You are currently viewing Create your own AI Chatbot to help you chat with all documents

Create your own AI Chatbot to help you chat with all documents

When searching for information in a document, you will need a lot of time to read and understand the content of that document. It would be great if there was a chatbot to help you. You just need to give the document to the chatbot, then you can ask it anything. You also don’t need to worry about data being exposed because your chatbot runs completely locally. And especially, you won’t need to code a single line.

To be

To work with the AI ​​model, you need to install Ollama. This is an AI tool designed to run LLMs models locally. Ollama supports multiple platforms from MacOS, Windows to Linux. It allows you to harness the power of AI without depending on external providers like OpenAI, Google…

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Ollama provides APIs for you to interact with LLMs easily. You can download and install Ollama here . Ollama also has many free models available for you to choose from, suitable for many different purposes. You can search for models here . With practical experience, using the model mistralor llama2regular model will yield better results. You can now run and interact with the model as follows:

ollama run mistral

On the first run, Ollama will need to download the model to your computer, which may take some time. After successful download, you will be redirected to the command line window and can chat with the model:

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So you have your own chatbot running locally. But with the initial goal of being able to chat with documents, you will need another application that connects to Ollama’s APIs and provides file storage and processing functionality. There are many options for you, the most popular is privateGPT , but there is another application with more options which is AnythingLLM .

AnythingLLM

AnythingLLM is an open source application that helps you chat with any document. You can connect to models from external providers, or you can combine with Ollama.

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AnythingLLM uses LangChain to process documents. Through many steps, the main content of the document will be converted to vector format and saved in Vectorstore. You can then chat with documents through Retrieval. Details about this process you can see here .

  • Clone AnythingLLM to your device:
git clone https://github.com/Mintplex-Labs/anything-llm anything-llm
  • Application setup:
cd anything-llm

yarn setup

Make sure you have it installed yarnon your machine.

  • Run back-end server:
yarn dev:server
  • Run front-end server:
yarn dev:frontend
  • Run collector:
yarn dev:collector

After the above steps, go to the browser and go to http://localhost:3000, if you see the interface of AnythingLLM then you have successfully installed.

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Chat with documents

After successfully installing Ollama and AnythingLLM, it’s time to combine them together. In the example below, I will create a file my-profile.txtcontaining some of my information as follows:

Hi, my name is Lam.
I am a web developer with 6 years of experience.
I am proficient in Ruby, PHP, and Javascript.
I started my programming career in late 2017.
Prior to that, I worked as a civil engineer for 2 years.

Then, we will provide this file to the chatbot and ask it a few questions related to the above content.

Setup Model

On the main screen of AnythingLLM, click on the settings button on the left bottom of the screen. Then go to the LLM Preference tab , select Ollama, enter and save the information as below:

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The Chat Model Selection section will display the models that Ollama has downloaded. In this case it’s the model mistralbecause we loaded it above.

Setup Embedding

Continue to move down to the Embedding Preference tab and save the information as below:

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Create Chat

Return to the main screen, click New Workspace , enter a name for the workspace as About Me . A chat window will appear, click on the upload a document link to go to the file upload screen:

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AnythingLLM supports many different file formats, you can use direct links from websites. After uploading the file, click Save and Embeded . And now it’s time to see the results:

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Great, the chatbot responded accurately with the content it provided.

Conclusion

So together we have created a chatbot that supports chatting with any document without depending on external providers. You can use it to build a virtual assistant to help answer questions based on the information you provide, along with many other benefits that you can gradually learn and exploit.

Source : https://viblo.asia/p/tu-tao-chatbot-ai-giup-ban-chat-voi-moi-tai-lieu-bXP4WjkoV7G

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