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import yaml
import os
# Ultimate Gradio compatibility fix - dynamically filter kwargs based on component signatures
import gradio as gr
from functools import wraps
import inspect
from huggingface_hub import login
from dotenv import load_dotenv
import os
load_dotenv()
def patch_gradio_component(component_class):
"""Patch a Gradio component to accept only supported kwargs"""
original_init = component_class.__init__
@wraps(original_init)
def patched_init(self, *args, **kwargs):
try:
sig = inspect.signature(original_init)
# Filter kwargs to only include parameters the original __init__ accepts
valid_params = set(sig.parameters.keys())
filtered_kwargs = {k: v for k, v in kwargs.items() if k in valid_params or
any(p.kind == inspect.Parameter.VAR_KEYWORD for p in sig.parameters.values())}
return original_init(self, *args, **filtered_kwargs)
except Exception as e:
# Fallback to original call
try:
return original_init(self, *args, **kwargs)
except TypeError:
# Last resort - call with no kwargs
return original_init(self, *args)
component_class.__init__ = patched_init
return component_class
# Patch all Gradio components
for name in dir(gr):
try:
obj = getattr(gr, name)
if inspect.isclass(obj) and hasattr(obj, '__init__'):
patch_gradio_component(obj)
except:
pass
from smolagents import GradioUI, CodeAgent, InferenceClientModel
# Get current directory path
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
from tools.web_search import DuckDuckGoSearchTool as WebSearch
from tools.suggest_menu import SimpleTool as SuggestMenu
from tools.final_answer import FinalAnswerTool as FinalAnswer
# Authenticate with Hugging Face using HF_TOKEN from environment
if hf_token := os.getenv('HF_TOKEN'):
login(hf_token)
model = InferenceClientModel(
model_id='Qwen/Qwen3-Next-80B-A3B-Thinking',
api_key=os.getenv('HF_TOKEN'),
)
web_search = WebSearch()
suggest_menu = SuggestMenu()
final_answer = FinalAnswer()
with open(os.path.join(CURRENT_DIR, "prompts.yaml"), 'r') as stream:
prompt_templates = yaml.safe_load(stream)
agent = CodeAgent(
model=model,
tools=[web_search, suggest_menu],
managed_agents=[],
max_steps=20,
verbosity_level=1,
planning_interval=None,
name=None,
description=None,
executor_type='local',
executor_kwargs={},
max_print_outputs_length=None,
prompt_templates=prompt_templates
)
if __name__ == "__main__":
GradioUI(agent).launch()
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