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Duplicate from ysharma/OSChatbots_ChatGPT_ToeToToe
Browse files- .gitattributes +34 -0
- README.md +14 -0
- app.py +299 -0
- requirements.txt +5 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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title: OSChatbots ChatGPT ToeToToe
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emoji: 🏢
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colorFrom: gray
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.20.1
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app_file: app.py
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pinned: false
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license: mit
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duplicated_from: ysharma/OSChatbots_ChatGPT_ToeToToe
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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import json
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import requests
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import os
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from text_generation import Client, InferenceAPIClient
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# Load pre-trained model and tokenizer - for THUDM model
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from transformers import AutoModel, AutoTokenizer
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tokenizer_glm = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
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model_glm = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
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model_glm = model_glm.eval()
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# Load pre-trained model and tokenizer for Chinese to English translator
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from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
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model_chtoen = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
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tokenizer_chtoen = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
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#Streaming endpoint for OPENAI ChatGPT
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API_URL = "https://api.openai.com/v1/chat/completions"
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#Streaming endpoint for OPENCHATKIT
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API_URL_TGTHR = os.getenv('API_URL_TGTHR')
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openchat_preprompt = (
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"\n<human>: Hi!\n<bot>: My name is Bot, model version is 0.15, part of an open-source kit for "
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"fine-tuning new bots! I was created by Together, LAION, and Ontocord.ai and the open-source "
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"community. I am not human, not evil and not alive, and thus have no thoughts and feelings, "
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"but I am programmed to be helpful, polite, honest, and friendly.\n")
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#Predict function for CHATGPT
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def predict_chatgpt(inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):
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#Define payload and header for chatgpt API
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payload = {
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"model": "gpt-3.5-turbo",
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"messages": [{"role": "user", "content": f"{inputs}"}],
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"temperature" : 1.0,
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"top_p":1.0,
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"n" : 1,
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"stream": True,
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"presence_penalty":0,
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"frequency_penalty":0,
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}
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {openai_api_key}"
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}
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#debug
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#print(f"chat_counter_chatgpt - {chat_counter_chatgpt}")
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#Handling the different roles for ChatGPT
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if chat_counter_chatgpt != 0 :
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messages=[]
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for data in chatbot_chatgpt:
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temp1 = {}
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temp1["role"] = "user"
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temp1["content"] = data[0]
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temp2 = {}
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temp2["role"] = "assistant"
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temp2["content"] = data[1]
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messages.append(temp1)
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messages.append(temp2)
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temp3 = {}
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temp3["role"] = "user"
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temp3["content"] = inputs
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messages.append(temp3)
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payload = {
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"model": "gpt-3.5-turbo",
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"messages": messages, #[{"role": "user", "content": f"{inputs}"}],
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"temperature" : temperature_chatgpt, #1.0,
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"top_p": top_p_chatgpt, #1.0,
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"n" : 1,
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"stream": True,
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"presence_penalty":0,
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"frequency_penalty":0,
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}
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chat_counter_chatgpt+=1
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history.append(inputs)
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# make a POST request to the API endpoint using the requests.post method, passing in stream=True
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response = requests.post(API_URL, headers=headers, json=payload, stream=True)
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token_counter = 0
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partial_words = ""
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counter=0
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for chunk in response.iter_lines():
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#Skipping the first chunk
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if counter == 0:
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counter+=1
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continue
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# check whether each line is non-empty
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if chunk.decode() :
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chunk = chunk.decode()
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# decode each line as response data is in bytes
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if len(chunk) > 13 and "content" in json.loads(chunk[6:])['choices'][0]["delta"]:
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partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
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if token_counter == 0:
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history.append(" " + partial_words)
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else:
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history[-1] = partial_words
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chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] # convert to tuples of list
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token_counter+=1
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yield chat, history, chat_counter_chatgpt # this resembles {chatbot: chat, state: history}
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#Predict function for OPENCHATKIT
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def predict_together(model: str,
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inputs: str,
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top_p: float,
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temperature: float,
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top_k: int,
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repetition_penalty: float,
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watermark: bool,
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chatbot,
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history,):
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client = Client(os.getenv("API_URL_TGTHR")) #get_client(model)
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# debug
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#print(f"^^client is - {client}")
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user_name, assistant_name = "<human>: ", "<bot>: "
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preprompt = openchat_preprompt
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sep = '\n'
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history.append(inputs)
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past = []
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for data in chatbot:
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user_data, model_data = data
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if not user_data.startswith(user_name):
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user_data = user_name + user_data
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if not model_data.startswith("\n" + assistant_name):
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model_data = "\n" + assistant_name + model_data
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past.append(user_data + model_data.rstrip() + "\n")
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if not inputs.startswith(user_name):
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inputs = user_name + inputs
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total_inputs = preprompt + "".join(past) + inputs + "\n" + assistant_name.rstrip()
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# truncate total_inputs
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#total_inputs = total_inputs[-1000:]
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partial_words = ""
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for i, response in enumerate(client.generate_stream(
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total_inputs,
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top_p=top_p,
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top_k=top_k,
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repetition_penalty=repetition_penalty,
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watermark=watermark,
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temperature=temperature,
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max_new_tokens=500,
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stop_sequences=[user_name.rstrip(), assistant_name.rstrip()],
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)):
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if response.token.special:
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continue
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partial_words = partial_words + response.token.text
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if partial_words.endswith(user_name.rstrip()):
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partial_words = partial_words.rstrip(user_name.rstrip())
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if partial_words.endswith(assistant_name.rstrip()):
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partial_words = partial_words.rstrip(assistant_name.rstrip())
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if i == 0:
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history.append(" " + partial_words)
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else:
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history[-1] = partial_words
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chat = [
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(history[i].strip(), history[i + 1].strip()) for i in range(0, len(history) - 1, 2)
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]
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yield chat, history
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# Define function to generate model predictions and update the history
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def predict_glm(input, history=[]):
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response, history = model_glm.chat(tokenizer_glm, input, history)
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# translate Chinese to English
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history = [(query, translate_Chinese_English(response)) for query, response in history]
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return history, history #[history] + updates
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def translate_Chinese_English(chinese_text):
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# translate Chinese to English
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tokenizer_chtoen.src_lang = "zh"
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encoded_zh = tokenizer_chtoen(chinese_text, return_tensors="pt")
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generated_tokens = model_chtoen.generate(**encoded_zh, forced_bos_token_id=tokenizer_chtoen.get_lang_id("en"))
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trans_eng_text = tokenizer_chtoen.batch_decode(generated_tokens, skip_special_tokens=True)
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return trans_eng_text[0]
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"""
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot()
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state = gr.State([])
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with gr.Row():
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txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
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txt.submit(predict, [txt, state], [chatbot, state])
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demo.launch(debug=True)
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"""
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def reset_textbox():
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return gr.update(value="")
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def reset_chat(chatbot, state):
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# debug
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#print(f"^^chatbot value is - {chatbot}")
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#print(f"^^state value is - {state}")
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return None, []
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#title = """<h1 align="center">🔥🔥Comparison: ChatGPT & OpenChatKit </h1><br><h3 align="center">🚀A Gradio Streaming Demo</h3><br>Official Demo: <a href="https://huggingface.co/spaces/togethercomputer/OpenChatKit">OpenChatKit feedback app</a>"""
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+
title = """<h1 align="center">🔥🔥Comparison: ChatGPT & Open Sourced CHatGLM-6B </h1><br><h3 align="center">🚀A Gradio Chatbot Demo</h3>"""
|
216 |
+
description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
|
217 |
+
```
|
218 |
+
User: <utterance>
|
219 |
+
Assistant: <utterance>
|
220 |
+
User: <utterance>
|
221 |
+
Assistant: <utterance>
|
222 |
+
...
|
223 |
+
```
|
224 |
+
In this app, you can explore the outputs of multiple LLMs when prompted in similar ways.
|
225 |
+
"""
|
226 |
+
|
227 |
+
with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
|
228 |
+
#chatgpt {height: 520px; overflow: auto;}
|
229 |
+
#chatglm {height: 520px; overflow: auto;} """ ) as demo:
|
230 |
+
#chattogether {height: 520px; overflow: auto;} """ ) as demo:
|
231 |
+
#clear {width: 100px; height:50px; font-size:12px}""") as demo:
|
232 |
+
gr.HTML(title)
|
233 |
+
with gr.Row():
|
234 |
+
with gr.Column(scale=14):
|
235 |
+
with gr.Box():
|
236 |
+
with gr.Row():
|
237 |
+
with gr.Column(scale=13):
|
238 |
+
openai_api_key = gr.Textbox(type='password', label="Enter your OpenAI API key here for ChatGPT")
|
239 |
+
inputs = gr.Textbox(placeholder="Hi there!", label="Type an input and press Enter ⤵️ " )
|
240 |
+
with gr.Column(scale=1):
|
241 |
+
b1 = gr.Button('🏃Run', elem_id = 'run').style(full_width=True)
|
242 |
+
b2 = gr.Button('🔄Clear up Chatbots!', elem_id = 'clear').style(full_width=True)
|
243 |
+
state_chatgpt = gr.State([])
|
244 |
+
#state_together = gr.State([])
|
245 |
+
state_glm = gr.State([])
|
246 |
+
|
247 |
+
with gr.Box():
|
248 |
+
with gr.Row():
|
249 |
+
chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label='ChatGPT API - OPENAI')
|
250 |
+
#chatbot_together = gr.Chatbot(elem_id="chattogether", label='OpenChatKit - Text Generation')
|
251 |
+
chatbot_glm = gr.Chatbot(elem_id="chatglm", label='THUDM-ChatGLM6B')
|
252 |
+
|
253 |
+
with gr.Column(scale=2, elem_id='parameters'):
|
254 |
+
with gr.Box():
|
255 |
+
gr.HTML("Parameters for #OpenCHAtKit", visible=False)
|
256 |
+
top_p = gr.Slider(minimum=-0, maximum=1.0,value=0.25, step=0.05,interactive=True, label="Top-p", visible=False)
|
257 |
+
temperature = gr.Slider(minimum=-0, maximum=5.0, value=0.6, step=0.1, interactive=True, label="Temperature", visible=False)
|
258 |
+
top_k = gr.Slider( minimum=1, maximum=50, value=50, step=1, interactive=True, label="Top-k", visible=False)
|
259 |
+
repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.01, step=0.01, interactive=True, label="Repetition Penalty", visible=False)
|
260 |
+
watermark = gr.Checkbox(value=True, label="Text watermarking", visible=False)
|
261 |
+
model = gr.CheckboxGroup(value="Rallio67/joi2_20B_instruct_alpha",
|
262 |
+
choices=["togethercomputer/GPT-NeoXT-Chat-Base-20B", "Rallio67/joi2_20B_instruct_alpha", "google/flan-t5-xxl", "google/flan-ul2", "bigscience/bloomz", "EleutherAI/gpt-neox-20b",],
|
263 |
+
label="Model",visible=False,)
|
264 |
+
temp_textbox_together = gr.Textbox(value=model.choices[0], visible=False)
|
265 |
+
|
266 |
+
with gr.Box():
|
267 |
+
gr.HTML("Parameters for OpenAI's ChatGPT")
|
268 |
+
top_p_chatgpt = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p",)
|
269 |
+
temperature_chatgpt = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
|
270 |
+
chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
|
271 |
+
|
272 |
+
inputs.submit(reset_textbox, [], [inputs])
|
273 |
+
|
274 |
+
inputs.submit( predict_chatgpt,
|
275 |
+
[inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt],
|
276 |
+
[chatbot_chatgpt, state_chatgpt, chat_counter_chatgpt],)
|
277 |
+
#inputs.submit( predict_together,
|
278 |
+
# [temp_textbox_together, inputs, top_p, temperature, top_k, repetition_penalty, watermark, chatbot_together, state_together, ],
|
279 |
+
# [chatbot_together, state_together],)
|
280 |
+
inputs.submit( predict_glm,
|
281 |
+
[inputs, state_glm, ],
|
282 |
+
[chatbot_glm, state_glm],)
|
283 |
+
b1.click( predict_chatgpt,
|
284 |
+
[inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt],
|
285 |
+
[chatbot_chatgpt, state_chatgpt, chat_counter_chatgpt],)
|
286 |
+
#b1.click( predict_together,
|
287 |
+
# [temp_textbox_together, inputs, top_p, temperature, top_k, repetition_penalty, watermark, chatbot_together, state_together, ],
|
288 |
+
# [chatbot_together, state_together],)
|
289 |
+
b1.click( predict_glm,
|
290 |
+
[inputs, state_glm, ],
|
291 |
+
[chatbot_glm, state_glm],)
|
292 |
+
|
293 |
+
b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
|
294 |
+
#b2.click(reset_chat, [chatbot_together, state_together], [chatbot_together, state_together])
|
295 |
+
b2.click(reset_chat, [chatbot_glm, state_glm], [chatbot_glm, state_glm])
|
296 |
+
|
297 |
+
gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/OpenChatKit_ChatGPT_Comparison?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
|
298 |
+
gr.Markdown(description)
|
299 |
+
demo.queue(concurrency_count=16).launch(height= 2500, debug=True)
|
requirements.txt
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
text_generation
|
2 |
+
protobuf>=3.19.5,<3.20.1
|
3 |
+
transformers>=4.26.1
|
4 |
+
icetk
|
5 |
+
cpm_kernels
|