Upload 6 files

app.py

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+import streamlit as st
+from bmr import get_bmr
+from maintenance_calories import get_maintenance_calories
+from required_calories import get_required_calories
+from openai_api_response import get_openai_response
+
+st.title("Get Your Custom Diet Plan")
+
+with st.form("calorie_form"):
+    name = st.sidebar.text_input("Your name", key="name")
+    age = st.sidebar.number_input("Your age", 0, 100, key="age")
+    current_weight = st.sidebar.number_input(
+        "Your current weight(in Kg)", 10, 200, key="current_weight"
+    )
+    desired_weight = st.sidebar.number_input(
+        "Your desired weight(in Kg)", 10, 200, key="desired_weight"
+    )
+    current_height = st.sidebar.number_input(
+        "Your current height(in cm)", 100, 250, key="current_height"
+    )
+    gender = st.sidebar.selectbox("Your gender", ["Male", "Female"], key="gender")
+    activity_level = st.sidebar.selectbox(
+        "Your activity level",
+        ["Sedentary", "Moderately active", "Highly active", "Extremely active"],
+        key="activity_level",
+    )
+    dietary = st.sidebar.selectbox(
+        "Your dietary restrictions",
+        ["Vegan", "Vegetarian", "Non-vegetarians"],
+        key="dietary_restrictions",
+    )
+
+if st.sidebar.button("Generate diet"):
+    bmr = get_bmr(current_weight, current_height, age, gender)
+    maintenance_calories = get_maintenance_calories(bmr, activity_level)
+    required_calories = get_required_calories(
+        maintenance_calories, current_weight, desired_weight
+    )
+    st.header("Hi " + name + "!")
+    st.write("Your maintenance calories are: " + str(round(maintenance_calories)))
+    st.write("Your required calories are: " + str(round(required_calories)))
+
+    response = get_openai_response(age, gender, required_calories, dietary)
+    st.header("Here is your custom meal plan:")
+    st.subheader("Breakfast:")
+    st.write(response.get("meal1"))
+    st.subheader("Mid-day snack:")
+    st.write(response.get("meal2"))
+    st.subheader("Lunch:")
+    st.write(response.get("meal3"))
+    st.subheader("Evening snack:")
+    st.write(response.get("meal4"))
+    st.subheader("Dinner:")
+    st.write(response.get("meal5"))

bmr.py

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+def get_bmr(weight, height, age, gender):
+    bmr = (10 * weight) + (6.25 * height) - (5 * age)
+    if gender == "Male":
+        bmr = bmr + 5
+    else:
+        bmr = bmr - 161
+    return bmr

maintenance_calories.py

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+def get_maintenance_calories(bmr, activity_level):
+    if activity_level == "Sedentary":
+        bmr *= 1.2
+    elif activity_level == "Moderately active":
+        bmr *= 1.375
+    elif activity_level == "Highly active":
+        bmr *= 1.725
+    else:
+        bmr *= 1.9
+    return bmr

openai_api_response.py

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+from langchain_openai import OpenAI
+from langchain.prompts import PromptTemplate
+from langchain.output_parsers import ResponseSchema, StructuredOutputParser
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+llm = OpenAI(temperature=0.0, openai_api_key=os.getenv("OPENAI_API_KEY"))
+
+question_string = """ \
+I am a {age} {gender}. \
+My calorie goal for the day is {required_calories}. \ 
+I am a {dietry}. I want to have 5 meals in a day. \ 
+Create a meal plan using these details. \
+Using these details answer the following question: \
+meal1: What should be the breakfast and how many calories are in there? \
+meal2: What should be the mid day snack and how many calories are in there? \
+meal3: What should be the lunch and how many calories are in there? \
+meal4: What should be the evening snack and how many calories are in there? \
+meal5: What should be the dinner and how many calories are in there? \
+
+{format_instructions}
+"""
+
+prompt_template = PromptTemplate(
+    input_variables=["age", "gender", "required_calories", "dietry"],
+    template=question_string,
+)
+
+meal1 = ResponseSchema(name="meal1", description="What should be the breakfast and how many calories are in there?")
+meal2 = ResponseSchema(name="meal2", description="What should be the mid day snack and how many calories are in there?")
+meal3 = ResponseSchema(name="meal3", description="What should be the lunch and how many calories are in there?")
+meal4 = ResponseSchema(name="meal4", description="What should be the evening snack and how many calories are in there?")
+meal5 = ResponseSchema(name="meal5", description="What should be the dinner and how many calories are in there?")
+
+response_schema = [meal1, meal2, meal3, meal4, meal5]
+
+output_parser = StructuredOutputParser.from_response_schemas(response_schema)
+format_instructions = output_parser.get_format_instructions()
+
+def get_openai_response(age,gender,required_calories,dietary):
+    question = prompt_template.format(
+        age=age,
+        gender=gender,
+        required_calories=required_calories,
+        dietry=dietary,
+        format_instructions=format_instructions
+    )
+    response = llm.invoke(question)
+    response = output_parser.parse(response)
+    return response

required_calories.py

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+def get_required_calories(maintenance_calories, current_weight, desired_weight):
+    if desired_weight > current_weight:
+        maintenance_calories += 500
+    elif desired_weight < current_weight:
+        maintenance_calories -= 500
+    else:
+        return maintenance_calories
+    return maintenance_calories

requirements.txt

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+streamlit
+langchain
+langchain_openai
+openai
+huggingface_hub
+python-dotenv