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‎.env.sample

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GOOGLE_API_KEY="your_api_key"

‎.gitignore

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.env

‎.ipynb_checkpoints/Untitled-checkpoint.ipynb

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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎README.md

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@@ -13,6 +13,46 @@ The chatbot will be designed to understand and respond to layman language questi
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A user interface will be created using Streamlit where users can input their PostgreSQL credentials and ask questions.
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### Setup Instructions
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Follow these steps to set up the project on your local machine:
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**1. Clone the Repository**
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Begin by cloning the repository to your local machine:
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```
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https://github.com/langchain-tech/postgres-chatbot.git
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cd postgres-chatbot
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```
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**2. Create a Virtual Environment**
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It is recommended to create a virtual environment to manage dependencies:
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```
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python -m venv venv
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source venv/bin/activate # On Windows, use `venv\Scripts\activate`
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```
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**3. Install Dependencies**
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Install the necessary packages listed in the requirements.txt file:
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```
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pip install -r requirements.txt
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```
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**4. Set Up Environment Variables**
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Create a .env file in the root directory of your project and add the required environment variables. For example:
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```
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LANGCHAIN_API_KEY=your_langchain_api_key
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```
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**5. Start the Application**
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Run the application using Streamlit:
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```
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streamlit run app.py
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```
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### Notes
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- Questions will not be limited to one table, so it should be done to ask from database

‎app.py

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import os
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import asyncio
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import streamlit as st
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from langchain_community.utilities import SQLDatabase
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_community.agent_toolkits import create_sql_agent
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from dotenv import load_dotenv
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load_dotenv()
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os.environ["GOOGLE_API_KEY"]=os.getenv("GOOGLE_API_KEY")
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groq_api_key=os.getenv('GROQ_API_KEY')
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async def get_answer_by_sql_query(db,input):
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llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro-latest",temperature=0)
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agent_executor = create_sql_agent(llm, db=db, verbose=True)
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response= agent_executor.invoke({"input": input})
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return response
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def main():
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st.header('Chat with your Postgres Sql Database...')
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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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st.session_state.chat_history=[]
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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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with st.sidebar:
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st.subheader('Please Enter your credentials')
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username = st.text_input("enter your username")
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password= st.text_input("enter your password")
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db_name= st.text_input("enter your database name")
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if st.button('Process'):
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if username is not None and password is not None:
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postgres_uri = f"postgresql+psycopg2://{username}:{password}@localhost:5432/{db_name}"
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st.write(f'Processed database: {postgres_uri}')
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st.write(f'Connection to database successfully..')
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db = SQLDatabase.from_uri(postgres_uri)
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if "db" not in st.session_state:
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st.session_state.db = db
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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 from the Database"):
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with st.chat_message("user", avatar = '👨🏻'):
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st.markdown(prompt)
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st.session_state.messages.append({"role": "user", "avatar" :'👨🏻', "content": prompt})
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db = st.session_state.db
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response = asyncio.run(get_answer_by_sql_query(db,prompt))
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cleaned_response=response["output"]
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with st.chat_message("assistant", avatar='🤖'):
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st.markdown(cleaned_response)
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st.session_state.messages.append({"role": "assistant", "avatar" :'🤖', "content": cleaned_response})
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else:
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st.markdown('Please Enter your credentials to chat')
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if __name__ == '__main__':
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main()

‎requirements.txt

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aiohttp==3.9.5
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aiosignal==1.3.1
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altair==5.3.0
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annotated-types==0.7.0
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anyio==4.3.0
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asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1698341106958/work
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async-timeout==4.0.3
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attrs==23.2.0
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blinker==1.8.2
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cachetools==5.3.3
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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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comm @ file:///home/conda/feedstock_root/build_artifacts/comm_1710320294760/work
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dataclasses-json==0.6.6
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debugpy @ file:///croot/debugpy_1690905042057/work
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decorator @ file:///home/conda/feedstock_root/build_artifacts/decorator_1641555617451/work
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distro==1.9.0
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exceptiongroup @ file:///home/conda/feedstock_root/build_artifacts/exceptiongroup_1704921103267/work
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executing @ file:///home/conda/feedstock_root/build_artifacts/executing_1698579936712/work
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frozenlist==1.4.1
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gitdb==4.0.11
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GitPython==3.1.43
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google-ai-generativelanguage==0.6.4
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google-api-core==2.19.0
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google-api-python-client==2.129.0
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google-auth==2.29.0
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google-auth-httplib2==0.2.0
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google-generativeai==0.5.4
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googleapis-common-protos==1.63.0
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greenlet==3.0.3
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groq==0.7.0
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grpcio==1.64.0
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grpcio-status==1.62.2
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h11==0.14.0
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httpcore==1.0.5
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httplib2==0.22.0
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httpx==0.27.0
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idna==3.7
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importlib_metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1710971335535/work
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ipykernel @ file:///home/conda/feedstock_root/build_artifacts/ipykernel_1708996548741/work
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ipython @ file:///home/conda/feedstock_root/build_artifacts/ipython_1701831663892/work
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jedi @ file:///home/conda/feedstock_root/build_artifacts/jedi_1696326070614/work
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Jinja2==3.1.4
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jsonpatch==1.33
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jsonpointer==2.4
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jsonschema==4.22.0
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jsonschema-specifications==2023.12.1
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jupyter_client @ file:///home/conda/feedstock_root/build_artifacts/jupyter_client_1710255804825/work
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jupyter_core @ file:///home/conda/feedstock_root/build_artifacts/jupyter_core_1710257447442/work
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langchain==0.2.0
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langchain-community==0.2.0
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langchain-core==0.2.0
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langchain-google-genai==1.0.4
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langchain-text-splitters==0.2.0
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langsmith==0.1.60
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markdown-it-py==3.0.0
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MarkupSafe==2.1.5
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marshmallow==3.21.2
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matplotlib-inline @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-inline_1713250518406/work
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mdurl==0.1.2
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multidict==6.0.5
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mypy-extensions==1.0.0
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nest_asyncio @ file:///home/conda/feedstock_root/build_artifacts/nest-asyncio_1705850609492/work
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numpy==1.26.4
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orjson==3.10.3
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packaging==23.2
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pandas==2.2.2
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parso @ file:///home/conda/feedstock_root/build_artifacts/parso_1712320355065/work
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pexpect @ file:///home/conda/feedstock_root/build_artifacts/pexpect_1706113125309/work
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pickleshare @ file:///home/conda/feedstock_root/build_artifacts/pickleshare_1602536217715/work
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pillow==10.3.0
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platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1715777629804/work
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prompt-toolkit @ file:///home/conda/feedstock_root/build_artifacts/prompt-toolkit_1702399386289/work
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proto-plus==1.23.0
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protobuf==4.25.3
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psutil @ file:///home/conda/feedstock_root/build_artifacts/psutil_1705722404069/work
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psycopg2-binary==2.9.9
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ptyprocess @ file:///home/conda/feedstock_root/build_artifacts/ptyprocess_1609419310487/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl
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pure-eval @ file:///home/conda/feedstock_root/build_artifacts/pure_eval_1642875951954/work
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pyarrow==16.1.0
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pyasn1==0.6.0
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pyasn1_modules==0.4.0
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pydantic==2.7.1
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pydantic_core==2.18.2
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pydeck==0.9.1
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Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1714846767233/work
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pyparsing==3.1.2
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python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
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python-dotenv==1.0.1
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pytz==2024.1
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PyYAML==6.0.1
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pyzmq @ file:///croot/pyzmq_1705605076900/work
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referencing==0.35.1
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requests==2.32.1
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rich==13.7.1
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rpds-py==0.18.1
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rsa==4.9
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six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
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smmap==5.0.1
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sniffio==1.3.1
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SQLAlchemy==2.0.30
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stack-data @ file:///home/conda/feedstock_root/build_artifacts/stack_data_1669632077133/work
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streamlit==1.34.0
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tenacity==8.3.0
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toml==0.10.2
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toolz==0.12.1
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tornado @ file:///home/conda/feedstock_root/build_artifacts/tornado_1708363103305/work
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tqdm==4.66.4
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traitlets @ file:///home/conda/feedstock_root/build_artifacts/traitlets_1713535121073/work
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typing-inspect==0.9.0
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typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1712329955671/work
113+
tzdata==2024.1
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uritemplate==4.1.1
115+
urllib3==2.2.1
116+
watchdog==4.0.0
117+
wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1704731205417/work
118+
yarl==1.9.4
119+
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1695255097490/work

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