Spaces:
Sleeping
Sleeping
saswattulo
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β’
b3f615c
1
Parent(s):
f4e28a0
Upload 4 files
Browse files- requirements.txt +152 -0
- secure-connect-temp-db.zip +3 -0
- temp_db-token.json +5 -0
- test.py +109 -0
requirements.txt
ADDED
@@ -0,0 +1,152 @@
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aenum==3.1.15
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aiohttp==3.9.3
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aiosignal==1.3.1
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aiostream==0.5.2
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altair==4.2.2
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annotated-types==0.6.0
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anyio==4.2.0
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asttokens==2.4.1
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async-timeout==4.0.3
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attrs==23.2.0
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beautifulsoup4==4.12.3
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bleach==6.1.0
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blinker==1.7.0
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cachetools==5.3.2
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cassandra-driver==3.29.0
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certifi==2024.2.2
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charset-normalizer==3.3.2
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click==8.1.7
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colorama==0.4.6
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comm==0.2.1
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contourpy==1.2.0
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cycler==0.12.1
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dataclasses-json==0.5.14
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debugpy==1.8.1
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decorator==5.1.1
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defusedxml==0.7.1
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Deprecated==1.2.14
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distro==1.9.0
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entrypoints==0.4
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exceptiongroup==1.2.0
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executing==2.0.1
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faiss-cpu==1.7.4
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Faker==23.2.1
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fastjsonschema==2.19.1
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favicon==0.7.0
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fonttools==4.49.0
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frozenlist==1.4.1
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fsspec==2024.2.0
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geomet==0.2.1.post1
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gitdb==4.0.11
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GitPython==3.1.41
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gradientai==1.7.0
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greenlet==3.0.3
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h11==0.14.0
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htbuilder==0.6.2
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httpcore==1.0.2
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httpx==0.26.0
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idna==3.6
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importlib-metadata==7.0.1
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ipykernel==6.29.2
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jedi==0.19.1
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Jinja2==3.1.3
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joblib==1.3.2
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jsonschema==4.21.1
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jsonschema-specifications==2023.12.1
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jupyter_client==8.6.0
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jupyter_core==5.7.1
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jupyterlab_pygments==0.3.0
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kiwisolver==1.4.5
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langchain==0.0.154
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llama-index==0.9.12
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lxml==5.1.0
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Markdown==3.5.2
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markdown-it-py==3.0.0
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markdownlit==0.0.7
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MarkupSafe==2.1.5
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marshmallow==3.20.2
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matplotlib==3.8.3
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matplotlib-inline==0.1.6
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mdurl==0.1.2
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mistune==3.0.2
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more-itertools==10.2.0
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multidict==6.0.5
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mypy-extensions==1.0.0
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nbclient==0.9.0
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nbconvert==7.16.0
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nbformat==5.9.2
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nest-asyncio==1.6.0
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nltk==3.8.1
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numexpr==2.9.0
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numpy==1.26.4
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openai==1.12.0
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openapi-schema-pydantic==1.2.4
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packaging==23.2
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pandas==2.2.0
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pandocfilters==1.5.1
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parso==0.8.3
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pillow==10.2.0
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platformdirs==4.2.0
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prometheus_client==0.20.0
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prompt-toolkit==3.0.43
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protobuf==3.20.3
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psutil==5.9.8
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pure-eval==0.2.2
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pyarrow==15.0.0
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pydantic==1.10.14
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pydantic_core==2.16.2
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pydeck==0.8.1b0
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Pygments==2.17.2
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pymdown-extensions==10.7
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Pympler==1.0.1
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pyparsing==3.1.1
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pypdf==4.0.1
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PyPDF2==3.0.1
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python-dateutil==2.8.2
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python-dotenv==1.0.0
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pytz==2024.1
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PyYAML==6.0.1
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pyzmq==25.1.2
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referencing==0.33.0
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regex==2023.12.25
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requests==2.31.0
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rich==13.7.0
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rpds-py==0.17.1
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semver==3.0.2
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six==1.16.0
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smmap==5.0.1
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sniffio==1.3.0
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soupsieve==2.5
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SQLAlchemy==2.0.27
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st-annotated-text==4.0.1
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stack-data==0.6.3
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streamlit==1.31.1
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streamlit-camera-input-live==0.2.0
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streamlit-card==1.0.0
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streamlit-embedcode==0.1.2
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streamlit-extras==0.4.0
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streamlit-faker==0.0.3
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streamlit-image-coordinates==0.1.6
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streamlit-keyup==0.2.3
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streamlit-toggle-switch==1.0.2
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streamlit-vertical-slider==2.5.5
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tenacity==8.2.3
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tiktoken==0.6.0
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tinycss2==1.2.1
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toml==0.10.2
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toolz==0.12.1
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tornado==6.4
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tqdm==4.66.2
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traitlets==5.14.1
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typing-inspect==0.9.0
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typing_extensions==4.9.0
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143 |
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tzdata==2024.1
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tzlocal==5.2
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urllib3==2.2.0
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146 |
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validators==0.22.0
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147 |
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watchdog==4.0.0
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148 |
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wcwidth==0.2.13
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149 |
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webencodings==0.5.1
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wrapt==1.16.0
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yarl==1.9.4
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zipp==3.17.0
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secure-connect-temp-db.zip
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:95aa8a081f163bff17243230a0a82175ec593f0a10e4ace26d3afcf0b2fa19ae
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size 12260
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temp_db-token.json
ADDED
@@ -0,0 +1,5 @@
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{
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"clientId": "nsJkarPpFtcNCEzGatNGTttm",
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"secret": "x9+CWlAOHuwtWKG6XY1Iv32THHlHSC.ZyB+-g+BaDZdWrAz7ZC01PdjaIzBO7OvIJvaLzglSmcOWjN2PAXbuS4uKT7Gq7kDMY4hwqovANflyA4xgW9ao-0FQqZnN4yG+",
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"token": "AstraCS:nsJkarPpFtcNCEzGatNGTttm:caf63b39a1eab4ba6e6bc99ba7b66ed549a7f0509080f7868140e4c3f472ee40"
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}
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test.py
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import json
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import os
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import streamlit as st
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from cassandra.auth import PlainTextAuthProvider
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from cassandra.cluster import Cluster
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from llama_index import ServiceContext
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from llama_index import set_global_service_context
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from llama_index import VectorStoreIndex, SimpleDirectoryReader, StorageContext
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from llama_index.embeddings import GradientEmbedding
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from llama_index.llms import GradientBaseModelLLM
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from llama_index.vector_stores import CassandraVectorStore
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from copy import deepcopy
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from tempfile import NamedTemporaryFile
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os.environ['GRADIENT_ACCESS_TOKEN'] = "sevG6Rqb0ztaquM4xjr83SBNSYj91cux"
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os.environ['GRADIENT_WORKSPACE_ID'] = "4de36c1f-5ee6-41da-8f95-9d2fb1ded33a_workspace"
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@st.cache_resource
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def create_datastax_connection():
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cloud_config= {'secure_connect_bundle': 'secure-connect-temp-db.zip'}
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with open("temp_db-token.json") as f:
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secrets = json.load(f)
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CLIENT_ID = secrets["clientId"]
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CLIENT_SECRET = secrets["secret"]
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auth_provider = PlainTextAuthProvider(CLIENT_ID, CLIENT_SECRET)
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cluster = Cluster(cloud=cloud_config, auth_provider=auth_provider)
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astra_session = cluster.connect()
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return astra_session
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def main():
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index_placeholder = None
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st.set_page_config(page_title = "NyayMitra", page_icon="π¦")
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st.header('NyayMitra')
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if "conversation" not in st.session_state:
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st.session_state.conversation = None
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if "activate_chat" not in st.session_state:
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st.session_state.activate_chat = False
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if "messages" not in st.session_state:
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st.session_state.messages = []
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for message in st.session_state.messages:
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with st.chat_message(message["role"], avatar = message['avatar']):
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st.markdown(message["content"])
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session = create_datastax_connection()
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os.environ['GRADIENT_ACCESS_TOKEN'] = "sevG6Rqb0ztaquM4xjr83SBNSYj91cux"
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os.environ['GRADIENT_WORKSPACE_ID'] = "4de36c1f-5ee6-41da-8f95-9d2fb1ded33a_workspace"
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llm = GradientBaseModelLLM(base_model_slug="llama2-7b-chat", max_tokens=400)
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embed_model = GradientEmbedding(
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gradient_access_token = os.environ["GRADIENT_ACCESS_TOKEN"],
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gradient_workspace_id = os.environ["GRADIENT_WORKSPACE_ID"],
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gradient_model_slug="bge-large")
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service_context = ServiceContext.from_defaults(
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llm = llm,
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embed_model = embed_model,
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chunk_size=256)
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set_global_service_context(service_context)
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with st.sidebar:
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st.subheader('Start your chat here')
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if st.button('Process'):
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with st.spinner('Processing'):
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reader = 'data'
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documents = SimpleDirectoryReader(reader).load_data()
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index = VectorStoreIndex.from_documents(documents,
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service_context=service_context)
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query_engine = index.as_query_engine()
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if "query_engine" not in st.session_state:
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st.session_state.query_engine = query_engine
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st.session_state.activate_chat = True
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if st.session_state.activate_chat == True:
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if prompt := st.chat_input("Ask your question"):
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with st.chat_message("user", avatar = 'π¨π»'):
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st.markdown(prompt)
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st.session_state.messages.append({"role": "user",
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"avatar" :'π¨π»',
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"content": prompt})
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query_index_placeholder = st.session_state.query_engine
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pdf_response = query_index_placeholder.query(prompt)
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cleaned_response = pdf_response.response
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with st.chat_message("assistant", avatar='π€'):
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st.markdown(cleaned_response)
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st.session_state.messages.append({"role": "assistant",
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"avatar" :'π€',
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"content": cleaned_response})
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else:
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st.markdown(
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' '
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)
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if __name__ == '__main__':
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main()
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