Merge branch 'master' into branch-0.2.9

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
-<img src="img/qr_code_83.jpg" alt="二维码" width="300" />
+<img src="img/qr_code_86.jpg" alt="二维码" width="300" />
 
 🎉 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。
 

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
+🌐 [AutoDL image](registry.cn-beijing.aliyuncs.com/chatchat/chatchat:0.2.5) is supported, and in v13 the codes are update
-to v0.2.5.
+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
 

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:
+    elif args.increment:
-        folder2db(kb_names=args.kb_name, mode="increament", embed_model=args.embed_model)
+        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:

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
+openai~=1.7.1
-fastapi>=0.105
+fastapi~=0.108.0
-sse_starlette
+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
+accelerate~=0.24.1
 spacy~=3.7.2
 PyMuPDF~=1.23.8
 rapidocr_onnxruntime==1.3.8
-requests>=2.31.0
+requests~=2.31.0
-pathlib>=1.0.1
+pathlib~=1.0.1
-pytest>=7.4.3
+pytest~=7.4.3
-numexpr>=2.8.6 # max version for py38
+numexpr~=2.8.6 # max version for py38
-strsimpy>=0.2.1
+strsimpy~=0.2.1
-markdownify>=0.11.6
+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
+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
+zhipuai==1.0.7 # zhipu
-dashscope>=1.13.6 # qwen
+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
+arxiv~=2.1.0
-youtube-search>=2.1.2
+youtube-search~=2.1.2
-duckduckgo-search>=3.9.9
+duckduckgo-search~=3.9.9
-metaphor-python>=0.1.23
+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

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
+openai~=1.7.1
-fastapi>=0.105
+fastapi~=0.108.0
-sse_starlette
+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
+accelerate~=0.24.1
 spacy~=3.7.2
 PyMuPDF~=1.23.8
-rapidocr_onnxruntime~=1.3.8
+rapidocr_onnxruntime==1.3.8
-requests>=2.31.0
+requests~=2.31.0
-pathlib>=1.0.1
+pathlib~=1.0.1
-pytest>=7.4.3
+pytest~=7.4.3
-numexpr>=2.8.6 # max version for py38
+numexpr~=2.8.6 # max version for py38
-strsimpy>=0.2.1
+strsimpy~=0.2.1
-markdownify>=0.11.6
+markdownify~=0.11.6
 tiktoken~=0.5.2
 tqdm>=4.66.1
 websockets>=12.0
-numpy~=1.26.2
+numpy~=1.24.4
-pandas~=2.1.4
+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
+# 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
+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
+zhipuai==1.0.7 # zhipu
-dashscope>=1.13.6 # qwen
+dashscope==1.13.6 # qwen
 # volcengine>=1.0.119 # fangzhou
 
 # uncomment libs if you want to use corresponding vector store

requirements_lite.txt

@@ -1,60 +1,44 @@
 # API requirements
 
-# On Windows system, install the cuda version manually from https://pytorch.org/
+langchain==0.0.354
-# 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-experimental==0.0.47
 pydantic==1.10.13
 fschat==0.2.34
-openai~=1.6.0
+openai~=1.7.1
-fastapi>=0.105
+fastapi~=0.108.0
-sse_starlette
+sse_starlette==1.8.2
 nltk>=3.8.1
 uvicorn>=0.24.0.post1
-starlette~=0.27.0
+starlette~=0.32.0
-unstructured[docx,csv]==0.11.0 # add pdf if need
+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
+faiss-cpu~=1.7.4
-# accelerate==0.24.1
+requests~=2.31.0
-# spacy~=3.7.2
+pathlib~=1.0.1
-# PyMuPDF~=1.23.8
+pytest~=7.4.3
-# rapidocr_onnxruntime~=1.3.8
+numexpr~=2.8.6 # max version for py38
-requests>=2.31.0
+strsimpy~=0.2.1
-pathlib>=1.0.1
+markdownify~=0.11.6
-pytest>=7.4.3
+tiktoken~=0.5.2
-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
+numpy~=1.24.4
-pandas~=2.1.4
+pandas~=2.0.3
-# einops>=0.7.0
+einops>=0.7.0
-# transformers_stream_generator==0.0.4
+transformers_stream_generator==0.0.4
-# vllm==0.2.6; sys_platform == "linux"
+vllm==0.2.6; sys_platform == "linux"
-httpx[brotli,http2,socks]~=0.25.2
+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
+zhipuai==1.0.7
-dashscope>=1.13.6 # qwen
+dashscope==1.13.6
-# volcengine>=1.0.119 # fangzhou
+# volcengine>=1.0.119
 
 # uncomment libs if you want to use corresponding vector store
 # pymilvus>=2.3.4
@@ -63,16 +47,17 @@ dashscope>=1.13.6 # qwen
 
 # Agent and Search Tools
 
-arxiv>=2.0.0
+arxiv~=2.1.0
-youtube-search>=2.1.2
+youtube-search~=2.1.2
-duckduckgo-search>=3.9.9
+duckduckgo-search~=3.9.9
-metaphor-python>=0.1.23
+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

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
+

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"]
                              )
 

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]):

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
 
 

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}",

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"]:
+def embedding_device(device: str = None) -> Literal["cuda", "mps", "cpu", "xpu"]:
-    device = device or EMBEDDING_DEVICE
+    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
 
 

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"),
+    "readme.md": str(root_path / "readme.md"),
-    "install.md": str(root_path / "docs" / "install.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)

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