镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 14:36:48 +00:00
revise milvus rag
这个提交包含在:
@@ -21,16 +21,25 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
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# 1. we retrieve rag worker from global context
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# 1. we retrieve rag worker from global context
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user_name = chatbot.get_user()
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user_name = chatbot.get_user()
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checkpoint_dir = get_log_folder(user_name, plugin_name='experimental_rag')
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if user_name in RAG_WORKER_REGISTER:
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if user_name in RAG_WORKER_REGISTER:
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rag_worker = RAG_WORKER_REGISTER[user_name]
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rag_worker = RAG_WORKER_REGISTER[user_name]
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else:
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else:
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rag_worker = RAG_WORKER_REGISTER[user_name] = LlamaIndexRagWorker(
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rag_worker = RAG_WORKER_REGISTER[user_name] = LlamaIndexRagWorker(
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user_name,
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user_name,
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llm_kwargs,
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llm_kwargs,
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checkpoint_dir=get_log_folder(user_name, plugin_name='experimental_rag'),
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checkpoint_dir=checkpoint_dir,
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auto_load_checkpoint=True)
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auto_load_checkpoint=True)
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current_context = f"{VECTOR_STORE_TYPE} @ {checkpoint_dir}"
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tip = "提示:输入“清空向量数据库”可以清空RAG向量数据库"
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if txt == "清空向量数据库":
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chatbot.append([txt, f'正在清空 ({current_context}) ...'])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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rag_worker.purge()
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yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0) # 刷新界面
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return
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chatbot.append([txt, '正在召回知识 ...'])
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chatbot.append([txt, f'正在召回知识 ({current_context}) ...'])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# 2. clip history to reduce token consumption
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# 2. clip history to reduce token consumption
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@@ -75,8 +84,8 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
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)
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)
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# 5. remember what has been asked / answered
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# 5. remember what has been asked / answered
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yield from update_ui_lastest_msg(model_say + '</br></br>' + '对话记忆中, 请稍等 ...', chatbot, history, delay=0.5) # 刷新界面
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yield from update_ui_lastest_msg(model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...', chatbot, history, delay=0.5) # 刷新界面
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rag_worker.remember_qa(i_say_to_remember, model_say)
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rag_worker.remember_qa(i_say_to_remember, model_say)
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history.extend([i_say, model_say])
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history.extend([i_say, model_say])
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yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0) # 刷新界面
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yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip) # 刷新界面
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@@ -62,18 +62,31 @@ class MilvusSaveLoad():
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else:
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else:
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return self.create_new_vs(checkpoint_dir)
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return self.create_new_vs(checkpoint_dir)
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def create_new_vs(self, checkpoint_dir):
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def create_new_vs(self, checkpoint_dir, overwrite=False):
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vector_store = MilvusVectorStore(
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vector_store = MilvusVectorStore(
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uri=os.path.join(checkpoint_dir, "milvus_demo.db"),
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uri=os.path.join(checkpoint_dir, "milvus_demo.db"),
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dim=self.embed_model.embedding_dimension()
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dim=self.embed_model.embedding_dimension(),
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overwrite=overwrite
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)
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)
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storage_context = StorageContext.from_defaults(vector_store=vector_store)
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storage_context = StorageContext.from_defaults(vector_store=vector_store)
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index = GptacVectorStoreIndex.default_vector_store(storage_context=storage_context, embed_model=self.embed_model)
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index = GptacVectorStoreIndex.default_vector_store(storage_context=storage_context, embed_model=self.embed_model)
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return index
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return index
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def purge(self):
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self.vs_index = self.create_new_vs(self.checkpoint_dir, overwrite=True)
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class MilvusRagWorker(LlamaIndexRagWorker):
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class MilvusRagWorker(MilvusSaveLoad, LlamaIndexRagWorker):
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def __init__(self, user_name, llm_kwargs, auto_load_checkpoint=True, checkpoint_dir=None) -> None:
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self.debug_mode = True
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self.embed_model = OpenAiEmbeddingModel(llm_kwargs)
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self.user_name = user_name
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self.checkpoint_dir = checkpoint_dir
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if auto_load_checkpoint:
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self.vs_index = self.load_from_checkpoint(checkpoint_dir)
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else:
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self.vs_index = self.create_new_vs(checkpoint_dir)
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atexit.register(lambda: self.save_to_checkpoint(checkpoint_dir))
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def inspect_vector_store(self):
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def inspect_vector_store(self):
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# This function is for debugging
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# This function is for debugging
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@@ -178,7 +178,7 @@ def update_ui(chatbot:ChatBotWithCookies, history, msg="正常", **kwargs): #
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yield cookies, chatbot_gr, history, msg
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yield cookies, chatbot_gr, history, msg
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def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay=1): # 刷新界面
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def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay=1, msg="正常"): # 刷新界面
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"""
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"""
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刷新用户界面
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刷新用户界面
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"""
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"""
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@@ -186,7 +186,7 @@ def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list,
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chatbot.append(["update_ui_last_msg", lastmsg])
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chatbot.append(["update_ui_last_msg", lastmsg])
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chatbot[-1] = list(chatbot[-1])
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chatbot[-1] = list(chatbot[-1])
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chatbot[-1][-1] = lastmsg
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chatbot[-1][-1] = lastmsg
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yield from update_ui(chatbot=chatbot, history=history)
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yield from update_ui(chatbot=chatbot, history=history, msg=msg)
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time.sleep(delay)
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time.sleep(delay)
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在新工单中引用
屏蔽一个用户