Update app.py flow

app.py

@@ -15,51 +15,26 @@ def get_documentation(query, platform):
 
     if platform == "Salesforce Marketing Cloud Intelligence":
         df = pd.read_csv("(sfmci)doc_embeddings.csv")
-        df.ada_search = df.ada_search.apply(
-            lambda x: np.array(x[1:-1].split(','), dtype=np.float32))
-        df["similarities"] = df.ada_search.apply(
-            lambda x: cosine_similarity(x, embedding))
-        df = df.sort_values("similarities", ascending=False).reset_index()
-        titles = df['title']
-        contents = df['body']
-        links = df['link']
-        res = []
-        for i in range(3):
-            res.append("Title: " + titles[i] + "\n\Content: " +
-                       contents[i] + "\n\nURL: " + links[i])
-        return res[0], res[1], res[2]
 
     elif platform == "Salesforce Marketing Cloud CDP":
         df = pd.read_csv("(sfmcdp)doc_embeddings.csv")
-        df.ada_search = df.ada_search.apply(
-            lambda x: np.array(x[1:-1].split(','), dtype=np.float32))
-        df["similarities"] = df.ada_search.apply(
-            lambda x: cosine_similarity(x, embedding))
-        df = df.sort_values("similarities", ascending=False).reset_index()
-        titles = df['title']
-        contents = df['body']
-        links = df['link']
-        res = []
-        for i in range(3):
-            res.append("Title: " + titles[i] + "\n\Content: " +
-                       contents[i] + "\n\nURL: " + links[i])
-        return res[0], res[1], res[2]
 
     elif platform == "Salesforce Marketing Cloud Personalization":
         df = pd.read_csv("(sfmcp)doc_embeddings.csv")
-        df.ada_search = df.ada_search.apply(
-            lambda x: np.array(x[1:-1].split(','), dtype=np.float32))
-        df["similarities"] = df.ada_search.apply(
-            lambda x: cosine_similarity(x, embedding))
-        df = df.sort_values("similarities", ascending=False).reset_index()
-        titles = df['title']
-        contents = df['body']
-        links = df['link']
-        res = []
-        for i in range(3):
-            res.append("Title: " + titles[i] + "\n\nContent: " +
-                       contents[i] + "\n\nURL: " + links[i])
-        return res[0], res[1], res[2]
+
+    df.ada_search = df.ada_search.apply(
+        lambda x: np.array(x[1:-1].split(','), dtype=np.float32))
+    df["similarities"] = df.ada_search.apply(
+        lambda x: cosine_similarity(x, embedding))
+    df = df.sort_values("similarities", ascending=False).reset_index()
+    titles = df['title']
+    contents = df['body']
+    links = df['link']
+    res = []
+    for i in range(3):
+        res.append("Title: " + titles[i] + "\n\nContent: " +
+                   contents[i] + "\n\nURL: " + links[i])
+    return res[0], res[1], res[2]
 
 
 demo = gr.Interface(