updating workflow without resume upload

app.py

@@ -17,11 +17,11 @@ with open("sys_prompt.txt") as f:
     sys_prompt = f.read()
 
 get_window_url_params = """
-    function(job, job_params) {
+    function(job, resume, job_params) {
         console.log(job, job_params);
         const params = new URLSearchParams(window.location.search);
         job_params = Object.fromEntries(params);
-        return [job, job_params];
+        return [job, resume, job_params];
         }
     """
 
@@ -76,21 +76,23 @@ def download_pdf_blob_as_text(storage_connection_string, container_name, blob_na
         print(f"Fehler beim Herunterladen und Konvertieren der Datei: {str(e)}")
         return None
 
-def load_job_data(job, job_params):
+def load_job_data(job, resume, job_params):
     if not job:
         try:
             print("Hello there")
             print(job_params["job"])
-            pdf_filename = job_params["job"]+".pdf"
+            pdf_filename_jobdescription = job_params["job"]+".pdf"
+            pdf_filename_cv = job_params["job"]+"_resume.pdf"
             json_filename = job_params["job"]+"_jsondata.json" 
             storage_connection_string = os_connection_string
             container_name = "jobdescriptions"  # Der Name des Blob-Containers
-            job = download_pdf_blob_as_text(storage_connection_string, container_name, pdf_filename)
+            job = download_pdf_blob_as_text(storage_connection_string, container_name, pdf_filename_jobdescription)
+            resume = download_pdf_blob_as_text(storage_connection_string, container_name, pdf_filename_cv)
             job_params = download_and_parse_json_blob(storage_connection_string,container_name,json_filename)
-            return job, job_params, gr.Label.update("Evaluation for the job: "+job_params[0])
+            return job, resume, job_params, gr.Label.update("Evaluation for the job: "+job_params[0])
         except:
             gr.Error("An error occurred, the job description could not be loaded. Please contact the recruiter.")
-            return job, job_params, gr.Label.update("An error occurred and the job description could not be loaded. Please contact the recruiter.", color="red") 
+            return job, resume, job_params, gr.Label.update("An error occurred and the job description could not be loaded. Please contact the recruiter.", color="red") 
         # print(job)
         # print(job_params)
 
@@ -165,7 +167,7 @@ def send_evaluation(history, job, resume, job_params):
     sg = sendgrid.SendGridAPIClient(api_key=os.environ.get('SENDGRID_API'))
 
     # Sender- und Empfänger-E-Mail-Adressen
-    sender_email = "marcel.bosse@tensora.co"
+    sender_email = "workgeniusjobevaluation@gmail.com"
     receiver_email = job_params[1]
     print(receiver_email)
 
@@ -189,13 +191,9 @@ def send_evaluation(history, job, resume, job_params):
     # E-Mail-Nachricht erstellen
     subject = "Evaluation for the job: "+job_params[0]
     message = f"""Dear Recruiter,
-
-Please find attached the complete chat history for this evaluation and resume.
-
+Please find attached the complete chat history for this evaluation, resume and summary.
 The evaluation AI-supported summarized:
-
 {ai_summary}
-
 Sincerely,
 Your Evaluation Tool
 """
@@ -210,6 +208,11 @@ Your Evaluation Tool
     with open(resume_file_path, 'wb') as resume_file:
         resume_file.write(resume.encode('utf-8'))
 
+    # Summary in eine TXT Datei schreiben
+    summary_file_path = "summary.txt"
+    with open(summary_file_path, 'wb') as summary_file:
+        summary_file.write(ai_summary.encode('utf-8'))
+
     # SendGrid-E-Mail erstellen
     message = Mail(
         from_email=sender_email,
@@ -238,13 +241,27 @@ Your Evaluation Tool
         resume_attachment.disposition = Disposition('attachment')
         message.attachment = resume_attachment
 
+    # Resume als Anhang hinzufügen
+    with open(summary_file_path, 'rb') as summary_file:
+        encode_file_summary = base64.b64encode(summary_file.read()).decode()
+        summary_attachment = Attachment()
+        summary_attachment.file_content = FileContent(encode_file_summary)
+        summary_attachment.file_name = FileName('ai_summary.txt')
+        summary_attachment.file_type = FileType('text/plain')
+        summary_attachment.disposition = Disposition('attachment')
+        message.attachment = summary_attachment
+
     try:
         response = sg.send(message)
         print("E-Mail wurde erfolgreich gesendet. Statuscode:", response.status_code)
     except Exception as e:
         print("Fehler beim Senden der E-Mail:", str(e))
 
-css = "footer {visibility: hidden} #component-0{height: 90vh !important} #chatbot{height: 85vh !important}}"
+def handle_start_click(welcome_label, start):
+    return gr.Label.update("", visible=False), gr.Button.update("Start Evaluation", scale=0,interactive=False)
+
+
+css = "footer {visibility: hidden} #component-0{height: 90vh !important} #chatbot{height: 85vh !important} #welcome_label {text-align: center!important}"
 
 with gr.Blocks(css=css) as app:
     job_params = gr.JSON({}, visible=False, label="URL Params")
@@ -253,22 +270,26 @@ with gr.Blocks(css=css) as app:
     gr.Markdown(
         f"<div style='display: flex; justify-content: space-between;align-items: center;margin-bottom: 1rem' ><h1>CV Evaluation</h1><img width='150' src='https://www.workgenius.com/wp-content/uploads/2023/03/WorkGenius_navy-1.svg' alt='WorkGeniusLogo' /></div>"
     )
-    input_test = gr.Label("An error occurred and the job description could not be loaded. Please contact the recruiter.", show_label=False)
-    app.load(load_job_data,[job, job_params], [job, job_params, input_test], _js=get_window_url_params)
+    job_title_label = gr.Label("An error occurred and the job description could not be loaded. Please contact the recruiter.", show_label=False)
+    welcome_label = gr.Label("Welcome to the interview chatbot from WorkGenius. After clicking on the 'Start interview' button, you will be asked 10 questions to discuss whether you are a good fit for the job. Please answer the questions honestly and in detail. Good luck!", show_label=False, elem_id="welcome_label")
+    app.load(load_job_data,[job,resume, job_params], [job,resume, job_params, job_title_label], _js=get_window_url_params)
     chat = gr.Chatbot(
-        [[None, "Please upload your resume to begin the evaluation process. After uploading, approximately 10 questions will be asked to determine if the position is a good fit for you. The entire process takes about 10 to 15 minutes."]], height=600, elem_id="chatbot"
+        [[None, None]], height=600, elem_id="chatbot"
     )
     with gr.Row():
         clr = gr.Button("Clear", scale=0)
         msg = gr.Textbox(lines=1, show_label=False, scale=1)
-        file = gr.UploadButton("Browse", file_types=[".pdf", ".txt"], scale=0)
+        start = gr.Button("Start interview", scale=0)
+        # file = gr.UploadButton("Browse", file_types=[".pdf", ".txt"], scale=0)
     msg.submit(user, [msg, chat], [msg, chat], queue=False).then(
         bot, [chat, job, resume, job_params], chat
     )
-    file.upload(
-        add_file, [file, chat, job, resume], [chat, job, resume], queue=False
-    ).then(bot, [chat, job, resume, job_params], chat)
+    # file.upload(
+    #     add_file, [file, chat, job, resume], [chat, job, resume], queue=False
+    # ).then(bot, [chat, job, resume, job_params], chat)
+    #().then
+    start.click(handle_start_click,[welcome_label, start],[welcome_label, start]).then(bot, [chat, job, resume, job_params], chat)
     clr.click(lambda: None, None, chat, queue=False)
 
 app.queue()
-app.launch()
+app.launch()