import json
import mimetypes
import os
import re
import shutil
import threading
from typing import Optional
import gradio as gr
from dotenv import load_dotenv
from huggingface_hub import login
from smolagents import (
CodeAgent,
HfApiModel,
Tool,
GoogleSearchTool
)
from smolagents.agent_types import (
AgentAudio,
AgentImage,
AgentText,
handle_agent_output_types,
)
from smolagents.gradio_ui import stream_to_gradio
from scripts.text_inspector_tool import TextInspectorTool
from scripts.text_web_browser import (
ArchiveSearchTool,
FinderTool,
FindNextTool,
PageDownTool,
PageUpTool,
SimpleTextBrowser,
VisitTool,
)
from scripts.visual_qa import visualizer
web_search = GoogleSearchTool(provider="serper")
print(web_search(query="Donald Trump news"))
# quit()
AUTHORIZED_IMPORTS = [
"requests",
"zipfile",
"pandas",
"numpy",
"sympy",
"json",
"bs4",
"pubchempy",
"xml",
"yahoo_finance",
"Bio",
"sklearn",
"scipy",
"pydub",
"PIL",
"chess",
"PyPDF2",
"pptx",
"torch",
"datetime",
"fractions",
"csv",
]
load_dotenv(override=True)
login(os.getenv("HF_TOKEN"))
append_answer_lock = threading.Lock()
custom_role_conversions = {"tool-call": "assistant", "tool-response": "user"}
user_agent = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36 Edg/119.0.0.0"
BROWSER_CONFIG = {
"viewport_size": 1024 * 5,
"downloads_folder": "downloads_folder",
"request_kwargs": {
"headers": {"User-Agent": user_agent},
"timeout": 300,
},
"serpapi_key": os.getenv("SERPAPI_API_KEY"),
}
os.makedirs(f"./{BROWSER_CONFIG['downloads_folder']}", exist_ok=True)
model = HfApiModel(
custom_role_conversions=custom_role_conversions,
)
text_limit = 20000
ti_tool = TextInspectorTool(model, text_limit)
browser = SimpleTextBrowser(**BROWSER_CONFIG)
WEB_TOOLS = [
web_search,
VisitTool(browser),
PageUpTool(browser),
PageDownTool(browser),
FinderTool(browser),
FindNextTool(browser),
ArchiveSearchTool(browser),
TextInspectorTool(model, text_limit),
]
# Agent creation in a factory function
def create_agent():
"""Creates a fresh agent instance for each session"""
return CodeAgent(
model=model,
tools=[visualizer] + WEB_TOOLS,
max_steps=10,
verbosity_level=1,
additional_authorized_imports=AUTHORIZED_IMPORTS,
planning_interval=4,
)
document_inspection_tool = TextInspectorTool(model, 20000)
class GradioUI:
"""A one-line interface to launch your agent in Gradio"""
def __init__(self, file_upload_folder: str | None = None):
self.file_upload_folder = file_upload_folder
if self.file_upload_folder is not None:
if not os.path.exists(file_upload_folder):
os.mkdir(file_upload_folder)
def interact_with_agent(self, prompt, messages, session_state):
# Get or create session-specific agent
if "agent" not in session_state:
session_state["agent"] = create_agent()
# Adding monitoring
try:
# log the existence of agent memory
has_memory = hasattr(session_state["agent"], "memory")
print(f"Agent has memory: {has_memory}")
if has_memory:
print(f"Memory type: {type(session_state['agent'].memory)}")
messages.append(gr.ChatMessage(role="user", content=prompt))
yield messages
for msg in stream_to_gradio(
session_state["agent"], task=prompt, reset_agent_memory=False
):
messages.append(msg)
yield messages
yield messages
except Exception as e:
print(f"Error in interaction: {str(e)}")
raise
def upload_file(
self,
file,
file_uploads_log,
allowed_file_types=[
"application/pdf",
"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
"text/plain",
],
):
"""
Handle file uploads, default allowed types are .pdf, .docx, and .txt
"""
if file is None:
return gr.Textbox("No file uploaded", visible=True), file_uploads_log
try:
mime_type, _ = mimetypes.guess_type(file.name)
except Exception as e:
return gr.Textbox(f"Error: {e}", visible=True), file_uploads_log
if mime_type not in allowed_file_types:
return gr.Textbox("File type disallowed", visible=True), file_uploads_log
# Sanitize file name
original_name = os.path.basename(file.name)
sanitized_name = re.sub(
r"[^\w\-.]", "_", original_name
) # Replace any non-alphanumeric, non-dash, or non-dot characters with underscores
type_to_ext = {}
for ext, t in mimetypes.types_map.items():
if t not in type_to_ext:
type_to_ext[t] = ext
# Ensure the extension correlates to the mime type
sanitized_name = sanitized_name.split(".")[:-1]
sanitized_name.append("" + type_to_ext[mime_type])
sanitized_name = "".join(sanitized_name)
# Save the uploaded file to the specified folder
file_path = os.path.join(
self.file_upload_folder, os.path.basename(sanitized_name)
)
shutil.copy(file.name, file_path)
return gr.Textbox(
f"File uploaded: {file_path}", visible=True
), file_uploads_log + [file_path]
def log_user_message(self, text_input, file_uploads_log):
return (
text_input
+ (
f"\nYou have been provided with these files, which might be helpful or not: {file_uploads_log}"
if len(file_uploads_log) > 0
else ""
),
gr.Textbox(
value="",
interactive=False,
placeholder="Please wait while Steps are getting populated",
),
gr.Button(interactive=False),
)
def detect_device(self, request: gr.Request):
# Check whether the user device is a mobile or a computer
if not request:
return "Unknown device"
# Method 1: Check sec-ch-ua-mobile header
is_mobile_header = request.headers.get("sec-ch-ua-mobile")
if is_mobile_header:
return "Mobile" if "?1" in is_mobile_header else "Desktop"
# Method 2: Check user-agent string
user_agent = request.headers.get("user-agent", "").lower()
mobile_keywords = ["android", "iphone", "ipad", "mobile", "phone"]
if any(keyword in user_agent for keyword in mobile_keywords):
return "Mobile"
# Method 3: Check platform
platform = request.headers.get("sec-ch-ua-platform", "").lower()
if platform:
if platform in ['"android"', '"ios"']:
return "Mobile"
elif platform in ['"windows"', '"macos"', '"linux"']:
return "Desktop"
# Default case if no clear indicators
return "Desktop"
def launch(self, **kwargs):
with gr.Blocks(theme="ocean", fill_height=True) as demo:
# Different layouts for mobile and computer devices
@gr.render()
def layout(request: gr.Request):
device = self.detect_device(request)
print(f"device - {device}")
# Render layout with sidebar
if device == "Desktop":
with gr.Blocks(
fill_height=True,
):
file_uploads_log = gr.State([])
with gr.Sidebar():
gr.Markdown("""# open Deep Research - free the AI agents!
OpenAI just published [Deep Research](https://openai.com/index/introducing-deep-research/), an amazing assistant that can perform deep searches on the web to answer user questions.
However, their agent has a huge downside: it's not open. So we've started a 24-hour rush to replicate and open-source it. Our resulting [open-Deep-Research agent](https://github.com/huggingface/smolagents/tree/main/examples/open_deep_research) took the #1 rank of any open submission on the GAIA leaderboard! ✨
You can try a simplified version here that uses `Qwen-Coder-32B` instead of `o1`.
""")
with gr.Group():
gr.Markdown("**Your request**", container=True)
text_input = gr.Textbox(
lines=3,
label="Your request",
container=False,
placeholder="Enter your prompt here and press Shift+Enter or press the button",
)
launch_research_btn = gr.Button(
"Run", variant="primary"
)
# If an upload folder is provided, enable the upload feature
if self.file_upload_folder is not None:
upload_file = gr.File(label="Upload a file")
upload_status = gr.Textbox(
label="Upload Status",
interactive=False,
visible=False,
)
upload_file.change(
self.upload_file,
[upload_file, file_uploads_log],
[upload_status, file_uploads_log],
)
gr.HTML("
Powered by:
")
with gr.Row():
gr.HTML("""""")
# Add session state to store session-specific data
session_state = gr.State(
{}
) # Initialize empty state for each session
stored_messages = gr.State([])
chatbot = gr.Chatbot(
label="open-Deep-Research",
type="messages",
avatar_images=(
None,
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/smolagents/mascot_smol.png",
),
resizeable=False,
scale=1,
elem_id="my-chatbot",
)
text_input.submit(
self.log_user_message,
[text_input, file_uploads_log],
[stored_messages, text_input, launch_research_btn],
).then(
self.interact_with_agent,
# Include session_state in function calls
[stored_messages, chatbot, session_state],
[chatbot],
).then(
lambda: (
gr.Textbox(
interactive=True,
placeholder="Enter your prompt here and press the button",
),
gr.Button(interactive=True),
),
None,
[text_input, launch_research_btn],
)
launch_research_btn.click(
self.log_user_message,
[text_input, file_uploads_log],
[stored_messages, text_input, launch_research_btn],
).then(
self.interact_with_agent,
# Include session_state in function calls
[stored_messages, chatbot, session_state],
[chatbot],
).then(
lambda: (
gr.Textbox(
interactive=True,
placeholder="Enter your prompt here and press the button",
),
gr.Button(interactive=True),
),
None,
[text_input, launch_research_btn],
)
# Render simple layout
else:
with gr.Blocks(
fill_height=True,
):
gr.Markdown("""# open Deep Research - free the AI agents!
_Built with [smolagents](https://github.com/huggingface/smolagents)_
OpenAI just published [Deep Research](https://openai.com/index/introducing-deep-research/), a very nice assistant that can perform deep searches on the web to answer user questions.
However, their agent has a huge downside: it's not open. So we've started a 24-hour rush to replicate and open-source it. Our resulting [open-Deep-Research agent](https://github.com/huggingface/smolagents/tree/main/examples/open_deep_research) took the #1 rank of any open submission on the GAIA leaderboard! ✨
You can try a simplified version below (uses `Qwen-Coder-32B` instead of `o1`, so much less powerful than the original open-Deep-Research)👇""")
# Add session state to store session-specific data
session_state = gr.State(
{}
) # Initialize empty state for each session
stored_messages = gr.State([])
file_uploads_log = gr.State([])
chatbot = gr.Chatbot(
label="open-Deep-Research",
type="messages",
avatar_images=(
None,
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/smolagents/mascot_smol.png",
),
resizeable=True,
scale=1,
)
# If an upload folder is provided, enable the upload feature
if self.file_upload_folder is not None:
upload_file = gr.File(label="Upload a file")
upload_status = gr.Textbox(
label="Upload Status", interactive=False, visible=False
)
upload_file.change(
self.upload_file,
[upload_file, file_uploads_log],
[upload_status, file_uploads_log],
)
text_input = gr.Textbox(
lines=1,
label="Your request",
placeholder="Enter your prompt here and press the button",
)
launch_research_btn = gr.Button(
"Run",
variant="primary",
)
text_input.submit(
self.log_user_message,
[text_input, file_uploads_log],
[stored_messages, text_input, launch_research_btn],
).then(
self.interact_with_agent,
# Include session_state in function calls
[stored_messages, chatbot, session_state],
[chatbot],
).then(
lambda: (
gr.Textbox(
interactive=True,
placeholder="Enter your prompt here and press the button",
),
gr.Button(interactive=True),
),
None,
[text_input, launch_research_btn],
)
launch_research_btn.click(
self.log_user_message,
[text_input, file_uploads_log],
[stored_messages, text_input, launch_research_btn],
).then(
self.interact_with_agent,
# Include session_state in function calls
[stored_messages, chatbot, session_state],
[chatbot],
).then(
lambda: (
gr.Textbox(
interactive=True,
placeholder="Enter your prompt here and press the button",
),
gr.Button(interactive=True),
),
None,
[text_input, launch_research_btn],
)
demo.launch(debug=True, **kwargs)
GradioUI().launch()
huggingface/smolagents