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Browse files- app.py +75 -0
- requirements.txt +11 -0
app.py
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import streamlit as st
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import google.generativeai as genai
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import os
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os.environ["google_API_KEY"] = 'AIzaSyAGB5JvQRItM2CeZjLhJp-KKljxfuPBOzo'
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genai.configure(api_key=os.getenv("google_API_KEY"))
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model = genai.GenerativeModel('gemini-pro')
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chat = model.start_chat(history=[])
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def get_gemini_response(question, gender, age, weight, height, activity_level, goals, dietary_restrictions):
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text = f'Act as a fitness trainer and give a short but to the point answer according to the given information that I am {age} years old {gender}, my weight is {weight} kg, my height is {height}cm, i am {activity_level}, my goal is to {goals} and i am {dietary_restrictions}. my question is that {question}'
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response =chat.send_message(text,stream=True)
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return response
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st.set_page_config(page_title="Fitness AI ChatBot", page_icon="🏋️♀️")
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st.title("🔹🔷Fitee🔷🔹")
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st.write("Made with ❤️ by Mainak")
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with st.sidebar:
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gender = st.selectbox("Gender", ["male", "female"])
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age = st.number_input("Age", min_value=0, max_value=150, value=30)
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weight = st.number_input("Weight (kg)", min_value=0.0, step=1.0, value=70.0)
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height = st.number_input("Height (cm)", min_value=0.0,step=1.0, value=170.0)
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activity_level = st.selectbox("Activity Level", ["Sedentary", "Lightly Active", "Moderately Active", "Very Active"])
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goals = st.radio("Goals", ["Loss Weight", "Maintain Weight", "Gain Weight"])
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dietary_restrictions = st.multiselect("Dietary Restrictions", ["Vegetarian", "Vegan", "Gluten-Free", "Dairy-Free"])
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if 'button_pressed' not in st.session_state:
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st.session_state.button_pressed = False
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# Button to start conversation
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start_conversation = st.button("Start Conversation")
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if start_conversation or st.session_state.button_pressed:
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st.session_state.button_pressed = True
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if "messages" not in st.session_state:
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st.session_state.messages = []
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# Display chat messages from history on app rerun
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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if prompt := st.chat_input("What is up?"):
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# Display user message in chat message container
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with st.chat_message("user"):
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st.markdown(prompt)
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": prompt})
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if prompt is None:
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response='Ask me anything about Fitness'
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else:
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with st.spinner('Typping...'):
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re = get_gemini_response(str(prompt), gender, age, weight, height, activity_level, goals, dietary_restrictions)
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response = ''
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for chunk in re:
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for ch in chunk.text.split(' '):
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response += ch + ' '
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# res = []
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# for chunk in re:
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# res.append(chunk.text)
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# st.write(chunk.text)
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# print("_"*80)
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# re = re["output_text"]
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# re=return_response(str(prompt),document_search,chain)
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# response = re
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# Display assistant response in chat message container
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with st.chat_message("assistant"):
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if type(response)==str:
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st.markdown(response)
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st.session_state.messages.append({"role": "assistant", "content": response})
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else:
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st.markdown(response)
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st.session_state.messages.append({"role": "assistant", "content": response})
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requirements.txt
ADDED
@@ -0,0 +1,11 @@
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1 |
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langchain
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2 |
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openai
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PyPDF2
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faiss-cpu
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tiktoken
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pinecone-client
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streamlit
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pyautogui
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streamlit_autorefresh
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google-generativeai
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langchain_google_genai
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