Open ai chat bot12/15/2023 ![]() I did this to make the chatbot as factually accurate as possible. As you may have noticed if you’ve looked at the code, I set the temperature of the chatbot to 0. ImportError: DLL load failed while importing interpreter: The specified module could not be found.Once you’ve done that, download the libraries that we’re going to be using by running the following in your terminal: pip3 install langchain flask llama_index gradio openai pandas numpy glob datetimeįinally, once you’ve installed all the necessary libraries, paste in this Python code from our repo into your Python file.įor this tutorial, I’m using the gpt-3.5-turbo OpenAI model, since it’s the fastest and is the most cost efficient. Then, save the file to the location where you created the “docs” folder (in my case, it’s the Desktop).įile “C:\Users\RHASH\OneDrive\Desktop\app.py”, line 1, inįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\gpt_index\_init_.py”, line 14, inįrom gpt_ import LangchainEmbeddingįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\gpt_index\embeddings\langchain.py”, line 6, inįrom import Embeddings as LCEmbeddingsįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\langchain\_init_.py”, line 6, inįrom langchain.agents import MRKLChain, ReActChain, SelfAskWithSearchChainįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\langchain\agents\_init_.py”, line 2, inįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\langchain\agents\agent.py”, line 17, inįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\langchain\chains\_init_.py”, line 16, inįrom _math.base import LLMMathChainįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\langchain\chains\llm_math\base.py”, line 6, inįile “C:\Users\RHASH\AppData\Local\Programs\Python\Python311\Lib\site-packages\numexpr\_init_.py”, line 24, inįrom numexpr.interpreter import MAX_THREADS, use_vml, _BLOCK_SIZE1_ After that, set the file name app.py and change the “Save as type” to “ All types”. Next, click on “File” in the top menu and select “ Save As…”. Inputs=gr.components.Textbox(lines=7, label="Enter your text"),Ģ. Response = index.query(input_text, response_mode="compact") Index = GPTSimpleVectorIndex.load_from_disk('index.json') Index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper) Llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=num_outputs))ĭocuments = SimpleDirectoryReader(directory_path).load_data() Prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit) Once again, I have taken great help from armrrs on Google Colab and tweaked the code to make it compatible with PDF files and create a Gradio interface on top.įrom gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelperįrom langchain.chat_models import ChatOpenAI Now, open a code editor like Sublime Text or launch Notepad++ and paste the below code. Set Up the Software Environment to Train an AI Chatbot Install Python and Pipġ. So go ahead and give it a try in your own language. ![]() Finally, the data set should be in English to get the best results, but according to OpenAI, it will also work with popular international languages like French, Spanish, German, etc. However, if you want to train a large set of data running into thousands of pages, it’s strongly recommended to use a powerful computer.Ĥ. I used a Chromebook to train the AI model using a book with 100 pages (~100MB). However, you can use any low-end computer for testing purposes, and it will work without any issues. Since we are going to train an AI Chatbot based on our own data, it’s recommended to use a capable computer with a good CPU and GPU. If you followed our previous ChatGPT bot article, it would be even easier to understand the process.ģ. So even if you have a cursory knowledge of computers and don’t know how to code, you can easily train and create a Q&A AI chatbot in a few minutes. The guide is meant for general users, and the instructions are explained in simple language. In this article, I’m using Windows 11, but the steps are nearly identical for other platforms.Ģ. ![]() You can train the AI chatbot on any platform, whether Windows, macOS, Linux, or ChromeOS. Notable Points Before You Train AI with Your Own Dataġ. Create ChatGPT AI Bot with Custom Knowledge Base.Add Your Documents to Train the AI Chatbot.Train and Create an AI Chatbot With Custom Knowledge Base.Install OpenAI, GPT Index, PyPDF2, and Gradio Libraries.Set Up the Software Environment to Train an AI Chatbot. ![]()
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