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import os
import subprocess
import random
from huggingface_hub import InferenceClient
import gradio as gr
from safe_search import safe_search
from i_search import google
from i_search import i_search as i_s
from agent import ( run_agent, create_interface, format_prompt_var, generate, MAX_HISTORY, client, VERBOSE, date_time_str, )
from utils import parse_action, parse_file_content, read_python_module_structure
from datetime import datetime
now = datetime.now()
date_time_str = now.strftime("%Y-%m-%d %H:%M:%S")
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
VERBOSE = True
MAX_HISTORY = 100
def format_prompt_var(message, history):
prompt = " "
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/usr]\n{bot_response}\n"
prompt += f"[INST] {message} [/usr]\n"
return prompt
def run_gpt(prompt_template, stop_tokens, max_tokens, purpose, **prompt_kwargs):
seed = random.randint(1, 1111111111111111)
print(seed)
generate_kwargs = dict(
temperature=1.0,
max_new_tokens=2096,
top_p=0.99,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
content = PREFIX.format(
date_time_str=date_time_str,
purpose=purpose,
safe_search=safe_search,
) + prompt_template.format(**prompt_kwargs)
if VERBOSE:
print(LOG_PROMPT.format(content))
stream = client.text_generation(content, **generate_kwargs, stream=True, details=True, return_full_text=False)
resp = ""
for response in stream:
resp += response.token.text
if VERBOSE:
print(LOG_RESPONSE.format(resp))
return resp
def compress_history(purpose, task, history, directory):
resp = run_gpt(
COMPRESS_HISTORY_PROMPT,
stop_tokens=["observation:", "task:", "action:", "thought:"],
max_tokens=512,
purpose=purpose,
task=task,
history=history,
)
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)
print(response)
history += "observation: search result is: {}\n".format(response)
else:
history += "observation: I need to provide a valid URL to 'action: SEARCH action_input=https://URL'\n"
except Exception as e:
history += "{}\n".format(e) # Fixing this line to include the exception message
if "COMPLETE" in action_name or "COMPLETE" in action_input:
task = "END"
return action_name, action_input, history, task
def call_set_task(purpose, task, history, directory, action_input):
task = run_gpt(
TASK_PROMPT,
stop_tokens=[],
max_tokens=64,
purpose=purpose,
task=task,
history=history,
).strip("\n")
history += "observation: task has been updated to: {}\n".format(task)
return "MAIN", None, history, task
def end_fn(purpose, task, history, directory, action_input):
task = "END"
return "COMPLETE", "COMPLETE", history, task
NAME_TO_FUNC = {
"MAIN": call_main,
"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"
return action_name, "COMPLETE", history, task
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 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):
task = None
directory = "./"
if history:
history = str(history).strip("[]")
if not history:
history = ""
action_name = "UPDATE-TASK" if task is None else "MAIN"
action_input = None
while True:
print("")
print("")
print("---")
print("purpose:", purpose)
print("task:", task)
print("---")
print(history)
print("---")
action_name, action_input, history, task = run_action(
purpose,
task,
history,
directory,
action_name,
action_input,
)
yield (history)
if task == "END":
return (history)
iface = gr.Interface(fn=run, inputs=["text", "text"], outputs="text", title="Interactive AI Assistant", description="Enter your purpose and history to interact with the AI assistant.")
# Launch the Gradio interface
iface.launch(share=True)
if __name__ == "__main__":
main("Sample Purpose", "Sample History") |