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Devoxx Greece 2024 Unleashing the GenAI magic: How we built a chatbot for traders with Generative AI
Learn how to build a chatbot for traders using Generative AI, applying Azure OpenAI and Golang, with semantic search, NLP, and ML to generate human-like responses and provide personalized insights.
- GenAI is a type of generative AI that can produce new content and ideas.
- To build a chatbot for traders, the speaker chose GenAI due to its ability to understand and generate human language.
- The chatbot uses semantic search to retrieve relevant news and analysis from XM’s research portal.
- The speaker used Azure OpenAI and Golang to build the chatbot.
- The chatbot uses a combination of natural language processing (NLP) and machine learning (ML) to generate responses to user questions.
- The speaker used RAG (Retrieval-Augmented Generation) to retrieve relevant information and generate responses.
- The chatbot can be trained to produce specific answers based on the user’s question and context.
- The speaker used a cron job to update the vector database every 24 hours to ensure freshness.
- The chatbot uses a combination of LLM (Large Language Model) and GPT (Generative Pre-trained Transformer) to generate responses.
- The speaker used Azure OpenAI’s GPT-4 model to generate responses.
- The chatbot can be used to answer user questions in real-time, such as the current price of a specific instrument.
- The speaker used a system message to provide context to the user’s question and to generate responses.
- The chatbot uses a combination of natural language processing (NLP) and machine learning (ML) to understand and generate human language.
- The speaker used Go concurrency to handle multiple requests simultaneously.
- The chatbot can be used to provide personalized advice to traders based on their individual needs and preferences.
- The speaker used a combination of NLP and ML to analyze user behavior and provide personalized advice.
- The chatbot can be used to analyze user data and provide insights to traders.
- The speaker used a combination of NLP and ML to analyze user data and provide insights to traders.
- The chatbot can be used to generate reports and analysis for traders.
- The speaker used a combination of NLP and ML to generate reports and analysis for traders.
- The chatbot can be used to provide real-time data and analysis to traders.
- The speaker used a combination of NLP and ML to provide real-time data and analysis to traders.