Spaces:
Runtime error
Runtime error
Kushwanth Chowday Kandala
commited on
Commit
•
9eb3e78
1
Parent(s):
8ce3d9b
update app.py with pinecone connection
Browse files
app.py
CHANGED
@@ -31,12 +31,50 @@ model = SentenceTransformer("all-MiniLM-L6-v2", device=device)
|
|
31 |
st.divider()
|
32 |
|
33 |
# Creating a Index(Pinecone Vector Database)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
34 |
def chat_actions():
|
|
|
|
|
|
|
|
|
35 |
st.session_state["chat_history"].append(
|
36 |
{"role": "user", "content": st.session_state["chat_input"]},
|
37 |
)
|
38 |
|
39 |
-
response = model.
|
40 |
st.session_state["chat_history"].append(
|
41 |
{
|
42 |
"role": "assistant",
|
@@ -54,3 +92,18 @@ st.chat_input("Enter your message", on_submit=chat_actions, key="chat_input")
|
|
54 |
for i in st.session_state["chat_history"]:
|
55 |
with st.chat_message(name=i["role"]):
|
56 |
st.write(i["content"])
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
31 |
st.divider()
|
32 |
|
33 |
# Creating a Index(Pinecone Vector Database)
|
34 |
+
import os
|
35 |
+
import pinecone
|
36 |
+
|
37 |
+
from pinecone import Index, GRPCIndex
|
38 |
+
|
39 |
+
PINECONE_API_KEY=os.getenv("PINECONE_API_KEY")
|
40 |
+
PINECONE_ENV=os.getenv("PINECONE_ENV")
|
41 |
+
PINECONE_ENVIRONMENT=os.getenv("PINECONE_ENVIRONMENT")
|
42 |
+
|
43 |
+
def connect_pinecone():
|
44 |
+
pinecone.init(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
|
45 |
+
st.code(pinecone)
|
46 |
+
st.divider()
|
47 |
+
st.text(pinecone.list_indexes())
|
48 |
+
st.divider()
|
49 |
+
st.text(f"Succesfully connected to the pinecone")
|
50 |
+
return pinecone
|
51 |
+
|
52 |
+
def get_pinecone_semantic_index(pinecone):
|
53 |
+
index_name = "sematic-search"
|
54 |
+
|
55 |
+
# only create if it deosnot exists
|
56 |
+
if index_name not in pinecone.list_indexes():
|
57 |
+
pinecone.create_index(
|
58 |
+
name=index_name,
|
59 |
+
description="Semantic search",
|
60 |
+
dimension=model.get_sentence_embedding_dimension(),
|
61 |
+
metric="cosine",
|
62 |
+
)
|
63 |
+
# now connect to index
|
64 |
+
index = pinecone.GRPCIndex(index_name)
|
65 |
+
st.text(f"Succesfully connected to the pinecone")
|
66 |
+
return index
|
67 |
+
|
68 |
def chat_actions():
|
69 |
+
|
70 |
+
pinecone = connect_pinecone()
|
71 |
+
index = get_pinecone_semantic_index(pinecone semantic index)
|
72 |
+
|
73 |
st.session_state["chat_history"].append(
|
74 |
{"role": "user", "content": st.session_state["chat_input"]},
|
75 |
)
|
76 |
|
77 |
+
response = model.encode(st.session_state["chat_input"])
|
78 |
st.session_state["chat_history"].append(
|
79 |
{
|
80 |
"role": "assistant",
|
|
|
92 |
for i in st.session_state["chat_history"]:
|
93 |
with st.chat_message(name=i["role"]):
|
94 |
st.write(i["content"])
|
95 |
+
|
96 |
+
### Creating a Index(Pinecone Vector Database)
|
97 |
+
# %%writefile .env
|
98 |
+
PINECONE_API_KEY=os.getenv("PINECONE_API_KEY")
|
99 |
+
PINECONE_ENV=os.getenv("PINECONE_ENV")
|
100 |
+
PINECONE_ENVIRONMENT=os.getenv("PINECONE_ENVIRONMENT")
|
101 |
+
|
102 |
+
import os
|
103 |
+
import pinecone
|
104 |
+
|
105 |
+
from pinecone import Index, GRPCIndex
|
106 |
+
pinecone.init(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
|
107 |
+
st.text(pinecone)
|
108 |
+
|
109 |
+
|