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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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.. | ||
_static | ||
ecosystem | ||
getting_started | ||
modules | ||
reference | ||
tracing | ||
use_cases | ||
conf.py | ||
deployments.md | ||
ecosystem.rst | ||
gallery.rst | ||
glossary.md | ||
index.rst | ||
make.bat | ||
Makefile | ||
model_laboratory.ipynb | ||
reference.rst | ||
requirements.txt | ||
tracing.md | ||
youtube.md |