chatbot using dialogflow for food orders

Author: dhavalsays

19_chatbot_food_business/README.txt

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+Directory structure
+===================
+backend: Contains Python FastAPI backend code
+db: contains the dump of the database. you need to import this into your MySQL db by using MySQL workbench tool
+dialogflow_assets: this has training phrases etc. for our intents
+frontend: website code
+
+Install these modules
+======================
+
+pip install mysql-connector
+pip install "fastapi[all]"
+
+OR just run pip install -r backend/requirements.txt to install both in one shot
+
+To start fastapi backend server
+================================
+1. Go to backend directory in your command prompt
+2. Run this command: uvicorn main:app --reload
+
+ngrok for https tunneling
+================================
+1. To install ngrok, go to https://ngrok.com/download and install ngrok version that is suitable for your OS
+2. Extract the zip file and place ngrok.exe in a folder.
+3. Open windows command prompt, go to that folder and run this command: ngrok http 80000
+
+NOTE: ngrok can timeout. you need to restart the session if you see session expired message.

19_chatbot_food_business/backend/db_helper.py

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+# Author: Dhaval Patel. Codebasics YouTube Channel
+
+import mysql.connector
+global cnx
+
+cnx = mysql.connector.connect(
+    host="localhost",
+    user="root",
+    password="root",
+    database="pandeyji_eatery"
+)
+
+# Function to call the MySQL stored procedure and insert an order item
+def insert_order_item(food_item, quantity, order_id):
+    try:
+        cursor = cnx.cursor()
+
+        # Calling the stored procedure
+        cursor.callproc('insert_order_item', (food_item, quantity, order_id))
+
+        # Committing the changes
+        cnx.commit()
+
+        # Closing the cursor
+        cursor.close()
+
+        print("Order item inserted successfully!")
+
+        return 1
+
+    except mysql.connector.Error as err:
+        print(f"Error inserting order item: {err}")
+
+        # Rollback changes if necessary
+        cnx.rollback()
+
+        return -1
+
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        # Rollback changes if necessary
+        cnx.rollback()
+
+        return -1
+
+# Function to insert a record into the order_tracking table
+def insert_order_tracking(order_id, status):
+    cursor = cnx.cursor()
+
+    # Inserting the record into the order_tracking table
+    insert_query = "INSERT INTO order_tracking (order_id, status) VALUES (%s, %s)"
+    cursor.execute(insert_query, (order_id, status))
+
+    # Committing the changes
+    cnx.commit()
+
+    # Closing the cursor
+    cursor.close()
+
+def get_total_order_price(order_id):
+    cursor = cnx.cursor()
+
+    # Executing the SQL query to get the total order price
+    query = f"SELECT get_total_order_price({order_id})"
+    cursor.execute(query)
+
+    # Fetching the result
+    result = cursor.fetchone()[0]
+
+    # Closing the cursor
+    cursor.close()
+
+    return result
+
+# Function to get the next available order_id
+def get_next_order_id():
+    cursor = cnx.cursor()
+
+    # Executing the SQL query to get the next available order_id
+    query = "SELECT MAX(order_id) FROM orders"
+    cursor.execute(query)
+
+    # Fetching the result
+    result = cursor.fetchone()[0]
+
+    # Closing the cursor
+    cursor.close()
+
+    # Returning the next available order_id
+    if result is None:
+        return 1
+    else:
+        return result + 1
+
+# Function to fetch the order status from the order_tracking table
+def get_order_status(order_id):
+    cursor = cnx.cursor()
+
+    # Executing the SQL query to fetch the order status
+    query = f"SELECT status FROM order_tracking WHERE order_id = {order_id}"
+    cursor.execute(query)
+
+    # Fetching the result
+    result = cursor.fetchone()
+
+    # Closing the cursor
+    cursor.close()
+
+    # Returning the order status
+    if result:
+        return result[0]
+    else:
+        return None
+
+
+if __name__ == "__main__":
+    # print(get_total_order_price(56))
+    # insert_order_item('Samosa', 3, 99)
+    # insert_order_item('Pav Bhaji', 1, 99)
+    # insert_order_tracking(99, "in progress")
+    print(get_next_order_id())

19_chatbot_food_business/backend/extra/extra.py

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+from fastapi import FastAPI
+from fastapi import Request
+from fastapi.responses import JSONResponse
+import random
+import ssl
+import uvicorn
+
+app = FastAPI()
+
+
+@app.post("/")
+async def handle_request(request: Request):
+    # Retrieve the JSON data from the request
+    payload = await request.json()
+
+    # Extract the necessary information from the payload
+    # based on the structure of the WebhookRequest from Dialogflow
+    intent = payload['queryResult']['intent']['displayName']
+    parameters = payload['queryResult']['parameters']
+
+    intent_handler_dict = {
+        'course.price': handle_course_price,
+        'eligibility.age': handle_eligibiliy_age,
+        'eligibility.background': handle_eligibility_background
+    }
+
+    return intent_handler_dict[intent](parameters)
+
+
+def handle_course_price(parameters: dict):
+    course_name = parameters["course-name"]
+    country = parameters["geo-country"]
+
+    price_dict = {
+        "SQL": 900,
+        "Power BI": 2400,
+        "Python": 800,
+        "Excel": 700,
+        "Data Analytics Bootcamp": 4800
+    }
+
+    course_price = price_dict.get(course_name)
+
+    response = {
+        "fulfillmentText": f"The course price for {course_name} is : {course_price}"
+    }
+
+    return JSONResponse(content=response)
+
+def handle_eligibiliy_age(parameters: dict):
+    course_name = parameters["course-name"]
+    age = parameters["age"]["amount"]
+
+    if age>30:
+        answer = random.choice([
+            '''There are many folks who have learned necessary data analyst skills at a later age
+            and successfully transitioned into a data analyst role. I know one person who made this transition
+            at the age of 51 and his past background was physical therapist. I've a video on my YouTube channel 
+            that has few such stories highlighted, please watch that to get 
+            some tips: https://www.youtube.com/watch?v=nkvInnpuic8 
+            In short: we believe it is possible to learn data analytics at this age 
+            ''',
+            '''
+            Hey, It is a common perception that at a later age it is hard to learn new things and switch your career 
+            but to be honest I personally know many folks who learned data analytics, data science at 40+ age and made 
+            this transition. One other person I know was a physical therapist till age 51 and now he is a data 
+            analyst working in a healthcare company. Watch this video to know about few such 
+            stories: https://www.youtube.com/watch?v=nkvInnpuic8
+            In short, it is 100% possible, if you have an eagerness to learn and a commitment 
+            towards making this career switch. 
+            Also one great thing about data analyst career is it requires very less coding so it will not 
+            be very difficult for you! So yes, you can learn data analysis at your age.
+            '''
+        ])
+
+    else:
+        answer ="Your age is less than 30 and you are too young to learn anything. Just do it my friend."
+
+    if course_name:
+        answer += " And yes you are eligible for " + "".join(course_name)
+
+    return JSONResponse(content={
+        "fulfillmentText": answer
+    })
+
+
+def handle_eligibility_background(parameters: dict):
+    course_name = parameters["course-name"]
+    background = parameters["degree-or-situation"]
+
+    if background:
+        if background == "Mechanical Engineer":
+            answer = '''I know many Mechanical Engineers who have successfully become data analysts. Watch these videos 
+            for these success stories: (1) https://www.youtube.com/watch?v=4BLxapDqrlA (2) https://www.youtube.com/watch?v=yKB6EUbGamo
+            Transition from mechanical engineering to data analyst is definitely possible. You need to learn necessary skills
+            such as Excel, Power BI, SQL etc.  
+            '''
+        elif background == "B.COM":
+            answer = '''There are many B.COM graduates who have transitioned into data analytics industry. For example watch 
+            Suryanshu's story here: https://www.youtube.com/watch?v=in3IB45YEgY
+            or How Hitesh is now working at Accenture with B.Com background: https://www.youtube.com/watch?v=lqEzYDuTnvU
+            Let your past not define what you can do in the future. The transition is definitely possible.
+            '''
+        elif background == "HR":
+            answer = '''If you are an HR trying to transition to data industry then I would suggest you leverage your past
+            experience. Meaning you already know HR domain, now you can learn necessary skills such as SQL, Excel, Power BI
+            and become an HR data analyst. This person Ankur Sharma was an HR and now he is working as a people analyst 
+            in an MNC: https://www.linkedin.com/in/ankur-sharma-b57266185/
+            '''
+        else:
+            answer = '''There are many folks who have breaked into a data analyst career despite irrelavant degree, 
+            work experience or an older age. So the transition to data analyst career, no matter what your past background
+            is possible for sure. Here is the playlist link with all such amazing transition stories to get some motivation:
+            https://www.youtube.com/playlist?list=PLeo1K3hjS3us2Ko99XX9V5phkf5_2CJpQ
+            If they can do it, you can do it too. 
+            '''
+        if course_name:
+            answer += " And yes you are eligible for " + "".join(course_name)
+    else:
+        answer = f"To understand if you are eligible for {course_name} or not, you can take this survey. It will" \
+                 f"tell you if you have natural abilities in the field of data analytics or not. Survey link: https://codebasics.io/find-your-match-da"
+
+    response = {
+        "fulfillmentText": answer
+    }
+
+    return JSONResponse(content=response)

19_chatbot_food_business/backend/generic_helper.py

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+# Author: Dhaval Patel. Codebasics YouTube Channel
+
+import re
+
+def get_str_from_food_dict(food_dict: dict):
+    result = ", ".join([f"{int(value)} {key}" for key, value in food_dict.items()])
+    return result
+
+
+def extract_session_id(session_str: str):
+    match = re.search(r"/sessions/(.*?)/contexts/", session_str)
+    if match:
+        extracted_string = match.group(0)
+        return extracted_string
+
+    return ""