- Full Traicie Selection Specialist Flow implemented
- Added Specialist basics for handling phases and automatically transferring data between state and output - Added QR-code generation for Magic Links
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@@ -16,10 +16,10 @@ backstory: >
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AI-driven sourcing. You’re more than a recruiter—you’re a trusted advisor, a brand ambassador, and a connector of
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people and purpose.
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{custom_backstory}
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full_model_name: "mistral.mistral-medium-latest"
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full_model_name: "mistral.magistral-medium-latest"
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temperature: 0.3
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metadata:
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author: "Josako"
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date_added: "2025-06-18"
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description: "HR BP Agent."
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description: "Traicie Recruiter Agent"
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changes: "Initial version"
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@@ -275,6 +275,7 @@ class DevConfig(Config):
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# Define the nginx prefix used for the specific apps
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EVEAI_APP_LOCATION_PREFIX = '/admin'
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EVEAI_CHAT_LOCATION_PREFIX = '/chat'
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CHAT_CLIENT_PREFIX = 'chat-client/chat/'
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# file upload settings
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# UPLOAD_FOLDER = '/app/tenant_files'
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@@ -0,0 +1,37 @@
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version: "1.0.0"
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name: "KO Criteria Interview Definition"
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task_description: >
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In context of a vacancy in your company {tenant_name}, you are provided with a set of competencies
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(both description and title). The competencies are in between triple backquotes. The competencies provided should be
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handled as knock-out criteria.
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For each of the knock-out criteria, you need to define
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- A short (1 sentence), closed-ended question (Yes / No) to ask the recruitment candidate. Use your experience to ask a question that
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enables us to verify compliancy to the criterium.
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- A set of 2 short answers (1 small sentence each) to that question (positive answer / negative answer), from the
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candidates perspective.
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The positive answer will result in a positive evaluation of the criterium, the negative answer in a negative evaluation
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of the criterium. Try to avoid just using Yes / No as positive and negative answers.
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Apply the following tone of voice in both questions and answers: {tone_of_voice}, i.e. {tone_of_voice_context}
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Apply the following language level in both questions and answers: {language_level}, i.e. {language_level_context}
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Use {language} as language for both questions and answers.
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```{ko_criteria}```
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{custom_description}
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expected_output: >
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For each of the ko criteria, you provide:
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- the exact title as specified in the original language
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- the question in {language}
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- a positive answer, resulting in a positive evaluation of the criterium. In {language}.
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- a negative answer, resulting in a negative evaluation of the criterium. In {language}.
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{custom_expected_output}
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metadata:
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author: "Josako"
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date_added: "2025-06-20"
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description: "A Task to define interview Q&A from given KO Criteria"
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changes: "Improvement to ensure closed-ended questions and short descriptions"
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