1. 修改stream_chat的接口，在请求体中选择knowledge_base_id;2. 增加stream_chat_bing接口；3.…

1. 修改stream_chat的接口，在请求体中选择knowledge_base_id;2. 增加stream_chat_bing接口；3. 增加了调用流式接口的方法说明；4. 优化cli_demo.py的逻辑：支持 输入提示；多输入；重新输入 (#630)

* 修复 bing_search.py的typo;更新model_config.py中Bing Subscription Key申请方式及注意事项

* 更新FAQ，增加了[Errno 110] Connection timed out的原因与解决方案

* 修改loader.py中load_in_8bit失败的原因和详细解决方案

* update loader.py

* stream_chat_bing

* 修改stream_chat的接口，在请求体中选择knowledge_base_id;增加stream_chat_bing接口

* 优化cli_demo.py的逻辑：支持 输入提示；多输入；重新输入

* update cli_demo.py

* 按照review建议进行修改

api.py

@@ -362,7 +362,7 @@ async def chat(
     )
 
 
-async def stream_chat(websocket: WebSocket, knowledge_base_id: str):
+async def stream_chat(websocket: WebSocket):
     await websocket.accept()
     turn = 1
     while True:
@@ -404,6 +404,41 @@ async def stream_chat(websocket: WebSocket, knowledge_base_id: str):
         )
         turn += 1
 
+async def stream_chat_bing(websocket: WebSocket):
+    """
+    基于bing搜索的流式问答
+    """
+    await websocket.accept()
+    turn = 1
+    while True:
+        input_json = await websocket.receive_json()
+        question, history = input_json["question"], input_json["history"]
+
+        await websocket.send_json({"question": question, "turn": turn, "flag": "start"})
+
+        last_print_len = 0
+        for resp, history in local_doc_qa.get_search_result_based_answer(question, chat_history=history, streaming=True):
+            await websocket.send_text(resp["result"][last_print_len:])
+            last_print_len = len(resp["result"])
+
+        source_documents = [
+            f"""出处 [{inum + 1}] {os.path.split(doc.metadata['source'])[-1]}：\n\n{doc.page_content}\n\n"""
+            f"""相关度：{doc.metadata['score']}\n\n"""
+            for inum, doc in enumerate(resp["source_documents"])
+        ]
+
+        await websocket.send_text(
+            json.dumps(
+                {
+                    "question": question,
+                    "turn": turn,
+                    "flag": "end",
+                    "sources_documents": source_documents,
+                },
+                ensure_ascii=False,
+            )
+        )
+        turn += 1
 
 async def document():
     return RedirectResponse(url="/docs")
@@ -428,10 +463,17 @@ def api_start(host, port):
             allow_methods=["*"],
             allow_headers=["*"],
         )
-    app.websocket("/local_doc_qa/stream-chat/{knowledge_base_id}")(stream_chat)
+    # 修改了stream_chat的接口，直接通过ws://localhost:7861/local_doc_qa/stream_chat建立连接，在请求体中选择knowledge_base_id
+    app.websocket("/local_doc_qa/stream_chat")(stream_chat)
 
     app.get("/", response_model=BaseResponse)(document)
 
+    # 增加基于bing搜索的流式问答
+    # 需要说明的是，如果想测试websocket的流式问答，需要使用支持websocket的测试工具，如postman,insomnia
+    # 强烈推荐开源的insomnia
+    # 在测试时选择new websocket request,并将url的协议改为ws,如ws://localhost:7861/local_doc_qa/stream_chat_bing
+    app.websocket("/local_doc_qa/stream_chat_bing")(stream_chat_bing)
+
     app.post("/chat", response_model=ChatMessage)(chat)
 
     app.post("/local_doc_qa/upload_file", response_model=BaseResponse)(upload_file)

chains/local_doc_qa.py

@@ -200,6 +200,7 @@ class LocalDocQA:
             return vs_path, loaded_files
         else:
             logger.info("文件均未成功加载，请检查依赖包或替换为其他文件再次上传。")
+
             return None, loaded_files
 
     def one_knowledge_add(self, vs_path, one_title, one_conent, one_content_segmentation, sentence_size):

cli_demo.py

@@ -23,11 +23,33 @@ def main():
                           top_k=VECTOR_SEARCH_TOP_K)
     vs_path = None
     while not vs_path:
+        print("注意输入的路径是完整的文件路径，例如knowledge_base/`knowledge_base_id`/content/file.md，多个路径用英文逗号分割")
         filepath = input("Input your local knowledge file path 请输入本地知识文件路径：")
+        
         # 判断 filepath 是否为空，如果为空的话，重新让用户输入,防止用户误触回车
         if not filepath:
             continue
-        vs_path, _ = local_doc_qa.init_knowledge_vector_store(filepath)
+
+        # 支持加载多个文件
+        filepath = filepath.split(",")
+        # filepath错误的返回为None, 如果直接用原先的vs_path,_ = local_doc_qa.init_knowledge_vector_store(filepath)
+        # 会直接导致TypeError: cannot unpack non-iterable NoneType object而使得程序直接退出
+        # 因此需要先加一层判断，保证程序能继续运行
+        temp,loaded_files = local_doc_qa.init_knowledge_vector_store(filepath)
+        if temp is not None:
+            vs_path = temp
+            # 如果loaded_files和len(filepath)不一致，则说明部分文件没有加载成功
+            # 如果是路径错误，则应该支持重新加载
+            if len(loaded_files) != len(filepath):
+                reload_flag = eval(input("部分文件加载失败，若提示路径不存在，可重新加载，是否重新加载，输入True或False: "))
+                if reload_flag:
+                    vs_path = None
+                    continue
+
+            print(f"the loaded vs_path is 加载的vs_path为: {vs_path}")
+        else:
+            print("load file failed, re-input your local knowledge file path 请重新输入本地知识文件路径")
+        
     history = []
     while True:
         query = input("Input your question 请输入问题：")