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Update Gradio_UI.py
Browse files- Gradio_UI.py +1 -172
Gradio_UI.py
CHANGED
@@ -129,175 +129,4 @@ def stream_to_gradio(
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reset_agent_memory: bool = False,
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additional_args: Optional[dict] = None,
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):
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"""Runs an agent with the given task and streams the messages from the agent as gradio
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if not _is_package_available("gradio"):
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raise ModuleNotFoundError(
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"Please install 'gradio' extra to use the GradioUI: `pip install 'smolagents[gradio]'`"
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)
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import gradio as gr
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total_input_tokens = 0
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total_output_tokens = 0
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for step_log in agent.run(task, stream=True, reset=reset_agent_memory, additional_args=additional_args):
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# Track tokens if model provides them
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if hasattr(agent.model, "last_input_token_count"):
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total_input_tokens += agent.model.last_input_token_count
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total_output_tokens += agent.model.last_output_token_count
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if isinstance(step_log, ActionStep):
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step_log.input_token_count = agent.model.last_input_token_count
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step_log.output_token_count = agent.model.last_output_token_count
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for message in pull_messages_from_step(
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step_log,
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):
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yield message
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final_answer = step_log # Last log is the run's final_answer
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final_answer = handle_agent_output_types(final_answer)
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if isinstance(final_answer, AgentText):
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yield gr.ChatMessage(
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role="assistant",
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content=f"**Final answer:**\n{final_answer.to_string()}\n",
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)
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elif isinstance(final_answer, AgentImage):
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yield gr.ChatMessage(
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role="assistant",
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content={"path": final_answer.to_string(), "mime_type": "image/png"},
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)
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elif isinstance(final_answer, AgentAudio):
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yield gr.ChatMessage(
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role="assistant",
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content={"path": final_answer.to_string(), "mime_type": "audio/wav"},
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)
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else:
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yield gr.ChatMessage(role="assistant", content=f"**Final answer:** {str(final_answer)}")
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class GradioUI:
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def __init__(self, agent):
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self.agent = agent
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def launch(self, share=False, **kwargs):
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import gradio as gr
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# Your interface setup here
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with gr.Blocks() as demo:
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gr.Markdown("### Welcome to the AI Agent UI")
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inp = gr.Textbox(label="Input")
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out = gr.Textbox(label="Output")
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def respond(message):
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return self.agent.run(message)
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btn = gr.Button("Submit")
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btn.click(fn=respond, inputs=inp, outputs=out)
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demo.launch(debug=True, share=share, **kwargs)
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def interact_with_agent(self, prompt, messages):
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import gradio as gr
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messages.append(gr.ChatMessage(role="user", content=prompt))
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yield messages
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for msg in stream_to_gradio(self.agent, task=prompt, reset_agent_memory=False):
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messages.append(msg)
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yield messages
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yield messages
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def upload_file(
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self,
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file,
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file_uploads_log,
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allowed_file_types=[
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"application/pdf",
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"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
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"text/plain",
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],
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):
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"""
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Handle file uploads, default allowed types are .pdf, .docx, and .txt
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"""
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import gradio as gr
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if file is None:
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return gr.Textbox("No file uploaded", visible=True), file_uploads_log
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try:
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mime_type, _ = mimetypes.guess_type(file.name)
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except Exception as e:
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return gr.Textbox(f"Error: {e}", visible=True), file_uploads_log
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if mime_type not in allowed_file_types:
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return gr.Textbox("File type disallowed", visible=True), file_uploads_log
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# Sanitize file name
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original_name = os.path.basename(file.name)
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sanitized_name = re.sub(
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r"[^\w\-.]", "_", original_name
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) # Replace any non-alphanumeric, non-dash, or non-dot characters with underscores
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type_to_ext = {}
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for ext, t in mimetypes.types_map.items():
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if t not in type_to_ext:
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type_to_ext[t] = ext
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# Ensure the extension correlates to the mime type
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sanitized_name = sanitized_name.split(".")[:-1]
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sanitized_name.append("" + type_to_ext[mime_type])
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sanitized_name = "".join(sanitized_name)
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# Save the uploaded file to the specified folder
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file_path = os.path.join(self.file_upload_folder, os.path.basename(sanitized_name))
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shutil.copy(file.name, file_path)
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return gr.Textbox(f"File uploaded: {file_path}", visible=True), file_uploads_log + [file_path]
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def log_user_message(self, text_input, file_uploads_log):
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return (
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text_input
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+ (
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f"\nYou have been provided with these files, which might be helpful or not: {file_uploads_log}"
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if len(file_uploads_log) > 0
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else ""
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),
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"",
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)
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def launch(self, **kwargs):
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import gradio as gr
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with gr.Blocks(fill_height=True) as demo:
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stored_messages = gr.State([])
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file_uploads_log = gr.State([])
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chatbot = gr.Chatbot(
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label="Agent",
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type="messages",
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avatar_images=(
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None,
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"https://huggingface.co/datasets/agents-course/course-images/resolve/main/en/communication/Alfred.png",
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),
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resizeable=True,
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scale=1,
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)
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# If an upload folder is provided, enable the upload feature
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if self.file_upload_folder is not None:
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upload_file = gr.File(label="Upload a file")
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upload_status = gr.Textbox(label="Upload Status", interactive=False, visible=False)
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upload_file.change(
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self.upload_file,
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[upload_file, file_uploads_log],
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[upload_status, file_uploads_log],
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)
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text_input = gr.Textbox(lines=1, label="Chat Message")
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text_input.submit(
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self.log_user_message,
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[text_input, file_uploads_log],
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[stored_messages, text_input],
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).then(self.interact_with_agent, [stored_messages, chatbot], [chatbot])
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demo.launch(debug=True, share=True, **kwargs)
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__all__ = ["stream_to_gradio", "GradioUI"]
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reset_agent_memory: bool = False,
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additional_args: Optional[dict] = None,
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):
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+
"""Runs an agent with the given task and streams the messages from the agent as gradio ChatMes
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