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import core
import openai
import models
import time
import gradio as gr
import os
import asyncio
import time
# openai.api_base = "https://lonlie.plus7.plus/v1"
# openai.api_key = "sk-ac6SSdDqwB6Syk0U3e88FcF49f6b4c3c9c4e0247A38aB699"
# os.environ["OPENAI_API_KEY"]="sk-ac6SSdDqwB6Syk0U3e88FcF49f6b4c3c9c4e0247A38aB699"
# os.environ["OPENAI_API_BASE"]="https://lonlie.plus7.plus/v1"
api_key = os.environ["OPENAI_API_KEY"]
api_base = os.environ["OPENAI_API_BASE"]
# def embed(texts: list):
# return openai.Embedding.create(input=texts, model="text-embedding-ada-002")["data"]["embedding"]
def chatbot_initialize():
retriever = core.retriever.ChromaRetriever(pdf_dir="",
collection_name="langchain",
split_args={"size": 2048, "overlap": 10}, #embedding_model="text-embedding-ada-002"
embed_model=models.BiomedModel()
)
Chatbot = core.chatbot.RetrievalChatbot(retriever=retriever)
return Chatbot
async def respond(query, chat_history, img_path_list, chat_history_string):
time1 = time.time()
global Chatbot
response, logs = await Chatbot.response(query, image_paths=img_path_list, return_logs=True)
chat_history.append((query, response))
if img_path_list is None:
chat_history_string += "Query: " + query + "\nImage: None" + "\nResponse: " + response + "\n\n\n"
else:
chat_history_string += "Query: " + query + "\nImages: " + "\n".join([path.name for path in img_path_list]) + "\nResponse: " + response + "\n\n\n"
time2 = time.time()
print(f"Total: {time2-time1}")
return "", chat_history, logs, chat_history_string
if __name__ == "__main__":
global Chatbot
Chatbot=chatbot_initialize()
with gr.Blocks() as demo:
# chat = gr.ChatInterface(
# fn=respond,
# chatbot=gr.Chatbot(show_label=True, show_copy_button=True),
# additional_inputs=[
# gr.Image(type="filepath"),
# ]
# )
with gr.Row():
with gr.Column(scale=2):
chatbot = gr.Chatbot()
msg = gr.Textbox(label="Query", show_label=True)
imgs = gr.File(file_count='multiple', file_types=['image'], type="filepath", label='Upload Images')
clear = gr.ClearButton([msg, chatbot])
with gr.Column(scale=1):
sidebar = gr.Textbox(label="Subquestions", show_label=True, show_copy_button=True, interactive=False, max_lines=30)
history = gr.Textbox(label="Copy Chat History", show_label=True, show_copy_button=True, interactive=False, max_lines=5)
msg.submit(respond, inputs=[msg, chatbot, imgs, history], outputs=[msg, chatbot, sidebar, history])
demo.queue().launch() |