From ed55b9ad37c2945c16ee4c438c3f010443143003 Mon Sep 17 00:00:00 2001 From: yanqiangmiffy <1185918903@qq.com> Date: Wed, 25 Sep 2024 16:00:37 +0800 Subject: [PATCH] =?UTF-8?q?features@=E5=AE=8C=E6=88=90=E6=9E=84=E5=BB=BA?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 3 +- api/apps/core/parser/views.py | 2 +- docs/quickstart.md | 185 +++++++++++++++++++++ docs/requirements-example.txt | 176 ++++++++++++++++++++ examples/rag/xunfei_rag.py | 159 +++++++++--------- gomate/modules/document/pdf_parser_fast.py | 38 ++++- gomate/version.py | 2 +- resources/install.png | Bin 0 -> 39833 bytes 8 files changed, 481 insertions(+), 84 deletions(-) create mode 100644 docs/requirements-example.txt create mode 100644 resources/install.png diff --git a/README.md b/README.md index 3a7623c..2563ba8 100644 --- a/README.md +++ b/README.md @@ -25,8 +25,9 @@ GoMate框架的设计核心在于其**高度的可配置性和模块化**，使 可靠的输入，可信的输出 -## 🏗️ 更新记录 +## 🎉 更新记录 +- gomate打包构建，支持pip和source两种方式安装 - 添加[MinerU文档解析](https://github.com/gomate-community/GoMate/blob/main/docs/mineru.md) ：一站式开源高质量数据提取工具，支持PDF/网页/多格式电子书提取`[20240907] ` - RAPTOR:递归树检索器实现 diff --git a/api/apps/core/parser/views.py b/api/apps/core/parser/views.py index 67166fc..a8a4d48 100644 --- a/api/apps/core/parser/views.py +++ b/api/apps/core/parser/views.py @@ -20,7 +20,7 @@ from gomate.modules.document.docx_parser import DocxParser from gomate.modules.document.excel_parser import ExcelParser from gomate.modules.document.html_parser import HtmlParser -from gomate.modules.document.pdf_parser import PdfSimParser +from gomate.modules.document.pdf_parser_fast import PdfSimParser from gomate.modules.document.ppt_parser import PptParser from gomate.modules.document.txt_parser import TextParser from gomate.modules.document.json_parser import JsonParser diff --git a/docs/quickstart.md b/docs/quickstart.md index e69de29..5c12961 100644 --- a/docs/quickstart.md +++ b/docs/quickstart.md @@ -0,0 +1,185 @@ +## GoMate快速上手教程 + +## 🛠️ 安装 + +### 方法1：使用`pip`安装 + +1. 创建conda环境（可选） + +```sehll +conda create -n gomate python=3.9 +conda activate gomate +``` + +2. 使用`pip`安装依赖 + +```sehll +pip install gomate +``` + +### 方法2：源码安装 + +1. 下载源码 + +```shell +git clone https://github.com/gomate-community/GoMate.git +``` + +2. 安装依赖 + +```shell +pip install -e . +``` + +## 🚀 快速上手 + +### 1 模块介绍📝 + +```text +├── applications +├── modules +| ├── citation:答案与证据引用 +| ├── document：文档解析与切块，支持多种文档类型 +| ├── generator：生成器 +| ├── judger：文档选择 +| ├── prompt：提示语 +| ├── refiner：信息总结 +| ├── reranker：排序模块 +| ├── retrieval：检索模块 +| └── rewriter：改写模块 +``` + + +### 2 导入模块 + +```python +import pickle +import pandas as pd +from tqdm import tqdm + +from gomate.modules.document.chunk import TextChunker +from gomate.modules.document.txt_parser import TextParser +from gomate.modules.document.utils import PROJECT_BASE +from gomate.modules.generator.llm import GLM4Chat +from gomate.modules.reranker.bge_reranker import BgeRerankerConfig, BgeReranker +from gomate.modules.retrieval.bm25s_retriever import BM25RetrieverConfig +from gomate.modules.retrieval.dense_retriever import DenseRetrieverConfig +from gomate.modules.retrieval.hybrid_retriever import HybridRetriever, HybridRetrieverConfig +``` + + +### 3 文档解析以及切片 + +```text +def generate_chunks(): + tp = TextParser()# 代表txt格式解析 + tc = TextChunker() + paragraphs = tp.parse(r'H:/2024-Xfyun-RAG/data/corpus.txt', encoding="utf-8") + print(len(paragraphs)) + chunks = [] + for content in tqdm(paragraphs): + chunk = tc.chunk_sentences([content], chunk_size=1024) + chunks.append(chunk) + + with open(f'{PROJECT_BASE}/output/chunks.pkl', 'wb') as f: + pickle.dump(chunks, f) +``` +>corpus.txt每行为一段新闻，可以自行选取paragraph读取的逻辑 + +`TextChunker`为文本块切块程序，主要特点使用[InfiniFlow/huqie](https://huggingface.co/InfiniFlow/huqie)作为文本检索的分词器，适合RAG场景。 + + +### 4 构建检索器 + +**配置检索器：** + +下面是一个混合检索器`HybridRetriever`配置参考，其中`HybridRetrieverConfig`需要由`BM25RetrieverConfig`和`DenseRetrieverConfig`配置构成。 + +```python +# BM25 and Dense Retriever configurations +bm25_config = BM25RetrieverConfig( + method='lucene', + index_path='indexs/description_bm25.index', + k1=1.6, + b=0.7 +) +bm25_config.validate() +print(bm25_config.log_config()) +dense_config = DenseRetrieverConfig( + model_name_or_path=embedding_model_path, + dim=1024, + index_path='indexs/dense_cache' +) +config_info = dense_config.log_config() +print(config_info) +# Hybrid Retriever configuration +# 由于分数框架不在同一维度，建议可以合并 +hybrid_config = HybridRetrieverConfig( + bm25_config=bm25_config, + dense_config=dense_config, + bm25_weight=0.7, # bm25检索结果权重 + dense_weight=0.3 # dense检索结果权重 +) +hybrid_retriever = HybridRetriever(config=hybrid_config) +``` + +**构建索引：** + +````python +# 构建索引 +hybrid_retriever.build_from_texts(corpus) +# 保存索引 +hybrid_retriever.save_index() +```` + +如果构建好索引之后，可以多次使用，直接跳过上面步骤，加载索引 +```text +hybrid_retriever.load_index() +``` + +**检索测试：** + +```python +query = "支付宝" +results = hybrid_retriever.retrieve(query, top_k=10) +print(len(results)) +# Output results +for result in results: + print(f"Text: {result['text']}, Score: {result['score']}") +``` + +### 5 排序模型 +```python +reranker_config = BgeRerankerConfig( + model_name_or_path=reranker_model_path +) +bge_reranker = BgeReranker(reranker_config) +``` +### 6 生成器配置 +```python +glm4_chat = GLM4Chat(llm_model_path) +``` + +### 6 检索问答 + +```python +# ====================检索问答========================= +test = pd.read_csv(test_path) +answers = [] +for question in tqdm(test['question'], total=len(test)): + search_docs = hybrid_retriever.retrieve(question, top_k=10) + search_docs = bge_reranker.rerank( + query=question, + documents=[doc['text'] for idx, doc in enumerate(search_docs)] + ) + # print(search_docs) + content = '\n'.join([f'信息[{idx}]：' + doc['text'] for idx, doc in enumerate(search_docs)]) + answer = glm4_chat.chat(prompt=question, content=content) + answers.append(answer[0]) + print(question) + print(answer[0]) + print("************************************/n") +test['answer'] = answers + +test[['answer']].to_csv(f'{PROJECT_BASE}/output/gomate_baseline.csv', index=False) +``` \ No newline at end of file diff --git a/docs/requirements-example.txt b/docs/requirements-example.txt new file mode 100644 index 0000000..7d7cb89 --- /dev/null +++ b/docs/requirements-example.txt @@ -0,0 +1,176 @@ +accelerate==0.34.2 +aiofiles==23.2.1 +aiohappyeyeballs==2.4.0 +aiohttp==3.10.6 +aiosignal==1.3.1 +annotated-types==0.7.0 +anyio==4.6.0 +async-timeout==4.0.3 +atlastk==0.13.3 +attrs==24.2.0 +beautifulsoup4==4.12.3 +bm25s==0.2.1 +certifi==2024.8.30 +cffi==1.17.1 +chardet==5.2.0 +charset-normalizer==3.3.2 +click==8.1.7 +cloudpickle==3.0.0 +codecov==2.1.13 +contourpy==1.3.0 +coverage==7.6.1 +cryptography==43.0.1 +cycler==0.12.1 +datasets==3.0.0 +datrie==0.8.2 +dill==0.3.8 +distro==1.9.0 +et-xmlfile==1.1.0 +exceptiongroup==1.2.2 +faiss-cpu==1.8.0.post1 +fastapi==0.115.0 +ffmpy==0.4.0 +filelock==3.16.1 +FlagEmbedding==1.2.11 +flake8==7.1.1 +flake8-docstrings==1.7.0 +fonttools==4.54.1 +frozenlist==1.4.1 +fsspec==2024.6.1 +future==1.0.0 +gradio==4.44.0 +gradio_client==1.3.0 +greenlet==3.1.1 +h11==0.14.0 +h5py==3.11.0 +hanziconv==0.3.2 +html2text==2024.2.26 +html_text==0.6.2 +httpcore==1.0.5 +httpx==0.27.2 +huggingface-hub==0.25.1 +hyperopt==0.2.7 +idna==3.10 +importlib_resources==6.4.5 +iniconfig==2.0.0 +jieba==0.42.1 +Jinja2==3.1.4 +jiter==0.5.0 +joblib==1.4.2 +jsonpatch==1.33 +jsonpointer==3.0.0 +kiwisolver==1.4.7 +langchain==0.3.0 +langchain-core==0.3.5 +langchain-huggingface==0.1.0 +langchain-openai==0.2.0 +langchain-text-splitters==0.3.0 +langsmith==0.1.128 +llvmlite==0.43.0 +loguru==0.7.2 +lxml==5.3.0 +lxml_html_clean==0.2.2 +markdown-it-py==3.0.0 +MarkupSafe==2.1.5 +matplotlib==3.9.2 +mccabe==0.7.0 +mdurl==0.1.2 +mpmath==1.3.0 +multidict==6.1.0 +multiprocess==0.70.16 +networkx==3.2.1 +nltk==3.9.1 +numba==0.60.0 +numpy==1.26.4 +nvidia-cublas-cu12==12.1.3.1 +nvidia-cuda-cupti-cu12==12.1.105 +nvidia-cuda-nvrtc-cu12==12.1.105 +nvidia-cuda-runtime-cu12==12.1.105 +nvidia-cudnn-cu12==9.1.0.70 +nvidia-cufft-cu12==11.0.2.54 +nvidia-curand-cu12==10.3.2.106 +nvidia-cusolver-cu12==11.4.5.107 +nvidia-cusparse-cu12==12.1.0.106 +nvidia-nccl-cu12==2.20.5 +nvidia-nvjitlink-cu12==12.6.68 +nvidia-nvtx-cu12==12.1.105 +openai==1.47.1 +openpyxl==3.1.5 +orjson==3.10.7 +packaging==24.1 +pandas==2.2.3 +pdfminer.six==20231228 +pdfplumber==0.11.4 +peft==0.12.0 +pillow==10.4.0 +pluggy==1.5.0 +protobuf==5.28.2 +psutil==6.0.0 +py4j==0.10.9.7 +pyarrow==17.0.0 +pycodestyle==2.12.1 +pycparser==2.22 +pydantic==2.9.2 +pydantic_core==2.23.4 +pydocstyle==6.3.0 +pydub==0.25.1 +pyflakes==3.2.0 +Pygments==2.18.0 +PyMuPDF==1.24.10 +PyMuPDFb==1.24.10 +pynndescent==0.5.13 +pyparsing==3.1.4 +PyPDF2==3.0.1 +pypdfium2==4.30.0 +pytest==8.3.3 +pytest-cov==5.0.0 +python-dateutil==2.9.0.post0 +python-docx==1.1.2 +python-magic==0.4.27 +python-multipart==0.0.10 +python-pptx==1.0.2 +pytz==2024.2 +PyYAML==6.0.2 +readability==0.3.1 +regex==2024.9.11 +requests==2.32.3 +rich==13.8.1 +ruff==0.6.7 +safetensors==0.4.5 +scikit-learn==1.5.2 +scipy==1.13.1 +semantic-version==2.10.0 +sentence-transformers==3.1.1 +sentencepiece==0.2.0 +shellingham==1.5.4 +six==1.16.0 +sniffio==1.3.1 +snowballstemmer==2.2.0 +soupsieve==2.6 +SQLAlchemy==2.0.35 +starlette==0.38.6 +sympy==1.13.3 +tenacity==8.5.0 +threadpoolctl==3.5.0 +tiktoken==0.7.0 +tokenizers==0.19.1 +tomli==2.0.1 +tomlkit==0.12.0 +torch==2.4.1 +tortoise==0.1.1 +tqdm==4.66.5 +transformers==4.44.2 +triton==3.0.0 +typer==0.12.5 +typing_extensions==4.12.2 +tzdata==2024.2 +umap-learn==0.5.6 +urllib3==2.2.3 +uvicorn==0.30.6 +websockets==12.0 +xgboost==2.1.1 +XlsxWriter==3.2.0 +xpinyin==0.7.6 +xxhash==3.5.0 +yarl==1.12.1 +zipp==3.20.2 diff --git a/examples/rag/xunfei_rag.py b/examples/rag/xunfei_rag.py index df663d9..edda83e 100644 --- a/examples/rag/xunfei_rag.py +++ b/examples/rag/xunfei_rag.py @@ -27,90 +27,91 @@ def generate_chunks(): pickle.dump(chunks, f) -if __name__ == '__main__': +# if __name__ == '__main__': - # test_path="H:/2024-Xfyun-RAG/data/test_question.csv" - # embedding_model_path="H:/pretrained_models/mteb/bge-m3" - # llm_model_path="H:/pretrained_models/llm/Qwen2-1.5B-Instruct" +# test_path="H:/2024-Xfyun-RAG/data/test_question.csv" +# embedding_model_path="H:/pretrained_models/mteb/bge-m3" +# llm_model_path="H:/pretrained_models/llm/Qwen2-1.5B-Instruct" - test_path = "/data/users/searchgpt/yq/GoMate_dev/data/competitions/xunfei/test_question.csv" - embedding_model_path = "/data/users/searchgpt/pretrained_models/bge-large-zh-v1.5" - llm_model_path = "/data/users/searchgpt/pretrained_models/glm-4-9b-chat" - # ====================文件解析+切片========================= - # generate_chunks() - with open(f'{PROJECT_BASE}/output/chunks.pkl', 'rb') as f: - chunks = pickle.load(f) - corpus = [] - for chunk in chunks: - corpus.extend(chunk) +test_path = "/data/users/searchgpt/yq/GoMate_dev/data/competitions/xunfei/test_question.csv" +embedding_model_path = "/data/users/searchgpt/pretrained_models/bge-large-zh-v1.5" +llm_model_path = "/data/users/searchgpt/pretrained_models/glm-4-9b-chat" +reranker_model_path = "/data/users/searchgpt/pretrained_models/bge-reranker-large" +# ====================文件解析+切片========================= +# generate_chunks() +with open(f'{PROJECT_BASE}/output/chunks.pkl', 'rb') as f: + chunks = pickle.load(f) +corpus = [] +for chunk in chunks: + corpus.extend(chunk) - # ====================检索器配置========================= - # BM25 and Dense Retriever configurations - bm25_config = BM25RetrieverConfig( - method='lucene', - index_path='indexs/description_bm25.index', - k1=1.6, - b=0.7 - ) - bm25_config.validate() - print(bm25_config.log_config()) - dense_config = DenseRetrieverConfig( - model_name_or_path=embedding_model_path, - dim=1024, - index_path='indexs/dense_cache' - ) - config_info = dense_config.log_config() - print(config_info) - # Hybrid Retriever configuration - # 由于分数框架不在同一维度，建议可以合并 - hybrid_config = HybridRetrieverConfig( - bm25_config=bm25_config, - dense_config=dense_config, - bm25_weight=0.7, # bm25检索结果权重 - dense_weight=0.3 # dense检索结果权重 - ) - hybrid_retriever = HybridRetriever(config=hybrid_config) - # 构建索引 - # hybrid_retriever.build_from_texts(corpus) - # 保存索引 - # hybrid_retriever.save_index() - # 加载索引 - hybrid_retriever.load_index() +# ====================检索器配置========================= +# BM25 and Dense Retriever configurations +bm25_config = BM25RetrieverConfig( + method='lucene', + index_path='indexs/description_bm25.index', + k1=1.6, + b=0.7 +) +bm25_config.validate() +print(bm25_config.log_config()) +dense_config = DenseRetrieverConfig( + model_name_or_path=embedding_model_path, + dim=1024, + index_path='indexs/dense_cache' +) +config_info = dense_config.log_config() +print(config_info) +# Hybrid Retriever configuration +# 由于分数框架不在同一维度，建议可以合并 +hybrid_config = HybridRetrieverConfig( + bm25_config=bm25_config, + dense_config=dense_config, + bm25_weight=0.7, # bm25检索结果权重 + dense_weight=0.3 # dense检索结果权重 +) +hybrid_retriever = HybridRetriever(config=hybrid_config) +# 构建索引 +# hybrid_retriever.build_from_texts(corpus) +# 保存索引 +# hybrid_retriever.save_index() +# 加载索引 +hybrid_retriever.load_index() - # ====================检索测试========================= - query = "支付宝" - results = hybrid_retriever.retrieve(query, top_k=10) - print(len(results)) - # Output results - for result in results: - print(f"Text: {result['text']}, Score: {result['score']}") +# ====================检索测试========================= +query = "支付宝" +results = hybrid_retriever.retrieve(query, top_k=10) +print(len(results)) +# Output results +for result in results: + print(f"Text: {result['text']}, Score: {result['score']}") - # ====================排序配置========================= - reranker_config = BgeRerankerConfig( - model_name_or_path="/data/users/searchgpt/pretrained_models/bge-reranker-large" - ) - bge_reranker = BgeReranker(reranker_config) +# ====================排序配置========================= +reranker_config = BgeRerankerConfig( + model_name_or_path=reranker_model_path +) +bge_reranker = BgeReranker(reranker_config) - # ====================生成器配置========================= - # qwen_chat = QwenChat(llm_model_path) - glm4_chat = GLM4Chat(llm_model_path) +# ====================生成器配置========================= +# qwen_chat = QwenChat(llm_model_path) +glm4_chat = GLM4Chat(llm_model_path) - # ====================检索问答========================= - test = pd.read_csv(test_path) - answers = [] - for question in tqdm(test['question'], total=len(test)): - search_docs = hybrid_retriever.retrieve(question, top_k=10) - search_docs = bge_reranker.rerank( - query=question, - documents=[doc['text'] for idx, doc in enumerate(search_docs)] - ) - # print(search_docs) - content = '\n'.join([f'信息[{idx}]：' + doc['text'] for idx, doc in enumerate(search_docs)]) - answer = glm4_chat.chat(prompt=question, content=content) - answers.append(answer[0]) - print(question) - print(answer[0]) - print("************************************/n") - test['answer'] = answers +# ====================检索问答========================= +test = pd.read_csv(test_path) +answers = [] +for question in tqdm(test['question'], total=len(test)): + search_docs = hybrid_retriever.retrieve(question, top_k=10) + search_docs = bge_reranker.rerank( + query=question, + documents=[doc['text'] for idx, doc in enumerate(search_docs)] + ) + # print(search_docs) + content = '\n'.join([f'信息[{idx}]：' + doc['text'] for idx, doc in enumerate(search_docs)]) + answer = glm4_chat.chat(prompt=question, content=content) + answers.append(answer[0]) + print(question) + print(answer[0]) + print("************************************/n") +test['answer'] = answers - test[['answer']].to_csv(f'{PROJECT_BASE}/output/gomate_baseline.csv', index=False) +test[['answer']].to_csv(f'{PROJECT_BASE}/output/gomate_baseline.csv', index=False) diff --git a/gomate/modules/document/pdf_parser_fast.py b/gomate/modules/document/pdf_parser_fast.py index 2cb078d..7adefad 100644 --- a/gomate/modules/document/pdf_parser_fast.py +++ b/gomate/modules/document/pdf_parser_fast.py @@ -11,10 +11,10 @@ """ import re from io import BytesIO - +from PyPDF2 import PdfReader as pdf2_read import fitz from tqdm import tqdm - +import logging class PdfParserUsingPyMuPDF(): """ @@ -63,6 +63,40 @@ def parse( return final_texts + final_tables +class PdfSimParser(object): + def parse(self, filename, from_page=0, to_page=100000, **kwargs): + self.outlines = [] + lines = [] + try: + self.pdf = pdf2_read( + filename if isinstance( + filename, str) else BytesIO(filename)) + for page in self.pdf.pages[from_page:to_page]: + lines.extend([t for t in page.extract_text().split("\n")]) + + outlines = self.pdf.outline + + def dfs(arr, depth): + for a in arr: + if isinstance(a, dict): + self.outlines.append((a["/Title"], depth)) + continue + dfs(a, depth + 1) + + dfs(outlines, 0) + except Exception as e: + logging.warning(f"Outlines exception: {e}") + if not self.outlines: + logging.warning(f"Miss outlines") + + return lines + + def crop(self, ck, need_position): + raise NotImplementedError + + @staticmethod + def remove_tag(txt): + raise NotImplementedError if __name__ == '__main__': pdf_parser = PdfParserUsingPyMuPDF() diff --git a/gomate/version.py b/gomate/version.py index 040a655..de54c15 100644 --- a/gomate/version.py +++ b/gomate/version.py @@ -1,3 +1,3 @@ """GoMate version file.""" -__version__ = '0.0.1' +__version__ = '0.0.13' diff --git a/resources/install.png b/resources/install.png new file mode 100644 index 0000000000000000000000000000000000000000..13d3fb8e383e2308a19f25ba9e9a00f088534d38 GIT binary patch literal 39833 zcmbTecT`i^yFWY@q<08X0@76oAP`DuLkBT{f=EI~q=Y6_5s{G+X;PIEdXb`p79bP_ 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