chore(frontend): add extra types to frontend

example.env

@@ -11,7 +11,7 @@ POSTGRES_DIR=
 
 # JWT
 JWT_SECRET_KEY=
-JWT_ACCESS_TOKEN_EXPIRES=1200
+JWT_ACCESS_TOKEN_EXPIRES=28800
 
 # Models
 HF_HOME=/models/huggingface

frontend/src/types/ApiTypes.ts

@@ -10,12 +10,6 @@ type FrequencyWord = {
     count: number;
 }
 
-type AverageEmotionByTopic = {
-    topic: string;
-    n: number;
-    [emotion: string]: string | number;
-}
-
 type Vocab = {
   author: string;
   events: number;
@@ -58,13 +52,25 @@ type HeatmapCell = {
 type TimeAnalysisResponse = {
     events_per_day: EventsPerDay[];
     weekday_hour_heatmap: HeatmapCell[];
-    burstiness: number;
 }
 
 // Content Analysis
+type NGram = {
+    count: number;
+    ngram: string;
+}
+
+type AverageEmotionByTopic = {
+    topic: string;
+    n: number;
+    [emotion: string]: string | number;
+}
+
 type ContentAnalysisResponse = {
     word_frequencies: FrequencyWord[];
     average_emotion_by_topic: AverageEmotionByTopic[];
+    common_three_phrases: NGram[];
+    common_two_phrases: NGram[];
 }
 
 // Summary

server/analysis/stat_gen.py

@@ -108,9 +108,7 @@ class StatGen:
         return {
             "top_users": self.interaction_analysis.top_users(filtered_df),
             "users": self.interaction_analysis.per_user_analysis(filtered_df),
-            "interaction_graph": self.interaction_analysis.interaction_graph(
-                filtered_df
-            ),
+            "interaction_graph": self.interaction_analysis.interaction_graph(filtered_df)
         }
 
     def get_interactional_analysis(self, df: pd.DataFrame, filters: dict | None = None) -> dict: