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import gradio as gr
import os
import shutil
import autogen
import chromadb
import multiprocessing as mp
from autogen.oai.openai_utils import config_list_from_json
from autogen.retrieve_utils import TEXT_FORMATS
from autogen.agentchat.contrib.retrieve_assistant_agent import RetrieveAssistantAgent
from autogen.agentchat.contrib.retrieve_user_proxy_agent import (
RetrieveUserProxyAgent,
PROMPT_DEFAULT,
)
def setup_configurations():
config_list = autogen.config_list_from_models(
model_list=["gpt-4", "gpt-3.5-turbo", "gpt-35-turbo"]
)
if len(config_list) > 0:
return [config_list[0]]
else:
return None
def initialize_agents(config_list, docs_path=None):
if docs_path is None:
docs_path = "https://raw.githubusercontent.com/microsoft/autogen/main/README.md"
autogen.ChatCompletion.start_logging()
assistant = RetrieveAssistantAgent(
name="assistant",
system_message="You are a helpful assistant.",
llm_config={
"request_timeout": 600,
"seed": 42,
"config_list": config_list,
},
)
ragproxyagent = RetrieveUserProxyAgent(
name="ragproxyagent",
human_input_mode="NEVER",
max_consecutive_auto_reply=5,
retrieve_config={
# "task": "qa",
"docs_path": docs_path,
"chunk_token_size": 2000,
"model": config_list[0]["model"],
"client": chromadb.PersistentClient(path="/tmp/chromadb"),
"embedding_model": "all-mpnet-base-v2",
"customized_prompt": PROMPT_DEFAULT,
},
)
return assistant, ragproxyagent
def initiate_chat(problem, queue, n_results=3):
global assistant, ragproxyagent
if assistant is None:
queue.put(["Please set the LLM config first"])
return
assistant.reset()
ragproxyagent.initiate_chat(
assistant, problem=problem, silent=False, n_results=n_results
)
# queue.put(ragproxyagent.last_message()["content"])
messages = ragproxyagent.chat_messages
messages = [messages[k] for k in messages.keys()][0]
messages = [m["content"] for m in messages if m["role"] == "user"]
print("messages: ", messages)
queue.put(messages)
def chatbot_reply(input_text):
"""Chat with the agent through terminal."""
queue = mp.Queue()
process = mp.Process(
target=initiate_chat,
args=(input_text, queue),
)
process.start()
process.join()
messages = queue.get()
return messages
def get_description_text():
return """
# Microsoft AutoGen: Retrieve Chat Demo
This demo shows how to use the RetrieveUserProxyAgent and RetrieveAssistantAgent to build a chatbot.
#### [GitHub](https://github.com/microsoft/autogen) [Discord](https://discord.gg/pAbnFJrkgZ) [Docs](https://microsoft.github.io/autogen/) [Paper](https://arxiv.org/abs/2308.08155)
"""
global config_list, assistant, ragproxyagent
config_list = setup_configurations()
assistant, ragproxyagent = (
initialize_agents(config_list) if config_list else (None, None)
)
with gr.Blocks() as demo:
gr.Markdown(get_description_text())
chatbot = gr.Chatbot(
[],
elem_id="chatbot",
bubble_full_width=False,
avatar_images=(None, (os.path.join(os.path.dirname(__file__), "autogen.png"))),
# height=600,
)
txt_input = gr.Textbox(
scale=4,
show_label=False,
placeholder="Enter text and press enter",
container=False,
)
with gr.Row():
def upload_file(file):
global config_list, assistant, ragproxyagent
update_context_url(file.name)
upload_button = gr.UploadButton(
"Click to Upload Document",
file_types=[f".{i}" for i in TEXT_FORMATS],
file_count="single",
)
upload_button.upload(upload_file, upload_button)
def update_config():
global config_list, assistant, ragproxyagent
config_list = setup_configurations()
assistant, ragproxyagent = (
initialize_agents(config_list) if config_list else (None, None)
)
def set_oai_key(secret):
os.environ["OPENAI_API_KEY"] = secret
update_config()
return secret
def set_aoai_key(secret):
os.environ["AZURE_OPENAI_API_KEY"] = secret
update_config()
return secret
def set_aoai_base(secret):
os.environ["AZURE_OPENAI_API_BASE"] = secret
update_config()
return secret
txt_oai_key = gr.Textbox(
label="OpenAI API Key",
placeholder="Enter key and press enter",
max_lines=1,
show_label=True,
value=os.environ.get("OPENAI_API_KEY", ""),
container=True,
type="password",
)
txt_oai_key.submit(set_oai_key, [txt_oai_key], [txt_oai_key])
txt_aoai_key = gr.Textbox(
label="Azure OpenAI API Key",
placeholder="Enter key and press enter",
max_lines=1,
show_label=True,
value=os.environ.get("AZURE_OPENAI_API_KEY", ""),
container=True,
type="password",
)
txt_aoai_key.submit(set_aoai_key, [txt_aoai_key], [txt_aoai_key])
txt_aoai_base_url = gr.Textbox(
label="Azure OpenAI API Base",
placeholder="Enter base url and press enter",
max_lines=1,
show_label=True,
value=os.environ.get("AZURE_OPENAI_API_BASE", ""),
container=True,
type="password",
)
txt_aoai_base_url.submit(
set_aoai_base, [txt_aoai_base_url], [txt_aoai_base_url]
)
clear = gr.ClearButton([txt_input, chatbot])
txt_context_url = gr.Textbox(
label="Enter the url to your context file and chat on the context",
info=f"File must be in the format of [{', '.join(TEXT_FORMATS)}]",
max_lines=1,
show_label=True,
value="https://raw.githubusercontent.com/microsoft/autogen/main/README.md",
container=True,
)
txt_prompt = gr.Textbox(
label="Enter your prompt for Retrieve Agent and press enter to replace the default prompt",
max_lines=40,
show_label=True,
value=PROMPT_DEFAULT,
container=True,
show_copy_button=True,
layout={"height": 20},
)
def respond(message, chat_history):
messages = chatbot_reply(message)
chat_history.append(
(message, messages[-1] if messages[-1] != "TERMINATE" else messages[-2])
)
return "", chat_history
def update_prompt(prompt):
ragproxyagent.customized_prompt = prompt
return prompt
def update_context_url(context_url):
global assistant, ragproxyagent
try:
shutil.rmtree("/tmp/chromadb/")
except:
pass
assistant, ragproxyagent = initialize_agents(config_list, docs_path=context_url)
return context_url
txt_input.submit(respond, [txt_input, chatbot], [txt_input, chatbot])
txt_prompt.submit(update_prompt, [txt_prompt], [txt_prompt])
txt_context_url.submit(update_context_url, [txt_context_url], [txt_context_url])
if __name__ == "__main__":
demo.launch(share=True)
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