Addind sqlite

.gitignore

@@ -1,3 +1,4 @@
 __pycache__/*
 vtt_files/*
-venv/*
+venv/*
+rag.db

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 import requests
 from mvp import tbl
-import sqlite3
 
 # # Function to call your system API and get the response
 # def search_question(question):

mvp.py

@@ -21,6 +21,21 @@ embedding_model = SentenceTransformer(model_name)
 model_registry = get_registry().get("sentence-transformers")
 model = model_registry.create(name="BAAI/bge-small-en-v1.5")
 
+def create_interactions(db_path = "/data/rag.db"):
+    conn = sqlite3.connect(db_path)
+    cursor = conn.cursor()
+    cursor.execute("""CREATE TABLE IF NOT EXISTS interactions (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            question TEXT,
+            chunks TEXT,
+            coherent_answer TEXT,
+            feedback TEXT,
+            additional_feedback TEXT
+        )""")    
+    conn.close()
+    
+create_interactions()
+
 class Document(LanceModel):
     text: str = model.SourceField()
     vector: Vector(384) = model.VectorField()
@@ -63,7 +78,7 @@ def read_chunks_from_db(db_path):
 reranker = ColbertReranker()
 
 # Function to log the interaction to the SQLite database
-def log_interaction(question, chunks, coherent_answer, feedback=None, additional_feedback=None, db_path='rag.db'):
+def log_interaction(question, chunks, coherent_answer, feedback=None, additional_feedback=None, db_path='/data/rag.db'):
     conn = sqlite3.connect(db_path)
     cursor = conn.cursor()
     cursor.execute('''