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docs: added Constitutional AI references (#25553)

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Added reference to the source paper.
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Leonid Ganeline 2024-08-20 05:00:58 -07:00 committed by GitHub
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docs/docs/versions/migrating_chains/constitutional_chain.ipynb
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@ -17,6 +17,8 @@
"source": [ "source": [
"[ConstitutionalChain](https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html) allowed for a LLM to critique and revise generations based on [principles](https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.models.ConstitutionalPrinciple.html), structured as combinations of critique and revision requests. For example, a principle might include a request to identify harmful content, and a request to rewrite the content.\n", "[ConstitutionalChain](https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html) allowed for a LLM to critique and revise generations based on [principles](https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.models.ConstitutionalPrinciple.html), structured as combinations of critique and revision requests. For example, a principle might include a request to identify harmful content, and a request to rewrite the content.\n",
"\n", "\n",
"`Constitutional AI principles` are based on the [Constitutional AI: Harmlessness from AI Feedback](https://arxiv.org/pdf/2212.08073) paper.\n",
"\n",
"In `ConstitutionalChain`, this structure of critique requests and associated revisions was formatted into a LLM prompt and parsed out of string responses. This is more naturally achieved via [structured output](/docs/how_to/structured_output/) features of chat models. We can construct a simple chain in [LangGraph](https://langchain-ai.github.io/langgraph/) for this purpose. Some advantages of this approach include:\n", "In `ConstitutionalChain`, this structure of critique requests and associated revisions was formatted into a LLM prompt and parsed out of string responses. This is more naturally achieved via [structured output](/docs/how_to/structured_output/) features of chat models. We can construct a simple chain in [LangGraph](https://langchain-ai.github.io/langgraph/) for this purpose. Some advantages of this approach include:\n",
"\n", "\n",
"- Leverage tool-calling capabilities of chat models that have been fine-tuned for this purpose;\n", "- Leverage tool-calling capabilities of chat models that have been fine-tuned for this purpose;\n",
@ -324,7 +326,7 @@
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