Added custom interview type

resources/data.py

@@ -1,3 +1,5 @@
+interview_types = ["coding", "ml_design", "ml_theory", "system_design", "math", "sql", "custom"]
+
 topic_lists = {
     "coding": [
         "Arrays",
@@ -112,6 +114,9 @@ topic_lists = {
         "Transfer Learning",
         "Explainable AI",
     ],
+    "custom": [
+        "Specify any topic",
+    ],
 }
 
 fixed_messages = {

resources/prompts.py

@@ -292,4 +292,7 @@ Provide specific feedback with examples from the interview, offering corrections
 Provide detailed feedback, highlighting strengths and areas where understanding is lacking, supported by specific examples from the interview. Suggest targeted resources or study areas to help candidates improve. Summarize key points at the end of your feedback, focusing on actionable steps for improvement and further learning.
 """
     ),
+    "custom_problem_generation_prompt": base_problem_generation,
+    "custom_interviewer_prompt": base_interviewer,
+    "custom_grading_feedback_prompt": base_grading_feedback,
 }

tests/test_resources.py

@@ -0,0 +1,25 @@
+from resources.data import topic_lists, interview_types
+from resources.prompts import prompts
+
+
+def test_topics_completeness() -> None:
+    """
+    Test the completeness of topic lists.
+    """
+
+    assert len(topic_lists) == len(interview_types)
+    for interview_type in interview_types:
+        assert interview_type in topic_lists
+        assert len(topic_lists[interview_type]) > 0
+
+
+def test_prompts_completeness() -> None:
+    """
+    Test the completeness of prompts.
+    """
+
+    assert len(prompts) == len(interview_types) * 3
+    for interview_type in interview_types:
+        assert f"{interview_type}_problem_generation_prompt" in prompts
+        assert f"{interview_type}_interviewer_prompt" in prompts
+        assert f"{interview_type}_grading_feedback_prompt" in prompts

ui/coding.py

@@ -5,7 +5,7 @@ import os
 from itertools import chain
 import time
 
-from resources.data import fixed_messages, topic_lists
+from resources.data import fixed_messages, topic_lists, interview_types
 from utils.ui import add_candidate_message, add_interviewer_message
 from typing import List, Dict, Generator, Optional, Tuple
 from functools import partial
@@ -127,7 +127,7 @@ def get_problem_solving_ui(llm: LLMManager, tts: TTSManager, stt: STTManager, de
                 interview_type_select = gr.Dropdown(
                     show_label=False,
                     info="Type of the interview.",
-                    choices=["coding", "ml_design", "ml_theory", "system_design", "math", "sql"],
+                    choices=interview_types,
                     value="coding",
                     container=True,
                     allow_custom_value=False,