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import os |
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from typing import Dict |
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|
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import gradio as gr |
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import pandas as pd |
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|
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from chat_task.chat import generate_chat |
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from doc_qa_task.doc_qa import generate_doc_qa |
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from examples import ( |
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load_examples, |
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preprocess_docqa_examples, |
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preprocess_extraction_examples, |
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preprocess_qa_generator_examples, |
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) |
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from extract_data_task.extract import extract_slots |
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from plugin_task.api import api_plugin_chat |
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from qa_generator_task.generate_qa import generate_qa_pairs |
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from plugin_task.plugins import PLUGIN_JSON_SCHEMA |
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|
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abs_path = os.path.abspath(__file__) |
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current_dir = os.path.dirname(abs_path) |
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statistic_path = os.path.join(current_dir, "images") |
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|
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load_examples() |
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|
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def clear_session(): |
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"""Clears the chat session.""" |
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return "", None |
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def clear_plugin_session(session: Dict): |
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"""Clears the plugin session.""" |
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session.clear() |
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return session, None, None |
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|
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def show_custom_fallback_textbox(x): |
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if x == "自定义话术": |
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return [gr.Row(visible=True), gr.Textbox()] |
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else: |
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return [gr.Row(visible=False), gr.Textbox()] |
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|
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def validate_field_word_count( |
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input_text: str, description: str, max_word_count: int = 3000 |
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): |
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""" |
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Validate the input text for word count |
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|
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:param input_text: |
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:return: |
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""" |
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if len(input_text) == 0: |
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raise gr.Error(f"{description}不能为空") |
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|
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if len(input_text) > max_word_count: |
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raise gr.Error(f"{description}字数不能超过{max_word_count}字") |
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|
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def validate_chat(input_text: str): |
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""" |
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Validate the input text |
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|
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:param input_text: |
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:return: |
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""" |
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validate_field_word_count(input_text, "输入", 500) |
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|
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|
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def validate_doc_qa( |
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input_text: str, |
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doc_df: "pd.DataFrame", |
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fallback_ratio: str, |
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fallback_text_input: str, |
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): |
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""" |
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Validate fields of doc_qa |
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:param input_text: |
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:param doc_df: |
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:param fallback_ratio: |
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:param fallback_text_input: |
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:return: |
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""" |
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|
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if fallback_ratio == "自定义话术": |
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validate_field_word_count(fallback_text_input, "自定义话术", 100) |
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|
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validate_field_word_count(input_text, "输入", 500) |
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|
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page_content_full_text = ( |
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" ".join(doc_df["文档片段名称"].tolist()) |
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+ " " |
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+ " ".join(doc_df["文档片段内容"].tolist()) |
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) |
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validate_field_word_count(page_content_full_text, "文档信息", 2500) |
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|
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def validate_qa_pair_generator(input_text: str): |
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""" |
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Validate the input text |
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:param input_text: |
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:return: |
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""" |
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return validate_field_word_count(input_text, "输入") |
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|
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def validate_extraction( |
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input_text: str, |
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extraction_df: "pd.DataFrame", |
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): |
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""" |
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Validate fields of extraction |
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""" |
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extraction_full_text = ( |
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" ".join(extraction_df["字段名称"].tolist()) |
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+ " " |
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+ " ".join(extraction_df["字段描述"].tolist()) |
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) |
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validate_field_word_count(input_text, "输入", 1500) |
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validate_field_word_count(extraction_full_text, "待抽取字段描述", 1500) |
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|
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def validate_plugin(input_text: str): |
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""" |
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Validate the input text |
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|
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:param input_text: |
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:return: |
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""" |
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validate_field_word_count(input_text, "输入", 500) |
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with gr.Blocks( |
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title="Orion-14B", |
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theme="shivi/calm_seafoam@>=0.0.1,<1.0.0", |
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) as demo: |
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|
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def user(user_message, history): |
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return user_message, (history or []) + [[user_message, ""]] |
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|
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gr.Markdown( |
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""" |
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<div style="overflow: hidden;color:#fff;display: flex;flex-direction: column;align-items: center; position: relative; width: 100%; height: 180px;background-size: cover; background-image: url(https://www.orionstar.com/res/orics/down/ow001_20240119_8369eca9013416109a2303bf4e329140.png);"> |
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<img style="width: 130px;height: 60px;position: absolute;top:10px;left:10px" src="https://www.orionstar.com/res/orics/down/ow001_20240119_1236eba7ea0ac15931f4518d7f211d47.png"/> |
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<img style="min-width: 1416px; width: 1416px;height: 100px;margin-top: 30px;" src="https://www.orionstar.com/res/orics/down/ow001_20240119_10c5ca12a57116bda0e35916a28b247f.png"/> |
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<span style="margin-top: 10px;font-size: 12px;">请在<a href="https://github.com/OrionStarAI/Orion" style="color: white;">Github</a>点击Star支持我们，加入<a href="https://www.orionstar.com/res/orics/down/ow001_20240122_d87e5b4ea66a31493c38fcffe7bdb453.png" style="color: white;">官方微信交流群</a></span> |
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</div> |
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""" |
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) |
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with gr.Tab("基础能力"): |
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chatbot = gr.Chatbot( |
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label="Orion-14B-Chat", |
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elem_classes="control-height", |
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show_copy_button=True, |
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min_width=1368, |
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height=416, |
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) |
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chat_text_input = gr.Textbox(label="输入", min_width=1368) |
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|
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with gr.Row(): |
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with gr.Column(scale=2): |
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gr.Examples( |
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[ |
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"可以给我讲个笑话吗？", |
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"什么是伟大的诗歌？", |
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"你知道李白吗？", |
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"黑洞是如何工作的？", |
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"在表中插入一条数据，id为1，name为张三，age为18，请问SQL语句是什么？", |
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], |
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chat_text_input, |
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label="试试问", |
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) |
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with gr.Column(scale=1): |
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with gr.Row(variant="compact"): |
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clear_history = gr.Button( |
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"清除历史", |
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min_width="17", |
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size="sm", |
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scale=1, |
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icon=os.path.join(statistic_path, "clear.png"), |
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) |
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submit = gr.Button( |
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"发送", |
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variant="primary", |
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min_width="17", |
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size="sm", |
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scale=1, |
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icon=os.path.join(statistic_path, "send.svg"), |
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) |
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|
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chat_text_input.submit( |
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fn=validate_chat, inputs=[chat_text_input], outputs=[], queue=False |
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).success( |
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user, [chat_text_input, chatbot], [chat_text_input, chatbot], queue=False |
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).success( |
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fn=generate_chat, |
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inputs=[chat_text_input, chatbot], |
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outputs=[chat_text_input, chatbot], |
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) |
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|
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submit.click( |
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fn=validate_chat, inputs=[chat_text_input], outputs=[], queue=False |
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).success( |
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user, [chat_text_input, chatbot], [chat_text_input, chatbot], queue=False |
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).success( |
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fn=generate_chat, |
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inputs=[chat_text_input, chatbot], |
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outputs=[chat_text_input, chatbot], |
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api_name="chat", |
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) |
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|
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clear_history.click( |
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fn=clear_session, inputs=[], outputs=[chat_text_input, chatbot], queue=False |
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) |
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|
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with gr.Tab("基于文档问答"): |
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with gr.Row(): |
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with gr.Column(scale=3, min_width=357, variant="panel"): |
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gr.Markdown( |
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'<span style="color:rgba(0, 0, 0, 0.5); font-size: 14px; font-weight: 400; line-height: 28px; letter-spacing: 0em; text-align: left; width: 42px; height: 14px; left: 36px; top: 255px;">配置项</span>' |
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) |
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citations_radio = gr.Radio( |
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["开启引用", "关闭引用"], label="引用", value="关闭引用" |
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) |
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fallback_radio = gr.Radio( |
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["使用大模型知识", "自定义话术"], |
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label="超纲问题回复", |
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value="自定义话术", |
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) |
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fallback_text_input = gr.Textbox( |
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label="自定义话术", |
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value="抱歉，我还在学习中，暂时无法回答您的问题。", |
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) |
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|
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gr.Markdown( |
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'<span style="color:rgba(0, 0, 0, 0.5); font-size: 14px; font-weight: 400; line-height: 28px; letter-spacing: 0em; text-align: left; width: 42px; height: 14px; left: 36px; top: 255px;">文档信息</span>' |
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) |
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|
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doc_df = gr.Dataframe( |
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headers=["文档片段内容", "文档片段名称"], |
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datatype=["str", "str"], |
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row_count=6, |
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col_count=(2, "fixed"), |
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label="", |
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interactive=True, |
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wrap=True, |
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elem_classes="control-height", |
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height=300, |
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) |
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|
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with gr.Column(scale=2, min_width=430): |
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chatbot = gr.Chatbot( |
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label="适用场景：预期LLM通过自由知识回答", |
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elem_classes="control-height", |
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show_copy_button=True, |
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min_width=999, |
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height=419, |
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) |
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|
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doc_qa_input = gr.Textbox(label="输入", min_width=999, max_lines=10) |
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|
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with gr.Row(): |
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with gr.Column(scale=2): |
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gr.Examples( |
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[ |
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"哪些情况下不能超车？", |
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"参观须知", |
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"青岛啤酒酒精含量是多少？", |
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], |
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doc_qa_input, |
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label="试试问", |
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cache_examples=True, |
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fn=preprocess_docqa_examples, |
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outputs=[doc_df], |
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) |
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with gr.Column(scale=1): |
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with gr.Row(variant="compact"): |
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clear_history = gr.Button( |
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"清除历史", |
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min_width="17", |
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size="sm", |
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scale=1, |
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icon=os.path.join(statistic_path, "clear.png"), |
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) |
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submit = gr.Button( |
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"发送", |
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variant="primary", |
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min_width="17", |
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size="sm", |
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scale=1, |
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icon=os.path.join(statistic_path, "send.svg"), |
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) |
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|
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doc_qa_input.submit( |
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fn=validate_doc_qa, |
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inputs=[ |
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doc_qa_input, |
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doc_df, |
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fallback_radio, |
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fallback_text_input, |
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], |
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outputs=[], |
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queue=False, |
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).success( |
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user, [doc_qa_input, chatbot], [doc_qa_input, chatbot], queue=False |
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).success( |
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fn=generate_doc_qa, |
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inputs=[ |
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doc_qa_input, |
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chatbot, |
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doc_df, |
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fallback_radio, |
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fallback_text_input, |
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citations_radio, |
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], |
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outputs=[doc_qa_input, chatbot], |
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scroll_to_output=True, |
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api_name="doc_qa", |
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) |
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|
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submit.click( |
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fn=validate_doc_qa, |
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inputs=[ |
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doc_qa_input, |
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doc_df, |
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fallback_radio, |
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fallback_text_input, |
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], |
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outputs=[], |
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queue=False, |
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).success( |
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user, [doc_qa_input, chatbot], [doc_qa_input, chatbot], queue=False |
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).success( |
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fn=generate_doc_qa, |
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inputs=[ |
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doc_qa_input, |
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chatbot, |
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doc_df, |
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fallback_radio, |
|
fallback_text_input, |
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citations_radio, |
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], |
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outputs=[doc_qa_input, chatbot], |
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scroll_to_output=True, |
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) |
|
|
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clear_history.click( |
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fn=lambda x: (None, None, None), |
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inputs=[], |
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outputs=[doc_df, doc_qa_input, chatbot], |
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queue=False, |
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) |
|
|
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with gr.Tab("插件能力"): |
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with gr.Row(): |
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with gr.Column(scale=1): |
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gr.Markdown( |
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'<span style="color:rgba(0, 0, 0, 0.5); font-size: 14px; font-weight: 400; line-height: 28px; letter-spacing: 0em; text-align: left; width: 42px; height: 14px; left: 36px; top: 255px;">配置项</span>' |
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) |
|
|
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radio_plugins = [ |
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gr.Radio( |
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["开启", "关闭"], |
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label=plugin_json["name_for_human"], |
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value="开启", |
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) |
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for plugin_json in PLUGIN_JSON_SCHEMA |
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] |
|
|
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with gr.Column(scale=3): |
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session = gr.State(value=dict()) |
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chatbot = gr.Chatbot( |
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label="适用场景:需要LLM调用API解决问题", |
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elem_classes="control-height", |
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show_copy_button=True, |
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) |
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plugin_text_input = gr.Textbox(label="输入") |
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with gr.Row(): |
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with gr.Column(scale=2): |
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gr.Examples( |
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[ |
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"北京天气怎么样？", |
|
"查询物流信息", |
|
"每日壁纸", |
|
"bing今天的壁纸是什么", |
|
"查询手机号码归属地", |
|
], |
|
plugin_text_input, |
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label="试试问", |
|
) |
|
with gr.Column(scale=1): |
|
with gr.Row(variant="compact"): |
|
clear_history = gr.Button( |
|
"清除历史", |
|
min_width="17", |
|
size="sm", |
|
scale=1, |
|
icon=os.path.join(statistic_path, "clear.png"), |
|
) |
|
submit = gr.Button( |
|
"发送", |
|
variant="primary", |
|
min_width="17", |
|
size="sm", |
|
scale=1, |
|
icon=os.path.join(statistic_path, "send.svg"), |
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) |
|
|
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plugin_text_input.submit( |
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fn=validate_plugin, |
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inputs=[ |
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plugin_text_input, |
|
], |
|
outputs=[], |
|
queue=False, |
|
).success( |
|
user, |
|
[plugin_text_input, chatbot], |
|
[plugin_text_input, chatbot], |
|
scroll_to_output=True, |
|
).success( |
|
fn=api_plugin_chat, |
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inputs=[session, plugin_text_input, chatbot, *radio_plugins], |
|
outputs=[session, plugin_text_input, chatbot], |
|
scroll_to_output=True, |
|
) |
|
|
|
submit.click( |
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fn=validate_plugin, |
|
inputs=[ |
|
plugin_text_input, |
|
], |
|
outputs=[], |
|
queue=False, |
|
).success( |
|
user, |
|
[plugin_text_input, chatbot], |
|
[plugin_text_input, chatbot], |
|
scroll_to_output=True, |
|
).success( |
|
fn=api_plugin_chat, |
|
inputs=[session, plugin_text_input, chatbot, *radio_plugins], |
|
outputs=[session, plugin_text_input, chatbot], |
|
api_name="plugin", |
|
scroll_to_output=True, |
|
) |
|
|
|
clear_history.click( |
|
fn=clear_plugin_session, |
|
inputs=[session], |
|
outputs=[session, plugin_text_input, chatbot], |
|
queue=False, |
|
) |
|
with gr.Tab("生成QA对"): |
|
with gr.Row(equal_height=True): |
|
qa_generator_output = gr.Code( |
|
language="json", |
|
show_label=False, |
|
min_width=1368, |
|
) |
|
with gr.Row(): |
|
qa_generator_input = gr.Textbox( |
|
label="输入", |
|
show_label=True, |
|
info="", |
|
min_width=1368, |
|
lines=5, |
|
max_lines=10, |
|
) |
|
|
|
with gr.Row(): |
|
with gr.Column(scale=2): |
|
gr.Examples( |
|
[ |
|
"第一章 总 则 \n第...", |
|
"金字塔，在建筑学上是...", |
|
"山西老陈醋是以高粱、...", |
|
"室内装饰构造虚拟仿真...", |
|
"猎户星空（Orion...", |
|
], |
|
qa_generator_input, |
|
label="试试问", |
|
cache_examples=True, |
|
fn=preprocess_qa_generator_examples, |
|
outputs=[qa_generator_input], |
|
) |
|
with gr.Column(scale=1): |
|
with gr.Row(variant="compact"): |
|
clear = gr.Button( |
|
"清除", |
|
min_width="17", |
|
size="sm", |
|
scale=1, |
|
icon=os.path.join(statistic_path, "clear.png"), |
|
) |
|
submit = gr.Button( |
|
"发送", |
|
variant="primary", |
|
min_width="17", |
|
size="sm", |
|
scale=1, |
|
icon=os.path.join(statistic_path, "send.svg"), |
|
) |
|
|
|
submit.click( |
|
fn=validate_qa_pair_generator, |
|
inputs=[qa_generator_input], |
|
outputs=[], |
|
).success( |
|
fn=generate_qa_pairs, |
|
inputs=[qa_generator_input], |
|
outputs=[qa_generator_output, qa_generator_input], |
|
scroll_to_output=True, |
|
api_name="qa_generator", |
|
) |
|
|
|
clear.click( |
|
fn=lambda x: ("", ""), |
|
inputs=[], |
|
outputs=[qa_generator_input, qa_generator_output], |
|
queue=False, |
|
) |
|
|
|
with gr.Tab("抽取数据"): |
|
extract_outpu_df = gr.Dataframe( |
|
label="", |
|
headers=["字段名称", "字段抽取结果"], |
|
datatype=["str", "str"], |
|
col_count=(2, "fixed"), |
|
wrap=True, |
|
elem_classes="control-height", |
|
height=234, |
|
row_count=5, |
|
) |
|
|
|
extract_input = gr.Textbox(label="输入", lines=5, min_width=1368, max_lines=10) |
|
|
|
extraction_df = gr.Dataframe( |
|
headers=["字段名称", "字段描述"], |
|
datatype=["str", "str"], |
|
row_count=3, |
|
col_count=(2, "fixed"), |
|
label="", |
|
interactive=True, |
|
wrap=True, |
|
elem_classes="control-height", |
|
height=180, |
|
) |
|
|
|
with gr.Row(): |
|
with gr.Column(scale=2): |
|
gr.Examples( |
|
["第一条合同当...", "发票编号: IN...", "发件人：John..."], |
|
extract_input, |
|
label="试试问", |
|
cache_examples=True, |
|
fn=preprocess_extraction_examples, |
|
outputs=[extract_input, extraction_df], |
|
) |
|
with gr.Column(scale=1): |
|
with gr.Row(variant="compact"): |
|
clear = gr.Button( |
|
"清除历史", |
|
min_width="17", |
|
size="sm", |
|
scale=1, |
|
icon=os.path.join(statistic_path, "clear.png"), |
|
) |
|
submit = gr.Button( |
|
"发送", |
|
variant="primary", |
|
min_width="17", |
|
size="sm", |
|
scale=1, |
|
icon=os.path.join(statistic_path, "send.svg"), |
|
) |
|
|
|
submit.click( |
|
fn=validate_extraction, |
|
inputs=[extract_input, extraction_df], |
|
outputs=[], |
|
).success( |
|
fn=extract_slots, |
|
inputs=[extract_input, extraction_df], |
|
outputs=[extract_outpu_df], |
|
scroll_to_output=True, |
|
api_name="extract", |
|
) |
|
|
|
clear.click( |
|
fn=lambda x: ("", None, None), |
|
inputs=[], |
|
outputs=[ |
|
extract_input, |
|
extraction_df, |
|
extract_outpu_df, |
|
], |
|
queue=False, |
|
) |
|
|
|
|
|
if __name__ == "__main__": |
|
demo.queue(api_open=False, max_size=40).launch( |
|
height=800, |
|
share=False, |
|
server_name="0.0.0.0", |
|
show_api=False, |
|
max_threads=4, |
|
) |
|
|
