Add app and embeddings

app.py

@@ -0,0 +1,66 @@
+import gradio as gr
+from openai.embeddings_utils import get_embedding, cosine_similarity
+import openai
+import pandas as pd
+import numpy as np
+
+openai.api_key = "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"
+
+
+def get_documentation(query, platform):
+    embedding = get_embedding(
+        query,
+        engine="text-embedding-ada-002")
+
+    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("Título: " + titles[i] + "\n\nContenido: " +
+                       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("Título: " + titles[i] + "\n\nContenido: " +
+                       contents[i] + "\n\nURL: " + links[i])
+        return res[0], res[1], res[2]
+
+
+demo = gr.Interface(
+    fn=get_documentation,
+    inputs=[
+        gr.Textbox(label="Question", lines=3,),
+        gr.Radio(["Salesforce Marketing Cloud Intelligence",
+                 "Salesforce Marketing Cloud CDP"])
+    ],
+    outputs=["text", "text", "text"],
+    title="Salesforce Documentation Search",
+    # examples=[
+    #    [2, "cat", "park", ["ran", "swam"], True],
+    #    [4, "dog", "zoo", ["ate", "swam"], False],
+    #    [10, "bird", "road", ["ran"], False],
+    #    [8, "cat", "zoo", ["ate"], True],
+    # ],
+)
+
+if __name__ == "__main__":
+    demo.launch()