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import streamlit as st | |
import os | |
from openai import OpenAI | |
from dotenv import load_dotenv | |
load_dotenv() | |
import base64 | |
load_dotenv() | |
def get_together_models(): | |
return [ | |
"meta-llama/Meta-Llama-3-8B-Instruct-Turbo", | |
"meta-llama/Meta-Llama-3-70B-Instruct-Lite", | |
"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo", | |
"google/gemma-2-9b-it", | |
"meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", | |
"deepseek-ai/deepseek-coder-33b-instruct", | |
"meta-llama/Meta-Llama-3-70B-Instruct-Turbo", | |
"meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo", | |
"meta-llama/Meta-Llama-3-8B-Instruct-Lite", | |
"meta-llama/Meta-Llama-3-70B-Instruct-Lite", | |
"google/gemma-2-27b-it", | |
"allenai/OLMo-7B-Instruct", | |
"zero-one-ai/Yi-34B-Chat", | |
"allenai/OLMo-7B-Twin-2T", | |
"allenai/OLMo-7B", | |
"Austism/chronos-hermes-13b", | |
"cognitivecomputations/dolphin-2.5-mixtral-8x7b", | |
"databricks/dbrx-instruct", | |
"deepseek-ai/deepseek-llm-67b-chat", | |
"garage-bAInd/Platypus2-70B-instruct", | |
"google/gemma-2b-it", | |
"google/gemma-7b-it", | |
"Gryphe/MythoMax-L2-13b", | |
"lmsys/vicuna-13b-v1.5", | |
"lmsys/vicuna-7b-v1.5", | |
"codellama/CodeLlama-13b-Instruct-hf", | |
"codellama/CodeLlama-34b-Instruct-hf", | |
"codellama/CodeLlama-70b-Instruct-hf", | |
"codellama/CodeLlama-7b-Instruct-hf", | |
"meta-llama/Llama-2-70b-chat-hf", | |
"meta-llama/Llama-2-13b-chat-hf", | |
"meta-llama/Llama-2-7b-chat-hf", | |
"meta-llama/Llama-3-8b-chat-hf", | |
"meta-llama/Llama-3-70b-chat-hf", | |
"mistralai/Mistral-7B-Instruct-v0.1", | |
"mistralai/Mistral-7B-Instruct-v0.2", | |
"mistralai/Mistral-7B-Instruct-v0.3", | |
"mistralai/Mixtral-8x7B-Instruct-v0.1", | |
"mistralai/Mixtral-8x22B-Instruct-v0.1", | |
"NousResearch/Nous-Capybara-7B-V1p9", | |
"NousResearch/Nous-Hermes-2-Mistral-7B-DPO", | |
"NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", | |
"NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT", | |
"NousResearch/Nous-Hermes-llama-2-7b", | |
"NousResearch/Nous-Hermes-Llama2-13b", | |
"NousResearch/Nous-Hermes-2-Yi-34B", | |
"openchat/openchat-3.5-1210", | |
"Open-Orca/Mistral-7B-OpenOrca", | |
"Qwen/Qwen1.5-0.5B-Chat", | |
"Qwen/Qwen1.5-1.8B-Chat", | |
"Qwen/Qwen1.5-4B-Chat", | |
"Qwen/Qwen1.5-7B-Chat", | |
"Qwen/Qwen1.5-14B-Chat", | |
"Qwen/Qwen1.5-32B-Chat", | |
"Qwen/Qwen1.5-72B-Chat", | |
"Qwen/Qwen1.5-110B-Chat", | |
"Qwen/Qwen2-72B-Instruct", | |
"snorkelai/Snorkel-Mistral-PairRM-DPO", | |
"Snowflake/snowflake-arctic-instruct", | |
"togethercomputer/alpaca-7b", | |
"teknium/OpenHermes-2-Mistral-7B", | |
"teknium/OpenHermes-2p5-Mistral-7B", | |
"togethercomputer/Llama-2-7B-32K-Instruct", | |
"togethercomputer/RedPajama-INCITE-Chat-3B-v1", | |
"togethercomputer/RedPajama-INCITE-7B-Chat", | |
"togethercomputer/StripedHyena-Nous-7B", | |
"Undi95/ReMM-SLERP-L2-13B", | |
"Undi95/Toppy-M-7B", | |
"WizardLM/WizardLM-13B-V1.2", | |
"upstage/SOLAR-10.7B-Instruct-v1.0" | |
] | |
# Function to get Groq chat models | |
def get_groq_models(): | |
return [ | |
# "llama-3.1-405b-reasoning", | |
"llama-3.1-70b-versatile", | |
"mixtral-8x7b-32768", | |
"llama3-groq-70b-8192-tool-use-preview", | |
"llama-3.1-8b-instant", | |
"llama3-groq-8b-8192-tool-use-preview", | |
"llama-guard-3-8b", | |
"llama3-70b-8192", | |
"llama3-8b-8192", | |
"gemma-7b-it", | |
"gemma2-9b-it", | |
"whisper-large-v3" | |
] | |
# Function to get OpenAI-like models | |
def get_openai_like_models(): | |
return [ | |
"claude-3-5-sonnet", | |
"gpt-4-turbo-128k-france", | |
"gemini-1.0-pro", | |
"gemini-1.5-pro", | |
"gemini-1.5-flash", | |
"Llama-3-70B-Instruct", | |
"Mixtral-8x7B-Instruct-v0.1", | |
"CodeLlama-2", | |
"jina-embeddings-v2-base-de", | |
"jina-embeddings-v2-base-code", | |
"text-embedding-bge-m3", | |
"llava-v1.6-34b", | |
"llava-v1.6-vicuna-13b", | |
"gpt-35-turbo", | |
"text-embedding-ada-002", | |
"gpt-4-32k-1", | |
"gpt-4-32k-canada", | |
"gpt-4-32k-france", | |
"text-embedding-ada-002-france", | |
"mistral-large-32k-france", | |
"Llama-3.1-405B-Instruct-US", | |
"Mistral-Large-2407", | |
"Mistral-Nemo-2407" | |
] | |
def to_leetspeak(text): | |
leet_dict = { | |
'a': '4', 'e': '3', 'g': '6', 'i': '1', 'o': '0', 's': '5', 't': '7', | |
'A': '4', 'E': '3', 'G': '6', 'I': '1', 'O': '0', 'S': '5', 'T': '7' | |
} | |
return ''.join(leet_dict.get(char, char) for char in text) | |
def to_base64(text): | |
return base64.b64encode(text.encode()).decode() | |
def to_binary(text): | |
return ' '.join(format(ord(char), '08b') for char in text) | |
def to_emoji(text): | |
emoji_dict = { | |
'a': 'π °', 'b': 'π ±', 'c': 'π ²', 'd': 'π ³', 'e': 'π ΄', 'f': 'π ΅', 'g': 'π Ά', 'h': 'π ·', 'i': 'π Έ', 'j': 'π Ή', | |
'k': 'π Ί', 'l': 'π »', 'm': 'π Ό', 'n': 'π ½', 'o': 'π Ύ', 'p': 'π Ώ', 'q': 'π', 'r': 'π', 's': 'π', 't': 'π', | |
'u': 'π', 'v': 'π ', 'w': 'π', 'x': 'π', 'y': 'π', 'z': 'π', | |
'A': 'π °', 'B': 'π ±', 'C': 'π ²', 'D': 'π ³', 'E': 'π ΄', 'F': 'π ΅', 'G': 'π Ά', 'H': 'π ·', 'I': 'π Έ', 'J': 'π Ή', | |
'K': 'π Ί', 'L': 'π »', 'M': 'π Ό', 'N': 'π ½', 'O': 'π Ύ', 'P': 'π Ώ', 'Q': 'π', 'R': 'π', 'S': 'π', 'T': 'π', | |
'U': 'π', 'V': 'π ', 'W': 'π', 'X': 'π', 'Y': 'π', 'Z': 'π' | |
} | |
return ''.join(emoji_dict.get(char, char) for char in text) | |
# Initialize session state | |
if 'messages' not in st.session_state: | |
st.session_state.messages = [] | |
if 'api_key' not in st.session_state: | |
st.session_state.api_key = "" | |
if 'selected_model' not in st.session_state: | |
st.session_state.selected_model = "" | |
if 'selected_service' not in st.session_state: | |
st.session_state.selected_service = "" | |
if 'base_url' not in st.session_state: | |
st.session_state.base_url = "" | |
# Sidebar | |
st.sidebar.title("Chat Settings") | |
# Service selection | |
service = st.sidebar.radio("Select a service:", ("Together AI","OpenAI-like", "Groq")) | |
st.session_state.selected_service = service | |
# Model selection based on the chosen service | |
if service == "OpenAI-like": | |
openai_like_models = get_openai_like_models() | |
selected_model = st.sidebar.selectbox("Select an OpenAI-like model:", openai_like_models) | |
base_url = st.sidebar.text_input("Enter the base URL for the OpenAI-like API:",type="password",value=os.getenv('API_BASE')) | |
api_key = st.sidebar.text_input("Enter your API Key:", type="password",value=os.getenv('API_KEY')) | |
if api_key: | |
st.session_state.api_key = api_key | |
if base_url: | |
st.session_state.base_url = base_url | |
elif service == "Groq": | |
groq_models = get_groq_models() | |
api_key = st.sidebar.text_input("Enter your API Key:", type="password",value=os.getenv('GROQ_API_KEY')) | |
if api_key: | |
st.session_state.api_key = api_key | |
selected_model = st.sidebar.selectbox("Select a Groq model:", groq_models) | |
base_url = "https://api.groq.com/openai/v1" | |
else: # OpenAI-like | |
together_models = get_together_models() | |
api_key = st.sidebar.text_input("Enter your API Key:", type="password",value=os.getenv('TOGETHER_API_KEY')) | |
if api_key: | |
st.session_state.api_key = api_key | |
selected_model = st.sidebar.selectbox("Select a Together AI model:", together_models) | |
base_url = "https://api.together.xyz/v1" | |
if selected_model: | |
st.session_state.selected_model = selected_model | |
# Main chat interface | |
st.title("AI Chat Application") | |
# Display chat messages | |
for message in st.session_state.messages: | |
with st.chat_message(message["role"]): | |
st.markdown(message["content"]) | |
# User input | |
if prompt := st.chat_input("You:"): | |
if not st.session_state.api_key: | |
st.error("Please enter an API key.") | |
elif not st.session_state.selected_model: | |
st.error("Please select a model.") | |
elif service == "OpenAI-like" and not st.session_state.base_url: | |
st.error("Please enter the base URL for the OpenAI-like API.") | |
else: | |
# Add user message to chat history | |
st.session_state.messages.append({"role": "user", "content": prompt}) | |
with st.chat_message("user"): | |
st.markdown(prompt) | |
# Generate AI response | |
with st.chat_message("assistant"): | |
message_placeholder = st.empty() | |
full_response = "" | |
try: | |
if service == "OpenAI-like": | |
client = OpenAI( | |
api_key=st.session_state.api_key, | |
base_url=st.session_state.base_url + '/v2', | |
) | |
else: | |
client = OpenAI(api_key=st.session_state.api_key, base_url=base_url) | |
for response in client.chat.completions.create( | |
model=st.session_state.selected_model, | |
messages=[ | |
{"role": m["role"], "content": m["content"]} | |
for m in st.session_state.messages | |
], | |
stream=True, | |
max_tokens=1000, | |
temperature=0.7 | |
): | |
full_response += (response.choices[0].delta.content or "") | |
message_placeholder.markdown(full_response + "β") | |
message_placeholder.markdown(full_response) | |
except Exception as e: | |
st.error(f"An error occurred: {str(e)}") | |
full_response = "I apologize, but an error occurred while generating the response." | |
# Add assistant response to chat history | |
st.session_state.messages.append({"role": "assistant", "content": full_response}) | |
# Clear chat button | |
if st.sidebar.button("Clear Chat"): | |
st.session_state.messages = [] | |
st.rerun() | |
with st.sidebar: | |
st.title("Text Conversion") | |
input_text = st.text_area("Enter text to convert:") | |
col1, col2 = st.columns(2) | |
with col1: | |
if st.button("To Leetspeak"): | |
if input_text: | |
converted_text = to_leetspeak(input_text) | |
st.text_area("Leetspeak Result:", converted_text, height=100) | |
st.code(converted_text, language="text") | |
if st.button("To Base64"): | |
if input_text: | |
converted_text = to_base64(input_text) | |
st.text_area("Base64 Result:", converted_text, height=100) | |
st.code(converted_text, language="text") | |
with col2: | |
if st.button("To Binary"): | |
if input_text: | |
converted_text = to_binary(input_text) | |
st.text_area("Binary Result:", converted_text, height=100) | |
st.code(converted_text, language="text") | |
if st.button("To Emoji"): | |
if input_text: | |
converted_text = to_emoji(input_text) | |
st.text_area("Emoji Result:", converted_text, height=100) | |
st.code(converted_text, language="text") | |