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| import gradio as gr | |
| import os | |
| import time | |
| from utils import * | |
| vectordb = "" | |
| histr = [[None, "Hi, I'm **everything-rag**🤖.\nI'm here to assist you and let you chat with _your_ pdfs!\nCheck [my website](https://astrabert.github.io/everything-rag/) for troubleshooting and documentation reference\nHave fun!😊"]] | |
| def print_like_dislike(x: gr.LikeData): | |
| print(x.index, x.value, x.liked) | |
| def add_message(history, message): | |
| global histr | |
| if history is not None: | |
| if len(message["files"]) > 0: | |
| history.append((message["files"], None)) | |
| histr.append([message["files"], None]) | |
| if message["text"] is not None and message["text"] != "": | |
| history.append((message["text"], None)) | |
| histr.append([message["text"], None]) | |
| else: | |
| history = histr | |
| add_message(history, message) | |
| return history, gr.MultimodalTextbox(value=None, interactive=False) | |
| def bot(history): | |
| global vectordb | |
| global tsk | |
| global histr | |
| if not history is None: | |
| if type(history[-1][0]) != tuple: | |
| if vectordb == "": | |
| pipe = pipeline(tsk, tokenizer=tokenizer, model=model) | |
| response = pipe(history[-1][0])[0] | |
| response = response["generated_text"] | |
| histr[-1][1] = response | |
| history[-1][1] = "" | |
| for character in response: | |
| history[-1][1] += character | |
| time.sleep(0.05) | |
| yield history | |
| else: | |
| try: | |
| response = just_chatting(task=tsk, model=model, tokenizer=tokenizer, query=history[-1][0], vectordb=vectordb, chat_history=[convert_none_to_str(his) for his in history])["answer"] | |
| history[-1][1] = "" | |
| histr[-1][1] = response | |
| for character in response: | |
| history[-1][1] += character | |
| time.sleep(0.05) | |
| yield history | |
| except Exception as e: | |
| response = f"Sorry, the error '{e}' occured while generating the response; check [troubleshooting documentation](https://astrabert.github.io/everything-rag/#troubleshooting) for more" | |
| if type(history[-1][0]) == tuple: | |
| filelist = [] | |
| for i in history[-1][0]: | |
| filelist.append(i) | |
| finalpdf = merge_pdfs(filelist) | |
| vectordb = create_a_persistent_db(finalpdf, os.path.dirname(finalpdf)+"_localDB", os.path.dirname(finalpdf)+"_embcache") | |
| response = "VectorDB was successfully created, now you can ask me anything about the document you uploaded!😊" | |
| histr[-1][1] = response | |
| history[-1][1] = "" | |
| for character in response: | |
| history[-1][1] += character | |
| time.sleep(0.05) | |
| yield history | |
| else: | |
| history = histr | |
| bot(history) | |
| with gr.Blocks() as demo: | |
| chatbot = gr.Chatbot( | |
| [[None, "Hi, I'm **everything-rag**🤖.\nI'm here to assist you and let you chat with _your_ pdfs!\nCheck [my website](https://astrabert.github.io/everything-rag/) for troubleshooting and documentation reference\nHave fun!😊"]], | |
| label="everything-rag", | |
| elem_id="chatbot", | |
| bubble_full_width=False, | |
| ) | |
| chat_input = gr.MultimodalTextbox(interactive=True, file_types=["pdf"], placeholder="Enter message or upload file...", show_label=False) | |
| chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input]) | |
| bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response") | |
| bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input]) | |
| chatbot.like(print_like_dislike, None, None) | |
| demo.queue() | |
| if __name__ == "__main__": | |
| demo.launch() | |