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import streamlit as st |
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import os |
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from PIL import Image |
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import tempfile |
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import google.generativeai as genai |
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secret_key = os.getenv("SECRET_KEY") |
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genai.configure(api_key=secret_key) |
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model2=genai.GenerativeModel('gemini-pro') |
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st.title('Mental Health') |
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video_url1= 'https://youtu.be/NQcYZplTXnQ?si=egutHE1H9YwQNk_I' |
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st.header("Video Demo") |
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st.video(video_url1) |
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from transformers import pipeline |
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classifier = pipeline("text-classification") |
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input1 = st.text_input('Enter text here:', '') |
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if input1: |
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outputs1 = classifier(input1) |
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st.write('You entered:', input1) |
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st.write('Emotion:', outputs1[0]['label']) |
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st.write('Confidence in Emotion:', outputs1[0]['score']) |
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if 'chat' not in st.session_state: |
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st.session_state.chat=model2.start_chat(history=[]) |
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def role_to_streamlit(role): |
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if role=='model': |
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return 'assistant' |
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else: |
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return role |
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for message in st.session_state.chat.history: |
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with st.chat_message(role_to_streamlit(message.role)): |
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st.markdown(message.parts[0].text) |
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if prompt2 := st.chat_input('Write your problem'): |
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st.chat_message('user').markdown(prompt2) |
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response2=st.session_state.chat.send_message(prompt2) |
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with st.chat_message('assistant'): |
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st.markdown(response2.text) |
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def get_gemini_response(input,image): |
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model = genai.GenerativeModel('gemini-pro-vision') |
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if input!="": |
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response = model.generate_content([input,image]) |
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else: |
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response = model.generate_content(image) |
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return response.text |
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input3='Tell me about the emotion shown in the image' |
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uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) |
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image="" |
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if uploaded_file is not None: |
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image = Image.open(uploaded_file) |
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st.image(image, caption="Uploaded Image.", use_column_width=True) |
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submit=st.button("Tell me about the emotion in image") |
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if submit: |
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response=get_gemini_response(input3,image) |
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st.subheader("The Response is") |
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st.write(response) |
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audio_prompt="""you are audio emotion detector.You will be taking the audio |
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and finding the emotion in audio. Please provide the emotion of the audio given here: """ |
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audio_text=st.text_input("What do you want to know about the audio:") |
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if audio_text: |
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audio_prompt=""".You will be analyse the audio and provide the answers of the question given here: """+text |
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audio_file = st.file_uploader("Upload an audio file", type=["mp3", "wav", "ogg"]) |
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def generate_gemini_content(prompt,audio_file): |
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with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp_file: |
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tmp_file.write(audio_file.getvalue()) |
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tmp_file.close() |
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model = genai.GenerativeModel("models/gemini-1.5-pro-latest") |
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your_file = genai.upload_file(tmp_file.name) |
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response = model.generate_content([prompt, your_file]) |
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return response.text |
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os.remove(tmp_file.name) |
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if st.button("Answer or summary"): |
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if audio_file: |
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summary=generate_gemini_content(prompt,audio_file) |
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st.markdown("## Summary:") |
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st.write(summary) |
