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Files changed (48) hide show
  1. README.md +4 -3
  2. app.py +1 -1
  3. as.py +0 -20
  4. inference.py +11 -9
  5. {recommendation_model/model → model/ranking_model}/fingerprint.pb +1 -1
  6. {recommendation_model/model → model/ranking_model}/keras_metadata.pb +2 -2
  7. {recommendation_model/index → model/ranking_model}/saved_model.pb +2 -2
  8. {recommendation_model/index → model/ranking_model}/variables/variables.data-00000-of-00001 +2 -2
  9. model/ranking_model/variables/variables.index +0 -0
  10. {recommendation_model/index → model/retrieval_index}/fingerprint.pb +1 -1
  11. {recommendation_model/index → model/retrieval_index}/keras_metadata.pb +2 -2
  12. {recommendation_model/model → model/retrieval_index}/saved_model.pb +2 -2
  13. {recommendation_model/model → model/retrieval_index}/variables/variables.data-00000-of-00001 +2 -2
  14. model/retrieval_index/variables/variables.index +0 -0
  15. products/{4470620803936518297 → 10109334388143567834}/00000000.shard/00000000.snapshot +2 -2
  16. products/{7776351335182402423 → 10330248599300921013}/00000000.shard/00000000.snapshot +2 -2
  17. products/1090696620989606176/00000000.shard/00000000.snapshot +3 -0
  18. products/10940474998907749160/00000000.shard/00000000.snapshot +3 -0
  19. products/12840975870241520537/00000000.shard/00000000.snapshot +3 -0
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  21. products/13899418556109793755/00000000.shard/00000000.snapshot +3 -0
  22. products/13990583163695514424/00000000.shard/00000000.snapshot +3 -0
  23. products/14345805792428425891/00000000.shard/00000000.snapshot +3 -0
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  29. products/17791542437248711493/00000000.shard/00000000.snapshot +3 -0
  30. products/17875886567290137253/00000000.shard/00000000.snapshot +3 -0
  31. products/2088096786386730064/00000000.shard/00000000.snapshot +3 -0
  32. products/2324640233395721909/00000000.shard/00000000.snapshot +3 -0
  33. products/2521887443494170149/00000000.shard/00000000.snapshot +3 -0
  34. products/2968513013644679377/00000000.shard/00000000.snapshot +3 -0
  35. products/4289417005664533190/00000000.shard/00000000.snapshot +3 -0
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  37. products/5285105494425665764/00000000.shard/00000000.snapshot +3 -0
  38. products/5612963723838050900/00000000.shard/00000000.snapshot +3 -0
  39. products/6294417851453925107/00000000.shard/00000000.snapshot +3 -0
  40. products/8014010485073505966/00000000.shard/00000000.snapshot +3 -0
  41. products/9249320478592962775/00000000.shard/00000000.snapshot +3 -0
  42. products/9662503285985067647/00000000.shard/00000000.snapshot +3 -0
  43. products/9722544657519255032/00000000.shard/00000000.snapshot +3 -0
  44. products/9925691710001970477/00000000.shard/00000000.snapshot +3 -0
  45. products/dataset_spec.pb +1 -1
  46. products/snapshot.metadata +1 -1
  47. recommendation_model/index/variables/variables.index +0 -0
  48. recommendation_model/model/variables/variables.index +0 -0
README.md CHANGED
@@ -1,13 +1,14 @@
1
  ---
2
  title: Recommendation Engine
3
- emoji: 🤗
4
- colorFrom: pink
5
- colorTo: green
6
  sdk: streamlit
7
  sdk_version: 1.38.0
8
  app_file: app.py
9
  pinned: false
10
  license: apache-2.0
 
11
  ---
12
 
13
  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
1
  ---
2
  title: Recommendation Engine
3
+ emoji: 🚀
4
+ colorFrom: green
5
+ colorTo: blue
6
  sdk: streamlit
7
  sdk_version: 1.38.0
8
  app_file: app.py
9
  pinned: false
10
  license: apache-2.0
11
+ tags: ["streamlit", "recommendation", "tensorflow", "deep learning"]
12
  ---
13
 
14
  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py CHANGED
@@ -18,7 +18,7 @@ class QueryInputForm:
18
  ]
19
 
20
  self.device_type_options = [
21
- 'Mobile', 'Desktop', 'Phablet', 'Tablet', '', 'TV',
22
  'Portable Media Player', 'Wearable',
23
  ]
24
 
 
18
  ]
19
 
20
  self.device_type_options = [
21
+ 'Mobile', 'Desktop', 'Phablet', 'Tablet', 'TV',
22
  'Portable Media Player', 'Wearable',
23
  ]
24
 
as.py DELETED
@@ -1,20 +0,0 @@
1
- import tensorflow as tf
2
- import os
3
- from datetime import datetime
4
- from inference import Inference
5
-
6
- products_path = os.path.join("products")
7
- inference = Inference()
8
-
9
- raw_query = {
10
- 'user_id': "new_user", # any user will be considered as a new user
11
- 'channel': 'Organic',
12
- 'device_type': 'Desktop',
13
- 'query_text': 'pizza',
14
- 'time': datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f"), # querytime
15
- }
16
-
17
- inference.get_recommendations(raw_query)
18
- print(inference.recommendations)
19
-
20
-
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
inference.py CHANGED
@@ -4,18 +4,21 @@ import os
4
 
5
  class Inference():
6
  def __init__(self):
7
- index_path = os.path.join("recommendation_model", "index")
8
- model_path = os.path.join("recommendation_model", "model")
 
 
 
 
 
 
 
 
9
  self.index = tf.keras.models.load_model(index_path)
10
  self.model = tf.keras.models.load_model(model_path)
11
 
12
  products_path = os.path.join("products")
13
  self.products = tf.data.Dataset.load(products_path)
14
-
15
- self.model_product_features = [
16
- 'product_id', 'category_name', 'merchant_name', 'merchant_city', 'merchant_state', 'merchant_region',
17
- 'free_shipping', 'is_sold_out', 'editor_pick', 'on_sale', 'product_name', 'price_in_cents', 'reviews'
18
- ]
19
 
20
  def get_recommendations(self, raw_query: dict):
21
  self.query_input = {
@@ -50,7 +53,7 @@ class Inference():
50
  return tf.reduce_any(tf.equal(item['product_id'], self.top_rec[0]))
51
 
52
  def get_score(self, item):
53
- input_data = {k: v for k, v in item.items() if k in self.model_product_features + list(self.query_input.keys())}
54
  _, _, score = self.model(input_data)
55
  item['score'] = score
56
  return item
@@ -62,7 +65,6 @@ class Inference():
62
  'price_in_cents': item['price_in_cents'],
63
  'reviews': item['reviews'],
64
  'merchant_name': item['merchant_name'],
65
- 'merchant_city': item['merchant_city'],
66
  'merchant_state': item['merchant_state'],
67
  'merchant_region': item['merchant_region'],
68
  'free_shipping': item['free_shipping'],
 
4
 
5
  class Inference():
6
  def __init__(self):
7
+ self.product_features = [
8
+ 'product_id', 'product_name', 'category_name',
9
+ 'merchant_name', 'merchant_state', 'merchant_region',
10
+ 'free_shipping', 'is_sold_out', 'editor_pick', 'on_sale',
11
+ 'sales_last_week', 'sales_last_month', 'sales_last_year',
12
+ 'price_in_cents', 'reviews'
13
+ ]
14
+
15
+ index_path = os.path.join("model", "retrieval_index")
16
+ model_path = os.path.join("model", "ranking_model")
17
  self.index = tf.keras.models.load_model(index_path)
18
  self.model = tf.keras.models.load_model(model_path)
19
 
20
  products_path = os.path.join("products")
21
  self.products = tf.data.Dataset.load(products_path)
 
 
 
 
 
22
 
23
  def get_recommendations(self, raw_query: dict):
24
  self.query_input = {
 
53
  return tf.reduce_any(tf.equal(item['product_id'], self.top_rec[0]))
54
 
55
  def get_score(self, item):
56
+ input_data = {k: v for k, v in item.items() if k in self.product_features + list(self.query_input.keys())}
57
  _, _, score = self.model(input_data)
58
  item['score'] = score
59
  return item
 
65
  'price_in_cents': item['price_in_cents'],
66
  'reviews': item['reviews'],
67
  'merchant_name': item['merchant_name'],
 
68
  'merchant_state': item['merchant_state'],
69
  'merchant_region': item['merchant_region'],
70
  'free_shipping': item['free_shipping'],
{recommendation_model/model → model/ranking_model}/fingerprint.pb RENAMED
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