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import gradio as gr |
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import random |
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models=[ |
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"facebook/MobileLLM-125M", |
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"facebook/MobileLLM-350M", |
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"facebook/MobileLLM-600M", |
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"facebook/MobileLLM-1B", |
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] |
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client_z=[] |
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def load_models(inp,new_models): |
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if not new_models: |
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new_models=models |
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out_box=[gr.Chatbot(),gr.Chatbot(),gr.Chatbot(),gr.Chatbot()] |
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print(type(inp)) |
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print(inp) |
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client_z.clear() |
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for z,ea in enumerate(inp): |
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client_z.append(gr.load("models/" + new_models[inp[z]])) |
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out_box[z]=(gr.update(label=new_models[inp[z]])) |
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return out_box[0],out_box[1],out_box[2],out_box[3] |
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def format_prompt_default(message, history): |
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prompt = "" |
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if history: |
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for user_prompt, bot_response in history: |
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prompt += f"{user_prompt}\n" |
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print(prompt) |
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prompt += f"{bot_response}\n" |
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print(prompt) |
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prompt += f"{message}\n" |
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return prompt |
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def format_prompt_gemma(message, history): |
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prompt = "" |
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if history: |
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for user_prompt, bot_response in history: |
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prompt += f"{user_prompt}\n" |
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print(prompt) |
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prompt += f"{bot_response}\n" |
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print(prompt) |
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prompt += f"<start_of_turn>user{message}<end_of_turn><start_of_turn>model" |
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return prompt |
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def format_prompt_mixtral(message, history): |
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prompt = "<s>" |
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if history: |
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for user_prompt, bot_response in history: |
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prompt += f"[INST] {user_prompt} [/INST]" |
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prompt += f" {bot_response}</s> " |
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prompt += f"[INST] {message} [/INST]" |
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return prompt |
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def format_prompt_choose(message, history, model_name, new_models=None): |
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if not new_models: |
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new_models=models |
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if "gemma" in new_models[model_name].lower() and "it" in new_models[model_name].lower(): |
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return format_prompt_gemma(message,history) |
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if "mixtral" in new_models[model_name].lower(): |
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return format_prompt_mixtral(message,history) |
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else: |
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return format_prompt_mixtral(message,history) |
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mega_hist=[[],[],[],[]] |
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def chat_inf_tree(system_prompt,prompt,history,client_choice,seed,temp,tokens,top_p,rep_p,hid_val): |
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if len(client_choice)>=hid_val: |
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client = gr.load() |
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if history: |
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mega_hist[hid_val-1]=history |
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hist_len=0 |
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generate_kwargs = dict( |
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temperature=temp, |
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max_new_tokens=tokens, |
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top_p=top_p, |
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repetition_penalty=rep_p, |
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do_sample=True, |
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seed=seed, |
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) |
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formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", mega_hist[hid_val-1]) |
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) |
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output = "" |
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for response in stream: |
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output += response.token.text |
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yield [(prompt,output)] |
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mega_hist[hid_val-1].append((prompt,output)) |
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yield mega_hist[hid_val-1] |
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else: |
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yield None |
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def chat_inf_a(system_prompt,prompt,history,client_choice,seed,temp,tokens,top_p,rep_p,hid_val): |
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if system_prompt: |
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system_prompt=f'{system_prompt}, ' |
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client1=gr.load("models/" + models[0]) |
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if not history: |
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history = [] |
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hist_len=0 |
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generate_kwargs = dict( |
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temperature=temp, |
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max_new_tokens=tokens, |
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top_p=top_p, |
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repetition_penalty=rep_p, |
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do_sample=True, |
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seed=seed, |
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) |
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formatted_prompt = format_prompt_choose(f"{system_prompt}{prompt}", history, client_choice[0]) |
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stream1 = client1.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) |
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output = "" |
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for response in stream1: |
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output += response.token.text |
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yield [(prompt,output)] |
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history.append((prompt,output)) |
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yield history |
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def chat_inf_b(system_prompt,prompt,history,client_choice,seed,temp,tokens,top_p,rep_p,hid_val): |
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if system_prompt: |
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system_prompt=f'{system_prompt}, ' |
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client2=gr.load("models/" + models[1]) |
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if not history: |
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history = [] |
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hist_len=0 |
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generate_kwargs = dict( |
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temperature=temp, |
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max_new_tokens=tokens, |
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top_p=top_p, |
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repetition_penalty=rep_p, |
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do_sample=True, |
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seed=seed, |
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) |
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formatted_prompt = format_prompt_choose(f"{system_prompt}{prompt}", history, client_choice[1]) |
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stream2 = client2.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) |
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output = "" |
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for response in stream2: |
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output += response.token.text |
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yield [(prompt,output)] |
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history.append((prompt,output)) |
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yield history |
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def chat_inf_c(system_prompt,prompt,history,client_choice,seed,temp,tokens,top_p,rep_p,hid_val): |
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if system_prompt: |
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system_prompt=f'{system_prompt}, ' |
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client3=gr.load("models/" + models[2]) |
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if not history: |
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history = [] |
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hist_len=0 |
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generate_kwargs = dict( |
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temperature=temp, |
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max_new_tokens=tokens, |
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top_p=top_p, |
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repetition_penalty=rep_p, |
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do_sample=True, |
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seed=seed, |
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) |
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formatted_prompt = format_prompt_choose(f"{system_prompt}{prompt}", history, client_choice[2]) |
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stream3 = client3.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) |
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output = "" |
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for response in stream3: |
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output += response.token.text |
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yield [(prompt,output)] |
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history.append((prompt,output)) |
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yield history |
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def chat_inf_d(system_prompt,prompt,history,client_choice,seed,temp,tokens,top_p,rep_p,hid_val): |
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if system_prompt: |
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system_prompt=f'{system_prompt}, ' |
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client4=gr.load("models/" + models[3]) |
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if not history: |
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history = [] |
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hist_len=0 |
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generate_kwargs = dict( |
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temperature=temp, |
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max_new_tokens=tokens, |
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top_p=top_p, |
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repetition_penalty=rep_p, |
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do_sample=True, |
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seed=seed, |
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) |
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formatted_prompt = format_prompt_choose(f"{system_prompt}{prompt}", history, client_choice[3]) |
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stream4 = client4.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) |
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output = "" |
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for response in stream4: |
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output += response.token.text |
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yield [(prompt,output)] |
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history.append((prompt,output)) |
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yield history |
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def add_new_model(inp, cur): |
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cur.append(inp) |
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return cur,gr.update(choices=[z for z in cur]) |
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def load_new(models=models): |
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return models |
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def clear_fn(): |
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return None,None,None,None,None,None |
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rand_val=random.randint(1,1111111111111111) |
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def check_rand(inp,val): |
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if inp==True: |
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return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=random.randint(1,1111111111111111)) |
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else: |
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return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=int(val)) |
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with gr.Blocks() as app: |
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new_models=gr.State([]) |
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gr.HTML("""<center><h1 style='font-size:xx-large;'>Chatbot Model Compare</h1>""") |
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with gr.Row(): |
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chat_a = gr.Chatbot(height=500) |
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chat_b = gr.Chatbot(height=500) |
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with gr.Row(): |
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chat_c = gr.Chatbot(height=500) |
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chat_d = gr.Chatbot(height=500) |
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with gr.Group(): |
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with gr.Row(): |
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with gr.Column(scale=3): |
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inp = gr.Textbox(label="Prompt") |
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sys_inp = gr.Textbox(label="System Prompt (optional)") |
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with gr.Row(): |
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with gr.Column(scale=2): |
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btn = gr.Button("Chat") |
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with gr.Column(scale=1): |
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with gr.Group(): |
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stop_btn=gr.Button("Stop") |
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clear_btn=gr.Button("Clear") |
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client_choice=gr.Dropdown(label="Models",type='index', choices=[c for c in models],max_choices=4,multiselect=True,interactive=True) |
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add_model=gr.Textbox(label="New Model") |
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add_btn=gr.Button("Add Model") |
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with gr.Column(scale=1): |
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with gr.Group(): |
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rand = gr.Checkbox(label="Random Seed", value=True) |
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seed=gr.Slider(label="Seed", minimum=1, maximum=1111111111111111,step=1, value=rand_val) |
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tokens = gr.Slider(label="Max new tokens",value=3840,minimum=0,maximum=8000,step=64,interactive=True, visible=True,info="The maximum number of tokens") |
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temp=gr.Slider(label="Temperature",step=0.01, minimum=0.01, maximum=1.0, value=0.9) |
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top_p=gr.Slider(label="Top-P",step=0.01, minimum=0.01, maximum=1.0, value=0.9) |
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rep_p=gr.Slider(label="Repetition Penalty",step=0.1, minimum=0.1, maximum=2.0, value=1.0) |
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hid1=gr.Number(value=1,visible=False) |
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hid2=gr.Number(value=2,visible=False) |
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hid3=gr.Number(value=3,visible=False) |
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hid4=gr.Number(value=4,visible=False) |
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app.load(load_new,None,new_models) |
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add_btn.click(add_new_model,[add_model,new_models],[new_models,client_choice]) |
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client_choice.change(load_models,[client_choice,new_models],[chat_a,chat_b,chat_c,chat_d]) |
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go1=btn.click(check_rand,[rand,seed],seed).then(chat_inf_a,[sys_inp,inp,chat_b,client_choice,seed,temp,tokens,top_p,rep_p,hid1],chat_a) |
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go2=btn.click(check_rand,[rand,seed],seed).then(chat_inf_b,[sys_inp,inp,chat_b,client_choice,seed,temp,tokens,top_p,rep_p,hid2],chat_b) |
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go3=btn.click(check_rand,[rand,seed],seed).then(chat_inf_c,[sys_inp,inp,chat_b,client_choice,seed,temp,tokens,top_p,rep_p,hid3],chat_c) |
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go4=btn.click(check_rand,[rand,seed],seed).then(chat_inf_d,[sys_inp,inp,chat_b,client_choice,seed,temp,tokens,top_p,rep_p,hid4],chat_d) |
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stop_btn.click(None,None,None,cancels=[go1,go2,go3,go4]) |
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clear_btn.click(clear_fn,None,[inp,sys_inp,chat_a,chat_b,chat_c,chat_d]) |
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app.queue(default_concurrency_limit=10).launch() |
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