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Runtime error
Runtime error
Kushwanth Chowday Kandala
commited on
Commit
•
64523d8
1
Parent(s):
e488916
add file upload and format
Browse files
app.py
CHANGED
@@ -26,10 +26,10 @@ import torch
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device = 'cuda' if torch.cuda.is_available() else 'cpu'
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if device != 'cuda':
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model = SentenceTransformer("all-MiniLM-L6-v2", device=device)
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st.divider()
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@@ -49,11 +49,11 @@ PINECONE_ENVIRONMENT=os.getenv("PINECONE_ENVIRONMENT")
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def connect_pinecone():
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pinecone = PineconeGRPC(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
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st.code(pinecone)
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st.divider()
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st.text(pinecone.list_indexes().names())
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st.divider()
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st.text(f"Succesfully connected to the pinecone")
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return pinecone
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def get_pinecone_semantic_index(pinecone):
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@@ -70,7 +70,7 @@ def get_pinecone_semantic_index(pinecone):
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)
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# now connect to index
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index = pinecone.Index(index_name)
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st.text(f"Succesfully connected to the pinecone index")
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return index
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def chat_actions():
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@@ -99,6 +99,7 @@ def chat_actions():
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resdf = pd.DataFrame(data, columns=['TopRank', 'Score', 'Text'])
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with st.sidebar:
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st.dataframe(resdf)
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for res in result['matches']:
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@@ -133,4 +134,8 @@ for i in st.session_state["chat_history"]:
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# pinecone.init(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
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# st.text(pinecone)
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device = 'cuda' if torch.cuda.is_available() else 'cpu'
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# if device != 'cuda':
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# st.text(f"you are using {device}. This is much slower than using "
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# "a CUDA-enabled GPU. If on colab you can chnage this by "
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# "clicking Runtime > change runtime type > GPU.")
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model = SentenceTransformer("all-MiniLM-L6-v2", device=device)
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st.divider()
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def connect_pinecone():
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pinecone = PineconeGRPC(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
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# st.code(pinecone)
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# st.divider()
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# st.text(pinecone.list_indexes().names())
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# st.divider()
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# st.text(f"Succesfully connected to the pinecone")
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return pinecone
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def get_pinecone_semantic_index(pinecone):
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)
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# now connect to index
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index = pinecone.Index(index_name)
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# st.text(f"Succesfully connected to the pinecone index")
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return index
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def chat_actions():
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resdf = pd.DataFrame(data, columns=['TopRank', 'Score', 'Text'])
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with st.sidebar:
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st.markdown("*:red[semantic search results]* with **:green[Retrieval Augmented Generation]** ***(RAG)***.")
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st.dataframe(resdf)
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for res in result['matches']:
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# pinecone.init(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
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# st.text(pinecone)
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uploaded_files = st.file_uploader("Choose a CSV file", accept_multiple_files=True)
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for uploaded_file in uploaded_files:
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bytes_data = uploaded_file.read()
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st.write("filename:", uploaded_file.name)
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st.write(bytes_data)
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