_data = response.json()
+
+    search_result = ""
+    for item in json_data.get("webPages", {}).get("value", []):
+        name = item.get("name", "")
+        snippet = item.get("snippet", "")
+        search_result += f"Name: {name}\nSnippet: {snippet}\n\n"
+
+    return search_result
+
+if __name__ == "__main__":
+    key_words_str = sys.argv[1]  # 将关键字作为一个字符串获取
+    bing_api_key = sys.argv[2]
+    api_key = sys.argv[3]
+    api_url_base = sys.argv[4]
+
+    key_words = key_words_str.split(',')  # 在代码中手动拆分关键字
+
+    search_result = ""
+    for key_word in key_words:
+        search_result += search_bing(key_word, bing_api_key)
+
+    sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8', errors='replace')
+
+    # 直接调用qa.py,并将search_result作为参数传递
+    # import qa
+    # qa.main(search_result, api_key, api_url_base)
+    print(search_result)

static/css/style.css

@@ -0,0 +1,403 @@
+:root {
+  --primary-color: #2196f3;
+  --secondary-color: #64b5f6;
+  --text-color: #e0e0e0;
+  --bg-color: #121212;
+  --input-bg-color: #1e1e1e;
+  --button-hover-color: #1976d2;
+  --delete-button-color: #f44336;
+  --accent-color: #ff9800;
+  --border-color: #424242;
+}
+
+body {
+  font-family: 'Roboto', sans-serif;
+  background-color: var(--bg-color);
+  color: var(--text-color);
+  margin: 0;
+  padding: 0;
+}
+
+.container {
+  max-width: 960px;
+  margin: 60px auto;
+  padding: 40px;
+  background-color: #1e1e1e;
+  border-radius: 12px;
+  box-shadow: 0 6px 10px rgba(0, 0, 0, 0.2);
+  border: 2px solid var(--border-color);
+  transition: transform 0.3s ease, box-shadow 0.3s ease;
+}
+
+.container:hover {
+  transform: translateY(-5px);
+  box-shadow: 0 10px 20px rgba(0, 0, 0, 0.3);
+}
+
+h1 {
+  text-align: center;
+  color: var(--primary-color);
+  font-size: 48px;
+  margin-bottom: 60px;
+  text-transform: uppercase;
+  letter-spacing: 3px;
+  text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
+  transition: color 0.3s ease, text-shadow 0.3s ease;
+}
+
+h1:hover {
+  color: var(--accent-color);
+  text-shadow: 3px 3px 6px rgba(0, 0, 0, 0.4);
+}
+
+.form-group {
+  margin-bottom: 30px;
+}
+
+label {
+  display: block;
+  font-weight: 500;
+  margin-bottom: 10px;
+  color: var(--text-color);
+  font-size: 18px;
+  text-transform: uppercase;
+  letter-spacing: 1px;
+  transition: color 0.3s ease;
+}
+
+label:hover {
+  color: var(--accent-color);
+}
+
+input[type="text"],
+select,
+textarea {
+  width: 100%;
+  padding: 15px;
+  border: none;
+  border-radius: 8px;
+  background-color: var(--input-bg-color);
+  color: var(--text-color);
+  font-size: 16px;
+  box-shadow: inset 0 2px 4px rgba(0, 0, 0, 0.1);
+  transition: box-shadow 0.3s ease, background-color 0.3s ease;
+}
+
+input[type="text"]:focus,
+select:focus,
+textarea:focus {
+  outline: none;
+  box-shadow: inset 0 2px 4px rgba(0, 0, 0, 0.1), 0 0 0 2px var(--secondary-color);
+  background-color: #2d2d2d;
+}
+
+button {
+  padding: 15px 30px;
+  background-color: var(--primary-color);
+  color: #fff;
+  border: none;
+  border-radius: 8px;
+  cursor: pointer;
+  transition: background-color 0.3s ease, transform 0.3s ease, box-shadow 0.3s ease;
+  font-size: 18px;
+  text-transform: uppercase;
+  letter-spacing: 2px;
+  box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+}
+
+button:hover {
+  background-color: var(--button-hover-color);
+  transform: translateY(-2px);
+  box-shadow: 0 6px 8px rgba(0, 0, 0, 0.2);
+}
+
+button:active {
+  transform: translateY(0);
+  box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+}
+
+#outline-container,
+#content-container,
+#key-word-container,
+#search-result-container {
+  margin-top: 60px;
+  border: 2px solid var(--border-color);
+  border-radius: 12px;
+  padding: 30px;
+  transition: border-color 0.3s ease, box-shadow 0.3s ease;
+}
+
+#outline-container:hover,
+#content-container:hover,
+#key-word-container:hover,
+#search-result-container:hover {
+  border-color: var(--accent-color);
+  box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+}
+
+h2 {
+  color: var(--secondary-color);
+  font-size: 36px;
+  margin-bottom: 30px;
+  text-transform: uppercase;
+  letter-spacing: 2px;
+  text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2);
+  position: relative;
+  display: inline-block;
+  transition: color 0.3s ease, text-shadow 0.3s ease;
+}
+
+h2::after {
+  content: '';
+  position: absolute;
+  bottom: -5px;
+  left: 0;
+  width: 100%;
+  height: 2px;
+  background-color: var(--accent-color);
+  transform: scaleX(0);
+  transition: transform 0.3s ease;
+}
+
+h2:hover {
+  color: var(--accent-color);
+  text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
+}
+
+h2:hover::after {
+  transform: scaleX(1);
+}
+
+#outline,
+#content,
+#search-result {
+  width: 100%;
+  min-height: 300px;
+  padding: 20px;
+  border: none;
+  border-radius: 8px;
+  background-color: var(--input-bg-color);
+  color: var(--text-color);
+  font-size: 16px;
+  line-height: 1.8;
+  box-shadow: inset 0 2px 4px rgba(0, 0, 0, 0.1);
+  resize: vertical;
+  transition: box-shadow 0.3s ease, background-color 0.3s ease;
+}
+
+#outline:focus,
+#content:focus,
+#search-result:focus {
+  outline: none;
+  box-shadow: inset 0 2px 4px rgba(0, 0, 0, 0.1), 0 0 0 2px var(--secondary-color);
+  background-color: #2d2d2d;
+}
+
+.key-word-button {
+  display: inline-block;
+  margin: 5px;
+  padding: 8px 16px;
+  background-color: #424242;
+  border: none;
+  border-radius: 20px;
+  cursor: pointer;
+  color: var(--text-color);
+  font-size: 14px;
+  text-transform: uppercase;
+  letter-spacing: 1px;
+  transition: background-color 0.3s ease, transform 0.3s ease, color 0.3s ease;
+}
+
+.key-word-button:hover {
+  background-color: var(--secondary-color);
+  transform: translateY(-2px);
+  color: #fff;
+}
+
+.key-word-button.selected {
+  background-color: var(--primary-color);
+  color: #fff;
+}
+
+.delete-button {
+  background-color: var(--delete-button-color);
+  color: #fff;
+  border: none;
+  border-radius: 50%;
+  width: 24px;
+  height: 24px;
+  line-height: 24px;
+  text-align: center;
+  font-size: 14px;
+  cursor: pointer;
+  margin-left: 8px;
+  transition: background-color 0.3s ease, transform 0.3s ease;
+}
+
+.delete-button:hover {
+  background-color: #d32f2f;
+  transform: scale(1.1);
+}
+
+#qa-result-container {
+  margin-top: 40px;
+  padding: 30px;
+  background-color: var(--input-bg-color);
+  border-radius: 8px;
+  box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+  border: 2px solid var(--border-color);
+  transition: border-color 0.3s ease, box-shadow 0.3s ease;
+}
+
+#qa-result-container:hover {
+  border-color: var(--accent-color);
+  box-shadow: 0 6px 8px rgba(0, 0, 0, 0.2);
+}
+
+.qa-item {
+  margin-bottom: 40px;
+  padding-bottom: 20px;
+  border-bottom: 1px solid var(--border-color);
+  transition: border-color 0.3s ease;
+}
+
+.qa-item:last-child {
+  margin-bottom: 0;
+  padding-bottom: 0;
+  border-bottom: none;
+}
+
+.qa-item:hover {
+  border-color: var(--accent-color);
+}
+
+.qa-item h3 {
+  color: var(--accent-color);
+  font-size: 24px;
+  margin-bottom: 15px;
+  text-transform: uppercase;
+  letter-spacing: 1px;
+  text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2);
+  transition: color 0.3s ease, text-shadow 0.3s ease;
+}
+
+.qa-item h3:hover {
+  color: var(--secondary-color);
+  text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
+}
+
+.qa-item p {
+  color: var(--text-color);
+  font-size: 16px;
+  line-height: 1.8;
+  transition: color 0.3s ease;
+}
+
+.qa-item p:hover {
+  color: #fff;
+}
+
+/* 动画效果 */
+@keyframes fadeIn {
+  0% {
+    opacity: 0;
+    transform: translateY(20px);
+  }
+  100% {
+    opacity: 1;
+    transform: translateY(0);
+  }
+}
+
+.container {
+  animation: fadeIn 0.6s ease;
+}
+
+@keyframes slideIn {
+  0% {
+    opacity: 0;
+    transform: translateX(-20px);
+  }
+  100% {
+    opacity: 1;
+    transform: translateX(0);
+  }
+}
+
+h1, h2, .form-group, #outline-container, #content-container, #key-word-container, #search-result-container, #qa-result-container {
+  animation: slideIn 0.6s ease;
+}
+
+/* 响应式设计 */
+@media screen and (max-width: 1024px) {
+  .container {
+    max-width: 90%;
+    padding: 30px;
+  }
+  
+  h1 {
+    font-size: 36px;
+    margin-bottom: 40px;
+  }
+  
+  h2 {
+    font-size: 30px;
+    margin-bottom: 20px;
+  }
+  
+  input[type="text"],
+  select,
+  textarea {
+    font-size: 14px;
+  }
+  
+  button {
+    font-size: 16px;
+    padding: 12px 24px;
+  }
+  
+  .qa-item h3 {
+    font-size: 20px;
+  }
+  
+  .qa-item p {
+    font-size: 14px;
+  }
+}
+
+@media screen and (max-width: 768px) {
+  .container {
+    margin: 30px auto;
+    padding: 20px;
+  }
+  
+  h1 {
+    font-size: 30px;
+    margin-bottom: 30px;
+  }
+  
+  h2 {
+    font-size: 24px;
+    margin-bottom: 15px;
+  }
+  
+  input[type="text"],
+  select,
+  textarea {
+    padding: 10px;
+    font-size: 12px;
+  }
+  
+  button {
+    font-size: 14px;
+    padding: 10px 20px;
+  }
+  
+  .qa-item h3 {
+    font-size: 18px;
+  }
+  
+  .qa-item p {
+    font-size: 12px;
+  }
+}

static/js/script.js

@@ -0,0 +1,384 @@
+document.addEventListener('DOMContentLoaded', function() {
+    const form = document.getElementById('article-form');
+    const outlineContainer = document.getElementById('outline-container');
+    const outlineElement = document.getElementById('outline');
+    const expandOutlineElement = document.getElementById('expand-outline');
+    const generateContentButton = document.getElementById('generate-content');
+    const contentContainer = document.getElementById('content-container');
+    const contentElement = document.getElementById('content');
+    const docType = document.getElementById('doc-type').value;  // 获取文档类型
+    const pauseContentButton = document.getElementById('pause-content');
+    
+
+    let isPaused = false;
+    let eventSource;
+    let controller = new AbortController();
+
+    form.addEventListener('submit', function(event) {
+        event.preventDefault();
+    
+        const formData = new FormData(form);
+        const requestData = {
+            outline_model: formData.get('outline_model'),
+            content_model: formData.get('content_model'),
+            proxy_url: formData.get('proxy_url'),
+            api_key: formData.get('api_key'),
+            title: formData.get('title'),
+            doc_type: formData.get('doc_type'),
+            notice: formData.get('notice'),
+        };
+    
+        outlineElement.value = '';
+        outlineContainer.style.display = 'block';
+    
+        // 添加加载状态
+        const generateOutlineButton = this.querySelector('button[type="submit"]');
+        generateOutlineButton.innerHTML = '<i class="fa fa-spinner fa-spin"></i> Generating Outline...';
+        generateOutlineButton.disabled = true;
+    
+        fetch('/generate_outline', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify(requestData)
+        })
+        .then(response => response.json())
+        .then(data => {
+            outlineElement.value = data.outline;
+            
+            // 移除加载状态
+            generateOutlineButton.innerHTML = 'Generate Outline';
+            generateOutlineButton.disabled = false;
+        })
+        .catch(error => {
+            console.error('Error:', error);
+            outlineElement.value = 'Failed to generate outline. Please check the console for more details.';
+            
+            // 移除加载状态
+            generateOutlineButton.innerHTML = 'Generate Outline';
+            generateOutlineButton.disabled = false;
+        });
+    });
+    
+    generateContentButton.addEventListener('click', function() {
+        const expandOutline = expandOutlineElement.value;
+        const optimizeToken = document.getElementById('optimize-token').value;
+        const outline = outlineElement.value;
+        const title = document.getElementById('title').value;
+        const contentModel = document.getElementById('content-model').value;
+        const apiKey = document.getElementById('api-key').value;
+        const proxyUrl = document.getElementById('proxy-url').value;
+        const topK = document.getElementById('top-k').value;
+        const similarityThreshold = document.getElementById('similarity-threshold').value;
+        eventSource = new EventSource('/generate_content');
+
+        const requestData = {
+            expand_outline: expandOutline,
+            //expand_outline: expandOutline,
+            optimize_token: optimizeToken,
+            outline: outline,
+            title: title,
+            content_model: contentModel,
+            api_key: apiKey,
+            proxy_url: proxyUrl,
+            doc_type: docType,
+            top_k: topK,
+            similarity_threshold: similarityThreshold
+        };
+
+        contentElement.innerText = 'Generating content...';
+        contentContainer.style.display = 'block';
+        pauseContentButton.style.display = 'inline-block';
+        controller = new AbortController();
+        const signal = controller.signal;
+
+
+        fetch('/generate_content', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify(requestData),
+            signal: signal
+        })
+        .then(response => {
+            if (!response.ok) {
+                throw new Error('Network response was not ok');
+            }
+            return response.body;
+        })
+        .then(body => {
+            const reader = body.getReader();
+            const decoder = new TextDecoder('utf-8');
+            return new ReadableStream({
+                start(controller) {
+                    function push() {
+                        reader.read().then(({ done, value }) => {
+                            if (done) {
+                                controller.close();
+                                return;
+                            }
+                            controller.enqueue(decoder.decode(value));
+                            push();
+                        });
+                    }
+                    push();
+                }
+            });
+        })
+        .then(stream => {
+            const reader = stream.getReader();
+            let fullContent = '';
+            function read() {
+                if (isPaused) {
+                    pauseContentButton.innerText = 'Resume Output';
+                    return;
+                }
+                reader.read().then(({ done, value }) => {
+                    if (done) {
+                        //pauseContentButton.style.display = 'none';
+                        // 内容生成完成后,将其发送到后端进行文件写入
+                        const title = document.getElementById('title').value;
+                        fetch('/write_to_file', {
+                            method: 'POST',
+                            headers: {
+                                'Content-Type': 'application/json'
+                            },
+                            body: JSON.stringify({ title: title, content: fullContent })
+                        })
+                        .then(response => response.json())
+                        .then(data => {
+                            console.log(data.message);
+                        })
+                        .catch(error => {
+                            console.error('Error:', error);
+                        });
+                        return;
+                    }
+                    fullContent += value;
+                    contentElement.innerText += value;
+                    read();
+                });
+            }
+            read();
+        })
+        .catch(error => {
+            console.error('Error:', error);
+            contentElement.innerText = 'Failed to generate content. Please check the console for more details.';
+        });
+    });
+
+    pauseContentButton.addEventListener('click', function() {
+        if (isPaused) {
+            fetch('/resume', { method: 'POST' })
+                .then(() => {
+                    isPaused = false;
+                    pauseContentButton.innerText = 'Pause Output';
+                });
+        } else {
+            controller.abort();
+            fetch('/pause', { method: 'POST' })
+                .then(() => {
+                    isPaused = true;
+                    pauseContentButton.innerText = 'Resume Output';
+                    
+                    // 在暂停时保存文件
+                    const title = document.getElementById('title').value;
+                    const content = contentElement.innerText;
+                    fetch('/write_to_file', {
+                        method: 'POST',
+                        headers: {
+                            'Content-Type': 'application/json'
+                        },
+                        body: JSON.stringify({ title: title, content: content })
+                    })
+                    .then(response => response.json())
+                    .then(data => {
+                        console.log(data.message);
+                    })
+                    .catch(error => {
+                        console.error('Error:', error);
+                    });
+                });
+        }
+    });
+    document.getElementById('generate-key-words').addEventListener('click', function() {
+        const keyWordModel = document.getElementById('key-word-model').value;
+        const apiKey = document.getElementById('api-key').value;
+        const proxyUrl = document.getElementById('proxy-url').value;
+        const outline = outlineElement.value;
+    
+        const requestData = {
+            key_word_model: keyWordModel,
+            api_key: apiKey,
+            proxy_url: proxyUrl,
+            outline: outline
+        };
+    
+        // 添加加载状态
+        const button = this;
+        button.innerHTML = '<i class="fa fa-spinner fa-spin"></i> Generating Key Words...';
+        button.disabled = true;
+    
+        fetch('/generate_key_words', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify(requestData)
+        })
+        .then(response => response.json())
+        .then(data => {
+            const keyWordContainer = document.getElementById('search-key-word-container');
+            keyWordContainer.innerHTML = ''; // 清空容器
+        
+            const keyWords = data.search_key_word.split(',');
+            keyWords.forEach(keyWord => {
+                const keyWordButton = document.createElement('button');
+                keyWordButton.innerText = keyWord;
+                keyWordButton.classList.add('key-word-button');
+                keyWordButton.addEventListener('click', function() {
+                    this.classList.toggle('selected');
+                });
+                keyWordContainer.appendChild(keyWordButton);
+            });
+            
+            // 移除加载状态
+            button.innerHTML = 'Generate Key Words';
+            button.disabled = false;
+        })
+        .catch(error => {
+            console.error('Error:', error);
+            
+            // 移除加载状态
+            button.innerHTML = 'Generate Key Words';
+            button.disabled = false;
+        });
+    });
+    document.getElementById('use-bing-search').addEventListener('change', function() {
+        const useBingSearch = this.value;
+        const keyWordContainer = document.getElementById('key-word-container');
+    
+        if (useBingSearch === 'y') {
+            keyWordContainer.style.display = 'block';
+        } else {
+            keyWordContainer.style.display = 'none';
+        }
+    });
+    document.getElementById('add-custom-key-word').addEventListener('click', function() {
+        const customKeyWord = document.getElementById('custom-key-word').value;
+        if (customKeyWord) {
+            const keyWordButton = document.createElement('button');
+            keyWordButton.innerText = customKeyWord;
+            keyWordButton.classList.add('key-word-button');
+            keyWordButton.addEventListener('click', function() {
+                this.classList.toggle('selected');
+            });
+    
+            document.getElementById('search-key-word-container').appendChild(keyWordButton);
+            document.getElementById('custom-key-word').value = '';
+        }
+    });
+    document.getElementById('print-selected-key-words').addEventListener('click', function() {
+        const selectedKeyWords = Array.from(document.querySelectorAll('.key-word-button.selected')).map(button => button.innerText);
+        console.log('Selected Key Words:', selectedKeyWords);
+    
+        const bingApiKey = document.getElementById('bing-api-key').value;
+        const proxyUrl = document.getElementById('proxy-url').value;
+        const apiKey = document.getElementById('api-key').value;
+    
+        // 添加加载状态
+        this.innerHTML = '<i class="fa fa-spinner fa-spin"></i> Searching...';
+        this.disabled = true;
+    
+        fetch('/search', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({ selected_key_words: selectedKeyWords, bing_api_key: bingApiKey, proxy_url: proxyUrl, api_key: apiKey })
+        })
+        .then(response => response.json())
+        .then(data => {
+            console.log('Search result:', data.search_result);
+            document.getElementById('search-result').value = data.search_result;
+            document.getElementById('search-result-container').style.display = 'block';
+            
+            // 移除加载状态
+            this.innerHTML = 'Search with Bing';
+            this.disabled = false;
+        })
+        .catch(error => {
+            console.error('Error:', error);
+            
+            // 移除加载状态
+            this.innerHTML = 'Search with Bing';
+            this.disabled = false;
+        });
+    });
+    
+    
+    const qaResultContainer = document.getElementById('qa-result-container');
+    const generateQABtn = document.getElementById('generate-qa-btn');
+    
+    generateQABtn.addEventListener('click', function() {
+        const searchResult = document.getElementById('search-result').value;
+        const apiKey = document.getElementById('api-key').value;
+        const proxyUrl = document.getElementById('proxy-url').value;
+        const topK = document.getElementById('top-k').value;
+        const similarityThreshold = document.getElementById('similarity-threshold').value;
+    
+        // 添加加载状态
+        const button = this;
+        button.innerHTML = '<i class="fa fa-spinner fa-spin"></i> Generating QA...';
+        button.disabled = true;
+    
+        fetch('/qa', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                search_result: searchResult,
+                api_key: apiKey,
+                proxy_url: proxyUrl,
+                top_k: topK,
+                similarity_threshold: similarityThreshold
+            })
+        })
+        .then(response => response.json())
+        .then(data => {
+            const qaResult = data.qa_result;
+            qaResultContainer.innerHTML = '';
+    
+            qaResult.forEach(([question, answer]) => {
+                const qaItem = document.createElement('div');
+                qaItem.classList.add('qa-item');
+    
+                const questionElement = document.createElement('h3');
+                questionElement.textContent = question;
+    
+                const answerElement = document.createElement('p');
+                answerElement.textContent = answer;
+    
+                qaItem.appendChild(questionElement);
+                qaItem.appendChild(answerElement);
+                qaResultContainer.appendChild(qaItem);
+            });
+            
+            // 移除加载状态
+            button.innerHTML = 'Generate QA';
+            button.disabled = false;
+        })
+        .catch(error => {
+            console.error('Error:', error);
+            
+            // 移除加载状态
+            button.innerHTML = 'Generate QA';
+            button.disabled = false;
+        });
+    });
+
+    
+});

templates/index.html

@@ -0,0 +1,123 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Article Generator</title>
+    <link rel="stylesheet" href="{{ url_for('static', filename='css/style.css') }}">
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.3/css/all.min.css">
+</head>
+<body>
+    <div class="container">
+        <h1>Article Generator</h1>
+        <form id="article-form">
+            <div class="form-group">
+                <label for="outline-model">Outline Model:</label>
+                <input type="text" id="outline-model" name="outline_model" required>
+            </div>
+            <div class="form-group">
+                <label for="content-model">Content Generation Model:</label>
+                <input type="text" id="content-model" name="content_model" required>
+            </div>
+            <div class="form-group">
+                <label for="proxy-url">Proxy URL:</label>
+                <input type="text" id="proxy-url" name="proxy_url" required>
+            </div>
+            <div class="form-group">
+                <label for="api-key">API Key:</label>
+                <input type="text" id="api-key" name="api_key" required>
+            </div>
+            <div class="form-group">
+                <label for="title">Title:</label>
+                <input type="text" id="title" name="title" required>
+            </div>
+            <div class="form-group">
+                <label for="doc-type">Document Type:</label>
+                <select id="doc-type" name="doc_type" required>
+                    <option value="1">论文</option>
+                    <option value="2">报告</option>
+                    <option value="3">文章</option>
+                </select>
+            </div>
+            <div class="form-group">
+                <label for="notice">Notice for AI:</label>
+                <textarea id="notice" name="notice" rows="4" required></textarea>
+            </div>
+            <button type="submit">Generate Outline</button>
+        </form>
+
+        <div id="outline-container" style="display: none;">
+            <h2>Generated Outline:</h2>
+            <textarea id="outline" rows="10"></textarea>
+            <div class="form-group">
+                <label for="expand-outline">Do you want to expand the outline further?</label>
+                <select id="expand-outline" name="expand_outline" required>
+                    <option value="y">Yes</option>
+                    <option value="n">No</option>
+                </select>
+            </div>
+            <div class="form-group">
+                <label for="optimize-token">是否开启token优化?</label>
+                <select id="optimize-token" name="optimize_token" required>
+                    <option value="y">开启</option>
+                    <option value="n">不开启</option>
+                </select>
+            </div>
+            <div class="form-group">
+                <label for="use-bing-search">是否启用调用外部 Bing 搜索 API?</label>
+                <select id="use-bing-search" name="use_bing_search" required>
+                    <option value="n">否</option>
+                    <option value="y">是</option>
+                </select>
+            </div>
+            
+            
+            <div id="key-word-container" style="display: none;">
+                <div class="form-group">
+                    <label for="key-word-model">关键词模型:</label>
+                    <input type="text" id="key-word-model" name="key_word_model" required>
+                </div>
+                <button id="generate-key-words">Generate Key Words</button>
+                <div id="search-key-word-container"></div>
+                <div class="form-group">
+                    <label for="custom-key-word">Custom Key Word:</label>
+                    <input type="text" id="custom-key-word" name="custom_key_word">
+                    <button id="add-custom-key-word">Add</button>
+                </div>
+                <div class="form-group">
+                    <label for="bing-api-key">Bing API Key:</label>
+                    <input type="text" id="bing-api-key" name="bing_api_key" required>
+                </div>
+                <div class="form-group">
+                    <label for="top-k">Top K:</label>
+                    <input type="number" id="top-k" name="top_k" value="5">
+                </div>
+                <div class="form-group">
+                    <label for="similarity-threshold">Similarity Threshold:</label>
+                    <input type="number" id="similarity-threshold" name="similarity_threshold" step="0.1" value="0.5">
+                </div>
+                <div id="search-result-container" style="display: none;">
+                    <h2>Search Result:</h2>
+                    <textarea id="search-result" rows="10"></textarea>
+                </div>
+                <button id="print-selected-key-words">Search with Bing</button>
+                <button id="generate-content">Generate Content</button>
+                
+            </div>
+            
+            <button id="generate-qa-btn">Generate QA</button>
+                <div id="qa-result-container"></div>
+        </div>
+
+        <div id="content-container" style="display: none;">
+            <h2>Generated Content:</h2>
+            <div id="content"></div>
+        </div>
+
+        <button id="pause-content" style="display: none;">Pause Output</button>
+
+    </div>
+
+    <script src="{{ url_for('static', filename='js/script.js') }}"></script>
+</body>
+</html>