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KnowMyDoc is a GPT3.5 Powered Python-based conversational AI utility that enables you to build a chatbot with your own data sources and web pages. With KnowMyDoc, you can easily create a chatbot that can answer complex questions by utilizing advanced machine learning techniques and natural language processing (NLP) algorithms.
KnowMyDoc is a GPT3.5 powered Python-based conversational AI tool that enables users to build a reference enabled chatbot by utilizing advanced machine learning techniques and natural language processing (NLP) algorithms. The utility is fully containerized and API-driven, which allows for a seamless and rapid chatbot creation experience.
KnowMyDoc leverages the LangChain library for LLM prompt engineering and conversation chaining. Users can easily customize the chatbot's prompts and personalize its responses based on the context and tone of the conversation. KnowMyDoc's LLM-based approach ensures that the chatbot can maintain a consistent and coherent conversation even when dealing with large amounts of data and provide relevant sources per response. The chatbots also remain in the confines of provided knowledge.
In addition, KnowMyDoc utilizes the Chroma vector similarity search engine to enable fast and efficient lookup of relevant data. By creating embeddings of users' documents and web pages, KnowMyDoc can quickly identify and retrieve the most relevant information for the user's queries.
Other features of KnowMyDoc include:
Before you can use the utility, you need to set up the configuration file. The configuration file is a YAML file that contains the following options:
To use this utility:
git clone https://github.com/jainsid24/know-my-doc
docker build -t know-my-doc:latest .
docker run -p 5001:5001 know-my-doc
curl --header "Content-Type: application/json" \
--request POST \
--data '{"question": "When was JWST launched?"}' \
http://<pods-ip-address>:5001/api/chat
If you find a bug or have an idea for a new feature, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.