app.py

import streamlit as st
import pandas as pd
import google.generativeai as genai
import re
from PIL import Image
import requests

#Je t'aime plus que les mots,
#Plus que les sentiments,
#Plus que la vie elle-même

st.set_page_config(
    page_title="Google AI Chat",
    page_icon="https://seeklogo.com/images/G/google-ai-logo-996E85F6FD-seeklogo.com.png",
    layout="wide",
)
# Path: Main.py
#Author: Sergio Demis Lopez Martinez
#------------------------------------------------------------
#HEADER
st.markdown('''
Powered by Google AI <img src="https://seeklogo.com/images/G/google-ai-logo-996E85F6FD-seeklogo.com.png" width="20" height="20">
, Streamlit and Python''', unsafe_allow_html=True)
st.caption("By Sergio Demis Lopez Martinez")

#------------------------------------------------------------
#LANGUAGE
langcols = st.columns([0.2,0.8])
with langcols[0]:
  lang = st.selectbox('Select your language',
  ('English', 'Español', 'Français', 'Deutsch',
  'Italiano', 'Português', 'Polski', 'Nederlands',
  'Русский', '日本語', '한국어', '中文', 'العربية',
  'हिन्दी', 'Türkçe', 'Tiếng Việt', 'Bahasa Indonesia',
  'ภาษาไทย', 'Română', 'Ελληνικά', 'Magyar', 'Čeština',
  'Svenska', 'Norsk', 'Suomi', 'Dansk', 'हिन्दी', 'हिन्�'),index=1)

if 'lang' not in st.session_state:
    st.session_state.lang = lang
st.divider()

#------------------------------------------------------------
#FUNCTIONS
def extract_graphviz_info(text: str) -> list[str]:
  """
  The function `extract_graphviz_info` takes in a text and returns a list of graphviz code blocks found in the text.

  :param text: The `text` parameter is a string that contains the text from which you want to extract Graphviz information
  :return: a list of strings that contain either the word "graph" or "digraph". These strings are extracted from the input
  text.
  """

  graphviz_info  = text.split('```')

  return [graph for graph in graphviz_info if ('graph' in graph or 'digraph' in graph) and ('{' in graph and '}' in graph)]

def append_message(message: dict) -> None:
    """
    The function appends a message to a chat session.

    :param message: The `message` parameter is a dictionary that represents a chat message. It typically contains
    information such as the user who sent the message and the content of the message
    :type message: dict
    :return: The function is not returning anything.
    """
    st.session_state.chat_session.append({'user': message})
    return

@st.cache_resource
def load_model() -> genai.GenerativeModel:
    """
    The function `load_model()` returns an instance of the `genai.GenerativeModel` class initialized with the model name
    'gemini-pro'.
    :return: an instance of the `genai.GenerativeModel` class.
    """
    model = genai.GenerativeModel('gemini-pro')
    return model

@st.cache_resource
def load_modelvision() -> genai.GenerativeModel:
    """
    The function `load_modelvision` loads a generative model for vision tasks using the `gemini-pro-vision` model.
    :return: an instance of the `genai.GenerativeModel` class.
    """
    model = genai.GenerativeModel('gemini-pro-vision')
    return model



#------------------------------------------------------------
#CONFIGURATION
genai.configure(api_key=st.secrets["GOOGLE_API_KEY"])

model = load_model()

vision = load_modelvision()

if 'chat' not in st.session_state:
    st.session_state.chat = model.start_chat(history=[])

if 'chat_session' not in st.session_state:
    st.session_state.chat_session = []

#st.session_state.chat_session

#------------------------------------------------------------
#CHAT

if 'messages' not in st.session_state:
    st.session_state.messages = []

if 'welcome' not in st.session_state or lang != st.session_state.lang:
    st.session_state.lang = lang
    welcome  = model.generate_content(f'''
    Da un saludo de bienvenida al usuario y sugiere que puede hacer
    (Puedes describir imágenes, responder preguntas, leer archivos texto, leer tablas,generar gráficos con graphviz, etc)
    eres un chatbot en una aplicación de chat creada en streamlit y python. generate the answer in {lang}''')
    welcome.resolve()
    st.session_state.welcome = welcome

    with st.chat_message('ai'):
        st.write(st.session_state.welcome.text)
else:
    with st.chat_message('ai'):
        st.write(st.session_state.welcome.text)

if len(st.session_state.chat_session) > 0:
    count = 0
    for message in st.session_state.chat_session:

        if message['user']['role'] == 'model':
            with st.chat_message('ai'):
                st.write(message['user']['parts'])
                graphs = extract_graphviz_info(message['user']['parts'])
                if len(graphs) > 0:
                    for graph in graphs:
                        st.graphviz_chart(graph,use_container_width=False)
                        if lang == 'Español':
                          view = "Ver texto"
                        else:
                          view = "View text"
                        with st.expander(view):
                          st.code(graph, language='dot')
        else:
            with st.chat_message('user'):
                st.write(message['user']['parts'][0])
                if len(message['user']['parts']) > 1:
                    st.image(message['user']['parts'][1], width=200)
        count += 1



#st.session_state.chat.history

cols=st.columns(4)

with cols[0]:
    if lang == 'Español':
      image_atachment = st.toggle("Adjuntar imagen", value=False, help="Activa este modo para adjuntar una imagen y que el chatbot pueda leerla")
    else:
      image_atachment = st.toggle("Attach image", value=False, help="Activate this mode to attach an image and let the chatbot read it")

with cols[1]:
    if lang == 'Español':
      txt_atachment = st.toggle("Adjuntar archivo de texto", value=False, help="Activa este modo para adjuntar un archivo de texto y que el chatbot pueda leerlo")
    else:
      txt_atachment = st.toggle("Attach text file", value=False, help="Activate this mode to attach a text file and let the chatbot read it")
with cols[2]:
    if lang == 'Español':
      csv_excel_atachment = st.toggle("Adjuntar CSV o Excel", value=False, help="Activa este modo para adjuntar un archivo CSV o Excel y que el chatbot pueda leerlo")
    else:
      csv_excel_atachment = st.toggle("Attach CSV or Excel", value=False, help="Activate this mode to attach a CSV or Excel file and let the chatbot read it")
with cols[3]:
    if lang == 'Español':
      graphviz_mode = st.toggle("Modo graphviz", value=False, help="Activa este modo para generar un grafo con graphviz en .dot a partir de tu mensaje")
    else:
      graphviz_mode = st.toggle("Graphviz mode", value=False, help="Activate this mode to generate a graph with graphviz in .dot from your message")
if image_atachment:
    if lang == 'Español':
      image = st.file_uploader("Sube tu imagen", type=['png', 'jpg', 'jpeg'])
      url = st.text_input("O pega la url de tu imagen")
    else:
      image = st.file_uploader("Upload your image", type=['png', 'jpg', 'jpeg'])
      url = st.text_input("Or paste your image url")
else:
    image = None
    url = ''



if txt_atachment:
    if lang == 'Español':
      txtattachment = st.file_uploader("Sube tu archivo de texto", type=['txt'])
    else:
      txtattachment = st.file_uploader("Upload your text file", type=['txt'])
else:
    txtattachment = None

if csv_excel_atachment:
    if lang == 'Español':
      csvexcelattachment = st.file_uploader("Sube tu archivo CSV o Excel", type=['csv', 'xlsx'])
    else:
      csvexcelattachment = st.file_uploader("Upload your CSV or Excel file", type=['csv', 'xlsx'])
else:
    csvexcelattachment = None
if lang == 'Español':
  prompt = st.chat_input("Escribe tu mensaje")
else:
  prompt = st.chat_input("Write your message")

if prompt:
    txt = ''
    if txtattachment:
        txt = txtattachment.getvalue().decode("utf-8")
        if lang == 'Español':
          txt = '   Archivo de texto: \n' + txt
        else:
          txt = '   Text file: \n' + txt

    if csvexcelattachment:
        try:
            df = pd.read_csv(csvexcelattachment)
        except:
            df = pd.read_excel(csvexcelattachment)
        txt += '   Dataframe: \n' + str(df)

    if graphviz_mode:
        if lang == 'Español':
          txt += '   Genera un grafo con graphviz en .dot \n'
        else:
          txt += '   Generate a graph with graphviz in .dot \n'

    if len(txt) > 5000:
        txt = txt[:5000] + '...'
    if image or url != '':
        if url != '':
            img = Image.open(requests.get(url, stream=True).raw)
        else:
            img = Image.open(image)
        prmt  = {'role': 'user', 'parts':[prompt+txt, img]}
    else:
        prmt  = {'role': 'user', 'parts':[prompt+txt]}

    append_message(prmt)

    if lang == 'Español':
      spinertxt = 'Espera un momento, estoy pensando...'
    else:
      spinertxt = 'Wait a moment, I am thinking...'
    with st.spinner(spinertxt):
        if len(prmt['parts']) > 1:
            response = vision.generate_content(prmt['parts'],stream=True,safety_settings=[
        {
            "category": "HARM_CATEGORY_HARASSMENT",
            "threshold": "BLOCK_LOW_AND_ABOVE",
        },
        {
            "category": "HARM_CATEGORY_HATE_SPEECH",
            "threshold": "BLOCK_LOW_AND_ABOVE",
        },
    ]
)
            response.resolve()
        else:
            response = st.session_state.chat.send_message(prmt['parts'][0])

        try:
          append_message({'role': 'model', 'parts':response.text})
        except Exception as e:
          append_message({'role': 'model', 'parts':f'{type(e).__name__}: {e}'})


        st.rerun()



#st.session_state.chat_session