From cda18c6a600f77a29466c8fe5bd9271cc7bae985 Mon Sep 17 00:00:00 2001 From: imClumsyPanda Date: Thu, 11 May 2023 00:08:39 +0800 Subject: [PATCH] update README.md --- webui.py | 49 +++++++++++++++++++++++++++---------------------- 1 file changed, 27 insertions(+), 22 deletions(-) diff --git a/webui.py b/webui.py index 1a4748e..b071e09 100644 --- a/webui.py +++ b/webui.py @@ -45,25 +45,29 @@ def get_answer(query, vs_path, history, mode, score_threshold=VECTOR_SEARCH_SCOR enumerate(resp["source_documents"])]) history[-1][-1] += source yield history, "" - elif mode == "知识库测试" and os.path.exists(vs_path): - resp, prompt = local_doc_qa.get_knowledge_based_conent_test(query=query, vs_path=vs_path, - score_threshold=score_threshold, - vector_search_top_k=vector_search_top_k, - chunk_conent=chunk_conent, - chunk_size=chunk_size) - if not resp["source_documents"]: - yield history + [[query, - "根据您的设定，没有匹配到任何内容，请确认您设置的score阈值是否过小或其他参数是否正确！"]], "" + elif mode == "知识库测试": + if os.path.exists(vs_path): + resp, prompt = local_doc_qa.get_knowledge_based_conent_test(query=query, vs_path=vs_path, + score_threshold=score_threshold, + vector_search_top_k=vector_search_top_k, + chunk_conent=chunk_conent, + chunk_size=chunk_size) + if not resp["source_documents"]: + yield history + [[query, + "根据您的设定，没有匹配到任何内容，请确认您设置的知识相关度 Score 阈值是否过小或其他参数是否正确。"]], "" + else: + source = "\n".join( + [ + f"""
【知识相关度 Score】：{doc.metadata["score"]} - 【出处{i + 1}】： {os.path.split(doc.metadata["source"])[-1]} \n""" + f"""{doc.page_content}\n""" + f"""
""" + for i, doc in + enumerate(resp["source_documents"])]) + history.append([query, "以下内容为知识库中满足设置条件的匹配结果：\n\n" + source]) + yield history, "" else: - source = "".join( - [ - f"""
【出处{i + 1}】： {os.path.split(doc.metadata["source"])[-1]} - 【内容匹配相关度 Score】：{doc.metadata["score"]}\n""" - f"""{doc.page_content}\n""" - f"""
""" - for i, doc in - enumerate(resp["source_documents"])]) - history.append([query, prompt + source]) - yield history, "" + yield history + [[query, + "请选择知识库后进行测试，当前未选择知识库。"]], "" else: for resp, history in local_doc_qa.llm._call(query, history, streaming=streaming): history[-1][-1] = resp + ( @@ -147,11 +151,12 @@ def change_vs_name_input(vs_id, history): knowledge_base_test_mode_info = ("【注意】\n\n" "1. 您已进入知识库测试模式，您输入的任何对话内容都将用于进行知识库查询，" "并仅输出知识库匹配出的内容及相似度分值和及输入的文本源路径，查询的内容并不会进入模型查询。\n\n" - "2. 匹配内容相关度 Score 经测试，建议设置为 500 或更低，具体设置情况请结合实际使用调整。" + "2. 知识相关度 Score 经测试，建议设置为 500 或更低，具体设置情况请结合实际使用调整。" """3. 使用"添加单条数据"添加文本至知识库时，内容如未分段，则内容越多越会稀释各查询内容与之关联的score阈值。\n\n""" "4. 单条内容长度建议设置在100-150左右。\n\n" "5. 本界面用于知识入库及知识匹配相关参数设定，但当前版本中，" - "本界面中修改的参数并不会直接修改对话界面中参数，仍需前往`configs/model_config.py`修改后生效") + "本界面中修改的参数并不会直接修改对话界面中参数，仍需前往`configs/model_config.py`修改后生效。" + "相关参数将在后续版本中支持本界面直接修改。") def change_mode(mode, history): @@ -308,7 +313,7 @@ with gr.Blocks(css=block_css) as demo: outputs=[vs_setting, knowledge_set, chatbot]) with knowledge_set: score_threshold = gr.Number(value=VECTOR_SEARCH_SCORE_THRESHOLD, - label="内容相关度 Score 阈值，分值越低匹配度越高", + label="知识相关度 Score 阈值，分值越低匹配度越高", precision=0, interactive=True) vector_search_top_k = gr.Number(value=VECTOR_SEARCH_TOP_K, precision=0, @@ -317,7 +322,7 @@ with gr.Blocks(css=block_css) as demo: label="是否启用上下文关联", interactive=True) chunk_sizes = gr.Number(value=CHUNK_SIZE, precision=0, - label="匹配单段内容的连接上下文长度", + label="匹配单段内容的连接上下文后最大长度", interactive=True, visible=False) chunk_conent.change(fn=change_chunk_conent, inputs=[chunk_conent, gr.Textbox(value="chunk_conent", visible=False), chatbot],