from huggingface_hub import InferenceClient
import gradio as gr
import random
import prompts
clients = [
    {'type':'image','name':'black-forest-labs/FLUX.1-dev','rank':'op','max_tokens':16384,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'deepseek-ai/DeepSeek-V2.5-1210','rank':'op','max_tokens':16384,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'Qwen/Qwen2.5-Coder-32B-Instruct','rank':'op','max_tokens':32768,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'meta-llama/Meta-Llama-3-8B','rank':'op','max_tokens':32768,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'Snowflake/snowflake-arctic-embed-l-v2.0','rank':'op','max_tokens':4096,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'Snowflake/snowflake-arctic-embed-m-v2.0','rank':'op','max_tokens':4096,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'HuggingFaceTB/SmolLM2-1.7B-Instruct','rank':'op','max_tokens':4096,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'Qwen/QwQ-32B-Preview','rank':'op','max_tokens':16384,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'meta-llama/Llama-3.3-70B-Instruct','rank':'pro','max_tokens':16384,'schema':{'bos':'<|im_start|>','eos':'<|im_end|>'}},
    {'type':'text','name':'mistralai/Mixtral-8x7B-Instruct-v0.1','rank':'op','max_tokens':40000,'schema':{'bos':'<s>','eos':'</s>'}},
]
def format_prompt(message, history):
  prompt = "<s>"
  for user_prompt, bot_response in history:
    prompt += f"[INST] {user_prompt} [/INST]"
    prompt += f" {bot_response}</s> "
  prompt += f"[INST] {message} [/INST]"
  return prompt
agents =[
    "WEB_DEV",
    "AI_SYSTEM_PROMPT",
    "PYTHON_CODE_DEV",
    "CODE_REVIEW_ASSISTANT",
    "CONTENT_WRITER_EDITOR",
    "SOCIAL_MEDIA_MANAGER",
    "MEME_GENERATOR",
    "QUESTION_GENERATOR",
    "IMAGE_GENERATOR",
    "HUGGINGFACE_FILE_DEV",

]
def generate(
        prompt, history, mod, agent_name=agents[0], sys_prompt="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
):
    seed = random.randint(1,1111111111111111)
    client=InferenceClient(clients[int(mod)]['name'])
    agent=prompts.WEB_DEV
    if agent_name == "WEB_DEV":
        agent = prompts.WEB_DEV_SYSTEM_PROMPT
    if agent_name == "CODE_REVIEW_ASSISTANT":
        agent = prompts.CODE_REVIEW_ASSISTANT
    if agent_name == "CONTENT_WRITER_EDITOR":
        agent = prompts.CONTENT_WRITER_EDITOR
    if agent_name == "SOCIAL_MEDIA_MANAGER":
        agent = prompts.SOCIAL_MEDIA_MANAGER        
    if agent_name == "AI_SYSTEM_PROMPT":
        agent = prompts.AI_SYSTEM_PROMPT
    if agent_name == "PYTHON_CODE_DEV":
        agent = prompts.PYTHON_CODE_DEV        
    if agent_name == "MEME_GENERATOR":
        agent = prompts.MEME_GENERATOR  
    if agent_name == "QUESTION_GENERATOR":
        agent = prompts.QUESTION_GENERATOR 
    if agent_name == "IMAGE_GENERATOR":
        agent = prompts.IMAGE_GENERATOR      
    if agent_name == "HUGGINGFACE_FILE_DEV":
        agent = prompts.HUGGINGFACE_FILE_DEV          
    system_prompt=agent
    temperature = float(temperature)
    if temperature < 1e-2:
        temperature = 1e-2
    top_p = float(top_p)

    generate_kwargs = dict(
        temperature=temperature,
        max_new_tokens=max_new_tokens,
        top_p=top_p,
        repetition_penalty=repetition_penalty,
        do_sample=True,
        seed=seed,
    )

    formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
    output = ""

    for response in stream:
        output += response.token.text
        yield [prompt,output]
    return [prompt,output]


additional_inputs=[
    gr.Dropdown(
        label="Model",
        choices=[sn['name'] for sn in clients],
        value=clients[2]['name'],
        interactive=True,
        type='index',
        ),
    gr.Dropdown(
        label="Agents",
        choices=[s for s in agents],
        value=agents[0],
        interactive=True,
        ),
    gr.Textbox(
        label="System Prompt",
        max_lines=1,
        interactive=True,
    ),
    gr.Slider(
        label="Temperature",
        value=0.9,
        minimum=0.0,
        maximum=1.0,
        step=0.05,
        interactive=True,
        info="Higher values produce more diverse outputs",
    ),

    gr.Slider(
        label="Max new tokens",
        value=1048*10,
        minimum=0,
        maximum=1048*10,
        step=64,
        interactive=True,
        info="The maximum numbers of new tokens",
    ),
    gr.Slider(
        label="Top-p (nucleus sampling)",
        value=0.90,
        minimum=0.0,
        maximum=1,
        step=0.05,
        interactive=True,
        info="Higher values sample more low-probability tokens",
    ),
    gr.Slider(
        label="Repetition penalty",
        value=1.2,
        minimum=1.0,
        maximum=2.0,
        step=0.05,
        interactive=True,
        info="Penalize repeated tokens",
    ),


]

examples=[["Write a simple working game in HTML5", agents[0], None, None, None, None, ],
          ["Choose 3 useful types of AI agents, and create a detailed System Prompt to align each of them.", agents[1], None, None, None, None, ],
          ["Create 3 of the funniest memes", agents[6], None, None, None, None, ],
          ["Explain it to me in a childrens story how Nuclear Fission works", agents[4], None, None, None, None, ],
          ["Show a bunch of examples of catchy ways to post, 'I had a ham sandwich for lunch today'", agents[5], None, None, None, None, ],
          ["Write high quality personal website to show off my adventure sports hobby", agents[0], None, None, None, None, ],
          ["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", agents[4], None, None, None, None, ],
          ["Can you write a short story about a time-traveling detective who solves historical mysteries?", agents[4], None, None, None, None,],
          ["I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", agents[4], None, None, None, None,],
          ["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", agents[4], None, None, None, None,],
          ["Can you explain how the QuickSort algorithm works and provide a Python implementation?", agents[2], None, None, None, None,],
          ["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", agents[3], None, None, None, None,],
         ]


gr.ChatInterface(
    fn=generate,
    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, layout="panel"),
    additional_inputs=additional_inputs,
    title="Mixtral 46.7B",
    examples=examples,
    concurrency_limit=20,
).queue(default_concurrency_limit=20).launch(max_threads=40)