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resolved issue of tdapiclient dependency #804

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resolved issue of tdapiclient dependency #804

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8 changes: 5 additions & 3 deletions UseCases/Chat_with_docs_GenAI/Chat_with_docs_VantageDB_GenAI_Python.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -129,6 +129,8 @@
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"\n",
"!pip install --upgrade -r requirements.txt --quiet"
]
},
Expand Down Expand Up @@ -449,7 +451,7 @@
"metadata": {},
"source": [
"<div class=\"alert alert-info\">\n",
" <p style = 'font-size:16px;font-family:Arial;color:#00233C'><i><b>Please be patient:</b> Generating embeddings for 1500+ document contents may take up to 2 to 4 minutes. It is depends on number of APMS in the database. Since the volume of data is large and the machine is small, going through the below code could take up to 4 minutes. </i></p>\n",
" <p style = 'font-size:16px;font-family:Arial;color:#00233C'><i><b>Please be patient:</b> Generating embeddings for 600+ document contents may take up to 2 to 4 minutes. It is depends on number of APMS in the database. Since the volume of data is large and the machine is small, going through the below code could take up to 4 minutes. </i></p>\n",
"</div>"
]
},
Expand Down Expand Up @@ -545,8 +547,8 @@
"outputs": [],
"source": [
"# store the embeddings if you're generating for new document for speed up in next run\n",
"df = tdf_text_embeddings.to_pandas().reset_index()\n",
"df.to_parquet('./embeddings/df_SmartTraveller_International_txt_emb_200_30.parquet.gzip',compression='gzip')"
"# df = tdf_text_embeddings.to_pandas().reset_index()\n",
"# df.to_parquet('./embeddings/df_SmartTraveller_International_txt_emb_200_30.parquet.gzip',compression='gzip')"
]
},
{
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2 changes: 2 additions & 0 deletions UseCases/Chat_with_docs_GenAI/requirements.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,8 @@ tiktoken
pypdf
PyMuPDF
panel==1.3.4
google-cloud-aiplatform
openai
pyopenssl
cryptography
tdapiclient
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