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import streamlit as st
import json
import os
import requests
from bardapi import Bard
# Load the GOOGLE_LANGUAGES_TO_CODES dictionary from lang.json
with open("lang.json", "r") as file:
GOOGLE_LANGUAGES_TO_CODES = json.load(file)
with st.sidebar:
# Add a selector in the sidebar using the dictionary's keys
selected_language_name = st.sidebar.selectbox("Select Language", list(GOOGLE_LANGUAGES_TO_CODES.keys()))
code_interpreter = st.sidebar.toggle("Code Interpreter", value=True)
system_prompt = st.sidebar.text_input("System prompt for code interpreter", value = "Rule 1: If a user provides a code explain it line by line")
useSystemPrompt = st.sidebar.toggle("Use System prompt", value=True)
exportToReplIt = st.sidebar.toggle("Export to repl.it", value=False)
showImages = st.sidebar.toggle("Show images", value=True)
# Retrieve the corresponding language code from the dictionary
selected_language_code = GOOGLE_LANGUAGES_TO_CODES[selected_language_name]
# Initialize Bard with the selected language code
bard = Bard(token=os.getenv("_BARD_API_KEY"), language=selected_language_code)
TITLE = "Ayush Dhawan's Codebot"
DESCRIPTION = """
Welcome to my coding chatbot! paste any code you want an explanation for!
"""
# Streamlit UI
st.title(TITLE)
st.write(DESCRIPTION)
# Prediction function
def predict(message):
with st.status("Requesting 🦔..."):
st.write("Requesting API...")
response = bard.get_answer(message if not (code_interpreter and useSystemPrompt) else message + " . "+system_prompt)
st.write("Done...")
st.write("Checking images...")
if 'images' in response.keys() and showImages:
for i in response['images']:
st.image(i)
return response
# Display chat messages from history on app rerun
if "messages" not in st.session_state:
st.session_state.messages = []
for message in st.session_state.messages:
with st.chat_message(message["role"], avatar=("🧑💻" if message["role"] == 'human' else '🦔')):
st.markdown(message["content"])
# React to user input
if prompt := st.chat_input("Ask Palm 2 anything..."):
st.chat_message("human", avatar="🧑💻").markdown(prompt)
st.session_state.messages.append({"role": "human", "content": prompt})
response = predict(prompt)
with st.chat_message("assistant", avatar='🦔'):
st.markdown(response['content'])
if response['code']:
if exportToReplIt:
with st.status("Exporting replit..."):
fale = False
try:
url = bard.export_replit(code=response['code'],program_lang=response['program_lang'])['url']
except error:
fale=True
st.write('ERROR')
if not fale:
st.title('Export to repl.it')
st.markdown(f'[link]({url})')
if code_interpreter:
try:
exec(response['code'])
except Exception as e:
st.write(f"ERROR {e}...")
st.session_state.messages.append({"role": "assistant", "content": response['content']})
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