Delete app_old.py

app_old.py

@@ -1,356 +0,0 @@
-import os
-import openai
-import datetime
-import gradio as gr
-import json
-from jinja2 import Template
-import csv
-import requests
-
-# Configuration variables
-AIRTABLE_API_KEY = os.getenv("AIRTABLE_API_KEY")
-
-# Airtable table names
-policies_table_name = 'tbla6PC65qZfqdJhE'
-prompts_table_name = 'tblYIZEB8m6JkGDEP'
-qalog_table_name = 'tbl4oNgFPWM5xH1XO'
-examples_table_name = 'tblu7sraOEmRgEGkp'
-users_table_name = 'tblLNe5ZL47SvrAEk'
-user_log_table_name = 'tblrlTsRrkl6BqMAJ'
-
-# Define the style and content for the response field
-label_text = "NILI Response"
-color = "#6562F4"
-background_color = "white"
-border_radius = "10px"
-response_label = f'<h3 style="color: {color}; background-color: {background_color}; border-radius: {border_radius}; padding: 10px;display: inline-block;">{label_text}</h3>'
-
-# Initialize OpenAI
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-base_id = 'appcUK3hUWC7GM2Kb'
-
-
-HEADERS = {
-    "Authorization": f"Bearer {AIRTABLE_API_KEY}",
-    "Content-Type": "application/json",
-    "Accept": "application/json",
-}
-
-
-
-def get_policies(school_selection):
-
-    AIRTABLE_ENDPOINT = f'https://api.airtable.com/v0/{base_id}/{policies_table_name}'    
-    school = ''
-    
-    # Parameters for the API request to filter by 'school' field and retrieve 'policy_text'
-    params = {
-        'filterByFormula': "OR({})".format(','.join(["school='{}'".format(school) for school in school_selection])),
-        'fields[]': 'policy_text',  # Replace with the name of your field
-    }
-
-    #print(params)
-
-    try:
-        # Send a GET request to the Airtable API
-        response = requests.get(AIRTABLE_ENDPOINT, headers=HEADERS, params=params)
-
-        # Check if the request was successful (status code 200)
-        if response.status_code == 200:
-            # Parse the JSON response
-            data = response.json()
-
-            # Check if there are records in the response
-            if data.get('records'):
-                # Initialize an empty string to store concatenated policies
-                concatenated_policies = ''
-                
-                # Extract the 'policy_text' values from each record and concatenate them
-                for record in data['records']:
-                    policy_text = record['fields']['policy_text']
-                    if concatenated_policies:
-                        concatenated_policies += "\n----------\n"
-                    concatenated_policies += policy_text
-
-            else:
-                print("No records found in the 'policies' table for the selected schools.")
-        else:
-            print(f"Failed to retrieve data. Status code: {response.status_code}")
-    except Exception as e:
-        print(f"An error occurred: {str(e)}")
-
-    #print(concatenated_policies)   
-
-    return concatenated_policies
-
-
-def get_schools():
-
-    AIRTABLE_ENDPOINT = f'https://api.airtable.com/v0/{base_id}/{policies_table_name}'    
-
-    # Parameters for the API request to select only the 'school' field
-    params = {
-        'fields[]': 'school',  # Replace with the name of your field
-        'sort[0][field]': 'school',  # Sort by the 'school' field
-        'sort[0][direction]': 'asc',  # Sort in ascending order
-    }
-
-    try:
-        # Send a GET request to the Airtable API
-        response = requests.get(AIRTABLE_ENDPOINT, headers=HEADERS, params=params)
-
-        # Check if the request was successful (status code 200)
-        if response.status_code == 200:
-            # Parse the JSON response
-            data = response.json()
-
-            # Check if there are records in the response
-            if data.get('records'):
-                # Extract the 'school' values from each record
-                schools = [record['fields']['school'] for record in data['records']]
-
-               # Print the list of 'school' values
-               # print(schools)
-            else:
-                print("No records found in the 'policies' table.")
-        else:
-            print(f"Failed to retrieve data. Status code: {response.status_code}")
-    except Exception as e:
-        print(f"An error occurred: {str(e)}")
-
-    return schools
-
-def get_prompt(header, template_content):
-
-    AIRTABLE_ENDPOINT = f'https://api.airtable.com/v0/{base_id}/{prompts_table_name}'    
-
-    params = {
-        'filterByFormula': "prompt_name='NILI_v1'",
-    }
-
-    response = requests.get(AIRTABLE_ENDPOINT, headers=HEADERS, params=params)
-
-    # Check for errors
-    response.raise_for_status()
-
-    data = response.json()
-
-    
-    # Check if there is at least one record matching the condition
-    if data.get('records'):
-        # Get the first record (there should be only one)
-            record = data['records'][0]['fields']
-            
-            # Assign system_prompt and user_prompt to variables
-            header = record.get('system_prompt', '')
-            template_content = record.get('user_prompt', '')
-
-    return header, template_content
-
-def get_examples():
-
-    AIRTABLE_ENDPOINT = f'https://api.airtable.com/v0/{base_id}/{examples_table_name}'    
-
-    # Send your request and parse the response
-    response = requests.get(AIRTABLE_ENDPOINT, headers=HEADERS)
-    data = json.loads(response.text)
-
-    # Check for errors
-    response.raise_for_status()
-
-    for record in data['records']:
-        nil_question = record['fields']['nil_question']
-        ui_examples.append([None, None, None, nil_question])
-
-    #print(ui_examples)
-           
-
-def append_to_at_qalog(your_role, school_selection, output_format, input_text, gpt_response,response_time,question_cost,prompt_tokens,completion_tokens):
-
-    AIRTABLE_ENDPOINT = f'https://api.airtable.com/v0/{base_id}/{qalog_table_name}'
-    
-    # Organize data for Airtable
-    new_fields = {
-            'your_role': str(your_role),
-            'school_selection': str(school_selection),
-            'output_format': str(output_format),
-            'input_text': str(input_text),
-            'gpt_response': str(gpt_response),
-            'response_time': str(response_time),
-            'question_cost': question_cost,
-            'user_name': str(logged_in_user),
-            'prompt_tokens': prompt_tokens,
-            'completion_tokens': completion_tokens
-        }
-
-    data = {
-        'fields': new_fields
-        }
-
-    try:
-    # Post data to Airtable
-        response = requests.post(AIRTABLE_ENDPOINT, headers=HEADERS, json=data)
-    
-        # Check for errors
-        response.raise_for_status()
-
-    except requests.exceptions.HTTPError as http_error:
-        # Handle the HTTP error (e.g., log it or display an error message)
-        print(f"HTTP error occurred: {http_error}")
-
-    except Exception as e:
-        # Handle exceptions, log errors, or raise them as needed
-        print(f"An error occurred: {str(e)}")
-
-#Chatbot Function
-def chatbot(your_role,school_selection,output_format,input_text):
-
-    start_time = datetime.datetime.now()
-
-    # school_selection holds an array of one or more schools
-    #print(school_selection)
-
-    # Read the Hydrated policies
-  
-    policies = get_policies(school_selection)
-
-    template_content = ''
-    header = ''
-
-    header, template_content = get_prompt(header, template_content)
-       
-    # Create a Jinja2 template from the content
-    template = Template(template_content)
-
-    # Render the template with the policy JSON
-    analysis_input = template.render(policies=policies, question=input_text,format=output_format)
-  
-    #with open('analysis_input.txt', 'w', encoding='utf-8') as out_file:
-        #out_file.write(analysis_input)
-  
-    response = openai.ChatCompletion.create(
-        model="gpt-4",
-      # model="gpt-3.5-turbo",
-        temperature=0,
-        messages=[
-            {
-                "role": "system",
-                "content": header
-            },
-            {
-                "role": "user",
-                "content": analysis_input
-            }
-          ]
-        )
-
-    gpt_response = response.choices[0].message["content"]
-
-    tokens_used = response.usage
-    question_cost = (tokens_used.get('total_tokens', 0) / 1000) * .03
-    prompt_tokens = tokens_used.get('prompt_tokens',)
-    completion_tokens = tokens_used.get('completion_tokens', 0)
-    end_time = datetime.datetime.now()
-    response_time = end_time - start_time
-
-    append_to_at_qalog(your_role, school_selection, output_format, input_text, gpt_response,response_time,question_cost,prompt_tokens,completion_tokens)
-
-    return response_label,gpt_response
-
-def log_login(username):
-
-    AIRTABLE_ENDPOINT = f'https://api.airtable.com/v0/{base_id}/{user_log_table_name}'
-
-    # Organize data for Airtable
-    new_fields = {
-            'user_name': str(username),
-        }
-
-    data = {
-        'fields': new_fields
-        }
-
-    try:
-        # Post data to Airtable
-        response = requests.post(AIRTABLE_ENDPOINT, headers=HEADERS, json=data)
-    
-        # Check for errors
-        response.raise_for_status()
-        
-    except requests.exceptions.HTTPError as http_error:
-        # Handle the HTTP error (e.g., log it or display an error message)
-        print(f"HTTP error occurred: {http_error}")
-
-    except Exception as e:
-        # Handle exceptions, log errors, or raise them as needed
-        print(f"An error occurred: {str(e)}")
-
-def login_auth(username, password):
-
-    AIRTABLE_ENDPOINT = f'https://api.airtable.com/v0/{base_id}/{users_table_name}'
-    
-    # Query the 'users' table to check for a match with the provided username and password
-    params = {
-        'filterByFormula': f'AND(user_name = "{username}", password = "{password}")'
-    }
-
-    response = requests.get(AIRTABLE_ENDPOINT, headers=HEADERS, params=params)
-
-    if response.status_code == 200:
-        data = response.json()
-        if data.get('records'):
-
-            log_login(username)
-            global logged_in_user
-            logged_in_user = username
-            
-            return True
-            
-        print(f"Invalid user/password combination")
-    
-    return False
-
-#Gradio UI
-CIMStheme = gr.themes.Soft().set(button_primary_background_fill='#6562F4')
-
-# Initialize an empty list to store the examples
-ui_examples = []
-school_selection = []
-
-schools = get_schools()
-
-get_examples()
-
-with gr.Blocks(CIMStheme) as iface:
-    with gr.Row():
-        with gr.Column(scale=2):
-            gr.Image(label="Logo",value="CIMS Logo Purple.png",width=10,show_download_button=False,interactive=False,show_label=False,elem_id="logo",container=False)
-        with gr.Column(scale=2):
-            gr.Markdown(value="# NILI - Powered by CIMS.AI")
-        with gr.Column(scale=2):
-            gr.Markdown("")
-    with gr.Row():
-        with gr.Column():
-            gr.Interface(fn=chatbot,
-                     inputs=[
-                         gr.components.Dropdown(["Student Athlete","Parent","Athletic Director"],multiselect=False,info="Select a role.",label="User Role", ),
-                         gr.components.Dropdown(schools,multiselect=True,info="Select one or more schools. This will help set the context of your question.",label="School Context"),
-                         gr.components.Dropdown(["Summary","Detailed Analysis","Table"],multiselect=False,info="Select the desired output format.",label="Output Format"),
-                         gr.components.Textbox(lines=5, placeholder="Enter your question here", label="NIL Question")],
-                     outputs=[
-                         gr.components.Markdown(response_label),
-                         gr.components.HTML(label="NILI Response")
-                         ],
-                     description="Ask any question about Name, Image, Likeness (NIL)",
-                     allow_flagging="manual",
-                     examples=ui_examples,
-                     cache_examples = False,
-                     flagging_options=["The response is incorrect","The response is inappropriate","The response doesn't make sense"]
-                      )
-    with gr.Row():
-        with gr.Column():
-            gr.HTML('<center><i>CIMS.AI Confidential 2023</i></center>')
-            
-iface.launch(auth=login_auth, auth_message= "Enter your username and password that you received from CIMS.AI. To request a login, please email '[email protected]'")
-#iface.launch(auth=('admin','cims.ai'))