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"""
🤖 Fagun Browser Automation Testing Agent - Agent Settings Tab
==============================================================
UI components for agent configuration and settings.
Author: Mejbaur Bahar Fagun
Role: Software Engineer in Test
LinkedIn: https://www.linkedin.com/in/mejbaur/
"""
import json
import os
import gradio as gr
from gradio.components import Component
from typing import Any, Dict, Optional
from src.webui.webui_manager import WebuiManager
from src.utils import config
import logging
from functools import partial
logger = logging.getLogger(__name__)
def update_model_dropdown(llm_provider):
"""
Update the model name dropdown with predefined models for the selected provider.
"""
# Use predefined models for the selected provider
if llm_provider in config.model_names:
return gr.Dropdown(choices=config.model_names[llm_provider], value=config.model_names[llm_provider][0],
interactive=True)
else:
return gr.Dropdown(choices=[], value="", interactive=True, allow_custom_value=True)
def create_agent_settings_tab(webui_manager: WebuiManager):
"""
Creates an agent settings tab.
"""
input_components = set(webui_manager.get_components())
tab_components = {}
with gr.Group():
with gr.Row():
llm_provider = gr.Dropdown(
choices=[provider for provider, model in config.model_names.items()],
label="🤖 AI Service Provider",
value=os.getenv("DEFAULT_LLM", "openai"),
info="Choose which AI company's service to use (OpenAI, Google, etc.)",
interactive=True
)
llm_model_name = gr.Dropdown(
label="🧠 AI Model",
choices=config.model_names[os.getenv("DEFAULT_LLM", "openai")],
value=config.model_names[os.getenv("DEFAULT_LLM", "openai")][0],
interactive=True,
allow_custom_value=True,
info="Pick the specific AI model to use (like GPT-4, Claude, etc.)"
)
with gr.Row():
llm_temperature = gr.Slider(
minimum=0.0,
maximum=2.0,
value=0.6,
step=0.1,
label="🎲 AI Creativity Level",
info="Lower = More predictable, Higher = More creative responses",
interactive=True
)
use_vision = gr.Checkbox(
label="👁️ Enable Visual Analysis",
value=True,
info="Let AI see and analyze screenshots of websites",
interactive=True
)
ollama_num_ctx = gr.Slider(
minimum=2 ** 8,
maximum=2 ** 16,
value=16000,
step=1,
label="📝 Memory Size (Ollama only)",
info="How much information AI can remember at once (higher = slower but smarter)",
visible=False,
interactive=True
)
with gr.Row():
llm_base_url = gr.Textbox(
label="🌐 Custom API URL",
value="",
info="Only needed if using a custom AI service (leave blank for standard services)"
)
llm_api_key = gr.Textbox(
label="🔑 Your API Key",
type="password",
value="",
info="Get this from your AI service provider (OpenAI, Google, etc.)"
)
with gr.Group():
with gr.Row():
planner_llm_provider = gr.Dropdown(
choices=[provider for provider, model in config.model_names.items()],
label="🎯 Planning AI Service",
info="Optional: Different AI for planning complex tasks",
value=None,
interactive=True
)
planner_llm_model_name = gr.Dropdown(
label="🧠 Planning AI Model",
interactive=True,
allow_custom_value=True,
info="AI model for planning and organizing tasks"
)
with gr.Row():
planner_llm_temperature = gr.Slider(
minimum=0.0,
maximum=2.0,
value=0.6,
step=0.1,
label="🎲 Planning AI Creativity",
info="How creative the planning AI should be",
interactive=True
)
planner_use_vision = gr.Checkbox(
label="👁️ Enable Visual Planning",
value=False,
info="Let planning AI see website screenshots",
interactive=True
)
planner_ollama_num_ctx = gr.Slider(
minimum=2 ** 8,
maximum=2 ** 16,
value=16000,
step=1,
label="📝 Planning Memory Size",
info="How much information planning AI can remember (Ollama only)",
visible=False,
interactive=True
)
with gr.Row():
planner_llm_base_url = gr.Textbox(
label="🌐 Planning API URL",
value="",
info="Custom URL for planning AI service (leave blank for standard)"
)
planner_llm_api_key = gr.Textbox(
label="🔑 Planning API Key",
type="password",
value="",
info="API key for planning AI service"
)
with gr.Row():
max_steps = gr.Slider(
minimum=1,
maximum=1000,
value=100,
step=1,
label="🔄 Maximum Testing Steps",
info="How many steps AI can take to complete a task",
interactive=True
)
max_actions = gr.Slider(
minimum=1,
maximum=100,
value=10,
step=1,
label="⚡ Actions Per Step",
info="How many actions AI can do in each step",
interactive=True
)
with gr.Row():
max_input_tokens = gr.Number(
label="📄 Maximum Text Input",
value=128000,
precision=0,
interactive=True
)
tool_calling_method = gr.Dropdown(
label="🛠️ AI Communication Method",
value="auto",
interactive=True,
allow_custom_value=True,
choices=['function_calling', 'json_mode', 'raw', 'auto', 'tools', "None"],
visible=True
)
tab_components.update(dict(
llm_provider=llm_provider,
llm_model_name=llm_model_name,
llm_temperature=llm_temperature,
use_vision=use_vision,
ollama_num_ctx=ollama_num_ctx,
llm_base_url=llm_base_url,
llm_api_key=llm_api_key,
planner_llm_provider=planner_llm_provider,
planner_llm_model_name=planner_llm_model_name,
planner_llm_temperature=planner_llm_temperature,
planner_use_vision=planner_use_vision,
planner_ollama_num_ctx=planner_ollama_num_ctx,
planner_llm_base_url=planner_llm_base_url,
planner_llm_api_key=planner_llm_api_key,
max_steps=max_steps,
max_actions=max_actions,
max_input_tokens=max_input_tokens,
tool_calling_method=tool_calling_method,
))
webui_manager.add_components("agent_settings", tab_components)
llm_provider.change(
fn=lambda x: gr.update(visible=x == "ollama"),
inputs=llm_provider,
outputs=ollama_num_ctx
)
llm_provider.change(
lambda provider: update_model_dropdown(provider),
inputs=[llm_provider],
outputs=[llm_model_name]
)
planner_llm_provider.change(
fn=lambda x: gr.update(visible=x == "ollama"),
inputs=[planner_llm_provider],
outputs=[planner_ollama_num_ctx]
)
planner_llm_provider.change(
lambda provider: update_model_dropdown(provider),
inputs=[planner_llm_provider],
outputs=[planner_llm_model_name]
)
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