Implement black code formatter

requirements.txt

@@ -1,2 +1,3 @@
 gradio==5.6.0
-gradio_client==1.4.3
+gradio_client==1.4.3
+black==24.10.0

src/domain/candidate.py

@@ -1,6 +1,7 @@
 from dataclasses import dataclass
 from typing import Dict, List
 
+
 @dataclass
 class Candidate:
     id: str
@@ -9,4 +10,4 @@ class Candidate:
     resume_data: Dict
     interview_responses: List[str]
     emotional_metrics: Dict
-    feedback: Dict
+    feedback: Dict

src/domain/emotion_metrics.py

@@ -1,6 +1,7 @@
 from dataclasses import dataclass
 from typing import List, Dict
 
+
 @dataclass
 class EmotionMetrics:
     confidence_score: float
@@ -11,4 +12,4 @@ class EmotionMetrics:
 
     def calculate_overall_score(self) -> float:
         # Implementation for calculating overall emotional score
-        pass
+        pass

src/domain/enums/emotion_types.py

@@ -1,5 +1,6 @@
 from enum import Enum
 
+
 class EmotionType(Enum):
     HAPPY = "happy"
     SAD = "sad"
@@ -15,4 +16,4 @@ class EmotionType(Enum):
 
     @classmethod
     def get_negative_emotions(cls):
-        return [cls.SAD, cls.ANGRY, cls.FEARFUL, cls.DISGUSTED]
+        return [cls.SAD, cls.ANGRY, cls.FEARFUL, cls.DISGUSTED]

src/domain/enums/interview_status.py

@@ -1,5 +1,6 @@
 from enum import Enum, auto
 
+
 class InterviewStatus(Enum):
     SCHEDULED = auto()
     IN_PROGRESS = auto()
@@ -7,4 +8,4 @@ class InterviewStatus(Enum):
     CANCELLED = auto()
     PENDING_REVIEW = auto()
     REVIEWED = auto()
-    FAILED = auto()
+    FAILED = auto()

src/domain/interview.py

@@ -4,6 +4,7 @@ from typing import List, Dict
 from src.domain.enums.interview_status import InterviewStatus
 from src.domain.enums.emotion_types import EmotionType
 
+
 @dataclass
 class Interview:
     id: str
@@ -21,4 +22,7 @@ class Interview:
         return self.status == InterviewStatus.COMPLETED
 
     def is_reviewable(self) -> bool:
-        return self.status in [InterviewStatus.COMPLETED, InterviewStatus.PENDING_REVIEW]
+        return self.status in [
+            InterviewStatus.COMPLETED,
+            InterviewStatus.PENDING_REVIEW,
+        ]

src/domain/resume.py

@@ -1,6 +1,7 @@
 from dataclasses import dataclass
 from typing import List, Dict
 
+
 @dataclass
 class Resume:
     id: str

src/frontend/interface.py

@@ -5,6 +5,7 @@ from src.infrastructure.llm import LangchainService
 from src.infrastructure.emotion import DeepFaceService
 from src.infrastructure.speech import GoogleSpeechService
 
+
 class GradioInterface:
     def __init__(self):
         # Initialize services
@@ -16,14 +17,12 @@ class GradioInterface:
         self.analyzer = InterviewAnalyzer(
             emotion_service=self.emotion_service,
             speech_service=self.speech_service,
-            llm_service=self.llm_service
+            llm_service=self.llm_service,
         )
 
     def create_interface(self) -> gr.Interface:
         def process_submission(
-                video_file: str,
-                resume_file: str,
-                job_requirements: str
+            video_file: str, resume_file: str, job_requirements: str
         ) -> Dict:
             # Implementation for processing submission
             pass
@@ -34,19 +33,21 @@ class GradioInterface:
             inputs=[
                 gr.Video(label="Interview Recording"),
                 gr.File(label="Resume"),
-                gr.Textbox(label="Job Requirements", lines=5)
+                gr.Textbox(label="Job Requirements", lines=5),
             ],
             outputs=gr.JSON(label="Analysis Results"),
             title="HR Interview Analysis System",
-            description="Upload interview recording and resume to analyze candidate performance"
+            description="Upload interview recording and resume to analyze candidate performance",
         )
 
         return interface
 
+
 def launch_app():
     app = GradioInterface()
     interface = app.create_interface()
     interface.launch()
 
+
 if __name__ == "__main__":
-    launch_app()
+    launch_app()

src/service/interview_analyzer.py

@@ -3,12 +3,15 @@ from src.domain.enums.emotion_types import EmotionType
 from src.domain.entities.interview import Interview
 from typing import Dict, List
 
+
 class InterviewAnalyzer:
     def validate_video(self, video_path: str) -> bool:
-        file_extension = video_path[video_path.rfind("."):]
+        file_extension = video_path[video_path.rfind(".") :]
         return VideoFileType.validate_format(file_extension)
 
-    def analyze_emotions(self, emotion_data: Dict[str, float]) -> Dict[EmotionType, float]:
+    def analyze_emotions(
+        self, emotion_data: Dict[str, float]
+    ) -> Dict[EmotionType, float]:
         analyzed_emotions = {}
         for emotion_name, score in emotion_data.items():
             try:
@@ -18,10 +21,12 @@ class InterviewAnalyzer:
                 continue
         return analyzed_emotions
 
-    def get_dominant_emotion(self, emotion_scores: Dict[EmotionType, float]) -> EmotionType:
+    def get_dominant_emotion(
+        self, emotion_scores: Dict[EmotionType, float]
+    ) -> EmotionType:
         return max(emotion_scores.items(), key=lambda x: x[1])[0]
 
     def is_positive_response(self, emotion_scores: Dict[EmotionType, float]) -> bool:
         positive_emotions = EmotionType.get_positive_emotions()
         dominant_emotion = self.get_dominant_emotion(emotion_scores)
-        return dominant_emotion in positive_emotions
+        return dominant_emotion in positive_emotions