113 lines
4.1 KiB
Python
113 lines
4.1 KiB
Python
#!/usr/bin/env python
|
|
# coding=utf-8
|
|
|
|
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
from .agent_types import AgentAudio, AgentImage, AgentText
|
|
from .agents import BaseAgent, AgentStep, ActionStep
|
|
import gradio as gr
|
|
|
|
|
|
def pull_messages_from_step(step_log: AgentStep, test_mode: bool = True):
|
|
"""Extract ChatMessage objects from agent steps"""
|
|
if isinstance(step_log, ActionStep):
|
|
yield gr.ChatMessage(role="assistant", content=step_log.llm_output)
|
|
if step_log.tool_call is not None:
|
|
used_code = step_log.tool_call.tool_name == "code interpreter"
|
|
content = step_log.tool_call.tool_arguments
|
|
if used_code:
|
|
content = f"```py\n{content}\n```"
|
|
yield gr.ChatMessage(
|
|
role="assistant",
|
|
metadata={"title": f"🛠️ Used tool {step_log.tool_call.tool_name}"},
|
|
content=str(content),
|
|
)
|
|
if step_log.observations is not None:
|
|
yield gr.ChatMessage(
|
|
role="assistant", content=f"```\n{step_log.observations}\n```"
|
|
)
|
|
if step_log.error is not None:
|
|
yield gr.ChatMessage(
|
|
role="assistant",
|
|
content=str(step_log.error),
|
|
metadata={"title": "💥 Error"},
|
|
)
|
|
|
|
|
|
def stream_to_gradio(
|
|
agent,
|
|
task: str,
|
|
test_mode: bool = False,
|
|
reset_agent_memory: bool = False,
|
|
**kwargs,
|
|
):
|
|
"""Runs an agent with the given task and streams the messages from the agent as gradio ChatMessages."""
|
|
|
|
for step_log in agent.run(task, stream=True, reset=reset_agent_memory, **kwargs):
|
|
for message in pull_messages_from_step(step_log, test_mode=test_mode):
|
|
yield message
|
|
|
|
final_answer = step_log # Last log is the run's final_answer
|
|
|
|
if isinstance(final_answer, AgentText):
|
|
yield gr.ChatMessage(
|
|
role="assistant",
|
|
content=f"**Final answer:**\n```\n{final_answer.to_string()}\n```",
|
|
)
|
|
elif isinstance(final_answer, AgentImage):
|
|
yield gr.ChatMessage(
|
|
role="assistant",
|
|
content={"path": final_answer.to_string(), "mime_type": "image/png"},
|
|
)
|
|
elif isinstance(final_answer, AgentAudio):
|
|
yield gr.ChatMessage(
|
|
role="assistant",
|
|
content={"path": final_answer.to_string(), "mime_type": "audio/wav"},
|
|
)
|
|
else:
|
|
yield gr.ChatMessage(role="assistant", content=str(final_answer))
|
|
|
|
|
|
class GradioUI:
|
|
"""A one-line interface to launch your agent in Gradio"""
|
|
|
|
def __init__(self, agent: BaseAgent):
|
|
self.agent = agent
|
|
|
|
def interact_with_agent(self, prompt, messages):
|
|
messages.append(gr.ChatMessage(role="user", content=prompt))
|
|
yield messages
|
|
for msg in stream_to_gradio(self.agent, task=prompt, reset_agent_memory=False):
|
|
messages.append(msg)
|
|
yield messages
|
|
yield messages
|
|
|
|
def run(self):
|
|
with gr.Blocks() as demo:
|
|
stored_message = gr.State([])
|
|
chatbot = gr.Chatbot(
|
|
label="Agent",
|
|
type="messages",
|
|
avatar_images=(
|
|
None,
|
|
"https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png",
|
|
),
|
|
)
|
|
text_input = gr.Textbox(lines=1, label="Chat Message")
|
|
text_input.submit(
|
|
lambda s: (s, ""), [text_input], [stored_message, text_input]
|
|
).then(self.interact_with_agent, [stored_message, chatbot], [chatbot])
|
|
|
|
demo.launch()
|