Stack | Name |
---|---|
Chatbot platform | Google Dialogflow Console |
Database | MySQL |
Backend framework | FastAPI |
Production Database | aiven.io |
Production server | render.com |
Integration site | Huggingface |
File Name | Fetch Handling to database |
---|---|
db_connection | Creates and close connection to the database. |
dates_db | Particular session start date and end date. |
match_db | toss decision, winning runs, winning wickets, match result type and dls method. |
player_of_the_match_db | player of the match. |
seasons_db | available unique sessions. |
teams_db | both teams, match winner and toss winner teams. |
umpires_db | first umpire, second umpire and both umpires. |
venues_db | venues for the particular session and date. |
File Name | Backend handling for intent |
---|---|
date_helper | Date |
match_info_helper | Match Info and Match Info Next. |
player_of_the_match_helper | Player of the Match. |
season_helper | Season. |
team_info_helper | Team Info and Team Info Next. |
umpire_info_helper | Umire Info and Umpire Info Next. |
venues_helper | Venue. |
I integrated my chatbot using google dialoglfow messenger api. I created a basic UI just for the sake of chatbot testing and deployed the website in huggingface. You can check it out here. Below the code snippet is given, in case you want to integrate and test: -
<script src="https://www.gstatic.com/dialogflow-console/fast/messenger/bootstrap.js?v=1"></script>
<df-messenger
intent="WELCOME"
chat-title="IPL_BOT"
agent-id="cc8dfc8c-36c0-420e-9c7b-aeb2ba566a1c"
language-code="en"
></df-messenger>
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