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import os
import openai
from openai.error import OpenAIError
import datetime
import gradio as gr
import json
from jinja2 import Template
import requests
# Initialize OpenAI
openai.api_key = os.environ.get('OPENAI_API_KEY')
# Configuration variables
airtable_api_key = os.environ.get('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'<span style="display: inline-block; position: relative; z-index: var(--layer-4); border: solid var(--block-title-border-width) var(--block-title-border-color); border-radius: var(--block-title-radius); background: var(--block-title-background-fill); padding: var(--block-title-padding); color: var(--block-title-text-color); font-weight: var(--block-title-text-weight); font-size: var(--block-title-text-size); line-height: var(--line-sm); margin-bottom: var(--spacing-lg);">{label_text}</span>'
#Airtable Base ID
base_id = 'appcUK3hUWC7GM2Kb'
#Name of the prompt temlate record
#prompt_name = "NILI_v1"
#App name for user login logging
app="NILI_Mobile"
#Header for the Airtable requests
headers = {
"Authorization": f"Bearer {airtable_api_key}",
"Content-Type": "application/json",
"Accept": "application/json",
}
def set_defaults(request: gr.Request):
if request.username:
print(request.username)
else:
print("No User Name")
return
#Function to trim prompts....not used
def prompt_trim(prompt: str) -> str:
lines = prompt.split('\n')
trimmed = '\n'.join([l.strip() for l in lines])
return trimmed
#Get the policies for the selected schools and concatenate them.
def get_policies(user_school):
airtable_endpoint = f'https://api.airtable.com/v0/{base_id}/{policies_table_name}'
# Parameters for the API request to filter by 'school' field and retrieve 'policy_text'
params = {
'filterByFormula': f'school = "{user_school}"',
'fields[]': 'policy_text' # Replace with the name of your field
}
# Initialize an empty string to store concatenated policies
concatenated_policies = ''
#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'):
# 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
#Get a list of School Name from the policies for the UI dropdown
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 = {
'filterByFormula': f'app = "{app}"',
'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
}
schools = []
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']]
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
#Get the designated prompt template record
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():
ui_examples = []
airtable_endpoint = f'https://api.airtable.com/v0/{base_id}/{examples_table_name}'
params = {
'filterByFormula': f'app = "{app}"',
'fields[]': 'nil_question'
}
# Send your request and parse the response
response = requests.get(airtable_endpoint, headers=headers,params=params)
data = json.loads(response.text)
# Check for errors
response.raise_for_status()
# Initialize a nested list to store nil_questions
nested_nil_questions = []
for record in data['records']:
nil_question = record['fields']['nil_question']
ui_examples.append(nil_question)
#print(ui_examples)
return 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(school_ddss,input_text):
start_time = datetime.datetime.now()
school_text = school_ddss
# Read the Hydrated policies
policies = get_policies(school_text)
template_content = ''
header = ''
header, template_content = get_prompt(header, template_content)
header_template = Template(header)
#merged_header = header_template.render(your_role=your_role)
merged_header = header_template.render(your_role=user_user_role)
# 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=user_output_format,your_role=user_user_role)
trimmed_input = prompt_trim(analysis_input)
response = openai.ChatCompletion.create(
model="gpt-4",
temperature=0,
messages=[
{
"role": "system",
"content": merged_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(user_user_role, school_text, user_output_format, input_text, gpt_response, response_time,
question_cost, prompt_tokens, completion_tokens)
return {nili_response_html: 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),
'app': str(app)
}
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 the matching user/password record is found:
if data.get('records'):
user_details = data['records'][0]['fields']
log_login(username)
#Set the global logged_in_user variable. This used in the append_to_at_qalog function to track what user asked the question
global logged_in_user,user_user_role, user_output_format, user_school
user_user_role = user_details.get('user_role')
user_output_format = user_details.get('output_format')
user_school = user_details.get('school_name', [None])[0]
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',body_background_fill='#e6effc')
CIMStheme = gr.themes.Soft().set(button_primary_background_fill='#6562F4')
# Initialize an empty list to store the examples
#ui_examples = []
school_selection = []
#username_text = ""
#Gets the school for the school selection DD
schools = get_schools()
#This code runs first before the login screen, so if there's no login screen used, this sets the logged_in_user. Otherwise it is set in the login function.
logged_in_user = 'admin'
#global user_user_role, user_output_format, user_school
user_user_role = "Student Athlete"
user_output_format = "Table"
#user_school = []
with gr.Blocks(CIMStheme) as iface:
with gr.Row():
with gr.Column():
gr.Image(label="Logo",value="CIMS Logo Purple.png",height=100,show_download_button=False,interactive=False,show_label=False,elem_id="logo",container=False)
with gr.Row():
with gr.Column():
gr.Markdown(value="<H2 style='text-align: center;'>NILI - Powered by CIMS.AI</h2>")
with gr.Row():
with gr.Column(variant='panel'):
school_ddss = gr.components.Dropdown(schools, multiselect=False, info="Select your school.", label="School")
with gr.Row():
with gr.Column(variant='panel'):
question_tbox= gr.components.Textbox(lines=3, placeholder="Enter your question here", label="NIL Question",info="Depending the scope of your question, results may take 30-60 sec.",interactive=True)
with gr.Row(variant='panel'):
with gr.Column():
examples_cmpt= gr.Examples(examples=get_examples(),inputs=question_tbox,label="Sample NIL questions - Click to select one")
with gr.Row():
with gr.Column():
submit_btn = gr.components.Button(value="Submit", size='sm', variant="primary")
with gr.Row():
with gr.Column(variant='panel'):
response_label_md = gr.components.Markdown(response_label)
nili_response_html = gr.components.HTML(label="NILI Response")
submit_btn.click(fn=chatbot,inputs=[school_ddss, question_tbox],
outputs=[nili_response_html])
with gr.Row():
with gr.Column():
gr.Markdown(value="[Ask Questions/Provide Feedback](https://discord.com/channels/1168589934244929647/1168589934244929650)")
with gr.Row():
with gr.Column():
gr.HTML('<center><i>© 2023 Collegiate Influencer Marketing Systems, Inc.</i><br>CIMS.AI, CIMS.AI logo, NILI, NILI logo, and EzNIL are trademarks of Collegiate Influencer Marketing Systems, Inc.</center>')
#iface.load(fn=set_defaults)
#iface.launch(auth=login_auth, auth_message= "Enter your username and password that you received from CIMS.AI. To request a login, please email 'info@cims.ai'")
#iface.launch(auth=("admin","admin"))
iface.launch()