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| from langchain_anthropic import ChatAnthropic | |
| from langchain_cohere import ChatCohere | |
| from langchain_groq import ChatGroq | |
| from langchain_openai import ChatOpenAI | |
| from langchain_core.output_parsers import StrOutputParser | |
| from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder | |
| from utils import Translation | |
| import time | |
| import gradio as gr | |
| NAME2CHAT = {"Cohere": ChatCohere, "claude-3-opus-20240229": ChatAnthropic, "claude-3-sonnet-20240229": ChatAnthropic, "claude-3-haiku-20240307": ChatAnthropic, "llama3-8b-8192": ChatGroq, "llama3-70b-8192": ChatGroq, "mixtral-8x7b-32768": ChatGroq, "gemma-7b-it": ChatGroq, "gpt-4o": ChatOpenAI, "gpt-3.5-turbo-0125": ChatOpenAI} | |
| NAME2APIKEY = {"Cohere": "COHERE_API_KEY", "claude-3-opus-20240229": "ANTHROPIC_API_KEY", "claude-3-sonnet-20240229": "ANTHROPIC_API_KEY", "claude-3-haiku-20240307": "ANTHROPIC_API_KEY", "llama3-8b-8192": "GROQ_API_KEY", "llama3-70b-8192": "GROQ_API_KEY", "mixtral-8x7b-32768": "GROQ_API_KEY", "gemma-7b-it": "GROQ_API_KEY", "gpt-4o": "OPENAI_API_KEY", "gpt-3.5-turbo-0125": "OPENAI_API_KEY"} | |
| parser = StrOutputParser() | |
| def reply(message, history, name, api_key, temperature, max_new_tokens, system_template): | |
| global pdfdb | |
| os.environ[NAME2APIKEY[name]] = api_key | |
| if name == "Cohere": | |
| model = NAME2CHAT[name](temperature=temperature, max_tokens=max_new_tokens) | |
| else: | |
| model = NAME2CHAT[name](model=name,temperature=temperature, max_tokens=max_new_tokens) | |
| prompt_template = ChatPromptTemplate.from_messages( | |
| [("system", system_template), ("user", "{text}")] | |
| ) | |
| chain = prompt_template | model | parser | |
| txt = Translation(message, "en") | |
| if txt.original == "en": | |
| response = chain.invoke({"text": message}) | |
| r = '' | |
| for c in response: | |
| r+=c | |
| time.sleep(0.001) | |
| yield r | |
| else: | |
| translation = txt.translatef() | |
| response = chain.invoke({"text": message}) | |
| t = Translation(response, txt.original) | |
| res = t.translatef() | |
| r = '' | |
| for c in res: | |
| r+=c | |
| time.sleep(0.001) | |
| yield r | |
| chat_model = gr.Dropdown( | |
| [m for m in list(NAME2APIKEY)], label="Chat Model", info="Choose one of the available chat models" | |
| ) | |
| user_api_key = gr.Textbox( | |
| label="API key", | |
| info="Paste your API key here", | |
| lines=1, | |
| type="password", | |
| ) | |
| user_temperature = gr.Slider(0, 1, value=0.5, label="Temperature", info="Select model temperature") | |
| user_max_new_tokens = gr.Slider(0, 8192, value=1024, label="Max new tokens", info="Select max output tokens (higher number of tokens will result in a longer latency)") | |
| user_session_id = gr.Textbox(label="System Template",info="Customize your assistant with your instructions",value="You are an helpful assistant") | |
| additional_accordion = gr.Accordion(label="Parameters to be set before you start chatting", open=True) | |
| demo = gr.ChatInterface(fn=reply, additional_inputs=[chat_model, user_api_key, user_temperature, user_max_new_tokens, user_session_id], additional_inputs_accordion=additional_accordion, title="Chat with Anthropic, OpenAI, Groq and Cohere Models🤖") | |
| if __name__=="__main__": | |
| demo.launch(server_name="0.0.0.0", share=False) | |