Update app.py

app.py

@@ -1,3 +1,4 @@
+```python
 import os
 import subprocess
 import random
@@ -28,14 +29,11 @@ client = InferenceClient(
     "mistralai/Mixtral-8x7B-Instruct-v0.1",
 )
 
-
 ############################################
 
-
 VERBOSE = True
 MAX_HISTORY = 125
 
-
 def format_prompt(message, history):
   prompt = "<s>"
   for user_prompt, bot_response in history:
@@ -44,8 +42,6 @@ def format_prompt(message, history):
   prompt += f"[INST] {message} [/INST]"
   return prompt
 
-
-
 def run_gpt(
     prompt_template,
     stop_tokens,
@@ -53,8 +49,8 @@ def run_gpt(
     purpose,
     **prompt_kwargs,
 ):
-    seed = random.randint(1,1111111111111111)
-    print (seed)
+    seed = random.randint(1, 1111111111111111)
+    print(seed)
     generate_kwargs = dict(
         temperature=1.0,
         max_new_tokens=2096,
@@ -64,7 +60,6 @@ def run_gpt(
         seed=seed,
     )
 
-    
     content = PREFIX.format(
         date_time_str=date_time_str,
         purpose=purpose,
@@ -72,8 +67,7 @@ def run_gpt(
     ) + prompt_template.format(**prompt_kwargs)
     if VERBOSE:
         print(LOG_PROMPT.format(content))
-    
-    
+
     #formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
     #formatted_prompt = format_prompt(f'{content}', history)
 
@@ -86,7 +80,6 @@ def run_gpt(
         print(LOG_RESPONSE.format(resp))
     return resp
 
-
 def compress_history(purpose, task, history, directory):
     resp = run_gpt(
         COMPRESS_HISTORY_PROMPT,
@@ -98,17 +91,16 @@ def compress_history(purpose, task, history, directory):
     )
     history = "observation: {}\n".format(resp)
     return history
-    
+
 def call_search(purpose, task, history, directory, action_input):
     print("CALLING SEARCH")
     try:
-        
         if "http" in action_input:
             if "<" in action_input:
                 action_input = action_input.strip("<")
             if ">" in action_input:
                 action_input = action_input.strip(">")
-            
+
             response = i_s(action_input)
             #response = google(search_return)
             print(response)
@@ -135,11 +127,9 @@ def call_main(purpose, task, history, directory, action_input):
         if line.startswith("thought: "):
             history += "{}\n".format(line)
         elif line.startswith("action: "):
-            
             action_name, action_input = parse_action(line)
-            print (f'ACTION_NAME :: {action_name}')
-            print (f'ACTION_INPUT :: {action_input}')
-            
+            print(f'ACTION_NAME :: {action_name}')
+            print(f'ACTION_INPUT :: {action_input}')
             history += "{}\n".format(line)
             if "COMPLETE" in action_name or "COMPLETE" in action_input:
                 task = "END"
@@ -149,12 +139,10 @@ def call_main(purpose, task, history, directory, action_input):
         else:
             history += "{}\n".format(line)
             #history += "observation: the following command did not produce any useful output: '{}', I need to check the commands syntax, or use a different command\n".format(line)
-            
             #return action_name, action_input, history, task
             #assert False, "unknown action: {}".format(line)
     return "MAIN", None, history, task
 
-
 def call_set_task(purpose, task, history, directory, action_input):
     task = run_gpt(
         TASK_PROMPT,
@@ -176,46 +164,41 @@ NAME_TO_FUNC = {
     "UPDATE-TASK": call_set_task,
     "SEARCH": call_search,
     "COMPLETE": end_fn,
-
 }
 
 def run_action(purpose, task, history, directory, action_name, action_input):
     print(f'action_name::{action_name}')
     try:
         if "RESPONSE" in action_name or "COMPLETE" in action_name:
-            action_name="COMPLETE"
-            task="END"
+            action_name = "COMPLETE"
+            task = "END"
             return action_name, "COMPLETE", history, task
-    
+
         # compress the history when it is long
         if len(history.split("\n")) > MAX_HISTORY:
             if VERBOSE:
                 print("COMPRESSING HISTORY")
             history = compress_history(purpose, task, history, directory)
         if not action_name in NAME_TO_FUNC:
-            action_name="MAIN"
-        if action_name == "" or action_name == None:
-            action_name="MAIN"
+            action_name = "MAIN"
+        if action_name == "" or action_name is None:
+            action_name = "MAIN"
         assert action_name in NAME_TO_FUNC
-    
+
         print("RUN: ", action_name, action_input)
         return NAME_TO_FUNC[action_name](purpose, task, history, directory, action_input)
     except Exception as e:
         history += "observation: the previous command did not produce any useful output, I need to check the commands syntax, or use a different command\n"
-
         return "MAIN", None, history, task
 
-def run(purpose,history):
-    
-    #print(purpose)
-    #print(hist)
-    task=None
-    directory="./"
+def run(purpose, history):
+    task = None
+    directory = "./"
     if history:
-        history=str(history).strip("[]")
+        history = str(history).strip("[]")
     if not history:
         history = ""
-    
+
     action_name = "UPDATE-TASK" if task is None else "MAIN"
     action_input = None
     while True:
@@ -242,8 +225,6 @@ def run(purpose,history):
             return (history)
             #return ("", [(purpose,history)])
 
-
-
 ################################################
 
 def format_prompt(message, history):
@@ -253,7 +234,8 @@ def format_prompt(message, history):
     prompt += f" {bot_response}</s> "
   prompt += f"[INST] {message} [/INST]"
   return prompt
-agents =[
+
+agents = [
     "WEB_DEV",
     "AI_SYSTEM_PROMPT",
     "PYTHON_CODE_DEV"
@@ -262,16 +244,16 @@ agents =[
 def generate(
         prompt, history, agent_name=agents[0], sys_prompt="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.7,
 ):
-    seed = random.randint(1,1111111111111111)
+    seed = random.randint(1, 1111111111111111)
 
-    agent=prompts.WEB_DEV
+    agent = prompts.WEB_DEV
     if agent_name == "WEB_DEV":
         agent = prompts.WEB_DEV
     if agent_name == "AI_SYSTEM_PROMPT":
         agent = prompts.AI_SYSTEM_PROMPT
     if agent_name == "PYTHON_CODE_DEV":
-        agent = prompts.PYTHON_CODE_DEV        
-    system_prompt=agent
+        agent = prompts.PYTHON_CODE_DEV
+    system_prompt = agent
     temperature = float(temperature)
     if temperature < 1e-2:
         temperature = 1e-2
@@ -295,14 +277,13 @@ def generate(
         yield output
     return output
 
-
-additional_inputs=[
+additional_inputs = [
     gr.Dropdown(
         label="Agents",
         choices=[s for s in agents],
         value=agents[0],
         interactive=True,
-        ),
+    ),
     gr.Textbox(
         label="System Prompt",
         max_lines=1,
@@ -320,9 +301,9 @@ additional_inputs=[
 
     gr.Slider(
         label="Max new tokens",
-        value=1048*10,
+        value=1048 * 10,
         minimum=0,
-        maximum=1048*10,
+        maximum=1048 * 10,
         step=64,
         interactive=True,
         info="The maximum numbers of new tokens",
@@ -345,19 +326,18 @@ additional_inputs=[
         interactive=True,
         info="Penalize repeated tokens",
     ),
-
-
 ]
 
+examples = [
+    ["Based on previous interactions, generate an interactive preview of the user's requested application.", None, None, None, None, None, ],
+    ["Utilize the relevant code snippets and components from previous interactions.", None, None, None, None, None, ],
+    ["Assemble a working demo that showcases the core functionality of the application.", None, None, None, None, None, ],
+    ["Present the demo in an interactive environment within the Gradio interface.", None, None, None, None, None, ],
+    ["Allow the user to explore and interact with the demo to test its features.", None, None, None, None, None, ],
+    ["Gather feedback from the user about the demo and potential improvements.", None, None, None, None, None, ],
+    ["If the user approves of the app's running state you should provide a bash script that will automate all aspects of a local run and also a docker image for ease-of-launch in addition to the huggingface-ready app.py with all functions and gui and the requirements.txt file comprised of all required libraries and packages the application is dependent on, avoiding openai api at all points as we only use huggingface transformers, models, agents, libraries, api.", None, None, None, None, None, ],
+]
 
-examples=[["Based on previous interactions, generate an interactive preview of the user's requested application.", None, None, None, None, None, ],
-          ["Utilize the relevant code snippets and components from previous interactions.", None, None, None, None, None, ],
-          ["Assemble a working demo that showcases the core functionality of the application.", None, None, None, None, None, ],
-          ["Present the demo in an interactive environment within the Gradio interface.", None, None, None, None, None,],
-          ["Allow the user to explore and interact with the demo to test its features.", None, None, None, None, None,],
-          ["Gather feedback from the user about the demo and potential improvements.", None, None, None, None, None,],
-          ["If the user approves of the app's running state you should provide a bash script that will automate all aspects of a local run and also a docker image for ease-of-launch in addition to the huggingface-ready app.py with all functions and gui and the requirements.txt file comprised of all required libraries and packages the application is dependent on, avoiding openai api at all points as we only use huggingface transformers, models, agents, libraries, api.", None, None, None, None, None,],
-         ]
 def create_interface():
     with gr.Blocks() as iface:
         gr.ChatInterface(
@@ -366,4 +346,31 @@ def create_interface():
             examples=examples,
             additional_inputs=additional_inputs,
         )
-    return iface
+    return iface
+
+def chat_interface(prompt, history, agent_name, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty):
+    return generate(prompt, history, agent_name, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty)
+
+iface = gr.Blocks()
+
+with iface:
+    gr.Markdown("# Fragmixt\nAgents With Agents,\nSurf With a Purpose")
+    
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.Button("Clear")
+
+    agent_dropdown = gr.Dropdown(label="Agents", choices=agents, value=agents[0])
+    sys_prompt = gr.Textbox(label="System Prompt", max_lines=1)
+    temperature = gr.Slider(label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05)
+    max_new_tokens = gr.Slider(label="Max new tokens", value=1048 * 10, minimum=0, maximum=1048 * 10, step=64)
+    top_p = gr.Slider(label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05)
+    repetition_penalty = gr.Slider(label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05)
+
+    msg.submit(chat_interface, [msg, chatbot, agent_dropdown, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty], [chatbot, msg])
+    clear.click(lambda: None, None, chatbot, queue=False)
+
+    gr.Examples(examples, [msg, agent_dropdown, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty])
+
+if __name__ == "__main__":
+    iface.launch(concurrency_limit=20)