根据系统指定binding_host

README_en.md

@@ -59,6 +59,7 @@ docker run -d --gpus all -p 80:8501 registry.cn-beijing.aliyuncs.com/chatchat/ch
 ## Environment Minimum Requirements
 
 To run this code smoothly, please configure it according to the following minimum requirements:
+
 + Python version: >= 3.8.5, < 3.11
 + Cuda version: >= 11.7, with Python installed.
 
@@ -70,7 +71,6 @@ If you want to run the native model (int4 version) on the GPU without problems,
 + LLaMA-30B Minimum Memory Requirement: 22GB Recommended Cards: RTX A5000,RTX 3090,RTX 4090,RTX 6000,Tesla V100,RTX Tesla P40
 + Minimum memory requirement for LLaMA-65B: 40GB Recommended cards: A100,A40,A6000
 
-
 If int8 then memory x1.5 fp16 x2.5 requirement.
 For example: using fp16 to reason about the Qwen-7B-Chat model requires 16GB of video memory.
 
@@ -137,7 +137,6 @@ The project use [FastChat](https://github.com/lm-sys/FastChat) to provide the AP
 * Any [EleutherAI](https://huggingface.co/EleutherAI) pythia model such as [pythia-6.9b](https://huggingface.co/EleutherAI/pythia-6.9b)(任何 [EleutherAI](https://huggingface.co/EleutherAI) 的 pythia 模型，如 [pythia-6.9b](https://huggingface.co/EleutherAI/pythia-6.9b))
 * Any [Peft](https://github.com/huggingface/peft) adapter trained on top of a model above. To activate, must have `peft` in the model path. Note: If loading multiple peft models, you can have them share the base model weights by setting the environment variable `PEFT_SHARE_BASE_WEIGHTS=true` in any model worker.
 
-
 The above model support list may be updated continuously as [FastChat](https://github.com/lm-sys/FastChat) is updated, see [FastChat Supported Models List](https://github.com/lm-sys/FastChat/blob/main /docs/model_support.md).
 In addition to local models, this project also supports direct access to online models such as OpenAI API, Wisdom Spectrum AI, etc. For specific settings, please refer to the configuration information of `llm_model_dict` in `configs/model_configs.py.example`.
 Online LLM models are currently supported:
@@ -230,6 +229,7 @@ $ git clone https://huggingface.co/moka-ai/m3e-base
 ```
 
 ### 3. Setting Configuration
+
 Copy the model-related parameter configuration template file [configs/model_config.py.example](configs/model_config.py.example) and store it under the project path `. /configs` path and rename it `model_config.py`.
 
 Copy the service-related parameter configuration template file [configs/server_config.py.example](configs/server_config.py.example) and store it under the project path `. /configs` path and rename it `server_config.py`.
@@ -237,6 +237,7 @@ Copy the service-related parameter configuration template file [configs/server_c
 Before you start executing the Web UI or command line interactions, check that each of the items in [configs/model_config.py](configs/model_config.py) and [configs/server_config.py](configs/server_config.py) The model parameters are designed to meet the requirements:
 
 - Please make sure that the local storage path of the downloaded LLM model is written in the `local_model_path` attribute of the corresponding model in `llm_model_dict`, e.g..
+
 ```
 "chatglm2-6b":"/Users/xxx/Downloads/chatglm2-6b",
 
@@ -330,9 +331,9 @@ CUDA_VISIBLE_DEVICES=0,1 python startup.py -a
 
 Including lora,p-tuning,prefix tuning, prompt tuning,ia3
 
-This project loads the LLM service based on FastChat, so one must load the PEFT in a FastChat way, that is, ensure that the word `peft` must be in the path name, the name of the configuration file must be `adapter_config.json`, and the path contains PEFT weights in `.bin` format. The peft path is specified in `args.model_names` of the `create_model_worker_app` function in `startup.py`, and enable the environment variable `PEFT_SHARE_BASE_WEIGHTS=true` parameter.
+This project loads the LLM service based on FastChat, so one must load the PEFT in a FastChat way. For models other than "chatglm", "falcon" or "code5p" and peft other than "p-tuning", ensure that the word `peft` must be in the path name, the name of the configuration file must be `adapter_config.json`, and the path contains PEFT weights in `.bin` format. The peft path is specified in `args.model_names` of the `create_model_worker_app` function in `startup.py`, and enable the environment variable `PEFT_SHARE_BASE_WEIGHTS=true` parameter.
 
-If the above method fails, you need to start standard fastchat service step by step.  Step-by-step procedure could be found Section 6. For further steps, please refer to [Model invalid after loading lora fine-tuning](https://github. com/chatchat-space/Langchain-Chatchat/issues/1130#issuecomment-1685291822).
+For "p-tuning" PEFT, please refer to [load p-tuning with chatchat](docs/chatchat加载ptuning.md).
 
 #### **5.5 Some Notes**
 
@@ -369,6 +370,7 @@ Please refer to [FAQ](docs/FAQ.md)
 - [X] Langchain applications
 
   - [X] Load local documents
+
     - [X] Unstructured documents
       - [X] .md
       - [X] .txt
@@ -376,29 +378,36 @@ Please refer to [FAQ](docs/FAQ.md)
     - [ ] Structured documents
       - [X] .csv
       - [ ] .xlsx
+
     - [] TextSplitter and Retriever
       - [X] multiple TextSplitter
       - [X] ChineseTextSplitter
       - [ ] Reconstructed Context Retriever
+
     - [ ] Webpage
     - [ ] SQL
     - [ ] Knowledge Database
   - [X] Search Engines
+
     - [X] Bing
     - [X] DuckDuckGo
   - [X] Agent
+
     - [X] Agent implementation in the form of basic React, including calls to calculators, etc.
     - [X] Langchain's own Agent implementation and calls
     - [ ] More Agent support for models
     - [ ] More tools
 - [X] LLM  Models
+
   - [X] [FastChat](https://github.com/lm-sys/fastchat) -based LLM Models
   - [ ] Mutiply Remote LLM API
 - [X] Embedding Models
+
   - [X] HuggingFace -based Embedding models
   - [ ] Mutiply Remote Embedding API
 - [X] FastAPI-based API
 - [X] Web UI
+
   - [X] Streamlit -based Web UI
 
 ---

configs/server_config.py.example

@@ -9,7 +9,7 @@ HTTPX_DEFAULT_TIMEOUT = 300.0
 OPEN_CROSS_DOMAIN = False
 
 # 各服务器默认绑定host。如改为"0.0.0.0"需要修改下方所有XX_SERVER的host
-DEFAULT_BIND_HOST = "0.0.0.0"
+DEFAULT_BIND_HOST = "0.0.0.0" if sys.platform != "win32" else "127.0.0.1"
 
 # webui.py server
 WEBUI_SERVER = {