Update app.py

app.py

@@ -76,58 +76,38 @@ headers = {"Authorization": f"Bearer {hf_token}"}
 
 hf_embeddings = HFEmbeddings(api_url, headers)
 
-#Pinecone账号：
-#PINECONE_API_KEY = os.getenv('PINECONE_API_KEY')
-#PINECONE_ENVIRONMENT = os.getenv('PINECONE_ENVIRONMENT')
-#PINECONE_INDEX_NAME = os.getenv('PINECONE_INDEX_NAME')
-
-#def generate_random_string(length):
-#    letters = string.ascii_letters
-#    random_string = ''.join(random.choice(letters) for _ in range(length))
-#    return random_string
-#random_string = generate_random_string(12)
+PINECONE_API_KEY = os.getenv('PINECONE_API_KEY')
+PINECONE_ENVIRONMENT = os.getenv('PINECONE_ENVIRONMENT')
+PINECONE_INDEX_NAME = os.getenv('PINECONE_INDEX_NAME')
+print(PINECONE_INDEX_NAME)
 
 def generate_random_string(length):
     letters = string.ascii_lowercase
     return ''.join(random.choice(letters) for i in range(length))      
 random_string = generate_random_string(10)
 
-PINECONE_API_KEY = "5f07b52e-2a16-42a3-89c4-8899c584109e"
-PINECONE_ENVIRONMENT = "asia-southeast1-gcp-free"
-PINECONE_INDEX_NAME = "myindex-allminilm-l6-v2-384"
-print(PINECONE_INDEX_NAME)
-
 #def exit_handler():
 #    pinecone.init(api_key=PINECONE_API_KEY, environment=PINECONE_ENVIRONMENT)
 #    index_namespace_to_delete = pinecone.Index(index_name=index_name)
 #    index_namespace_to_delete.delete(delete_all=True, namespace=namespace)
-
 #atexit.register(exit_handler)
 
 pinecone.init(api_key=PINECONE_API_KEY, environment=PINECONE_ENVIRONMENT)
 index_name = PINECONE_INDEX_NAME
+#index_name = pinecone.Index(index_name)
 print(index_name)
-#namespace = random_string
 namespace = random_string
-#index_name = pinecone.Index(index_name)
 print(namespace)
 
 vector_db = Pinecone.from_texts(db_texts, hf_embeddings, index_name=index_name, namespace=namespace)
-
-#Considering Python apps automatically execute codes, a Vector-DB should have been created under namespace = "HF-GRADIO-0909"
-#when this app begins to run, however, the real world test results show not that way (i.e. namespace not created).
-#then input something in the input text box and click submit, to see how the app will react.
-
 #vector_db = Pinecone.from_texts([t.page_content for t in db_texts], hf_embeddings, index_name=index_name, namespace=namespace)
 #docsearch = Pinecone.from_texts([t.page_content for t in texts], embeddings, index_name=index_name, namespace=namespace)
 print("***********************************")
 print("Pinecone Vector/Embedding DB Ready.")
 
-#查看Pinecone账户下的Index（名称）
 index_name_extracted=pinecone.list_indexes()
 print(index_name_extracted)
 
-#查看Pinecone的Index状态
 index_current = pinecone.Index(index_name=index_name)
 index_status=index_current.describe_index_stats() 
 print(index_status)