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| import os | |
| import gradio as gr | |
| from openai import OpenAI | |
| # from huggingface_hub import InferenceClient | |
| """ | |
| For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference | |
| """ | |
| # I can run it on the workstation with LMStudio and access it via the proxy | |
| # client = InferenceClient("DevQuasar/llama3_8b_chat_brainstorm-v2.1") | |
| self_host_url = os.environ['URL'] | |
| api_key = os.environ['API_KEY'] | |
| client = OpenAI(base_url=self_host_url, api_key=api_key) | |
| def respond( | |
| message, | |
| history: list[tuple[str, str]], | |
| system_message, | |
| max_tokens, | |
| temperature, | |
| top_p, | |
| ): | |
| messages = [{"role": "system", "content": system_message+" "}] | |
| for val in history: | |
| if val[0]: | |
| messages.append({"role": "user", "content": val[0]}) | |
| if val[1]: | |
| messages.append({"role": "assistant", "content": val[1]}) | |
| messages.append({"role": "user", "content": message}) | |
| response = "" | |
| try: | |
| for message in client.chat.completions.create( | |
| model="DevQuasar/llama3_8b_chat_brainstorm-GGUF", | |
| messages=messages, | |
| temperature=temperature, | |
| stream=True, | |
| ): | |
| token = message.choices[0].delta.content | |
| try: | |
| response += token | |
| except: | |
| # LMStudio response has empty token | |
| pass | |
| yield response | |
| except: | |
| raise gr.Warning("Apologies for the inconvenience! Our model is currently self-hosted and unavailable at the moment.") | |
| """ | |
| For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface | |
| """ | |
| title = "Brainstorm Demo by devquasar.com" | |
| desc = "Please note that this model is self-hosted, which means it may not be available at all times. Thank you for your understanding!" | |
| long_desc = """Brainstorm facilitates idea exploration through interaction with a Language Model (LLM). | |
| Rather than providing direct answers, the model engages in a dialogue with users, offering probing | |
| questions aimed at fostering deeper contemplation and consideration of various facets of their ideas.""" | |
| demo = gr.ChatInterface( | |
| respond, | |
| additional_inputs=[ | |
| gr.Textbox(value="You are a helpful assistant helps to brainstorm ideas.", label="System message"), | |
| #gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), | |
| gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), | |
| #gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"), | |
| ], | |
| title=title, | |
| description=desc | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |