Create app.py

app.py

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+from huggingface_hub import InferenceClient
+#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 generate(prompt,history,mod=2,tok=None,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 == "ASSISTANT":
+        system_prompt = prompts.ASSISTANT
+        formatted_prompt = format_prompt(f'USER:{prompt}', history, system_prompt)
+    elif role == "CREATE_FILE":
+        system_prompt = prompts.CREATE_FILE.replace("**FILENAME**",str(data[4]))
+        formatted_prompt = format_prompt(prompt, history, system_prompt)
+    elif role == "MANAGER":
+        system_prompt = prompts.MANAGER.replace("**TIMELINE**",data[4]).replace("**HISTORY**",str(history))
+        formatted_prompt = format_prompt(prompt, history, system_prompt)
+    elif role == "SEARCH":
+        system_prompt = prompts.SEARCH.replace("**DATA**",data)
+        formatted_prompt = format_prompt(f'USER:{prompt}', history, system_prompt)
+    else: system_prompt = "";formatted_prompt = format_prompt(f'USER:{prompt}', history, 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=="ASSISTANT" or role=="WEBDEVELOPER" or 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
+        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:
+        #access_token=""
+        client = hf_api(access_token)
+        # Create a new Space
+        response = client.create_repo(repo_name)
+        space_info = response.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=space_id, 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:
+        return [{'role':'assistant','content': 'There was an Error: '+e}]
+
+        
+def agent(prompt,history,mod,data="None"):
+    in_data=[None,None,None,None,None,]
+    in_data[0]=data
+    prompt=prompt['text']
+    fn=""
+    com=""
+    go=True
+    while go == True:
+        seed = random.randint(1,9999999999999)
+        c=0
+        history = [history[-4:]]
+        if len(str(history)) > MAX_DATA*4:
+            history = [history[-2:]]
+        role="MANAGER"
+        outp=generate(prompt,history,mod,128,seed,role,in_data)
+        outpp=list(outp)[0]
+        outp0 = re.sub('[^a-zA-Z0-9\s.,?!%()]', '', outpp)
+        history=history+[{'role':'assistant','content':str(outp0)}]
+        yield history
+        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].split('<|im_end|>')[0]
+                    #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')
+                    out_w =generate(com,history,mod=mod,tok=None,seed=seed,role="CREATE_FILE")
+                    build_space(out_w[0],out_w[1])
+                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')
+
+            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,file_name,file_json],chatbot)
+    sub_p = prompt.submit(agent, [prompt,chatbot,mod_c,file_name,file_json],chatbot)
+    stop_b.click(None,None,None, cancels=[sub_b,sub_p])
+ux.queue(default_concurrency_limit=20).launch(max_threads=40)
+
+
+
+
+
+
+