diff --git a/README.md b/README.md index 953a049..f529f42 100644 --- a/README.md +++ b/README.md @@ -42,7 +42,7 @@ 🚩 本项目未涉及微调、训练过程，但可利用微调或训练对本项目效果进行优化。 -🌐 [AutoDL 镜像](https://www.codewithgpu.com/i/chatchat-space/Langchain-Chatchat/Langchain-Chatchat) 中 `v11` 版本所使用代码已更新至本项目 `v0.2.7` 版本。 +🌐 [AutoDL 镜像](https://www.codewithgpu.com/i/chatchat-space/Langchain-Chatchat/Langchain-Chatchat) 中 `v13` 版本所使用代码已更新至本项目 `v0.2.9` 版本。 🐳 [Docker 镜像](registry.cn-beijing.aliyuncs.com/chatchat/chatchat:0.2.6) 已经更新到 ```0.2.7``` 版本。 @@ -67,10 +67,10 @@ docker run -d --gpus all -p 80:8501 registry.cn-beijing.aliyuncs.com/chatchat/ch ### 1. 环境配置 -+ 首先，确保你的机器安装了 Python 3.8 - 3.10 ++ 首先，确保你的机器安装了 Python 3.8 - 3.11 ``` $ python --version -Python 3.10.12 +Python 3.11.7 ``` 接着，创建一个虚拟环境，并在虚拟环境内安装项目的依赖 ```shell @@ -88,6 +88,7 @@ $ pip install -r requirements_webui.txt # 默认依赖包括基本运行环境（FAISS向量库）。如果要使用 milvus/pg_vector 等向量库，请将 requirements.txt 中相应依赖取消注释再安装。 ``` +请注意，LangChain-Chatchat `0.2.x` 系列是针对 Langchain `0.0.x` 系列版本的，如果你使用的是 Langchain `0.1.x` 系列版本，需要降级。 ### 2， 模型下载 如需在本地或离线环境下运行本项目，需要首先将项目所需的模型下载至本地，通常开源 LLM 与 Embedding 模型可以从 [HuggingFace](https://huggingface.co/models) 下载。 @@ -148,7 +149,7 @@ $ python startup.py -a [![Telegram](https://img.shields.io/badge/Telegram-2CA5E0?style=for-the-badge&logo=telegram&logoColor=white "langchain-chatglm")](https://t.me/+RjliQ3jnJ1YyN2E9) ### 项目交流群 -二维码 +二维码 🎉 Langchain-Chatchat 项目微信交流群，如果你也对本项目感兴趣，欢迎加入群聊参与讨论交流。 diff --git a/README_en.md b/README_en.md index c0b88ab..cfe21e0 100644 --- a/README_en.md +++ b/README_en.md @@ -55,10 +55,10 @@ The main process analysis from the aspect of document process: 🚩 The training or fine-tuning are not involved in the project, but still, one always can improve performance by do these. -🌐 [AutoDL image](registry.cn-beijing.aliyuncs.com/chatchat/chatchat:0.2.5) is supported, and in v9 the codes are update -to v0.2.5. +🌐 [AutoDL image](registry.cn-beijing.aliyuncs.com/chatchat/chatchat:0.2.5) is supported, and in v13 the codes are update +to v0.2.9. -🐳 [Docker image](registry.cn-beijing.aliyuncs.com/chatchat/chatchat:0.2.5) +🐳 [Docker image](registry.cn-beijing.aliyuncs.com/chatchat/chatchat:0.2.7) ## Pain Points Addressed @@ -98,6 +98,7 @@ $ pip install -r requirements_webui.txt # 默认依赖包括基本运行环境（FAISS向量库）。如果要使用 milvus/pg_vector 等向量库，请将 requirements.txt 中相应依赖取消注释再安装。 ``` +Please note that the LangChain-Chachat `0.2.x` series is for the Langchain `0.0.x` series version. If you are using the Langchain `0.1.x` series version, you need to downgrade. ### Model Download diff --git a/img/qr_code_82.jpg b/img/qr_code_82.jpg deleted file mode 100644 index c3e0cfe..0000000 Binary files a/img/qr_code_82.jpg and /dev/null differ diff --git a/img/qr_code_83.jpg b/img/qr_code_83.jpg deleted file mode 100644 index bfde76a..0000000 Binary files a/img/qr_code_83.jpg and /dev/null differ diff --git a/img/qr_code_85.jpg b/img/qr_code_85.jpg new file mode 100644 index 0000000..d294f22 Binary files /dev/null and b/img/qr_code_85.jpg differ diff --git a/img/qr_code_86.jpg b/img/qr_code_86.jpg new file mode 100644 index 0000000..f353a04 Binary files /dev/null and b/img/qr_code_86.jpg differ diff --git a/init_database.py b/init_database.py index dc4743a..a394b75 100644 --- a/init_database.py +++ b/init_database.py @@ -6,7 +6,6 @@ from configs.model_config import NLTK_DATA_PATH, EMBEDDING_MODEL import nltk nltk.data.path = [NLTK_DATA_PATH] + nltk.data.path from datetime import datetime -import sys if __name__ == "__main__": @@ -50,11 +49,11 @@ if __name__ == "__main__": ) parser.add_argument( "-i", - "--increament", + "--increment", action="store_true", help=(''' update vector store for files exist in local folder and not exist in database. - use this option if you want to create vectors increamentally. + use this option if you want to create vectors incrementally. ''' ) ) @@ -100,7 +99,7 @@ if __name__ == "__main__": if args.clear_tables: reset_tables() - print("database talbes reseted") + print("database tables reset") if args.recreate_vs: create_tables() @@ -110,8 +109,8 @@ if __name__ == "__main__": import_from_db(args.import_db) elif args.update_in_db: folder2db(kb_names=args.kb_name, mode="update_in_db", embed_model=args.embed_model) - elif args.increament: - folder2db(kb_names=args.kb_name, mode="increament", embed_model=args.embed_model) + elif args.increment: + folder2db(kb_names=args.kb_name, mode="increment", embed_model=args.embed_model) elif args.prune_db: prune_db_docs(args.kb_name) elif args.prune_folder: diff --git a/requirements.txt b/requirements.txt index 6c9d4df..9c6e60d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,5 @@ # API requirements -# On Windows system, install the cuda version manually from https://pytorch.org/ torch~=2.1.2 torchvision~=0.16.2 torchaudio~=2.1.2 @@ -8,30 +7,30 @@ xformers==0.0.23.post1 transformers==4.36.2 sentence_transformers==2.2.2 -langchain==0.0.352 +langchain==0.0.354 langchain-experimental==0.0.47 pydantic==1.10.13 fschat==0.2.34 -openai~=1.6.0 -fastapi>=0.105 -sse_starlette +openai~=1.7.1 +fastapi~=0.108.0 +sse_starlette==1.8.2 nltk>=3.8.1 uvicorn>=0.24.0.post1 -starlette~=0.27.0 +starlette~=0.32.0 unstructured[all-docs]==0.11.0 python-magic-bin; sys_platform == 'win32' SQLAlchemy==2.0.19 -faiss-cpu~=1.7.4 # `conda install faiss-gpu -c conda-forge` if you want to accelerate with gpus -accelerate==0.24.1 +faiss-cpu~=1.7.4 # `conda install faiss-gpu -c conda-forge` if you want to accelerate with gpus +accelerate~=0.24.1 spacy~=3.7.2 PyMuPDF~=1.23.8 rapidocr_onnxruntime==1.3.8 -requests>=2.31.0 -pathlib>=1.0.1 -pytest>=7.4.3 -numexpr>=2.8.6 # max version for py38 -strsimpy>=0.2.1 -markdownify>=0.11.6 +requests~=2.31.0 +pathlib~=1.0.1 +pytest~=7.4.3 +numexpr~=2.8.6 # max version for py38 +strsimpy~=0.2.1 +markdownify~=0.11.6 tiktoken~=0.5.2 tqdm>=4.66.1 websockets>=12.0 @@ -46,15 +45,14 @@ llama-index # optional document loaders # rapidocr_paddle[gpu]>=1.3.0.post5 # gpu accelleration for ocr of pdf and image files -jq>=1.6.0 # for .json and .jsonl files. suggest `conda install jq` on windows -# html2text # for .enex files +jq==1.6.0 # for .json and .jsonl files. suggest `conda install jq` on windows beautifulsoup4~=4.12.2 # for .mhtml files pysrt~=1.1.2 # Online api libs dependencies -zhipuai>=1.0.7, <=2.0.0 # zhipu -dashscope>=1.13.6 # qwen +zhipuai==1.0.7 # zhipu +dashscope==1.13.6 # qwen # volcengine>=1.0.119 # fangzhou # uncomment libs if you want to use corresponding vector store @@ -64,14 +62,14 @@ dashscope>=1.13.6 # qwen # Agent and Search Tools -arxiv>=2.0.0 -youtube-search>=2.1.2 -duckduckgo-search>=3.9.9 -metaphor-python>=0.1.23 +arxiv~=2.1.0 +youtube-search~=2.1.2 +duckduckgo-search~=3.9.9 +metaphor-python~=0.1.23 # WebUI requirements -streamlit~=1.29.0 # do remember to add streamlit to environment variables if you use windows +streamlit~=1.29.0 streamlit-option-menu>=0.3.6 streamlit-chatbox==1.1.11 streamlit-modal>=0.1.0 diff --git a/requirements_api.txt b/requirements_api.txt index 2210fe2..3ceabc7 100644 --- a/requirements_api.txt +++ b/requirements_api.txt @@ -1,6 +1,3 @@ -# API requirements - -# On Windows system, install the cuda version manually from https://pytorch.org/ torch~=2.1.2 torchvision~=0.16.2 torchaudio~=2.1.2 @@ -8,52 +5,52 @@ xformers==0.0.23.post1 transformers==4.36.2 sentence_transformers==2.2.2 -langchain==0.0.352 +langchain==0.0.354 langchain-experimental==0.0.47 pydantic==1.10.13 fschat==0.2.34 -openai~=1.6.0 -fastapi>=0.105 -sse_starlette +openai~=1.7.1 +fastapi~=0.108.0 +sse_starlette==1.8.2 nltk>=3.8.1 uvicorn>=0.24.0.post1 -starlette~=0.27.0 +starlette~=0.32.0 unstructured[all-docs]==0.11.0 python-magic-bin; sys_platform == 'win32' SQLAlchemy==2.0.19 -faiss-cpu~=1.7.4 # `conda install faiss-gpu -c conda-forge` if you want to accelerate with gpus -accelerate==0.24.1 +faiss-cpu~=1.7.4 # `conda install faiss-gpu -c conda-forge` if you want to accelerate with gpus +accelerate~=0.24.1 spacy~=3.7.2 PyMuPDF~=1.23.8 -rapidocr_onnxruntime~=1.3.8 -requests>=2.31.0 -pathlib>=1.0.1 -pytest>=7.4.3 -numexpr>=2.8.6 # max version for py38 -strsimpy>=0.2.1 -markdownify>=0.11.6 +rapidocr_onnxruntime==1.3.8 +requests~=2.31.0 +pathlib~=1.0.1 +pytest~=7.4.3 +numexpr~=2.8.6 # max version for py38 +strsimpy~=0.2.1 +markdownify~=0.11.6 tiktoken~=0.5.2 tqdm>=4.66.1 websockets>=12.0 -numpy~=1.26.2 -pandas~=2.1.4 +numpy~=1.24.4 +pandas~=2.0.3 einops>=0.7.0 transformers_stream_generator==0.0.4 vllm==0.2.6; sys_platform == "linux" -httpx[brotli,http2,socks]~=0.25.2 +httpx[brotli,http2,socks]==0.25.2 +llama-index # optional document loaders -rapidocr_paddle[gpu]>=1.3.0.post5 # gpu accelleration for ocr of pdf and image files -jq>=1.6.0 # for .json and .jsonl files. suggest `conda install jq` on windows -# html2text # for .enex files +# rapidocr_paddle[gpu]>=1.3.0.post5 # gpu accelleration for ocr of pdf and image files +jq==1.6.0 # for .json and .jsonl files. suggest `conda install jq` on windows beautifulsoup4~=4.12.2 # for .mhtml files pysrt~=1.1.2 # Online api libs dependencies -zhipuai>=1.0.7, <=2.0.0 # zhipu -dashscope>=1.13.6 # qwen +zhipuai==1.0.7 # zhipu +dashscope==1.13.6 # qwen # volcengine>=1.0.119 # fangzhou # uncomment libs if you want to use corresponding vector store @@ -67,4 +64,4 @@ arxiv>=2.0.0 youtube-search>=2.1.2 duckduckgo-search>=3.9.9 metaphor-python>=0.1.23 -docx2txt \ No newline at end of file +docx2txt diff --git a/requirements_lite.txt b/requirements_lite.txt index b022f57..584d0c7 100644 --- a/requirements_lite.txt +++ b/requirements_lite.txt @@ -1,60 +1,44 @@ # API requirements -# On Windows system, install the cuda version manually from https://pytorch.org/ -# torch~=2.1.2 -# torchvision~=0.16.2 -# torchaudio~=2.1.2 -# xformers==0.0.23.post1 -# transformers==4.36.2 -# sentence_transformers==2.2.2 - -langchain==0.0.352 +langchain==0.0.354 langchain-experimental==0.0.47 pydantic==1.10.13 fschat==0.2.34 -openai~=1.6.0 -fastapi>=0.105 -sse_starlette +openai~=1.7.1 +fastapi~=0.108.0 +sse_starlette==1.8.2 nltk>=3.8.1 uvicorn>=0.24.0.post1 -starlette~=0.27.0 -unstructured[docx,csv]==0.11.0 # add pdf if need +starlette~=0.32.0 +unstructured[all-docs]==0.11.0 python-magic-bin; sys_platform == 'win32' SQLAlchemy==2.0.19 -faiss-cpu~=1.7.4 # `conda install faiss-gpu -c conda-forge` if you want to accelerate with gpus -# accelerate==0.24.1 -# spacy~=3.7.2 -# PyMuPDF~=1.23.8 -# rapidocr_onnxruntime~=1.3.8 -requests>=2.31.0 -pathlib>=1.0.1 -pytest>=7.4.3 -numexpr>=2.8.6 # max version for py38 -strsimpy>=0.2.1 -markdownify>=0.11.6 -# tiktoken~=0.5.2 +faiss-cpu~=1.7.4 +requests~=2.31.0 +pathlib~=1.0.1 +pytest~=7.4.3 +numexpr~=2.8.6 # max version for py38 +strsimpy~=0.2.1 +markdownify~=0.11.6 +tiktoken~=0.5.2 tqdm>=4.66.1 websockets>=12.0 -numpy~=1.26.2 -pandas~=2.1.4 -# einops>=0.7.0 -# transformers_stream_generator==0.0.4 -# vllm==0.2.6; sys_platform == "linux" -httpx[brotli,http2,socks]~=0.25.2 +numpy~=1.24.4 +pandas~=2.0.3 +einops>=0.7.0 +transformers_stream_generator==0.0.4 +vllm==0.2.6; sys_platform == "linux" +httpx[brotli,http2,socks]==0.25.2 +requests +pathlib +pytest -# optional document loaders - -rapidocr_paddle[gpu]>=1.3.0.post5 # gpu accelleration for ocr of pdf and image files -jq>=1.6.0 # for .json and .jsonl files. suggest `conda install jq` on windows -# html2text # for .enex files -beautifulsoup4~=4.12.2 # for .mhtml files -pysrt~=1.1.2 # Online api libs dependencies -zhipuai>=1.0.7, <=2.0.0 # zhipu -dashscope>=1.13.6 # qwen -# volcengine>=1.0.119 # fangzhou +zhipuai==1.0.7 +dashscope==1.13.6 +# volcengine>=1.0.119 # uncomment libs if you want to use corresponding vector store # pymilvus>=2.3.4 @@ -63,17 +47,18 @@ dashscope>=1.13.6 # qwen # Agent and Search Tools -arxiv>=2.0.0 -youtube-search>=2.1.2 -duckduckgo-search>=3.9.9 -metaphor-python>=0.1.23 +arxiv~=2.1.0 +youtube-search~=2.1.2 +duckduckgo-search~=3.9.9 +metaphor-python~=0.1.23 # WebUI requirements -streamlit~=1.29.0 # do remember to add streamlit to environment variables if you use windows +streamlit>=1.29.0 streamlit-option-menu>=0.3.6 -streamlit-chatbox==1.1.11 +streamlit-antd-components>=0.3.0 +streamlit-chatbox>=1.1.11 streamlit-modal>=0.1.0 streamlit-aggrid>=0.3.4.post3 httpx[brotli,http2,socks]>=0.25.2 -watchdog>=3.0.0 +watchdog>=3.0.0 \ No newline at end of file diff --git a/requirements_webui.txt b/requirements_webui.txt index 160d823..3c515d1 100644 --- a/requirements_webui.txt +++ b/requirements_webui.txt @@ -1,10 +1,12 @@ # WebUI requirements -streamlit~=1.29.0 # do remember to add streamlit to environment variables if you use windows +streamlit>=1.29.0 streamlit-option-menu>=0.3.6 -streamlit-chatbox==1.1.11 +streamlit-antd-components>=0.3.0 +streamlit-chatbox>=1.1.11 streamlit-modal>=0.1.0 streamlit-aggrid>=0.3.4.post3 httpx[brotli,http2,socks]>=0.25.2 watchdog>=3.0.0 docx2txt + diff --git a/server/knowledge_base/kb_service/milvus_kb_service.py b/server/knowledge_base/kb_service/milvus_kb_service.py index dc392ee..f08b62b 100644 --- a/server/knowledge_base/kb_service/milvus_kb_service.py +++ b/server/knowledge_base/kb_service/milvus_kb_service.py @@ -53,7 +53,7 @@ class MilvusKBService(KBService): self.milvus = Milvus(embedding_function=EmbeddingsFunAdapter(self.embed_model), collection_name=self.kb_name, connection_args=kbs_config.get("milvus"), - index_params=kbs_config.ge("milvus_kwargs")["index_params"], + index_params=kbs_config.get("milvus_kwargs")["index_params"], search_params=kbs_config.get("milvus_kwargs")["search_params"] ) diff --git a/server/knowledge_base/migrate.py b/server/knowledge_base/migrate.py index bde6e1f..596e1f6 100644 --- a/server/knowledge_base/migrate.py +++ b/server/knowledge_base/migrate.py @@ -84,7 +84,7 @@ def file_to_kbfile(kb_name: str, files: List[str]) -> List[KnowledgeFile]: def folder2db( kb_names: List[str], - mode: Literal["recreate_vs", "update_in_db", "increament"], + mode: Literal["recreate_vs", "update_in_db", "increment"], vs_type: Literal["faiss", "milvus", "pg", "chromadb"] = DEFAULT_VS_TYPE, embed_model: str = EMBEDDING_MODEL, chunk_size: int = CHUNK_SIZE, @@ -97,7 +97,7 @@ def folder2db( recreate_vs: recreate all vector store and fill info to database using existed files in local folder fill_info_only(disabled): do not create vector store, fill info to db using existed files only update_in_db: update vector store and database info using local files that existed in database only - increament: create vector store and database info for local files that not existed in database only + increment: create vector store and database info for local files that not existed in database only """ def files2vs(kb_name: str, kb_files: List[KnowledgeFile]): @@ -142,7 +142,7 @@ def folder2db( files2vs(kb_name, kb_files) kb.save_vector_store() # 对比本地目录与数据库中的文件列表，进行增量向量化 - elif mode == "increament": + elif mode == "increment": db_files = kb.list_files() folder_files = list_files_from_folder(kb_name) files = list(set(folder_files) - set(db_files)) @@ -150,7 +150,7 @@ def folder2db( files2vs(kb_name, kb_files) kb.save_vector_store() else: - print(f"unspported migrate mode: {mode}") + print(f"unsupported migrate mode: {mode}") def prune_db_docs(kb_names: List[str]): diff --git a/server/knowledge_base/utils.py b/server/knowledge_base/utils.py index 9e024f3..e5a5f77 100644 --- a/server/knowledge_base/utils.py +++ b/server/knowledge_base/utils.py @@ -272,7 +272,7 @@ def make_text_splitter( print(e) text_splitter_module = importlib.import_module('langchain.text_splitter') TextSplitter = getattr(text_splitter_module, "RecursiveCharacterTextSplitter") - text_splitter = TextSplitter(chunk_size=250, chunk_overlap=50) + text_splitter = TextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap) return text_splitter diff --git a/server/model_workers/minimax.py b/server/model_workers/minimax.py index 947782a..deae07e 100644 --- a/server/model_workers/minimax.py +++ b/server/model_workers/minimax.py @@ -73,7 +73,7 @@ class MiniMaxWorker(ApiModelWorker): with response as r: text = "" for e in r.iter_text(): - if not e.startswith("data: "): # 真是优秀的返回 + if not e.startswith("data: "): data = { "error_code": 500, "text": f"minimax返回错误的结果：{e}", diff --git a/server/utils.py b/server/utils.py index 21b1baf..5512ee6 100644 --- a/server/utils.py +++ b/server/utils.py @@ -10,10 +10,11 @@ from configs import (LLM_MODELS, LLM_DEVICE, EMBEDDING_DEVICE, import os from concurrent.futures import ThreadPoolExecutor, as_completed from langchain.chat_models import ChatOpenAI -from langchain.llms import OpenAI, AzureOpenAI, Anthropic +from langchain.llms import OpenAI import httpx from typing import Literal, Optional, Callable, Generator, Dict, Any, Awaitable, Union, Tuple import logging +import torch async def wrap_done(fn: Awaitable, event: asyncio.Event): @@ -58,6 +59,7 @@ def get_ChatOpenAI( ) return model + def get_OpenAI( model_name: str, temperature: float, @@ -151,7 +153,6 @@ class ChatMessage(BaseModel): def torch_gc(): try: - import torch if torch.cuda.is_available(): # with torch.cuda.device(DEVICE): torch.cuda.empty_cache() @@ -499,29 +500,58 @@ def set_httpx_config( # 自动检查torch可用的设备。分布式部署时，不运行LLM的机器上可以不装torch +def is_mps_available(): + return hasattr(torch.backends, "mps") and torch.backends.mps.is_available() + + +def is_cuda_available(): + return torch.cuda.is_available() + + def detect_device() -> Literal["cuda", "mps", "cpu"]: try: - import torch if torch.cuda.is_available(): return "cuda" - if torch.backends.mps.is_available(): + if is_mps_available(): return "mps" except: pass return "cpu" -def llm_device(device: str = None) -> Literal["cuda", "mps", "cpu"]: +def llm_device(device: str = None) -> Literal["cuda", "mps", "cpu", "xpu"]: device = device or LLM_DEVICE - if device not in ["cuda", "mps", "cpu"]: + if device not in ["cuda", "mps", "cpu", "xpu"]: + logging.warning(f"device not in ['cuda', 'mps', 'cpu','xpu'], device = {device}") device = detect_device() + elif device == 'cuda' and not is_cuda_available() and is_mps_available(): + logging.warning("cuda is not available, fallback to mps") + return "mps" + if device == 'mps' and not is_mps_available() and is_cuda_available(): + logging.warning("mps is not available, fallback to cuda") + return "cuda" + + # auto detect device if not specified + if device not in ["cuda", "mps", "cpu", "xpu"]: + return detect_device() return device -def embedding_device(device: str = None) -> Literal["cuda", "mps", "cpu"]: - device = device or EMBEDDING_DEVICE +def embedding_device(device: str = None) -> Literal["cuda", "mps", "cpu", "xpu"]: + device = device or LLM_DEVICE if device not in ["cuda", "mps", "cpu"]: + logging.warning(f"device not in ['cuda', 'mps', 'cpu','xpu'], device = {device}") device = detect_device() + elif device == 'cuda' and not is_cuda_available() and is_mps_available(): + logging.warning("cuda is not available, fallback to mps") + return "mps" + if device == 'mps' and not is_mps_available() and is_cuda_available(): + logging.warning("mps is not available, fallback to cuda") + return "cuda" + + # auto detect device if not specified + if device not in ["cuda", "mps", "cpu"]: + return detect_device() return device diff --git a/tests/test_migrate.py b/tests/test_migrate.py index b794b02..0a967d1 100644 --- a/tests/test_migrate.py +++ b/tests/test_migrate.py @@ -14,8 +14,7 @@ from server.knowledge_base.migrate import folder2db, prune_db_docs, prune_folder # setup test knowledge base kb_name = "test_kb_for_migrate" test_files = { - "faq.md": str(root_path / "docs" / "faq.md"), - "install.md": str(root_path / "docs" / "install.md"), + "readme.md": str(root_path / "readme.md"), } @@ -56,13 +55,13 @@ def test_recreate_vs(): assert doc.metadata["source"] == name -def test_increament(): +def test_increment(): kb = KBServiceFactory.get_service_by_name(kb_name) kb.clear_vs() assert kb.list_files() == [] assert kb.list_docs() == [] - folder2db([kb_name], "increament") + folder2db([kb_name], "increment") files = kb.list_files() print(files) diff --git a/webui_pages/utils.py b/webui_pages/utils.py index b7c5967..11b45dd 100644 --- a/webui_pages/utils.py +++ b/webui_pages/utils.py @@ -136,6 +136,8 @@ class ApiRequest: try: if chunk.startswith("data: "): data = json.loads(chunk[6:-2]) + elif chunk.startswith(":"): # skip sse comment line + continue else: data = json.loads(chunk) yield data @@ -170,6 +172,8 @@ class ApiRequest: try: if chunk.startswith("data: "): data = json.loads(chunk[6:-2]) + elif chunk.startswith(":"): # skip sse comment line + continue else: data = json.loads(chunk) yield data