Recommender basics

app.py

@@ -1,7 +1,60 @@
 import gradio as gr
+from pinecone import Pinecone
+import torch
+from transformers import AutoTokenizer, AutoModel
+import pandas as pd
+import os
+import openai
+import textwrap
 
-def greet(name):
-    return "Hello " + name + "!!"
+MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2'
+INDEX_NAME = 'charity-assistant'
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModel.from_pretrained(MODEL_NAME)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def text_to_embedding(text):
+    inputs = tokenizer(text, padding=True, truncation=True, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    embeddings = outputs.last_hidden_state.mean(dim=1).numpy()
+    return embeddings.flatten().tolist()
+
+def find_similar_media(query_text, top_k=1):
+    query_embedding = text_to_embedding(query_text)
+    results = index.query(vector=query_embedding, top_k=top_k, include_metadata=True)
+    matches=results['matches']
+    resultsdf=pd.DataFrame({'album':[m['id'] for m in matches],\
+                            'artist':[m['metadata']['artist'] for m in matches],\
+                            'score':[m['score'] for m in matches],\
+                            'description':[m['metadata']['description'] for m in matches]})
+    return resultsdf
+
+def motivate_recommendation(album, artist, description, query_text):
+    prompt = (f"Based on the description: '{description}', explain why \"{album}\" by \"{artist}\" "
+              f"matches the query: '{query_text}'.")
+
+    response = openai.ChatCompletion.create(
+        model="gpt-4",  #
+        messages=[
+            {"role": "system", "content": "You are helping to recommend music albums based on their description."},
+            {"role": "user", "content": prompt}
+        ]
+    )
+
+    explanation = response.choices[0].message['content'].strip()
+    clean_explanation = explanation.replace('\'', '"').replace('\"', '"')
+    wrapped_explanation = textwrap.fill(clean_explanation, width=70)
+    recommendation = (f"May I suggest \"{album}\" by \"{artist}\"? It matches what you were "
+                      f"looking for because {wrapped_explanation}")
+    return textwrap.fill(recommendation, width=70)
+
+def recommend(user_query: str) -> str:
+  most_similar = find_similar_media(user_query).loc[0]
+  motivation=motivate_recommendation(most_similar.album, most_similar.artist, most_similar.description, user_query).replace("\n"," ")
+  return motivation
+
+pc=Pinecone()
+index = pc.Index(INDEX_NAME)
+openai.api_key = os.environ['OPENAI_API_KEY']
+recommender = gr.Interface(fn=recommend, inputs="text", outputs="text")
+recommender.launch()

requirements.txt

@@ -1 +1,5 @@
-gradio
+gradio
+pinecone-client
+torch
+transformers
+openai==0.28