Spaces:
Sleeping
Sleeping
File size: 5,275 Bytes
fb531d8 7e0a969 b9ace18 7e0a969 62a872b b9ace18 6be0d08 b9ace18 7e0a969 6be0d08 b9ace18 7e0a969 b9ace18 7e0a969 b9ace18 62a872b b9ace18 0d10bbe b9ace18 7e0a969 b9ace18 62a872b 7e0a969 7883aa8 62a872b 7883aa8 3ae2913 7883aa8 3ae2913 7883aa8 7e0a969 b9ace18 62a872b 3ae2913 62a872b d97a87b 7e0a969 b9ace18 62a872b 3ae2913 7883aa8 62a872b 53acd3d 7883aa8 40f6db2 53acd3d d97a87b 62a872b d97a87b 62a872b d97a87b 3ae2913 029d034 3ae2913 57f45cf 3ae2913 029d034 3ae2913 53acd3d 3ae2913 53acd3d 7e0a969 53acd3d b9ace18 6be0d08 7e0a969 53acd3d 7e181cd febf51b 53acd3d febf51b b9ace18 febf51b b9ace18 febf51b 7e181cd febf51b b9ace18 40f6db2 4d17849 b9ace18 4d17849 b9ace18 e134b0e b9ace18 4d17849 b9ace18 4d17849 b9ace18 68574ac b9ace18 4d17849 b9ace18 4d17849 b9ace18 7e181cd b9ace18 e134b0e 66d8eed 4d17849 888f5c1 b9ace18 68574ac b9ace18 4d17849 888f5c1 4d17849 b9ace18 4d17849 b9ace18 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 | import streamlit as st
import streamlit.components.v1 as components
from huggingface_hub import InferenceClient
import os
# ================= BMI FUNCTIONS =================
def calculate_bmi(weight, height):
if height == 0:
return 0
height_m = height / 100
return weight / (height_m ** 2)
def bmi_category(bmi):
if bmi < 18.5:
return "Underweight"
elif bmi < 25:
return "Normal Weight"
elif bmi < 30:
return "Overweight"
else:
return "Obese"
def build_prompt(name, gender, height, weight, goal, fitness_level, equipment):
bmi = calculate_bmi(weight, height)
bmi_status = bmi_category(bmi)
equipment_list = ", ".join(equipment) if equipment else "No Equipment"
prompt = f"""
You are a certified professional fitness trainer.
Create a structured 5-day personalized workout plan.
User Profile:
- Name: {name}
- Gender: {gender}
- Height: {height} cm
- Weight: {weight} kg
- BMI: {bmi:.2f} ({bmi_status})
- Goal: {goal}
- Fitness Level: {fitness_level}
- Available Equipment: {equipment_list}
Instructions:
1. Divide clearly into Day 1 to Day 5.
2. Include exercise name.
3. Include sets and reps.
4. Include rest period.
5. Adjust intensity based on BMI category.
6. Avoid unsafe exercises for beginners.
7. Keep the plan professional and easy to follow.
"""
return prompt, bmi, bmi_status
# ================= QUERY MODEL =================
def query_model(prompt):
try:
HF_TOKEN = os.getenv("HF_TOKENN")
client = InferenceClient(
model="mistralai/Mistral-7B-Instruct-v0.2",
token=HF_TOKEN
)
response = client.chat_completion(
messages=[
{"role": "system", "content": "You are a certified professional fitness trainer."},
{"role": "user", "content": prompt}
],
max_tokens=600,
temperature=0.7
)
return response.choices[0].message.content
except Exception as e:
return f"Error: {str(e)}"
# ================= PAGE CONFIG =================
st.set_page_config(
page_title="FitPlan AI",
page_icon="πͺ",
layout="wide"
)
# ================= SIDEBAR =================
st.sidebar.title("πͺ FitPlan AI")
page = st.sidebar.radio(
"Navigate",
["π Fitness Form", "π BMI Result"]
)
# ================= FORM PAGE =================
if page == "π Fitness Form":
st.title("π Fitness Profile Form")
name = st.text_input("Name")
gender = st.selectbox(
"Gender",
["Male", "Female"]
)
fitness_level = st.selectbox(
"Fitness Level",
["Beginner", "Intermediate", "Advanced"]
)
height_cm = st.number_input(
"Height (cm)",
min_value=0.0
)
weight_kg = st.number_input(
"Weight (kg)",
min_value=0.0
)
goal = st.selectbox(
"Fitness Goal",
["Build Muscle", "Weight Loss", "Strength Gain", "Abs Building", "Flexible"]
)
equipment = st.multiselect(
"Available Equipment",
["Dumbbells", "Resistance Band", "Yoga Mat", "No Equipment"]
)
submit = st.button("Submit Profile")
if submit:
bmi = calculate_bmi(weight_kg, height_cm)
category = bmi_category(bmi)
st.session_state["name"] = name
st.session_state["gender"] = gender
st.session_state["fitness_level"] = fitness_level
st.session_state["bmi"] = bmi
st.session_state["category"] = category
st.session_state["goal"] = goal
st.session_state["equipment"] = equipment
# ADD THESE TWO (IMPORTANT)
st.session_state["height"] = height_cm
st.session_state["weight"] = weight_kg
st.success("Profile submitted successfully! Go to BMI Result page.")
# ================= RESULT PAGE =================
elif page == "π BMI Result":
st.title("π BMI Result")
if "bmi" not in st.session_state:
st.warning("Please fill the Fitness Form first.")
else:
st.write(f"Name: {st.session_state['name']}")
st.write(f"Gender: {st.session_state['gender']}")
st.write(f"Fitness Level: {st.session_state['fitness_level']}")
st.write(f"BMI: {st.session_state['bmi']}")
st.write(f"Category: {st.session_state['category']}")
st.write(f"Goal: {st.session_state['goal']}")
st.write(f"Equipment: {', '.join(st.session_state['equipment'])}")
gender = st.session_state["gender"]
bmi_status = st.session_state["category"]
goal = st.session_state["goal"]
fitness_level = st.session_state["fitness_level"]
equipment_list = ", ".join(st.session_state["equipment"])
prompt, bmi, bmi_status = build_prompt(
st.session_state["name"],
st.session_state["gender"],
st.session_state["height"],
st.session_state["weight"],
st.session_state["goal"],
st.session_state["fitness_level"],
st.session_state["equipment"]
)
# FIXED POSITION
with st.spinner("Generating AI Fitness Plan..."):
result = query_model(prompt)
st.subheader("AI Fitness Plan")
st.write(result)
|