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import os |
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import gradio as gr |
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import openai |
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from langdetect import detect |
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from gtts import gTTS |
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from pdfminer.high_level import extract_text |
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import pinecone |
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from langchain.llms import OpenAI |
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from langchain.text_splitter import SpacyTextSplitter |
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from langchain.document_loaders import TextLoader |
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from langchain.document_loaders import DirectoryLoader |
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from langchain.indexes import VectorstoreIndexCreator |
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from langchain.embeddings.openai import OpenAIEmbeddings |
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from langchain.vectorstores import Pinecone |
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openai.api_key = os.environ['OPENAI_API_KEY'] |
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pinecone_key = os.environ['PINECONE_API_KEY'] |
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pinecone_environment='us-west1-gcp-free' |
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user_db = {os.environ['username1']: os.environ['password1']} |
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messages = [{"role": "system", "content": 'You are a helpful assistant.'}] |
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def process_file(index_name, dir): |
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pinecone.init( |
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api_key=pinecone_key, |
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environment=pinecone_environment |
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) |
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pinecone.create_index(index_name, dimension=1536, metric="euclidean") |
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embeddings = OpenAIEmbeddings(openai_api_key=os.environ['OPENAI_API_KEY']) |
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splter = SpacyTextSplitter(chunk_size=1000,chunk_overlap=200) |
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for doc in dir: |
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loader = TextLoader(doc.name , encoding='utf8') |
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content = loader.load() |
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split_text = splter.split_documents(content) |
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for text in split_text: |
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Pinecone.from_documents([text], embeddings, index_name=index_name) |
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return list_pinecone(index_name) |
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def list_pinecone(index_name): |
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index = pinecone.Index(index_name) |
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stats = index.describe_index_stats() |
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return stats |
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def roleChoice(role): |
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global messages |
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messages = [{"role": "system", "content": role}] |
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return "role:" + role |
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def textGPT(text): |
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global messages |
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messages.append({"role": "user", "content": text}) |
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response = openai.ChatCompletion.create(model="gpt-4", messages=messages) |
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system_message = response["choices"][0]["message"] |
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messages.append(system_message) |
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chats = "" |
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for msg in messages: |
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if msg['role'] != 'system': |
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chats += msg['role'] + ": " + msg['content'] + "\n\n" |
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return chats |
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def fileGPT(prompt, file_obj): |
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global messages |
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file_text = extract_text(file_obj.name) |
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text = prompt + "\n\n" + file_text |
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messages.append({"role": "user", "content": text}) |
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response = openai.ChatCompletion.create(model="gpt-4", messages=messages) |
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system_message = response["choices"][0]["message"] |
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messages.append(system_message) |
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chats = "" |
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for msg in messages: |
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if msg['role'] != 'system': |
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chats += msg['role'] + ": " + msg['content'] + "\n\n" |
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return chats |
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def clear(): |
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global messages |
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messages = [{"role": "system", "content": 'You are a helpful technology assistant.'}] |
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return |
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def show(): |
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global messages |
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chats = "" |
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for msg in messages: |
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if msg['role'] != 'system': |
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chats += msg['role'] + ": " + msg['content'] + "\n\n" |
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return chats |
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with gr.Blocks() as chatHistory: |
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gr.Markdown("Click the Clear button below to remove all the chat history.") |
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clear_btn = gr.Button("Clear") |
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clear_btn.click(fn=clear, inputs=None, outputs=None, queue=False) |
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gr.Markdown("Click the Display button below to show all the chat history.") |
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show_out = gr.Textbox() |
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show_btn = gr.Button("Display") |
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show_btn.click(fn=show, inputs=None, outputs=show_out, queue=False) |
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role = gr.Interface(fn=roleChoice, inputs="text", outputs="text", description = "Choose your GPT roles, e.g. You are a helpful technology assistant. 你是一位 IT 架构师。 你是一位开发者关系顾问。你是一位机器学习工程师。你是一位高级 C++ 开发人员 ") |
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text = gr.Interface(fn=textGPT, inputs="text", outputs="text") |
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pinecone = gr.Interface(fn=process_file, inputs=["text", gr.inputs.File(file_count="directory")], outputs="text") |
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file = gr.Interface(fn=fileGPT, inputs=["text", "file"], outputs="text", description = "Enter prompt sentences and your PDF. e.g. lets think step by step, summarize this following text: 或者 让我们一步一步地思考,总结以下的内容:") |
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demo = gr.TabbedInterface([role, text, file, chatHistory, pinecone], [ "roleChoice", "chatGPT", "fileGPT", "ChatHistory", "Pinecone"]) |
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if __name__ == "__main__": |
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demo.launch(enable_queue=False, auth=lambda u, p: user_db.get(u) == p, |
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auth_message="This is not designed to be used publicly as it links to a personal openAI API. However, you can copy my code and create your own multi-functional ChatGPT with your unique ID and password by utilizing the 'Repository secrets' feature in huggingface.") |
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