| | import gradio as gr |
| | import os |
| | import requests |
| |
|
| | zephyr_7b_beta = "https://api-inference.huggingface.co/models/Undi95/Toppy-M-7B/" |
| |
|
| | HF_TOKEN = os.getenv("HF_TOKEN") |
| | HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} |
| |
|
| | def build_input_prompt(message, chatbot, system_prompt): |
| | """ |
| | Constructs the input prompt string from the chatbot interactions and the current message. |
| | """ |
| | input_prompt = "<|system|>\n" + system_prompt + "</s>\n<|user|>\n" |
| | for interaction in chatbot: |
| | input_prompt = input_prompt + str(interaction[0]) + "</s>\n<|assistant|>\n" + str(interaction[1]) + "\n</s>\n<|user|>\n" |
| |
|
| | input_prompt = input_prompt + str(message) + "</s>\n<|assistant|>" |
| | return input_prompt |
| |
|
| |
|
| | def post_request_beta(payload): |
| | """ |
| | Sends a POST request to the predefined Zephyr-7b-Beta URL and returns the JSON response. |
| | """ |
| | response = requests.post(zephyr_7b_beta, headers=HEADERS, json=payload) |
| | response.raise_for_status() |
| | return response.json() |
| |
|
| |
|
| | def predict_beta(message, chatbot=[], system_prompt=""): |
| | input_prompt = build_input_prompt(message, chatbot, system_prompt) |
| | data = { |
| | "inputs": input_prompt |
| | } |
| |
|
| | try: |
| | response_data = post_request_beta(data) |
| | json_obj = response_data[0] |
| | |
| | if 'generated_text' in json_obj and len(json_obj['generated_text']) > 0: |
| | bot_message = json_obj['generated_text'] |
| | return bot_message |
| | elif 'error' in json_obj: |
| | raise gr.Error(json_obj['error'] + ' Please refresh and try again with smaller input prompt') |
| | else: |
| | warning_msg = f"Unexpected response: {json_obj}" |
| | raise gr.Error(warning_msg) |
| | except requests.HTTPError as e: |
| | error_msg = f"Request failed with status code {e.response.status_code}" |
| | raise gr.Error(error_msg) |
| | except json.JSONDecodeError as e: |
| | error_msg = f"Failed to decode response as JSON: {str(e)}" |
| | raise gr.Error(error_msg) |
| |
|
| | def test_preview_chatbot(message, history): |
| | response = predict_beta(message, history, SYSTEM_PROMPT) |
| | text_start = response.rfind("<|assistant|>", ) + len("<|assistant|>") |
| | response = response[text_start:] |
| | return response |
| |
|
| |
|
| | welcome_preview_message = f""" |
| | Welcome to **{TITLE}**! Say something like: |
| | |
| | "{EXAMPLE_INPUT}" |
| | """ |
| |
|
| | chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)]) |
| | textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT) |
| |
|
| | demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview) |
| |
|
| | demo.launch() |