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ac85144
1
Parent(s):
43577b0
deleted multiple cache files and some modified files
Browse files- .DS_Store +0 -0
- chroma/.DS_Store +0 -0
- chroma/198995c5-3e47-440b-98d8-b095e7b992c3/data_level0.bin +0 -3
- chroma/198995c5-3e47-440b-98d8-b095e7b992c3/header.bin +0 -3
- chroma/198995c5-3e47-440b-98d8-b095e7b992c3/length.bin +0 -3
- chroma/198995c5-3e47-440b-98d8-b095e7b992c3/link_lists.bin +0 -0
- chroma/ed2d8aa0-0cf3-4a31-b498-d3e7dcdc5566/data_level0.bin +0 -3
- chroma/ed2d8aa0-0cf3-4a31-b498-d3e7dcdc5566/header.bin +0 -3
- chroma/ed2d8aa0-0cf3-4a31-b498-d3e7dcdc5566/length.bin +0 -3
- chroma/ed2d8aa0-0cf3-4a31-b498-d3e7dcdc5566/link_lists.bin +0 -0
- chroma/f190ba25-fd88-4232-a7dc-2390c45704d4/data_level0.bin +0 -3
- chroma/f190ba25-fd88-4232-a7dc-2390c45704d4/header.bin +0 -3
- chroma/f190ba25-fd88-4232-a7dc-2390c45704d4/length.bin +0 -3
- chroma/f190ba25-fd88-4232-a7dc-2390c45704d4/link_lists.bin +0 -0
- chroma/f28c5b78-1366-45d0-b9f9-10f0ba9054ed/data_level0.bin +0 -3
- chroma/f28c5b78-1366-45d0-b9f9-10f0ba9054ed/header.bin +0 -3
- chroma/f28c5b78-1366-45d0-b9f9-10f0ba9054ed/length.bin +0 -3
- chroma/f28c5b78-1366-45d0-b9f9-10f0ba9054ed/link_lists.bin +0 -0
- chroma/fc83983d-80db-49a4-a6fb-42834cc83377/data_level0.bin +0 -3
- chroma/fc83983d-80db-49a4-a6fb-42834cc83377/header.bin +0 -3
- chroma/fc83983d-80db-49a4-a6fb-42834cc83377/length.bin +0 -3
- chroma/fc83983d-80db-49a4-a6fb-42834cc83377/link_lists.bin +0 -0
- chroma/fd3b321e-3bab-4583-88b0-405d918cd938/data_level0.bin +0 -3
- chroma/fd3b321e-3bab-4583-88b0-405d918cd938/header.bin +0 -3
- chroma/fd3b321e-3bab-4583-88b0-405d918cd938/length.bin +0 -3
- chroma/fd3b321e-3bab-4583-88b0-405d918cd938/link_lists.bin +0 -0
- chroma/fd9978b6-a866-4bec-9cea-1215ebeb34e9/data_level0.bin +0 -3
- chroma/fd9978b6-a866-4bec-9cea-1215ebeb34e9/header.bin +0 -3
- chroma/fd9978b6-a866-4bec-9cea-1215ebeb34e9/length.bin +0 -3
- chroma/fd9978b6-a866-4bec-9cea-1215ebeb34e9/link_lists.bin +0 -0
- chroma/ff952c54-2ce3-4bd1-b8d0-3430b4745e3e/data_level0.bin +0 -3
- chroma/ff952c54-2ce3-4bd1-b8d0-3430b4745e3e/header.bin +0 -3
- chroma/ff952c54-2ce3-4bd1-b8d0-3430b4745e3e/length.bin +0 -3
- chroma/ff952c54-2ce3-4bd1-b8d0-3430b4745e3e/link_lists.bin +0 -0
- helpmate_ai.py +3 -17
.DS_Store
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Binary files a/.DS_Store and b/.DS_Store differ
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chroma/.DS_Store
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chroma/198995c5-3e47-440b-98d8-b095e7b992c3/data_level0.bin
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chroma/198995c5-3e47-440b-98d8-b095e7b992c3/link_lists.bin
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chroma/ed2d8aa0-0cf3-4a31-b498-d3e7dcdc5566/data_level0.bin
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size 4000
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chroma/ed2d8aa0-0cf3-4a31-b498-d3e7dcdc5566/link_lists.bin
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chroma/f190ba25-fd88-4232-a7dc-2390c45704d4/data_level0.bin
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chroma/f190ba25-fd88-4232-a7dc-2390c45704d4/header.bin
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chroma/f190ba25-fd88-4232-a7dc-2390c45704d4/link_lists.bin
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chroma/f28c5b78-1366-45d0-b9f9-10f0ba9054ed/link_lists.bin
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chroma/fc83983d-80db-49a4-a6fb-42834cc83377/data_level0.bin
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chroma/fc83983d-80db-49a4-a6fb-42834cc83377/header.bin
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chroma/fc83983d-80db-49a4-a6fb-42834cc83377/length.bin
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version https://git-lfs.github.com/spec/v1
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chroma/fc83983d-80db-49a4-a6fb-42834cc83377/link_lists.bin
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helpmate_ai.py
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# -*- coding: utf-8 -*-
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# Install all the required libraries
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# !pip install -U -q pdfplumber tiktoken openai chromaDB sentence-transformers
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# Import all the required Libraries
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# import pdfplumber
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# from pathlib import Path
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import pandas as pd
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# from operator import itemgetter
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# import json
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# import tiktoken
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# import openai
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import chromadb
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# openai.api_key = open("api_key.txt", "r").read().strip()
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def initialize_conversation():
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"""
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Generate a response using GPT-3.5's ChatCompletion based on the user query and retrieved information.
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# Query the collection against the user query and return the top 10 results
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results = insurance_collection.query(
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)
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# Store the query in cache_collection as document w.r.t to ChromaDB so that it can be embedded and searched against later
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top_docs = top_ranks_df[["Documents", "Metadatas"]][:top_k]
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# top_ranks = top_ranks[:][:top_k]
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print(top_docs)
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return top_docs #, top_ranks_df
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# -*- coding: utf-8 -*-
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import pandas as pd
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import chromadb
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def initialize_conversation():
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"""
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Generate a response using GPT-3.5's ChatCompletion based on the user query and retrieved information.
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# Query the collection against the user query and return the top 10 results
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results = insurance_collection.query(
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query_texts=query,
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n_results=10
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)
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# Store the query in cache_collection as document w.r.t to ChromaDB so that it can be embedded and searched against later
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top_docs = top_ranks_df[["Documents", "Metadatas"]][:top_k]
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# top_ranks = top_ranks[:][:top_k]
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# print(top_docs)
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return top_docs #, top_ranks_df
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