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I would like to contribute with a jupyter notebook example implementation of an AI Sales Agent using `langchain`. The bot understands the conversation stage (you can define your own stages fitting your needs) using two chains: 1. StageAnalyzerChain - takes context and LLM decides what part of sales conversation is one in 2. SalesConversationChain - generate next message Schema: https://images-genai.s3.us-east-1.amazonaws.com/architecture2.png my original repo: https://github.com/filip-michalsky/SalesGPT This example creates a sales person named Ted Lasso who is trying to sell you mattresses. Happy to update based on your feedback. Thanks, Filip https://twitter.com/FilipMichalsky |
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agent_simulations | ||
agents | ||
autonomous_agents | ||
chatbots | ||
code | ||
evaluation | ||
question_answering | ||
agent_simulations.md | ||
apis.md | ||
autonomous_agents.md | ||
chatbots.md | ||
code.md | ||
evaluation.rst | ||
extraction.md | ||
personal_assistants.md | ||
question_answering.md | ||
summarization.md | ||
tabular.md |