Ludovicollin commited on
Commit
1fd02ed
·
1 Parent(s): bcc83c3

Update main.py

Browse files
Files changed (1) hide show
  1. main.py +8 -9
main.py CHANGED
@@ -29,20 +29,12 @@ import datetime
29
 
30
  os.environ["TOKENIZERS_PARALLELISM"] = os.environ["TOKENIZERS_PARALLELISM"]
31
  os.environ['ANTHROPIC_API_KEY'] = os.environ['ANTHROPIC_API_KEY']
32
- #index_name = os.environ['PINECONE_INDEX_NAME']
33
  embeddings = HuggingFaceEmbeddings()
34
  pinecone.init(
35
  api_key=os.environ['PINECONE_API_KEY'],
36
  environment="us-west4-gcp-free"
37
  )
38
- index_name = pinecone.Index("")
39
- @cl.cache
40
- def retriever_to_cache():
41
- vectorstore = Pinecone.from_existing_index(
42
- index_name=index_name, embedding=embeddings
43
- )
44
- retriever = vectorstore.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .7, "k": 30,"filter": {'categorie': {'$eq': 'OF'}}})
45
- return retriever
46
 
47
  @cl.author_rename
48
  def rename(orig_author: str):
@@ -98,6 +90,13 @@ def to_cache(file):
98
  #time.sleep(5) # Simulate a time-consuming process
99
  return "https://cipen.univ-gustave-eiffel.fr/fileadmin/CIPEN/datas/assets/docs/" + file + ".csv"
100
 
 
 
 
 
 
 
 
101
 
102
  @cl.set_chat_profiles
103
  async def chat_profile():
 
29
 
30
  os.environ["TOKENIZERS_PARALLELISM"] = os.environ["TOKENIZERS_PARALLELISM"]
31
  os.environ['ANTHROPIC_API_KEY'] = os.environ['ANTHROPIC_API_KEY']
32
+ index_name = os.environ['PINECONE_INDEX_NAME']
33
  embeddings = HuggingFaceEmbeddings()
34
  pinecone.init(
35
  api_key=os.environ['PINECONE_API_KEY'],
36
  environment="us-west4-gcp-free"
37
  )
 
 
 
 
 
 
 
 
38
 
39
  @cl.author_rename
40
  def rename(orig_author: str):
 
90
  #time.sleep(5) # Simulate a time-consuming process
91
  return "https://cipen.univ-gustave-eiffel.fr/fileadmin/CIPEN/datas/assets/docs/" + file + ".csv"
92
 
93
+ @cl.cache
94
+ def retriever_to_cache():
95
+ vectorstore = Pinecone.from_existing_index(
96
+ index_name=index_name, embedding=embeddings
97
+ )
98
+ retriever = vectorstore.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .7, "k": 30,"filter": {'categorie': {'$eq': 'OF'}}})
99
+ return retriever
100
 
101
  @cl.set_chat_profiles
102
  async def chat_profile():