Download connection_setup.py from VinayRevanuru/Medical_Chat_App: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/VinayRevanuru/Medical_Chat_App/resolve/main/connection_setup.py
- Command line
-
hf download hf://VinayRevanuru/Medical_Chat_App/connection_setup.py
-
curl -L -o connection_setup.py https://huggingface.co/VinayRevanuru/Medical_Chat_App/resolve/main/connection_setup.py
3.64 kB
| import psycopg2 | |
| from dotenv import load_dotenv | |
| import os | |
| load_dotenv('.env') | |
| # connection establishment | |
| conn = psycopg2.connect( | |
| database="postgres", | |
| user='postgres', | |
| password=os.getenv('TEMBO_PASSWORD'), | |
| host=os.getenv('TEMBO_HOST'), | |
| port='5432' | |
| ) | |
| conn.autocommit = True | |
| # Creating a cursor object | |
| cursor = conn.cursor() | |
| #create a table in the database named 'Patient' and the following attributes | |
| # """First Name, Last Name, Date of Birth, Phone Number, | |
| # Email, Medical Condition, Medication Regimen, Last Appointment DateTime, | |
| # Next Appointment DateTime, Doctor’s Name.""" if the table does not exist | |
| #delete the table if it already exists | |
| cursor.execute('''DROP TABLE IF EXISTS Patient;''') | |
| cursor.execute('''CREATE TABLE Patient | |
| (ID INT PRIMARY KEY NOT NULL, | |
| FIRST_NAME TEXT NOT NULL, | |
| LAST_NAME TEXT NOT NULL, | |
| LOCATION VARCHAR(50), | |
| DOB DATE, | |
| PHONE_NUMBER VARCHAR(10), | |
| EMAIL VARCHAR(50), | |
| EMERGENCY_CONTACT_NAME VARCHAR(50), | |
| EMERGENCY_CONTACT_NUMBER VARCHAR(10), | |
| MEDICAL_CONDITION VARCHAR(50), | |
| MEDICATION_REGIMEN VARCHAR(50), | |
| LAST_APPOINTMENT_DATE_TIME TIMESTAMP, | |
| NEXT_APPOINTMENT_DATE_TIME TIMESTAMP, | |
| DOCTORS_NAME VARCHAR(50)); | |
| ''') | |
| print("Table created successfully") | |
| #enter a record into the table | |
| cursor.execute(""" INSERT INTO Patient (ID, FIRST_NAME, LAST_NAME, LOCATION, DOB, PHONE_NUMBER, EMAIL, EMERGENCY_CONTACT_NAME, EMERGENCY_CONTACT_NUMBER, MEDICAL_CONDITION, MEDICATION_REGIMEN, LAST_APPOINTMENT_DATE_TIME, NEXT_APPOINTMENT_DATE_TIME, DOCTORS_NAME) | |
| VALUES (1, 'Michael','Scott', 'Scranton', '1964-03-15', '1234567890', 'Mscott@dundlermifflin.org', 'Pam Beesly', '0987654321', 'Diabetes', 'Insulin', '2024-03-15 08:00:00', '2024-03-15 09:00:00', 'Dr. Jan Levinsky');""") | |
| cursor.execute('''DROP TABLE IF EXISTS responses;''') | |
| cursor.execute('''CREATE TABLE responses( | |
| id SERIAL PRIMARY KEY, | |
| time_stamp TIMESTAMP, | |
| response_type VARCHAR(50), | |
| response TEXT | |
| );''') | |
| cursor.execute('''INSERT INTO responses (time_stamp, response_type, response) VALUES ('2024-03-15 08:00:00', 'assistant','Hello , your personlized agent is ready to assist you');''') | |
| # Drop the table if it already exists | |
| cursor.execute('''DROP TABLE IF EXISTS patient_knowledge_graph;''') | |
| # Create the new table to store knowledge graphs for each patient | |
| cursor.execute(''' | |
| CREATE TABLE patient_knowledge_graph ( | |
| patient_id INT PRIMARY KEY, | |
| graph_data JSONB | |
| ); | |
| ''') | |
| #Insert a record into the table | |
| # Drop the table if it already exists | |
| cursor.execute('''DROP TABLE IF EXISTS patient_knowledge_graph;''') | |
| # Create the new table with only timestamp and graphdata columns | |
| cursor.execute(''' | |
| CREATE TABLE patient_knowledge_graph ( | |
| time_stamp TIMESTAMP PRIMARY KEY, | |
| graph_data JSONB | |
| ); | |
| ''') | |
| print("Knowledge Graph table created successfully") | |
| # Closing the connection | |
| import pandas as pd | |
| # Reading the data from the csv file | |
| data = pd.read_sql_query("SELECT * FROM Patient", conn) | |
| df = pd.read_sql_query("SELECT * FROM responses", conn) | |
| data.to_json('data.json', orient='records') | |
| print(data) | |
| print(df) | |
| # Closing the connection | |
| conn.close() | |