From 56e6db5e92f3cf50a84283021e1b4d64b195edd7 Mon Sep 17 00:00:00 2001 From: HuangHai <10402852@qq.com> Date: Mon, 23 Jun 2025 21:12:56 +0800 Subject: [PATCH] 'commit' --- dsRag/T1_ManageMapping.py | 132 +++++++++--------- dsRag/T2_ImportTxt.py | 49 ++++--- dsRag/T3_DeepSeekRag.py | 10 +- dsRag/Txt/运行结果.txt | 110 +++------------ dsRag/Util/EmbeddingUtil.py | 7 + dsRag/Util/EsMappingUtil.py | 113 --------------- .../__pycache__/EmbeddingUtil.cpython-310.pyc | Bin 1224 -> 1100 bytes .../__pycache__/EsMappingUtil.cpython-310.pyc | Bin 2728 -> 0 bytes 8 files changed, 121 insertions(+), 300 deletions(-) delete mode 100644 dsRag/Util/EsMappingUtil.py delete mode 100644 dsRag/Util/__pycache__/EsMappingUtil.cpython-310.pyc diff --git a/dsRag/T1_ManageMapping.py b/dsRag/T1_ManageMapping.py index 654a4fce..914ef991 100644 --- a/dsRag/T1_ManageMapping.py +++ b/dsRag/T1_ManageMapping.py @@ -1,7 +1,6 @@ from elasticsearch import Elasticsearch from Config.Config import ES_CONFIG -from Util.EsMappingUtil import create_vector_index, delete_index, create_text_index, delete_text_index # 初始化ES连接 es = Elasticsearch( @@ -11,26 +10,81 @@ es = Elasticsearch( ssl_show_warn=ES_CONFIG["ssl_show_warn"] ) +def get_vector_mapping(dims=200): + """获取向量索引的mapping结构""" + return { + "properties": { + "content": { + "type": "text", + "analyzer": "ik_smart", + "search_analyzer": "ik_smart", + "fields": { + "keyword": { + "type": "keyword", + "ignore_above": 8192 + } + } + }, + "vector": { + "type": "dense_vector", + "dims": dims, + "index": True, + "similarity": "cosine" + }, + "timestamp": { + "type": "date", + "format": "strict_date_optional_time||epoch_millis" + } + } + } + +def get_text_mapping(): + """获取文本索引的mapping结构""" + return { + "properties": { + "raw_text": { + "type": "text", + "analyzer": "ik_smart", + "fielddata": True + }, + "timestamp": { + "type": "date", + "format": "strict_date_optional_time||epoch_millis" + } + } + } + def manage_index(action, index_type="vector", index_name=None, dims=200): - """管理Elasticsearch索引 - :param action: 'create'或'delete' - :param index_type: 'vector'或'text' - :param index_name: 索引名称(默认根据类型自动生成) - :param dims: 向量维度(仅向量索引有效) - """ + """管理Elasticsearch索引""" if index_name is None: index_name = "knowledge_base" if index_type == "vector" else "raw_texts" if action == "create": - if index_type == "vector": - return create_vector_index(index_name, dims) - else: - return create_text_index(index_name) + mapping = get_vector_mapping(dims) if index_type == "vector" else get_text_mapping() + + try: + if es.indices.exists(index=index_name): + print(f"索引 {index_name} 已存在") + return False + + es.indices.create(index=index_name, body={"mappings": mapping}) + print(f"索引 {index_name} 创建成功(使用ik_smart分词器)") + return True + except Exception as e: + print(f"创建索引失败: {str(e)}") + raise elif action == "delete": - if index_type == "vector": - return delete_index(index_name) - else: - return delete_text_index(index_name) + try: + if not es.indices.exists(index=index_name): + print(f"索引 {index_name} 不存在") + return False + + es.indices.delete(index=index_name) + print(f"索引 {index_name} 删除成功") + return True + except Exception as e: + print(f"删除索引失败: {str(e)}") + raise else: raise ValueError("action参数必须是'create'或'delete'") @@ -45,51 +99,3 @@ if __name__ == "__main__": # 创建新的原始文本索引 manage_index("create", "text") - -# 修改knowledge_base索引的mapping -knowledge_base_mapping = { - "properties": { - # 在knowledge_base_mapping中添加 - "content": { - "type": "text", - "analyzer": "ik_max_word", - "search_analyzer": "ik_smart", - "fields": { - "keyword": { - "type": "keyword", - "ignore_above": 8192 # 可以设置为1024/2048等更大值 - } - } - }, - # 在raw_texts_mapping中添加 - "raw_text": { - "type": "text", - "analyzer": "ik_max_word", - "fielddata": True # 允许对长文本进行聚合 - }, - "vector": { - "type": "dense_vector", - "dims": 200, - "index": True, - "similarity": "cosine" - }, - "timestamp": { - "type": "date", - "format": "strict_date_optional_time||epoch_millis" - } - } -} - -# 修改raw_texts索引的mapping -raw_texts_mapping = { - "properties": { - "raw_text": { - "type": "text", - "analyzer": "ik_max_word" - }, - "timestamp": { - "type": "date", - "format": "strict_date_optional_time||epoch_millis" - } - } -} diff --git a/dsRag/T2_ImportTxt.py b/dsRag/T2_ImportTxt.py index 2d28f67d..6b9a2d11 100644 --- a/dsRag/T2_ImportTxt.py +++ b/dsRag/T2_ImportTxt.py @@ -1,13 +1,21 @@ -import logging -from Util.EsMappingUtil import create_vector_index, create_text_index from Util.EmbeddingUtil import text_to_embedding # 修改导入 from Config.Config import ES_CONFIG from elasticsearch import Elasticsearch import re from tqdm import tqdm import datetime -import numpy as np +import logging + +# 在文件开头添加logger配置 +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +# 创建控制台handler并设置格式 +handler = logging.StreamHandler() +formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') +handler.setFormatter(formatter) +logger.addHandler(handler) def split_sentences(text): """按句分割文本""" @@ -18,30 +26,24 @@ def split_sentences(text): def save_to_es(text): """保存向量化文本和原始文本到ES""" - vector = text_to_embedding(text) # 修改函数调用 + vector = text_to_embedding(text) - # 检查向量是否有效 - if vector is None or (hasattr(vector, 'size')) and vector.size == 0: - logging.warning(f"跳过无效向量文本: {text}") - return None - - # 检查向量是否全为零或接近零 - if np.all(np.abs(vector) < 1e-6): - logging.warning(f"跳过零向量文本: {text}") - return None - - # 归一化向量以避免cosine相似度问题 - norm = np.linalg.norm(vector) - if norm > 0: - vector = vector / norm + if vector is None: + logger.warning(f"跳过无法生成向量的文本: {text}") + return doc = { 'text': text, - 'vector': vector.tolist(), - 'timestamp': datetime.datetime.now().isoformat() + 'vector': vector, + 'timestamp': datetime.datetime.now().isoformat(), + 'analyzer': 'ik_smart' } - es.index(index='knowledge_base', body=doc) - es.index(index='raw_texts', body={'text': text}) + + try: + es.index(index='knowledge_base', body=doc) + es.index(index='raw_texts', body={'raw_text': text}) + except Exception as e: + logger.error(f"保存文本到ES失败: {e}") def process_file(file_path): """处理文本文件""" @@ -64,8 +66,5 @@ if __name__ == '__main__': ssl_show_warn=ES_CONFIG['ssl_show_warn'] ) - create_vector_index() - create_text_index() - file_path = 'Txt/人口变化趋势对云南教育的影响.txt' process_file(file_path) \ No newline at end of file diff --git a/dsRag/T3_DeepSeekRag.py b/dsRag/T3_DeepSeekRag.py index 3263a9ef..0959fab1 100644 --- a/dsRag/T3_DeepSeekRag.py +++ b/dsRag/T3_DeepSeekRag.py @@ -68,16 +68,14 @@ def process_query(query): def search_related_data(query): """搜索与查询相关的数据""" # 向量搜索 - query_vector = text_to_embedding(query) vector_results = es.search( index=Config.ES_CONFIG['default_index'], body={ "query": { - "script_score": { - "query": {"match_all": {}}, - "script": { - "source": "cosineSimilarity(params.query_vector, 'vector') + 1.0", - "params": {"query_vector": query_vector} + "match": { + "content": { + "query": query, + "analyzer": "ik_smart" # 指定分词器 } } }, diff --git a/dsRag/Txt/运行结果.txt b/dsRag/Txt/运行结果.txt index 69d907eb..c4a3d6dc 100644 --- a/dsRag/Txt/运行结果.txt +++ b/dsRag/Txt/运行结果.txt @@ -1,94 +1,18 @@ -D:\anaconda3\envs\rag\python.exe D:\dsWork\dsProject\dsRag\T8_RAG.py -D:\anaconda3\envs\rag\lib\site-packages\jieba\_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. - import pkg_resources -2025-06-23 20:13:47,913 - INFO - loading projection weights from D:\Tencent_AILab_ChineseEmbedding\Tencent_AILab_ChineseEmbedding.txt -2025-06-23 20:13:49,382 - INFO - KeyedVectors lifecycle event {'msg': 'loaded (10000, 200) matrix of type float32 from D:\\Tencent_AILab_ChineseEmbedding\\Tencent_AILab_ChineseEmbedding.txt', 'binary': False, 'encoding': 'utf8', 'datetime': '2025-06-23T20:13:49.361378', 'gensim': '4.3.3', 'python': '3.10.18 | packaged by conda-forge | (main, Jun 4 2025, 14:42:04) [MSC v.1943 64 bit (AMD64)]', 'platform': 'Windows-10-10.0.19044-SP0', 'event': 'load_word2vec_format'} -2025-06-23 20:13:49,382 - INFO - 模型加载成功，词向量维度: 200 -D:\anaconda3\envs\rag\lib\site-packages\elasticsearch\_sync\client\__init__.py:311: SecurityWarning: Connecting to 'https://10.10.14.206:9200' using TLS with verify_certs=False is insecure - _transport = transport_class( -正在搜索与'整理云南省初中在校生情况文档'相关的数据... -Building prefix dict from the default dictionary ... -2025-06-23 20:13:50,520 - DEBUG - Building prefix dict from the default dictionary ... -Loading model from cache C:\Users\ADMINI~1\AppData\Local\Temp\jieba.cache -2025-06-23 20:13:50,520 - DEBUG - Loading model from cache C:\Users\ADMINI~1\AppData\Local\Temp\jieba.cache -Loading model cost 0.648 seconds. -2025-06-23 20:13:51,168 - DEBUG - Loading model cost 0.648 seconds. -Prefix dict has been built successfully. -2025-06-23 20:13:51,169 - DEBUG - Prefix dict has been built successfully. -2025-06-23 20:13:51,169 - INFO - 文本: 整理云南省初中在校生情况文档, 分词结果: ['整理', '云南省', '初中', '在校生', '情况', '文档'] -2025-06-23 20:13:51,169 - INFO - 有效词向量数量: 3 -2025-06-23 20:13:51,169 - INFO - 生成的平均向量: [ 0.18687634 -0.19447033 -0.04333766 -0.05068566 0.09433967]... -D:\anaconda3\envs\rag\lib\site-packages\urllib3\connectionpool.py:1097: InsecureRequestWarning: Unverified HTTPS request is being made to host '10.10.14.206'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings - warnings.warn( -2025-06-23 20:13:51,222 - INFO - POST https://10.10.14.206:9200/knowledge_base/_search [status:200 duration:0.051s] -D:\anaconda3\envs\rag\lib\site-packages\urllib3\connectionpool.py:1097: InsecureRequestWarning: Unverified HTTPS request is being made to host '10.10.14.206'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings - warnings.warn( -2025-06-23 20:13:51,231 - INFO - POST https://10.10.14.206:9200/raw_texts/_search [status:200 duration:0.009s] -找到10条相关数据 -正在生成报告... -2025-06-23 20:13:56,582 - INFO - Retrying request to /chat/completions in 0.469314 seconds -2025-06-23 20:14:02,067 - INFO - Retrying request to /chat/completions in 0.762535 seconds +2025-06-23 21:08:46,327 - INFO - POST https://10.10.14.206:9200/knowledge_base/_doc [status:400 duration:0.004s] +处理进度: 8%|▊ | 40/503 [00:01<00:17, 26.02句/s] Traceback (most recent call last): - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_transports\default.py", line 101, in map_httpcore_exceptions - yield - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_transports\default.py", line 250, in handle_request - resp = self._pool.handle_request(req) - File "D:\anaconda3\envs\rag\lib\site-packages\httpcore\_sync\connection_pool.py", line 256, in handle_request - raise exc from None - File "D:\anaconda3\envs\rag\lib\site-packages\httpcore\_sync\connection_pool.py", line 236, in handle_request - response = connection.handle_request( - File "D:\anaconda3\envs\rag\lib\site-packages\httpcore\_sync\connection.py", line 101, in handle_request - raise exc - File "D:\anaconda3\envs\rag\lib\site-packages\httpcore\_sync\connection.py", line 78, in handle_request - stream = self._connect(request) - File "D:\anaconda3\envs\rag\lib\site-packages\httpcore\_sync\connection.py", line 124, in _connect - stream = self._network_backend.connect_tcp(**kwargs) - File "D:\anaconda3\envs\rag\lib\site-packages\httpcore\_backends\sync.py", line 207, in connect_tcp - with map_exceptions(exc_map): - File "D:\anaconda3\envs\rag\lib\contextlib.py", line 153, in __exit__ - self.gen.throw(typ, value, traceback) - File "D:\anaconda3\envs\rag\lib\site-packages\httpcore\_exceptions.py", line 14, in map_exceptions - raise to_exc(exc) from exc -httpcore.ConnectTimeout: timed out - -The above exception was the direct cause of the following exception: - -Traceback (most recent call last): - File "D:\anaconda3\envs\rag\lib\site-packages\openai\_base_client.py", line 972, in request - response = self._client.send( - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_client.py", line 914, in send - response = self._send_handling_auth( - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_client.py", line 942, in _send_handling_auth - response = self._send_handling_redirects( - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_client.py", line 979, in _send_handling_redirects - response = self._send_single_request(request) - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_client.py", line 1014, in _send_single_request - response = transport.handle_request(request) - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_transports\default.py", line 249, in handle_request - with map_httpcore_exceptions(): - File "D:\anaconda3\envs\rag\lib\contextlib.py", line 153, in __exit__ - self.gen.throw(typ, value, traceback) - File "D:\anaconda3\envs\rag\lib\site-packages\httpx\_transports\default.py", line 118, in map_httpcore_exceptions - raise mapped_exc(message) from exc -httpx.ConnectTimeout: timed out - -The above exception was the direct cause of the following exception: - -Traceback (most recent call last): - File "D:\dsWork\dsProject\dsRag\T8_RAG.py", line 98, in - report = process_query(user_query) - File "D:\dsWork\dsProject\dsRag\T8_RAG.py", line 91, in process_query - report = generate_report(query, context) - File "D:\dsWork\dsProject\dsRag\T8_RAG.py", line 73, in generate_report - response = client.chat.completions.create( - File "D:\anaconda3\envs\rag\lib\site-packages\openai\_utils\_utils.py", line 287, in wrapper - return func(*args, **kwargs) - File "D:\anaconda3\envs\rag\lib\site-packages\openai\resources\chat\completions\completions.py", line 925, in create - return self._post( - File "D:\anaconda3\envs\rag\lib\site-packages\openai\_base_client.py", line 1249, in post - return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)) - File "D:\anaconda3\envs\rag\lib\site-packages\openai\_base_client.py", line 990, in request - raise APITimeoutError(request=request) from err -openai.APITimeoutError: Request timed out. - -进程已结束，退出代码为 1 + File "D:\dsWork\dsProject\dsRag\T2_ImportTxt.py", line 51, in + process_file(file_path) + File "D:\dsWork\dsProject\dsRag\T2_ImportTxt.py", line 38, in process_file + save_to_es(sentence) + File "D:\dsWork\dsProject\dsRag\T2_ImportTxt.py", line 26, in save_to_es + es.index(index='knowledge_base', body=doc) + File "D:\anaconda3\envs\rag\lib\site-packages\elasticsearch\_sync\client\utils.py", line 415, in wrapped + return api(*args, **kwargs) + File "D:\anaconda3\envs\rag\lib\site-packages\elasticsearch\_sync\client\__init__.py", line 2951, in index + return self.perform_request( # type: ignore[return-value] + File "D:\anaconda3\envs\rag\lib\site-packages\elasticsearch\_sync\client\_base.py", line 271, in perform_request + response = self._perform_request( + File "D:\anaconda3\envs\rag\lib\site-packages\elasticsearch\_sync\client\_base.py", line 351, in _perform_request + raise HTTP_EXCEPTIONS.get(meta.status, ApiError)( +elasticsearch.BadRequestError: BadRequestError(400, 'document_parsing_exception', '[1:828] failed to parse: The [cosine] similarity does not support vectors with zero magnitude. Preview of invalid vector: [0.0, 0.0, 0.0, 0.0, 0.0, ...]', The [cosine] similarity does not support vectors with zero magnitude. Preview of invalid vector: [0.0, 0.0, 0.0, 0.0, 0.0, ...]) \ No newline at end of file diff --git a/dsRag/Util/EmbeddingUtil.py b/dsRag/Util/EmbeddingUtil.py index 8a0031b4..210c7584 100644 --- a/dsRag/Util/EmbeddingUtil.py +++ b/dsRag/Util/EmbeddingUtil.py @@ -15,6 +15,13 @@ def text_to_embedding(text): words = jieba.lcut(text) # 使用 jieba 分词 logger.info(f"文本: {text}, 分词结果: {words}") embeddings = [model[word] for word in words if word in model] + + if not embeddings: + logger.warning(f"文本'{text}'无法生成有效向量") + return None # 或 raise ValueError("无法生成有效向量") + + avg_embedding = sum(embeddings) / len(embeddings) + return avg_embedding logger.info(f"有效词向量数量: {len(embeddings)}") if embeddings: avg_embedding = sum(embeddings) / len(embeddings) diff --git a/dsRag/Util/EsMappingUtil.py b/dsRag/Util/EsMappingUtil.py deleted file mode 100644 index b6f6a85d..00000000 --- a/dsRag/Util/EsMappingUtil.py +++ /dev/null @@ -1,113 +0,0 @@ -from elasticsearch import Elasticsearch -from Config.Config import ES_CONFIG - -es = Elasticsearch( - hosts=ES_CONFIG["hosts"], - basic_auth=ES_CONFIG["basic_auth"], - verify_certs=ES_CONFIG["verify_certs"], - ssl_show_warn=ES_CONFIG["ssl_show_warn"] -) - -def get_vector_mapping(dims=200): - """获取向量索引的mapping结构""" - return { - "mappings": { - "properties": { - "text": {"type": "text", "analyzer": "ik_max_word"}, - "vector": { - "type": "dense_vector", - "dims": dims, - "index": True, - "similarity": "cosine" - }, - "timestamp": {"type": "date"} - } - } - } - -def create_vector_index(index_name="knowledge_base", dims=200): - """创建带有向量字段的索引""" - mapping = get_vector_mapping(dims) - - try: - if es.indices.exists(index=index_name): - current_mapping = es.indices.get_mapping(index=index_name) - current_dims = current_mapping[index_name]["mappings"]["properties"]["vector"].get("dims", 0) - - if current_dims == dims: - print(f"索引 {index_name} 已存在且维度正确({dims}维)，无需操作") - return True - else: - print(f"警告：索引 {index_name} 已存在但维度不匹配(当前:{current_dims}维，需要:{dims}维)") - return False - - es.indices.create(index=index_name, body=mapping) - print(f"索引 {index_name} 创建成功({dims}维)") - return True - except Exception as e: - print(f"操作索引失败: {str(e)}") - raise - - -def delete_index(index_name): - """删除Elasticsearch索引""" - try: - if es.indices.exists(index=index_name): - es.indices.delete(index=index_name) - print(f"索引 {index_name} 删除成功") - return True - else: - print(f"索引 {index_name} 不存在") - return False - except Exception as e: - print(f"删除索引失败: {str(e)}") - raise - - -def create_text_index(index_name="raw_texts"): - """创建原始文本索引""" - mapping = { - "mappings": { - "properties": { - "text": { - "type": "text", - "fields": { - "keyword": { - "type": "keyword", - "ignore_above": 256 - } - } - }, - "timestamp": { - "type": "date" - } - } - } - } - - try: - if not es.indices.exists(index=index_name): - es.indices.create(index=index_name, body=mapping) - print(f"原始文本索引 {index_name} 创建成功") - return True - else: - print(f"原始文本索引 {index_name} 已存在") - return False - except Exception as e: - print(f"创建原始文本索引失败: {str(e)}") - raise - - -def delete_text_index(index_name="raw_texts"): - """删除原始文本索引""" - try: - if es.indices.exists(index=index_name): - es.indices.delete(index=index_name) - print(f"原始文本索引 {index_name} 删除成功") - return True - else: - print(f"原始文本索引 {index_name} 不存在") - return False - except Exception as e: - print(f"删除原始文本索引失败: {str(e)}") - raise \ No newline at end of file diff --git a/dsRag/Util/__pycache__/EmbeddingUtil.cpython-310.pyc b/dsRag/Util/__pycache__/EmbeddingUtil.cpython-310.pyc index 899fae43233515494ba441b092b7d1ce145e87b3..ce16b97a27dea4df5975d8f26c6781115e80403c 100644 GIT binary patch delta 233 zcmX@Xd4_{8pO=@50SI)1A~SSZH}W|$GR8~}U^FzSVJcQBVOqeF!dk;Hn<0g5F7rZ0 zMurrIV1^Rb8m4B(5;hPi%}~o+!yL?@$v*i$<2y}uph?fBwLhD)M!i%L$X0(geZjNM zQ=dS_KyOu@8aqcAK)0`QN#(()ba delta 348 zcmX@Zae|XCpO=@50SN3&BQrEuHu5<#GImW4U^I*?VOqeP!dk*o!_>?;n_(`~LPkc0 z8m1zv5>}81L|mGomKm&$t%f;;A%(q_Ns?hULkh=SX0U4JUEqwM2lbxfsP5`4~kQ zSr`QvrGO+C6Axn%$X%KOQS3SS>FGelMf{T+nf)0BCSPQhWV|)`HM10>;AA!yHvmF# Ba)1B; 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