add full examples

app.py

@@ -5,27 +5,29 @@ from pydantic import BaseModel
 import openai
 import os
 
-
 openai.api_base = "https://api.wzunjh.top/v1"
 
+
 def ask_gpt(prompt):
     response = openai.ChatCompletion.create(
-    model="gpt-3.5-turbo",  # here we use `gpt-3.5-turbo` model, while Stanford-Alpaca uses `text-davinci-003`
-    messages=[
-      {"role": "user", "content": prompt},
-    ]
+        model="gpt-3.5-turbo",  # here we use `gpt-3.5-turbo` model, while Stanford-Alpaca uses `text-davinci-003`
+        messages=[
+            {"role": "user", "content": prompt},
+        ]
     )
     print(response)
     return response.choices[0].message.content.strip()
 
+
 def ask_gpt_with_history(history):
     response = openai.ChatCompletion.create(
-    model="gpt-3.5-turbo",  # here we use `gpt-3.5-turbo` model, while Stanford-Alpaca uses `text-davinci-003`
-    messages=history
+        model="gpt-3.5-turbo",  # here we use `gpt-3.5-turbo` model, while Stanford-Alpaca uses `text-davinci-003`
+        messages=history
     )
     print(response)
     return response.choices[0].message.content.strip()
 
+
 async def predict(input, history):
     """
     Predict the response of the chatbot and complete a running list of chat history.
@@ -173,20 +175,22 @@ with gr.Blocks(title="HRMaster", theme="soft") as demo:
                 eduLevel_input = gr.Textbox(label="最低学历要求")
                 workYearArr_input = gr.Textbox(label="工作年限要求")
             with gr.Column():
-                jd_output_text = gr.outputs.Textbox(label="生成的岗位JD")
+                jd_output_text = gr.Textbox(label="生成的岗位JD")
                 jd_button = gr.Button(value="岗位JD生成")
                 jd_button.click(generate_jd, [jobTitle_input, eduLevel_input, workYearArr_input], jd_output_text)
-            # with gr.Column():
-        gr.Examples([["java开发工程师","本科","三年以上"],["算法工程师","研究生","一年以上"]],[jobTitle_input,eduLevel_input,workYearArr_input],[jd_output_text],fn=generate_jd, cache_examples=True,)
+            with gr.Column():
+                gr.Examples([["java开发工程师", "本科", "三年以上"], ["算法工程师", "研究生", "一年以上"]],
+                            [jobTitle_input, eduLevel_input, workYearArr_input], [jd_output_text], fn=generate_jd,
 
+                            )
 
     with gr.Tab("简历筛选辅助"):
         with gr.Row():
             resume_file = gr.File(label="请上传简历（目前仅支持上传txt格式简历）", file_types=["text"])
-            text_output = gr.outputs.Textbox(label="简历信息")
+            text_output = gr.Textbox(label="简历信息")
         talent_row = gr.Row(visible=False)
         with talent_row:
-            resume_text = gr.outputs.Textbox(label="人才画像")
+            resume_text = gr.Textbox(label="人才画像")
             hua_button = gr.Button(value="生成人才画像", )
             hua_button.click(generate_talent_portrait, text_output, resume_text)
 
@@ -196,16 +200,34 @@ with gr.Blocks(title="HRMaster", theme="soft") as demo:
             person_job_fit = gr.Textbox(label="人岗匹配度")
             fit_button = gr.Button(value="计算人岗匹配度", )
             fit_button.click(person_job_fit_gene, [text_output, jd], person_job_fit)
-
-        radar_row = gr.Row(visible=False)
-        with radar_row:
-            radar_outputs = gr.Plot(label="能力雷达图")
-            radar_reasons = gr.Textbox(label="打分理由")
-            radar_button = gr.Button(value="生成能力雷达图")
-            radar_button.click(gene_talent_radar, [text_output, jd], [radar_outputs, radar_reasons])
+            test_jd = '''
+            职位名称：Java开发工程师工作职责：
+            1. 根据业务需求，参与需求分析、系统设计和架构设计。
+            2. 开发和维护基于Java技术的Web应用程序、服务端组件和工具。
+            3. 编写高质量的可维护、可扩展的代码，并进行单元测试和代码审查。
+            4. 对现有系统进行优化和性能调优，确保系统的高可用性和稳定性。
+            5. 与产品经理、设计师和测试人员紧密合作，确保产品质量和用户体验。
+            6. 持续学习和研究新的技术和开发工具，提出并实施技术创新和改进。
+
+            任职要求：
+            1. 精通Java编程语言，熟悉Java相关的开发框架和工具，如Spring、Hibernate等。
+            2. 具备扎实的计算机基础知识，熟悉面向对象设计和设计模式。
+            3. 具备良好的数据结构和算法基础，对系统性能优化有一定的经验。
+            4. 熟悉Web开发相关的技术，如HTML、CSS、JavaScript等。
+            5. 具备良好的沟通能力和团队协作能力，能够与团队成员和其他相关岗位进行有效的沟通和合作。
+            6. 具备良好的问题解决能力和学习能力，能够快速地理解和解决技术问题。
+            7. 具备良好的代码风格和规范意识，注重代码质量和可维护性。
+            '''
+            gr.Examples([test_jd], [jd], [person_job_fit], fn=person_job_fit_gene, )
+            radar_row = gr.Row(visible=False)
+            with radar_row:
+                radar_outputs = gr.Plot(label="能力雷达图")
+                radar_reasons = gr.Textbox(label="打分理由")
+                radar_button = gr.Button(value="生成能力雷达图")
+                radar_button.click(gene_talent_radar, [text_output, jd], [radar_outputs, radar_reasons])
+        gr.Examples([os.path.join(os.path.dirname(__file__), "test_resume.txt")], resume_file,
+                    [text_output, talent_row, jd_row, radar_row], fn=parse_file, cache_examples=True)
         resume_file.change(parse_file, resume_file, [text_output, talent_row, jd_row, radar_row])
-        # gr.Examples([os.path.join(os.path.dirname(__file__), "test_resume.txt")],resume_file,[text_output, talent_row, jd_row, radar_row],fn=parse_file,cache_examples=True,)
-
 
     with gr.Tab("面试过程辅助"):
         interview_row = gr.Row(visible=True)
@@ -214,7 +236,8 @@ with gr.Blocks(title="HRMaster", theme="soft") as demo:
             interview_questions_generator_button = gr.Button(value="面试问题生成")
             copy_interview_questions_button = gr.Button(value="拷贝面试问题", visible=False)
             interview_questions_generator_button.click(generate_interview_questions_new, [text_output, jd],
-                                                       [interview_questions_text, copy_interview_questions_button])
+                                                       [interview_questions_text,
+                                                        copy_interview_questions_button])
 
     with gr.Tab("测试数据生成"):
         with gr.Row():
@@ -224,28 +247,42 @@ with gr.Blocks(title="HRMaster", theme="soft") as demo:
                 value=["个人信息", "教育背景", "工作经历", "技能专长", "项目经验", "自我评价"], multiselect=True, label="简历维度",
                 info="测试简历维度信息"
             )
-            test_resume_text = gr.outputs.Textbox(label="生成的测试简历信息")
+            test_resume_text = gr.Textbox(label="生成的测试简历信息")
             resume_gene_button = gr.Button("测试数据生成")
             resume_gene_button.click(generate_test_resume, [targrt_job, resume_item_list], test_resume_text)
+            test_targrt_job = "java开发工程师"
+            test_resume_item_list = ["个人信息", "教育背景", "工作经历", "实习经历", "技能专长", "项目经验", "获奖与荣誉", "自我评价"]
+            gr.Examples([[test_targrt_job, test_resume_item_list]], targrt_job, resume_item_list,
+                        fn=generate_test_resume,
+                        )
 
     with gr.Tab("面试评价生成器"):
         with gr.Row():
             with gr.Column():
-                commu_skills = gr.Radio(["强", "中", "弱"], label="沟通能力", info="评估候选人的口头表达能力、听取并理解问题的能力、回答问题的清晰度和逻辑性等。")
+                commu_skills = gr.Radio(["强", "中", "弱"], label="沟通能力",
+                                        info="评估候选人的口头表达能力、听取并理解问题的能力、回答问题的清晰度和逻辑性等。")
                 pro_skills = gr.Radio(["强", "中", "弱"], label="专业知识", info="评估候选人在岗位所需的专业知识的掌握程度。")
                 tech_skills = gr.Radio(["强", "中", "弱"], label="技术能力", info="评估候选人在岗位所需的专业技能方面的掌握程度。")
-                solve_skills = gr.Radio(["强", "中", "弱"], label="解决问题的能力", info="评估候选人在面对问题时的分析能力、创新思维、解决问题的方法和结果。")
+                solve_skills = gr.Radio(["强", "中", "弱"], label="解决问题的能力",
+                                        info="评估候选人在面对问题时的分析能力、创新思维、解决问题的方法和结果。")
                 team_skills = gr.Radio(["强", "中", "弱"], label="团队合作能力",
                                        info="评估候选人在与他人合作、协调和沟通方面的能力，包括与面试官的互动、参与小组讨论等。")
-                pressure_resistance = gr.Radio(["强", "中", "弱"], label="抗压能力", info="评估候选人在应对压力、处理复杂情境以及适应变化上的能力。")
+                pressure_resistance = gr.Radio(["强", "中", "弱"], label="抗压能力",
+                                               info="评估候选人在应对压力、处理复杂情境以及适应变化上的能力。")
                 if_ok = gr.Radio(["是", "否"], label="是否录用", info="最终结果")
+
             with gr.Column():
-                interview_feedback_text = gr.outputs.Textbox(label="面试评价")
+                interview_feedback_text = gr.Textbox(label="面试评价")
                 result_button = gr.Button(value="面试评价生成")
                 result_button.click(generate_interview_feedback,
                                     inputs=[commu_skills, pro_skills, tech_skills, solve_skills, team_skills,
                                             pressure_resistance, if_ok],
                                     outputs=interview_feedback_text)
+            gr.Examples([["强", "中", "弱", "强", "中", "弱", "是"]],
+                        [commu_skills, pro_skills, tech_skills, solve_skills, team_skills,
+                         pressure_resistance, if_ok], interview_feedback_text,
+                        fn=generate_interview_feedback,
+                        )
     with gr.Tab("HRChat"):
         with gr.Column():
             chatbot = gr.Chatbot(label="HRChat")
@@ -254,8 +291,8 @@ with gr.Blocks(title="HRMaster", theme="soft") as demo:
             txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
             txt.submit(predict, [txt, state], [chatbot, state])
             clear.click(lambda: None, None, chatbot, queue=False)
-    # with gr.Accordion("Open for More!"):
-    #     gr.Markdown("Look at me...")
+            # with gr.Accordion("Open for More!"):
+            #     gr.Markdown("Look at me...")
 
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0")
+        if __name__ == "__main__":
+            demo.launch()