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"""Main entrypoint for the app."""
import os
import time
from queue import Queue
from timeit import default_timer as timer
import gradio as gr
from anyio.from_thread import start_blocking_portal
from app_modules.init import app_init
from app_modules.llm_chat_chain import ChatChain
from app_modules.utils import print_llm_response, remove_extra_spaces
llm_loader, qa_chain = app_init()
show_param_settings = os.environ.get("SHOW_PARAM_SETTINGS") == "true"
share_gradio_app = os.environ.get("SHARE_GRADIO_APP") == "true"
using_openai = os.environ.get("LLM_MODEL_TYPE") == "openai"
chat_with_llama_2 = (
not using_openai and os.environ.get("USE_LLAMA_2_PROMPT_TEMPLATE") == "true"
)
chat_history_enabled = (
not chat_with_llama_2 and os.environ.get("CHAT_HISTORY_ENABLED") == "true"
)
model = (
"OpenAI GPT-3.5"
if using_openai
else os.environ.get("HUGGINGFACE_MODEL_NAME_OR_PATH")
)
href = (
"https://platform.openai.com/docs/models/gpt-3-5"
if using_openai
else f"https://huggingface.co/{model}"
)
if chat_with_llama_2:
qa_chain = ChatChain(llm_loader)
name = "Llama-2"
else:
name = "AI Books"
title = f"""<h1 align="left" style="min-width:200px; margin-top:0;"> Chat with {name} </h1>"""
description_top = f"""\
<div align="left">
<p> Currently Running: <a href="{href}">{model}</a></p>
</div>
"""
description = """\
<div align="center" style="margin:16px 0">
The demo is built on <a href="https://github.com/hwchase17/langchain">LangChain</a>.
</div>
"""
CONCURRENT_COUNT = 1
def qa(chatbot):
user_msg = chatbot[-1][0]
q = Queue()
result = Queue()
job_done = object()
def task(question, chat_history):
start = timer()
inputs = {"question": question}
if not chat_with_llama_2:
inputs["chat_history"] = chat_history
ret = qa_chain.call_chain(inputs, None, q)
end = timer()
print(f"Completed in {end - start:.3f}s")
print_llm_response(ret)
q.put(job_done)
result.put(ret)
with start_blocking_portal() as portal:
chat_history = []
if chat_history_enabled:
for i in range(len(chatbot) - 1):
element = chatbot[i]
item = (element[0] or "", element[1] or "")
chat_history.append(item)
portal.start_task_soon(task, user_msg, chat_history)
content = ""
count = 2 if len(chat_history) > 0 else 1
while count > 0:
while q.empty():
print("nothing generated yet - retry in 0.5s")
time.sleep(0.5)
for next_token in llm_loader.streamer:
if next_token is job_done:
break
content += next_token or ""
chatbot[-1][1] = remove_extra_spaces(content)
if count == 1:
yield chatbot
count -= 1
if not chat_with_llama_2:
chatbot[-1][1] += "\n\nSources:\n"
ret = result.get()
titles = []
for doc in ret["source_documents"]:
page = doc.metadata["page"] + 1
url = f"{doc.metadata['url']}#page={page}"
file_name = doc.metadata["source"].split("/")[-1]
title = f"{file_name} Page: {page}"
if title not in titles:
titles.append(title)
chatbot[-1][1] += f"1. [{title}]({url})\n"
yield chatbot
with open("assets/custom.css", "r", encoding="utf-8") as f:
customCSS = f.read()
with gr.Blocks(css=customCSS) as demo:
user_question = gr.State("")
with gr.Row():
gr.HTML(title)
gr.Markdown(description_top)
with gr.Row().style(equal_height=True):
with gr.Column(scale=5):
with gr.Row():
chatbot = gr.Chatbot(elem_id="inflaton_chatbot").style(height="100%")
with gr.Row():
with gr.Column(scale=2):
user_input = gr.Textbox(
show_label=False, placeholder="Enter your question here"
).style(container=False)
with gr.Column(
min_width=70,
):
submitBtn = gr.Button("Send")
with gr.Column(
min_width=70,
):
clearBtn = gr.Button("Clear")
if show_param_settings:
with gr.Column():
with gr.Column(
min_width=50,
):
with gr.Tab(label="Parameter Setting"):
gr.Markdown("# Parameters")
top_p = gr.Slider(
minimum=-0,
maximum=1.0,
value=0.95,
step=0.05,
# interactive=True,
label="Top-p",
)
temperature = gr.Slider(
minimum=0.1,
maximum=2.0,
value=0,
step=0.1,
# interactive=True,
label="Temperature",
)
max_new_tokens = gr.Slider(
minimum=0,
maximum=2048,
value=2048,
step=8,
# interactive=True,
label="Max Generation Tokens",
)
max_context_length_tokens = gr.Slider(
minimum=0,
maximum=4096,
value=4096,
step=128,
# interactive=True,
label="Max Context Tokens",
)
gr.Markdown(description)
def chat(user_message, history):
return "", history + [[user_message, None]]
user_input.submit(
chat, [user_input, chatbot], [user_input, chatbot], queue=True
).then(qa, chatbot, chatbot)
submitBtn.click(
chat, [user_input, chatbot], [user_input, chatbot], queue=True, api_name="chat"
).then(qa, chatbot, chatbot)
def reset():
return "", []
clearBtn.click(
reset,
outputs=[user_input, chatbot],
show_progress=True,
api_name="reset",
)
demo.title = "Chat with AI Books" if chat_with_llama_2 else "Chat with Llama-2"
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(share=share_gradio_app)
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