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Update app.py
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app.py
CHANGED
@@ -1,9 +1,23 @@
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import gradio as gr
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from styles import MODEL_SELECTION_CSS
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from js import GET_LOCAL_STORAGE, UPDATE_LEFT_BTNS_STATE, UPDATE_PLACEHOLDERS
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from templates import templates
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ex_file = open("examples.txt", "r")
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examples = ex_file.read().split("\n")
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ex_btns = []
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@@ -36,10 +50,28 @@ def fill_up_placeholders(txt):
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"" if len(placeholders) >= 1 else txt
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)
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with gr.Blocks(css=MODEL_SELECTION_CSS, theme='gradio/soft') as demo:
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with gr.Column() as chat_view:
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idx = gr.State(0)
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chat_state = gr.State(
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local_data = gr.JSON({}, visible=False)
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with gr.Row():
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@@ -169,4 +201,10 @@ with gr.Blocks(css=MODEL_SELECTION_CSS, theme='gradio/soft') as demo:
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visible=False
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)
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demo.launch()
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import gradio as gr
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from llama2 import GradioLLaMA2ChatPPManager
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from llama2 import gen_text
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from styles import MODEL_SELECTION_CSS
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from js import GET_LOCAL_STORAGE, UPDATE_LEFT_BTNS_STATE, UPDATE_PLACEHOLDERS
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from templates import templates
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from pingpong.context import CtxLastWindowStrategy
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TOKEN = os.getenv('HF_TOKEN')
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MODEL_ID = 'meta-llama/Llama-2-70b-chat-hf'
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def build_prompts(ppmanager, global_context, win_size=3):
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dummy_ppm = copy.deepcopy(ppmanager)
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dummy_ppm.ctx = global_context
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lws = CtxLastWindowStrategy(win_size)
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return lws(dummy_ppm)
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ex_file = open("examples.txt", "r")
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examples = ex_file.read().split("\n")
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ex_btns = []
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"" if len(placeholders) >= 1 else txt
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)
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async def chat_stream(idx, local_data, instruction_txtbox, chat_state):
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res = [
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chat_state["ppmanager_type"].from_json(json.dumps(ppm))
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for ppm in local_data
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]
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ppm = res[idx]
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ppm.add_pingpong(
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PingPong(instruction_txtbox, "")
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)
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prompt = build_prompts(ppm, "global context", 3)
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for result in await gen_text(prompt, hf_model=MODEL_ID, hf_token=TOKEN):
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ppm.append_pong(result)
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yield ppm.build_uis(), str(res)
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with gr.Blocks(css=MODEL_SELECTION_CSS, theme='gradio/soft') as demo:
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with gr.Column() as chat_view:
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idx = gr.State(0)
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chat_state = gr.State({
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"ppmanager_type": GradioLLaMA2ChatPPManager
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})
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local_data = gr.JSON({}, visible=False)
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with gr.Row():
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visible=False
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)
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instruction_txtbox.submit(
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chat_stream,
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[idx, local_data, instruction_txtbox, chat_state]
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[chatbot, local_data]
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)
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demo.launch()
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