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Upload app.py

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+
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+
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+
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+ import streamlit as st
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+ import os
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+ from openai import OpenAI
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+ from dotenv import load_dotenv
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+ load_dotenv()
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+ import base64
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+
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+ load_dotenv()
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+
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+ def get_together_models():
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+ return [
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+ "meta-llama/Meta-Llama-3-8B-Instruct-Turbo",
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+ "meta-llama/Meta-Llama-3-70B-Instruct-Lite",
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+ "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
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+ "google/gemma-2-9b-it",
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+ "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
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+ "deepseek-ai/deepseek-coder-33b-instruct",
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+ "meta-llama/Meta-Llama-3-70B-Instruct-Turbo",
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+ "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
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+ "meta-llama/Meta-Llama-3-8B-Instruct-Lite",
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+ "meta-llama/Meta-Llama-3-70B-Instruct-Lite",
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+ "google/gemma-2-27b-it",
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+ "allenai/OLMo-7B-Instruct",
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+ "zero-one-ai/Yi-34B-Chat",
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+ "allenai/OLMo-7B-Twin-2T",
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+ "allenai/OLMo-7B",
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+ "Austism/chronos-hermes-13b",
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+ "cognitivecomputations/dolphin-2.5-mixtral-8x7b",
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+ "databricks/dbrx-instruct",
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+
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+ "deepseek-ai/deepseek-llm-67b-chat",
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+ "garage-bAInd/Platypus2-70B-instruct",
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+ "google/gemma-2b-it",
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+ "google/gemma-7b-it",
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+ "Gryphe/MythoMax-L2-13b",
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+ "lmsys/vicuna-13b-v1.5",
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+ "lmsys/vicuna-7b-v1.5",
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+ "codellama/CodeLlama-13b-Instruct-hf",
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+ "codellama/CodeLlama-34b-Instruct-hf",
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+ "codellama/CodeLlama-70b-Instruct-hf",
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+ "codellama/CodeLlama-7b-Instruct-hf",
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+ "meta-llama/Llama-2-70b-chat-hf",
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+ "meta-llama/Llama-2-13b-chat-hf",
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+ "meta-llama/Llama-2-7b-chat-hf",
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+ "meta-llama/Llama-3-8b-chat-hf",
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+ "meta-llama/Llama-3-70b-chat-hf",
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+ "mistralai/Mistral-7B-Instruct-v0.1",
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+ "mistralai/Mistral-7B-Instruct-v0.2",
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+ "mistralai/Mistral-7B-Instruct-v0.3",
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+ "mistralai/Mixtral-8x7B-Instruct-v0.1",
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+ "mistralai/Mixtral-8x22B-Instruct-v0.1",
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+ "NousResearch/Nous-Capybara-7B-V1p9",
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+ "NousResearch/Nous-Hermes-2-Mistral-7B-DPO",
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+ "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
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+ "NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT",
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+ "NousResearch/Nous-Hermes-llama-2-7b",
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+ "NousResearch/Nous-Hermes-Llama2-13b",
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+ "NousResearch/Nous-Hermes-2-Yi-34B",
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+ "openchat/openchat-3.5-1210",
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+ "Open-Orca/Mistral-7B-OpenOrca",
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+ "Qwen/Qwen1.5-0.5B-Chat",
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+ "Qwen/Qwen1.5-1.8B-Chat",
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+ "Qwen/Qwen1.5-4B-Chat",
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+ "Qwen/Qwen1.5-7B-Chat",
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+ "Qwen/Qwen1.5-14B-Chat",
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+ "Qwen/Qwen1.5-32B-Chat",
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+ "Qwen/Qwen1.5-72B-Chat",
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+ "Qwen/Qwen1.5-110B-Chat",
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+ "Qwen/Qwen2-72B-Instruct",
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+ "snorkelai/Snorkel-Mistral-PairRM-DPO",
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+ "Snowflake/snowflake-arctic-instruct",
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+ "togethercomputer/alpaca-7b",
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+ "teknium/OpenHermes-2-Mistral-7B",
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+ "teknium/OpenHermes-2p5-Mistral-7B",
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+ "togethercomputer/Llama-2-7B-32K-Instruct",
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+ "togethercomputer/RedPajama-INCITE-Chat-3B-v1",
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+ "togethercomputer/RedPajama-INCITE-7B-Chat",
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+ "togethercomputer/StripedHyena-Nous-7B",
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+ "Undi95/ReMM-SLERP-L2-13B",
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+ "Undi95/Toppy-M-7B",
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+ "WizardLM/WizardLM-13B-V1.2",
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+ "upstage/SOLAR-10.7B-Instruct-v1.0"
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+ ]
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+
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+
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+ # Function to get Groq chat models
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+ def get_groq_models():
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+ return [
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+ # "llama-3.1-405b-reasoning",
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+ "llama-3.1-70b-versatile",
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+ "mixtral-8x7b-32768",
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+ "llama3-groq-70b-8192-tool-use-preview",
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+ "llama-3.1-8b-instant",
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+ "llama3-groq-8b-8192-tool-use-preview",
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+ "llama-guard-3-8b",
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+ "llama3-70b-8192",
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+ "llama3-8b-8192",
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+ "gemma-7b-it",
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+ "gemma2-9b-it",
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+ "whisper-large-v3"
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+ ]
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+
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+ # Function to get OpenAI-like models
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+ def get_openai_like_models():
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+ return [
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+ "claude-3-5-sonnet",
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+ "gpt-4-turbo-128k-france",
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+ "gemini-1.0-pro",
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+ "gemini-1.5-pro",
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+ "gemini-1.5-flash",
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+ "Llama-3-70B-Instruct",
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+ "Mixtral-8x7B-Instruct-v0.1",
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+ "CodeLlama-2",
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+ "jina-embeddings-v2-base-de",
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+ "jina-embeddings-v2-base-code",
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+ "text-embedding-bge-m3",
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+ "llava-v1.6-34b",
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+ "llava-v1.6-vicuna-13b",
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+ "gpt-35-turbo",
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+ "text-embedding-ada-002",
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+ "gpt-4-32k-1",
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+ "gpt-4-32k-canada",
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+ "gpt-4-32k-france",
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+ "text-embedding-ada-002-france",
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+ "mistral-large-32k-france",
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+ "Llama-3.1-405B-Instruct-US",
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+ "Mistral-Large-2407",
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+ "Mistral-Nemo-2407"
132
+ ]
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+
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+
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+
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+ def to_leetspeak(text):
137
+ leet_dict = {
138
+ 'a': '4', 'e': '3', 'g': '6', 'i': '1', 'o': '0', 's': '5', 't': '7',
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+ 'A': '4', 'E': '3', 'G': '6', 'I': '1', 'O': '0', 'S': '5', 'T': '7'
140
+ }
141
+ return ''.join(leet_dict.get(char, char) for char in text)
142
+
143
+ def to_base64(text):
144
+ return base64.b64encode(text.encode()).decode()
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+
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+ def to_binary(text):
147
+ return ' '.join(format(ord(char), '08b') for char in text)
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+
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+ def to_emoji(text):
150
+ emoji_dict = {
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+ 'a': 'πŸ…°', 'b': 'πŸ…±', 'c': 'πŸ…²', 'd': 'πŸ…³', 'e': 'πŸ…΄', 'f': 'πŸ…΅', 'g': 'πŸ…Ά', 'h': 'πŸ…·', 'i': 'πŸ…Έ', 'j': 'πŸ…Ή',
152
+ 'k': 'πŸ…Ί', 'l': 'πŸ…»', 'm': 'πŸ…Ό', 'n': 'πŸ…½', 'o': 'πŸ…Ύ', 'p': 'πŸ…Ώ', 'q': 'πŸ†€', 'r': 'πŸ†', 's': 'πŸ†‚', 't': 'πŸ†ƒ',
153
+ 'u': 'πŸ†„', 'v': 'πŸ†…', 'w': 'πŸ††', 'x': 'πŸ†‡', 'y': 'πŸ†ˆ', 'z': 'πŸ†‰',
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+ 'A': 'πŸ…°', 'B': 'πŸ…±', 'C': 'πŸ…²', 'D': 'πŸ…³', 'E': 'πŸ…΄', 'F': 'πŸ…΅', 'G': 'πŸ…Ά', 'H': 'πŸ…·', 'I': 'πŸ…Έ', 'J': 'πŸ…Ή',
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+ 'K': 'πŸ…Ί', 'L': 'πŸ…»', 'M': 'πŸ…Ό', 'N': 'πŸ…½', 'O': 'πŸ…Ύ', 'P': 'πŸ…Ώ', 'Q': 'πŸ†€', 'R': 'πŸ†', 'S': 'πŸ†‚', 'T': 'πŸ†ƒ',
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+ 'U': 'πŸ†„', 'V': 'πŸ†…', 'W': 'πŸ††', 'X': 'πŸ†‡', 'Y': 'πŸ†ˆ', 'Z': 'πŸ†‰'
157
+ }
158
+ return ''.join(emoji_dict.get(char, char) for char in text)
159
+
160
+ # Initialize session state
161
+ if 'messages' not in st.session_state:
162
+ st.session_state.messages = []
163
+
164
+ if 'api_key' not in st.session_state:
165
+ st.session_state.api_key = ""
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+
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+ if 'selected_model' not in st.session_state:
168
+ st.session_state.selected_model = ""
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+
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+ if 'selected_service' not in st.session_state:
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+ st.session_state.selected_service = ""
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+
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+ if 'base_url' not in st.session_state:
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+ st.session_state.base_url = ""
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+
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+ # Sidebar
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+ st.sidebar.title("Chat Settings")
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+
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+
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+ # Service selection
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+ service = st.sidebar.radio("Select a service:", ("Together AI","OpenAI-like", "Groq"))
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+ st.session_state.selected_service = service
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+
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+ # Model selection based on the chosen service
185
+ if service == "OpenAI-like":
186
+ openai_like_models = get_openai_like_models()
187
+ selected_model = st.sidebar.selectbox("Select an OpenAI-like model:", openai_like_models)
188
+ base_url = st.sidebar.text_input("Enter the base URL for the OpenAI-like API:",type="password",value=os.getenv('API_BASE'))
189
+ api_key = st.sidebar.text_input("Enter your API Key:", type="password",value=os.getenv('API_KEY'))
190
+ if api_key:
191
+ st.session_state.api_key = api_key
192
+ if base_url:
193
+ st.session_state.base_url = base_url
194
+
195
+
196
+
197
+ elif service == "Groq":
198
+ groq_models = get_groq_models()
199
+ api_key = st.sidebar.text_input("Enter your API Key:", type="password",value=os.getenv('GROQ_API_KEY'))
200
+ if api_key:
201
+ st.session_state.api_key = api_key
202
+ selected_model = st.sidebar.selectbox("Select a Groq model:", groq_models)
203
+ base_url = "https://api.groq.com/openai/v1"
204
+ else: # OpenAI-like
205
+ together_models = get_together_models()
206
+ api_key = st.sidebar.text_input("Enter your API Key:", type="password",value=os.getenv('TOGETHER_API_KEY'))
207
+ if api_key:
208
+ st.session_state.api_key = api_key
209
+ selected_model = st.sidebar.selectbox("Select a Together AI model:", together_models)
210
+ base_url = "https://api.together.xyz/v1"
211
+
212
+ if selected_model:
213
+ st.session_state.selected_model = selected_model
214
+
215
+ # Main chat interface
216
+ st.title("AI Chat Application")
217
+
218
+ # Display chat messages
219
+ for message in st.session_state.messages:
220
+ with st.chat_message(message["role"]):
221
+ st.markdown(message["content"])
222
+
223
+ # User input
224
+ if prompt := st.chat_input("You:"):
225
+ if not st.session_state.api_key:
226
+ st.error("Please enter an API key.")
227
+ elif not st.session_state.selected_model:
228
+ st.error("Please select a model.")
229
+ elif service == "OpenAI-like" and not st.session_state.base_url:
230
+ st.error("Please enter the base URL for the OpenAI-like API.")
231
+ else:
232
+ # Add user message to chat history
233
+ st.session_state.messages.append({"role": "user", "content": prompt})
234
+ with st.chat_message("user"):
235
+ st.markdown(prompt)
236
+
237
+ # Generate AI response
238
+ with st.chat_message("assistant"):
239
+ message_placeholder = st.empty()
240
+ full_response = ""
241
+
242
+ try:
243
+ if service == "OpenAI-like":
244
+ client = OpenAI(
245
+ api_key=st.session_state.api_key,
246
+ base_url=st.session_state.base_url + '/v2',
247
+ )
248
+ else:
249
+ client = OpenAI(api_key=st.session_state.api_key, base_url=base_url)
250
+
251
+ for response in client.chat.completions.create(
252
+ model=st.session_state.selected_model,
253
+ messages=[
254
+ {"role": m["role"], "content": m["content"]}
255
+ for m in st.session_state.messages
256
+ ],
257
+ stream=True,
258
+ max_tokens=1000,
259
+ temperature=0.7
260
+ ):
261
+ full_response += (response.choices[0].delta.content or "")
262
+ message_placeholder.markdown(full_response + "β–Œ")
263
+
264
+ message_placeholder.markdown(full_response)
265
+ except Exception as e:
266
+ st.error(f"An error occurred: {str(e)}")
267
+ full_response = "I apologize, but an error occurred while generating the response."
268
+
269
+ # Add assistant response to chat history
270
+ st.session_state.messages.append({"role": "assistant", "content": full_response})
271
+
272
+ # Clear chat button
273
+ if st.sidebar.button("Clear Chat"):
274
+ st.session_state.messages = []
275
+
276
+ st.rerun()
277
+
278
+
279
+ with st.sidebar:
280
+ st.title("Text Conversion")
281
+ input_text = st.text_area("Enter text to convert:")
282
+
283
+ col1, col2 = st.columns(2)
284
+
285
+ with col1:
286
+ if st.button("To Leetspeak"):
287
+ if input_text:
288
+ converted_text = to_leetspeak(input_text)
289
+ st.text_area("Leetspeak Result:", converted_text, height=100)
290
+ st.code(converted_text, language="text")
291
+
292
+ if st.button("To Base64"):
293
+ if input_text:
294
+ converted_text = to_base64(input_text)
295
+ st.text_area("Base64 Result:", converted_text, height=100)
296
+ st.code(converted_text, language="text")
297
+
298
+ with col2:
299
+ if st.button("To Binary"):
300
+ if input_text:
301
+ converted_text = to_binary(input_text)
302
+ st.text_area("Binary Result:", converted_text, height=100)
303
+ st.code(converted_text, language="text")
304
+
305
+ if st.button("To Emoji"):
306
+ if input_text:
307
+ converted_text = to_emoji(input_text)
308
+ st.text_area("Emoji Result:", converted_text, height=100)
309
+ st.code(converted_text, language="text")
310
+
311
+