By Houd Fathi - July 8, 2023

If you've been using chatGPT or similar large language models(LLMs), you may have experienced "hallucinations" - instances where the model generates inaccurate responses. To mitigate this issue and obtain more precise answers, particularly in the business sphere, one effective approach is attaching content as context and prompting chatGPT(LLM) to respond based on the provided context. If the answer cannot be found within the context, the model can simply acknowledge that it doesn't know or couldn't find the information.

Climr contextual chatbots provide answers reliant on the given context and can even represent specific characters and adopt distinctive tones of voice. You can develop and distribute these contextual chatbots, all without the need for coding expertise.

The procedure couldn't be easier: provide the context, select the voice tone you want, choose the LLM to generate the response, and hit publish. You also have the option to share the URL of your chatbot.

• Integrate a chatbot URL on your website to provide immediate responses to questions about your product.
• Develop an internal knowledge-based chatbot to answer queries using your internal knowledge documents as context.

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