合并分支，支持 (#1808)

* 北京黑客松更新

知识库支持：
支持zilliz数据库
Agent支持：
支持以下工具调用
1. 支持互联网Agent调用
2. 支持知识库Agent调用
3. 支持旅游助手工具(未上传）

知识库更新
1. 支持知识库简介，用于Agent选择
2. UI对应知识库简介

提示词选择
1. UI 和模板支持提示词模板更换选择

* 数据库更新介绍问题解决

* 关于Langchain自己支持的模型

1. 修复了Openai无法调用的bug
2. 支持了Azure Openai Claude模型
（在模型切换界面由于优先级问题，显示的会是其他联网模型)
3. 422问题被修复，用了另一种替代方案。
4. 更新了部分依赖

configs/kb_config.py.example

@@ -1,6 +1,5 @@
 import os
 
-
 # 默认使用的知识库
 DEFAULT_KNOWLEDGE_BASE = "samples"
 
@@ -57,14 +56,11 @@ KB_INFO = {
     "知识库名称": "知识库介绍",
     "samples": "关于本项目issue的解答",
 }
-
 # 通常情况下不需要更改以下内容
-
 # 知识库默认存储路径
 KB_ROOT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "knowledge_base")
 if not os.path.exists(KB_ROOT_PATH):
     os.mkdir(KB_ROOT_PATH)
-
 # 数据库默认存储路径。
 # 如果使用sqlite，可以直接修改DB_ROOT_PATH；如果使用其它数据库，请直接修改SQLALCHEMY_DATABASE_URI。
 DB_ROOT_PATH = os.path.join(KB_ROOT_PATH, "info.db")

configs/model_config.py.example

@@ -112,7 +112,8 @@ TEMPERATURE = 0.7
 # TOP_P = 0.95 # ChatOpenAI暂不支持该参数
 
 
-ONLINE_LLM_MODEL = {
+LANGCHAIN_LLM_MODEL = {
+    # 不需要走Fschat封装的，Langchain直接支持的模型。
     # 调用chatgpt时如果报出： urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='api.openai.com', port=443):
     #  Max retries exceeded with url: /v1/chat/completions
     # 则需要将urllib3版本修改为1.25.11
@@ -128,11 +129,29 @@ ONLINE_LLM_MODEL = {
     # 4.0 seconds as it raised APIConnectionError: Error communicating with OpenAI.
     # 需要添加代理访问(正常开的代理软件可能会拦截不上)需要设置配置openai_proxy 或者 使用环境遍历OPENAI_PROXY 进行设置
     # 比如: "openai_proxy": 'http://127.0.0.1:4780'
-    "gpt-3.5-turbo": {
+
+    # 这些配置文件的名字不能改动
+    "Azure-OpenAI": {
+        "deployment_name": "your Azure deployment name",
+        "model_version": "0701",
+        "openai_api_type": "azure",
+        "api_base_url": "https://your Azure point.azure.com",
+        "api_version": "2023-07-01-preview",
+        "api_key": "your Azure api key",
+        "openai_proxy": "",
+    },
+    "OpenAI": {
+        "model_name": "your openai model name(such as gpt-4)",
         "api_base_url": "https://api.openai.com/v1",
         "api_key": "your OPENAI_API_KEY",
-        "openai_proxy": "your OPENAI_PROXY",
+        "openai_proxy": "",
     },
+    "Anthropic": {
+        "model_name": "your claude model name(such as claude2-100k)",
+        "api_key":"your ANTHROPIC_API_KEY",
+    }
+}
+ONLINE_LLM_MODEL = {
     # 线上模型。请在server_config中为每个在线API设置不同的端口
     # 具体注册及api key获取请前往 http://open.bigmodel.cn
     "zhipu-api": {

init_database.py

@@ -1,3 +1,5 @@
+import sys
+sys.path.append(".")
 from server.knowledge_base.migrate import create_tables, reset_tables, folder2db, prune_db_docs, prune_folder_files
 from configs.model_config import NLTK_DATA_PATH
 import nltk

requirements.txt

@@ -1,14 +1,15 @@
-langchain==0.0.317
+langchain>=0.0.319
-langchain-experimental==0.0.30
+langchain-experimental>=0.0.30
 fschat[model_worker]==0.2.31
-openai
+xformers>=0.0.22.post4
+openai>=0.28.1
 sentence_transformers
 transformers>=4.34
 torch>=2.0.1 # 推荐2.1
 torchvision
 torchaudio
-fastapi>=0.103.2
+fastapi>=0.104
-nltk~=3.8.1
+nltk>=3.8.1
 uvicorn~=0.23.1
 starlette~=0.27.0
 pydantic~=1.10.11

requirements_api.txt

@@ -1,13 +1,14 @@
-langchain==0.0.317
+langchain>=0.0.319
-langchain-experimental==0.0.30
+langchain-experimental>=0.0.30
 fschat[model_worker]==0.2.31
-openai
+xformers>=0.0.22.post4
+openai>=0.28.1
 sentence_transformers>=2.2.2
 transformers>=4.34
-torch>=2.0.1
+torch>=2.1
 torchvision
 torchaudio
-fastapi>=0.103.1
+fastapi>=0.104
 nltk~=3.8.1
 uvicorn~=0.23.1
 starlette~=0.27.0

requirements_webui.txt

@@ -1,11 +1,11 @@
 numpy~=1.24.4
 pandas~=2.0.3
-streamlit>=1.26.0
+streamlit>=1.27.2
 streamlit-option-menu>=0.3.6
-streamlit-antd-components>=0.1.11
+streamlit-antd-components>=0.2.3
 streamlit-chatbox==1.1.10
 streamlit-aggrid>=0.3.4.post3
-httpx~=0.24.1
+httpx>=0.25.0
-nltk
+nltk>=3.8.1
 watchdog
 websockets

server/agent/callbacks.py

@@ -97,7 +97,6 @@ class CustomAsyncIteratorCallbackHandler(AsyncIteratorCallbackHandler):
             llm_token="",
         )
         self.queue.put_nowait(dumps(self.cur_tool))
-
     async def on_chat_model_start(
         self,
         serialized: Dict[str, Any],

server/agent/custom_template.py

@@ -4,7 +4,6 @@ from langchain.prompts import StringPromptTemplate
 from typing import List
 from langchain.schema import AgentAction, AgentFinish
 from server.agent import model_container
-begin = False
 class CustomPromptTemplate(StringPromptTemplate):
     # The template to use
     template: str
@@ -38,7 +37,7 @@ class CustomOutputParser(AgentOutputParser):
 
     def parse(self, llm_output: str) -> AgentFinish | tuple[dict[str, str], str] | AgentAction:
         # Check if agent should finish
-        support_agent = ["gpt","Qwen","qwen-api","baichuan-api"]
+        support_agent = ["Azure-OpenAI", "OpenAI", "Anthropic", "Qwen", "qwen-api", "baichuan-api"]  # 目前支持agent的模型
         if not any(agent in model_container.MODEL for agent in support_agent) and self.begin:
             self.begin = False
             stop_words = ["Observation:"]

server/agent/tools/__init__.py

@@ -2,7 +2,6 @@
 from .search_knowledge_simple import knowledge_search_simple
 from .search_all_knowledge_once import knowledge_search_once
 from .search_all_knowledge_more import knowledge_search_more
-# from .travel_assistant import travel_assistant
 from .calculate import calculate
 from .translator import translate
 from .weather import weathercheck

server/knowledge_base/utils.py

@@ -1,7 +1,5 @@
 import os
-
 from transformers import AutoTokenizer
-
 from configs import (
     EMBEDDING_MODEL,
     KB_ROOT_PATH,

server/llm_api.py

@@ -1,5 +1,5 @@
 from fastapi import Body
-from configs import logger, log_verbose, LLM_MODEL, HTTPX_DEFAULT_TIMEOUT
+from configs import logger, log_verbose, LLM_MODEL, HTTPX_DEFAULT_TIMEOUT,LANGCHAIN_LLM_MODEL
 from server.utils import (BaseResponse, fschat_controller_address, list_config_llm_models,
                           get_httpx_client, get_model_worker_config)
 
@@ -52,7 +52,6 @@ def get_model_config(
     获取LLM模型配置项（合并后的）
     '''
     config = get_model_worker_config(model_name=model_name)
-
     # 删除ONLINE_MODEL配置中的敏感信息
     del_keys = set(["worker_class"])
     for k in config:

server/utils.py

@@ -5,12 +5,11 @@ from fastapi import FastAPI
 from pathlib import Path
 import asyncio
 from configs import (LLM_MODEL, LLM_DEVICE, EMBEDDING_DEVICE,
-                     MODEL_PATH, MODEL_ROOT_PATH, ONLINE_LLM_MODEL,
+                     MODEL_PATH, MODEL_ROOT_PATH, ONLINE_LLM_MODEL, LANGCHAIN_LLM_MODEL, logger, log_verbose,
-                     logger, log_verbose,
                      FSCHAT_MODEL_WORKERS, HTTPX_DEFAULT_TIMEOUT)
 import os
 from concurrent.futures import ThreadPoolExecutor, as_completed
-from langchain.chat_models import ChatOpenAI
+from langchain.chat_models import ChatOpenAI, AzureChatOpenAI, ChatAnthropic
 import httpx
 from typing import Literal, Optional, Callable, Generator, Dict, Any, Awaitable, Union
 
@@ -40,19 +39,64 @@ def get_ChatOpenAI(
         verbose: bool = True,
         **kwargs: Any,
 ) -> ChatOpenAI:
-    config = get_model_worker_config(model_name)
+    ## 以下模型是Langchain原生支持的模型，这些模型不会走Fschat封装
-    model = ChatOpenAI(
+    config_models = list_config_llm_models()
-        streaming=streaming,
+    if model_name in config_models.get("langchain", {}):
-        verbose=verbose,
+        config = config_models["langchain"][model_name]
-        callbacks=callbacks,
+        if model_name == "Azure-OpenAI":
-        openai_api_key=config.get("api_key", "EMPTY"),
+            model = AzureChatOpenAI(
-        openai_api_base=config.get("api_base_url", fschat_openai_api_address()),
+                streaming=streaming,
-        model_name=model_name,
+                verbose=verbose,
-        temperature=temperature,
+                callbacks=callbacks,
-        max_tokens=max_tokens,
+                deployment_name=config.get("deployment_name"),
-        openai_proxy=config.get("openai_proxy"),
+                model_version=config.get("model_version"),
-        **kwargs
+                openai_api_type=config.get("openai_api_type"),
-    )
+                openai_api_base=config.get("api_base_url"),
+                openai_api_version=config.get("api_version"),
+                openai_api_key=config.get("api_key"),
+                openai_proxy=config.get("openai_proxy"),
+                temperature=temperature,
+                max_tokens=max_tokens,
+            )
+
+        elif model_name == "OpenAI":
+            model = ChatOpenAI(
+                streaming=streaming,
+                verbose=verbose,
+                callbacks=callbacks,
+                model_name=config.get("model_name"),
+                openai_api_base=config.get("api_base_url"),
+                openai_api_key=config.get("api_key"),
+                openai_proxy=config.get("openai_proxy"),
+                temperature=temperature,
+                max_tokens=max_tokens,
+            )
+        elif model_name == "Anthropic":
+            model = ChatAnthropic(
+                streaming=streaming,
+                verbose=verbose,
+                callbacks=callbacks,
+                model_name=config.get("model_name"),
+                anthropic_api_key=config.get("api_key"),
+
+            )
+    ## TODO 支持其他的Langchain原生支持的模型
+    else:
+        ## 非Langchain原生支持的模型，走Fschat封装
+        config = get_model_worker_config(model_name)
+        model = ChatOpenAI(
+            streaming=streaming,
+            verbose=verbose,
+            callbacks=callbacks,
+            openai_api_key=config.get("api_key", "EMPTY"),
+            openai_api_base=config.get("api_base_url", fschat_openai_api_address()),
+            model_name=model_name,
+            temperature=temperature,
+            max_tokens=max_tokens,
+            openai_proxy=config.get("openai_proxy"),
+            **kwargs
+        )
+
     return model
 
 
@@ -249,8 +293,9 @@ def MakeFastAPIOffline(
                 redoc_favicon_url=favicon,
             )
 
+    # 从model_config中获取模型信息
+
 
-# 从model_config中获取模型信息
 def list_embed_models() -> List[str]:
     '''
     get names of configured embedding models
@@ -266,9 +311,9 @@ def list_config_llm_models() -> Dict[str, Dict]:
     workers = list(FSCHAT_MODEL_WORKERS)
     if LLM_MODEL not in workers:
         workers.insert(0, LLM_MODEL)
-
     return {
         "local": MODEL_PATH["llm_model"],
+        "langchain": LANGCHAIN_LLM_MODEL,
         "online": ONLINE_LLM_MODEL,
         "worker": workers,
     }
@@ -300,8 +345,9 @@ def get_model_path(model_name: str, type: str = None) -> Optional[str]:
                 return str(path)
         return path_str  # THUDM/chatglm06b
 
+    # 从server_config中获取服务信息
+
 
-# 从server_config中获取服务信息
 def get_model_worker_config(model_name: str = None) -> dict:
     '''
     加载model worker的配置项。
@@ -316,6 +362,10 @@ def get_model_worker_config(model_name: str = None) -> dict:
     config.update(FSCHAT_MODEL_WORKERS.get(model_name, {}))
 
     # 在线模型API
+    if model_name in LANGCHAIN_LLM_MODEL:
+        config["langchain_model"] = True
+        config["worker_class"] = ""
+
     if model_name in ONLINE_LLM_MODEL:
         config["online_api"] = True
         if provider := config.get("provider"):
@@ -389,7 +439,7 @@ def webui_address() -> str:
     return f"http://{host}:{port}"
 
 
-def get_prompt_template(type:str,name: str) -> Optional[str]:
+def get_prompt_template(type: str, name: str) -> Optional[str]:
     '''
     从prompt_config中加载模板内容
     type: "llm_chat","agent_chat","knowledge_base_chat","search_engine_chat"的其中一种，如果有新功能，应该进行加入。
@@ -459,8 +509,9 @@ def set_httpx_config(
     import urllib.request
     urllib.request.getproxies = _get_proxies
 
+    # 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
+
 
-# 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 detect_device() -> Literal["cuda", "mps", "cpu"]:
     try:
         import torch

startup.py

@@ -68,7 +68,9 @@ def create_model_worker_app(log_level: str = "INFO", **kwargs) -> FastAPI:
     controller_address:
     worker_address:
 
-
+    对于Langchain支持的模型：
+        langchain_model:True
+        不会使用fschat
     对于online_api:
         online_api:True
         worker_class: `provider`
@@ -85,9 +87,11 @@ def create_model_worker_app(log_level: str = "INFO", **kwargs) -> FastAPI:
 
     for k, v in kwargs.items():
         setattr(args, k, v)
-
+    if worker_class := kwargs.get("langchain_model"): #Langchian支持的模型不用做操作
+        from fastchat.serve.base_model_worker import app
+        worker = ""
     # 在线模型API
-    if worker_class := kwargs.get("worker_class"):
+    elif worker_class := kwargs.get("worker_class"):
         from fastchat.serve.base_model_worker import app
 
         worker = worker_class(model_names=args.model_names,
@@ -127,8 +131,8 @@ def create_model_worker_app(log_level: str = "INFO", **kwargs) -> FastAPI:
             args.engine_use_ray = False
             args.disable_log_requests = False
 
-            # 0.2.0 vllm后要加的参数
+            # 0.2.0 vllm后要加的参数, 但是这里不需要
-            args.max_model_len = 8192 # 模型可以处理的最大序列长度。请根据你的大模型设置，
+            args.max_model_len = None
             args.revision = None
             args.quantization = None
             args.max_log_len = None

webui_pages/dialogue/dialogue.py

@@ -4,10 +4,9 @@ from streamlit_chatbox import *
 from datetime import datetime
 import os
 from configs import (LLM_MODEL, TEMPERATURE, HISTORY_LEN, PROMPT_TEMPLATES,
-                     DEFAULT_KNOWLEDGE_BASE, DEFAULT_SEARCH_ENGINE)
+                     DEFAULT_KNOWLEDGE_BASE, DEFAULT_SEARCH_ENGINE,LANGCHAIN_LLM_MODEL)
 from typing import List, Dict
 
-
 chat_box = ChatBox(
     assistant_avatar=os.path.join(
         "img",
@@ -42,7 +41,6 @@ def get_default_llm_model(api: ApiRequest) -> (str, bool):
     返回类型为（model_name, is_local_model）
     '''
     running_models = api.list_running_models()
-
     if not running_models:
         return "", False
 
@@ -52,7 +50,6 @@ def get_default_llm_model(api: ApiRequest) -> (str, bool):
     local_models = [k for k, v in running_models.items() if not v.get("online_api")]
     if local_models:
         return local_models[0], True
-
     return list(running_models)[0], False
 
 
@@ -82,7 +79,7 @@ def dialogue_page(api: ApiRequest):
                                       "搜索引擎问答",
                                       "自定义Agent问答",
                                       ],
-                                     index=3,
+                                     index=0,
                                      on_change=on_mode_change,
                                      key="dialogue_mode",
                                      )
@@ -100,16 +97,18 @@ def dialogue_page(api: ApiRequest):
             return x
 
         running_models = list(api.list_running_models())
+        running_models += LANGCHAIN_LLM_MODEL.keys()
         available_models = []
         config_models = api.list_config_models()
         worker_models = list(config_models.get("worker", {}))  # 仅列出在FSCHAT_MODEL_WORKERS中配置的模型
         for m in worker_models:
             if m not in running_models and m != "default":
                 available_models.append(m)
-        for k, v in config_models.get("online", {}).items():  # 列出ONLINE_MODELS中直接访问的模型（如GPT）
+        for k, v in config_models.get("online", {}).items():  # 列出ONLINE_MODELS中直接访问的模型
             if not v.get("provider") and k not in running_models:
-                print(k, v)
                 available_models.append(k)
+        for k, v in config_models.get("langchain", {}).items():  # 列出LANGCHAIN_LLM_MODEL支持的模型
+            available_models.append(k)
         llm_models = running_models + available_models
         index = llm_models.index(st.session_state.get("cur_llm_model", get_default_llm_model(api)[0]))
         llm_model = st.selectbox("选择LLM模型：",
@@ -119,10 +118,10 @@ def dialogue_page(api: ApiRequest):
                                  on_change=on_llm_change,
                                  key="llm_model",
                                  )
-        if (llm_model
+        if (st.session_state.get("prev_llm_model") != llm_model
-            and st.session_state.get("prev_llm_model") != llm_model
+                and not llm_model in config_models.get("online", {})
-            and not api.get_model_config(llm_model).get("online_api")
+                and not llm_model in config_models.get("langchain", {})
-            and llm_model not in running_models):
+                and llm_model not in running_models):
             with st.spinner(f"正在加载模型： {llm_model}，请勿进行操作或刷新页面"):
                 prev_model = st.session_state.get("prev_llm_model")
                 r = api.change_llm_model(prev_model, llm_model)
@@ -228,9 +227,9 @@ def dialogue_page(api: ApiRequest):
             ])
             text = ""
             ans = ""
-            support_agent = ["gpt", "Qwen", "qwen-api", "baichuan-api"]  # 目前支持agent的模型
+            support_agent = ["Azure-OpenAI", "OpenAI", "Anthropic", "Qwen", "qwen-api", "baichuan-api"]  # 目前支持agent的模型
             if not any(agent in llm_model for agent in support_agent):
-                ans += "正在思考... \n\n <span style='color:red'>该模型并没有进行Agent对齐，无法正常使用Agent功能！</span>\n\n\n<span style='color:red'>请更换 GPT4或Qwen-14B等支持Agent的模型获得更好的体验！ </span> \n\n\n"
+                ans += "正在思考... \n\n <span style='color:red'>该模型并没有进行Agent对齐，请更换支持Agent的模型获得更好的体验！</span>\n\n\n"
                 chat_box.update_msg(ans, element_index=0, streaming=False)
             for d in api.agent_chat(prompt,
                                     history=history,