app.py

from huggingface_hub import InferenceClient, HfApi
#from html2image import Html2Image
import gradio as gr
#import markdown
import requests
import random
import prompts
#import im_prompts
import uuid
import json
#import PIL
#import bs4
import re
import os
loc_folder="chat_history"
loc_file="chat_json"

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, mod, system):
    eos=f"{clients[int(mod)]['schema']['eos']}\n"
    bos=f"{clients[int(mod)]['schema']['bos']}\n"
    prompt=""
    prompt+=bos
    prompt+=system
    prompt+=eos
    prompt+=bos
    prompt += f"[INST] {message} [/INST]"
    prompt+=eos
    prompt+=bos
    return prompt
def generate(prompt,history,mod=2,tok=4000,seed=1,role="ASSISTANT",data=None):
    #print("#####",history,"######")
    gen_images=False
    client=InferenceClient(clients[int(mod)]['name'])
    client_tok=clients[int(mod)]['max_tokens']
    good_seed=[947385642222,7482965345792,8584806344673]
    if not history:
        history=[{'role':'user','content':prompt}]
    if not os.path.isdir(loc_folder):os.mkdir(loc_folder)

    if os.path.isfile(f'{loc_folder}/{loc_file}.json'):
        with open(f'{loc_folder}/{loc_file}.json','r') as word_dict:
            lod=json.loads(word_dict.read())
        word_dict.close()    
    else:
        lod=[]
    if role == "MANAGER":
        system_prompt = prompts.MANAGER.replace("**TIMELINE**",data[4]).replace("**HISTORY**",str(history))
        formatted_prompt = format_prompt(prompt, mod, system_prompt)
    elif role == "PATHMAKER":
        system_prompt = prompts.PATH_MAKER.replace("**CURRENT_OR_NONE**",str(data[4])).replace("**PROMPT**",json.dumps(data[0],indent=4)).replace("**HISTORY**",str(history))
        formatted_prompt = format_prompt(prompt, mod, system_prompt)
    elif role == "CREATE_FILE":
        system_prompt = prompts.CREATE_FILE.replace("**TIMELINE**",data[4]).replace("**FILENAME**",str(data[1]))
        formatted_prompt = format_prompt(prompt, mod, system_prompt)
    elif role == "SEARCH":
        system_prompt = prompts.SEARCH.replace("**DATA**",data)
        formatted_prompt = format_prompt(f'USER:{prompt}', mod, system_prompt)
    else: system_prompt = "";formatted_prompt = format_prompt(f'USER:{prompt}', mod, system_prompt)
    
    if tok==None:tok=client_tok-len(formatted_prompt)+10
    print("tok",tok)
    generate_kwargs = dict(
        temperature=0.9,
        max_new_tokens=tok, #total tokens - input tokens
        top_p=0.99,
        repetition_penalty=1.0,
        do_sample=True,
        seed=seed,
    )
    output = ""
    if role=="MANAGER":
        print("Running Manager")
        stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
        for response in stream:
            output += response.token.text
        yield output
        yield history
        yield prompt

    elif role=="PATHMAKER":
        print("Runnning ", role)
        stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
        #prompt=f"We just completed role:{role}, now choose the next tool to complete the task:{prompt}, or COMPLETE"
        for response in stream:
            output += response.token.text
        print(output)
        yield output
        yield history
        yield prompt
        
    elif role=="CREATE_FILE":
        print("Running Create File")
        stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
        for response in stream:
            output += response.token.text
        #print(file_content)
        print(output)
        yield 'test1'
        yield data[1]
        yield output
        
        #yield output
        #yield history
        #yield prompt
    #with open(f'{loc_folder}/{loc_file}.json','w') as jobj:
    #    lod.append({'prompt':prompt,'response':output,'image':im_box,'model':clients[1]['name'],'seed':seed}),
    #    jobj.write(json.dumps(lod,indent=4))
    #jobj.close()    
    #chat_im_out=chat_img(output)

'''def gen_im(prompt,seed):
    print('generating image')
    image_out = im_client.text_to_image(prompt=prompt['text'],height=128,width=128,num_inference_steps=10,seed=seed)
    #print(type(image_out))
    output=f'images/{uuid.uuid4()}.png'
    image_out.save(output)
    print('Done: ',output)
    return [{'role':'assistant','content': {'path':output}}]'''

def build_space(repo_name,file_name,file_content,access_token=""):
    try:
        repo_path="broadfield/"+repo_name
        if not access_token:access_token=os.environ['HF_TOKEN']

        api=HfApi(endpoint="https://huggingface.co", token=access_token)
        repo_url = api.create_repo(
                repo_id=repo_path,
                repo_type="space",
                space_sdk="gradio",
                exist_ok=True,
                private=False,
            )
        # Create a new Space
        #response = api.create_repo(repo_path)
        #space_info = repo_url.json()
        #print(space_info)
        #space_id = space_info["name"]
        #print(f"Created Space with ID: {space_id}")
        local_file_path=str(uuid.uuid4())
        with open(local_file_path, 'w') as f:
            f.write(str(file_content))
        f.close()
        # Upload a local file to the Space
        commit_message = "Adding file test: "+str(uuid.uuid4())
        client.upload_file(local_file_path, repo_id=repo_path, path=file_name, commit_message=commit_message)
        print("File uploaded successfully.")
        # Commit changes
        commit_message += "\nInitial commit to the repository."+ local_file_path
        client.commit_repo(space_id, message=commit_message)
        return [{'role':'assistant','content': commit_message+'\nCommit Success' }]
    except Exception as e:
        print("ERROR ",e)
        return [{'role':'assistant','content': 'There was an Error: ' + str(e)}]

        
def agent(prompt_in,history,mod=2):
    print(prompt_in)
    print('mod ',mod)
    in_data=[None,None,None,None,None,]
    #in_data[0]=prompt_in['text']
    in_data[0]=prompt_in
    prompt=prompt_in
    fn=""
    com=""
    go=True
    MAX_DATA=int(clients[int(mod)]['max_tokens'])*2
    while go == True:
        seed = random.randint(1,9999999999999)
        c=0
        history = [history[-4:]]
        if len(str(history)) > MAX_DATA*4:
            history = [history[-2:]]
        role="PATHMAKER"
        outph= list(generate(prompt,history,mod,2400,seed,role,in_data))[0]
        in_data[4]=outph
        print(outph)
        history=history+[{'role':'assistant','content':str(outph)}]
        yield [{'role':'assistant','content':str(outph)}]
        role="MANAGER"
        outp=generate(prompt,history,mod,128,seed,role,in_data)
        outp0=list(outp)[0].split('<|im_end}>')[0]
        #outp0 = re.sub('[^a-zA-Z0-9\s.,?!%()]', '', outpp)
        history=history+[{'role':'assistant','content':str(outp0)}]
        yield [{'role':'assistant','content':str(outp0)}]
        for line in outp0.split("\n"):
            if "action:" in line:
                try:
                    com_line = line.split('action:')[1]
                    fn = com_line.split('action_input=')[0]
                    com = com_line.split('action_input=')[1]
                    #com = com_line.split('action_input=')[1].replace('<|im_end|>','').replace("}","").replace("]","").replace("'","")
                    print(com)
                except Exception as e:
                    pass
                    fn="NONE"
                if 'CREATE_FILE' in fn:
                    print('CREATE_FILE called')
                    in_data[1]=com
                    out_o =generate(prompt,history,mod=mod,tok=10000,seed=seed,role="CREATE_FILE",data=in_data)
                    out_w=list(out_o)
                    build_space(out_w[0],out_w[1],out_w[2])
                elif 'IMAGE' in fn:
                    print('IMAGE called')
                    #out_im=gen_im(prompt,seed)
                    #yield [{'role':'assistant','content': out_im}]
                elif 'SEARCH' in fn:
                    print('SEARCH called')
                elif 'COMPLETE' in fn:
                    print('COMPLETE')
                    go=False
                    break
                elif 'NONE' in fn:
                    print('ERROR ACTION NOT FOUND')
                    history+=[{'role':'system','content':f'observation:The last thing we attempted resulted in an error, check formatting on the tool call'}]

                else:pass;seed = random.randint(1,9999999999999)
with gr.Blocks() as ux:
    with gr.Row():
        with gr.Column():
            gr.HTML("""<center><div style='font-size:xx-large;font-weight:900;'>Chatbo</div>""")
            chatbot=gr.Chatbot(type='messages',show_label=False, show_share_button=False, show_copy_button=True, layout="panel")
            prompt=gr.MultimodalTextbox(label="Prompt",file_count="multiple", file_types=["image"])
            mod_c=gr.Dropdown(choices=[n['name'] for n in clients],value='Qwen/Qwen2.5-Coder-32B-Instruct',type='index')
            #chat_ux=gr.ChatInterface(fn=agent,chatbot=chatbot,additional_inputs=[mod_c]).load()
            #chat_ux.additional_inputs=[mod_c]
            #chat_ux.load()
            with gr.Row():
                submit_b = gr.Button()
                stop_b = gr.Button("Stop")
                clear = gr.ClearButton([chatbot,prompt])
            with gr.Row(visible=False):
                stt=gr.Textbox()
        with gr.Column():
            file_name=gr.Textbox(label="File Name")
            file_btn=gr.Button("Load Files")
            file_json=gr.JSON()
    sub_b = submit_b.click(agent, [prompt,chatbot,mod_c],chatbot)
    sub_p = prompt.submit(agent, [prompt,chatbot,mod_c],chatbot)
    stop_b.click(None,None,None, cancels=[sub_b,sub_p])
ux.queue(default_concurrency_limit=20).launch(max_threads=40)