File size: 6,287 Bytes
815128e 4359eb6 e182c41 2826548 815128e 2826548 815128e c815d49 99d65c0 c815d49 e182c41 2826548 815128e e182c41 815128e e182c41 815128e e182c41 815128e e182c41 815128e e182c41 99d65c0 815128e c815d49 815128e 2826548 815128e e1a6c78 8c37fda e1a6c78 815128e e182c41 815128e c815d49 815128e 99d65c0 815128e 99d65c0 815128e e182c41 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 |
"""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.utils import print_llm_response, remove_extra_spaces
llm_loader, qa_chain = app_init()
chat_history_enabled = os.environ.get("CHAT_HISTORY_ENABLED") == "true"
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"
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}"
)
title = """<h1 align="left" style="min-width:200px; margin-top:0;"> Chat with AI Books </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 = 100
def qa(chatbot):
user_msg = chatbot[-1][0]
q = Queue()
result = Queue()
job_done = object()
def task(question, chat_history):
start = timer()
ret = qa_chain.call_chain(
{"question": question, "chat_history": chat_history}, 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
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"
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(share=share_gradio_app)
|