gemini streamlit

gemini_streamlit.py

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+import streamlit as st
+import textwrap
+import google.generativeai as genai
+from IPython.display import display
+from IPython.display import Markdown
+import PIL.Image
+
+def load_img(file_pth):
+    return PIL.Image.open(file_pth)
+
+def to_markdown(text):
+    text = text.replace('•', '  *')
+    return Markdown(textwrap.indent(text, '> ', predicate=lambda _: True))
+
+def vision(img):
+    model = genai.GenerativeModel('gemini-pro-vision')
+    response = model.generate_content(img)
+    to_markdown(response.text)
+    response = model.generate_content(["Tell me the fruit name and ripeness level.", img], stream=True)
+    response.resolve()
+    to_markdown(response.text)
+    vision_output = response.text
+    return vision_output
+
+def chat(inpt_frm_vsn):
+    model = genai.GenerativeModel('gemini-pro')
+    chat = model.start_chat(history=[])
+    chat
+
+    res = inpt_frm_vsn + 'Tell me the fruit name and nutrition'
+
+    while True:
+        response = chat.send_message(res, generation_config=genai.types.GenerationConfig(
+            max_output_tokens=200
+        ))
+        to_markdown(response.text)
+
+        st.text('Gemini: ' + response.text)
+        res = st.text_input('User: ')
+
+def main():
+    st.title("Gemini")
+
+    img_path = 'assets/apple.jpg'
+    img = load_img(img_path)
+    st.image(img, caption='Uploaded Image.', use_column_width=True)
+
+    GOOGLE_API_KEY = 'AIzaSyA1bYLSWmPCXiN7C6LdyrLtXmtw7ylbuS0'
+
+    genai.configure(api_key=GOOGLE_API_KEY)
+
+    vision_result = vision(img)
+    st.text(vision_result)
+
+    check_point = st.text_input("If you want to continue chat write 'nutrition': ")
+
+    if check_point.lower() == 'nutrition':
+        chat(vision_result)
+
+if __name__ == "__main__":
+    main()