LangGraph Crash Course #12 - Reflexion Agent - Building Revisor Chain

Summary

In this section, the focus is on building a 'revisor chain' that updates answers based on critiques and search results. The process involves using the same 'actor prompt template' as before but modifying the first instruction to revise answers with new information. The revised answer includes numerical citations for verification and removes any unnecessary details. A separate class for 'revise answer' is created to handle this process, and tools are piped in to structure the revised response. The video concludes with a preview of the next section, which will address connecting all components using L graph.

Takeaways

• 😀 The section focuses on building a reviser chain, following a similar approach to the responder chain previously discussed.
• 😀 The process for constructing the reviser chain involves reusing the actor prompt template, modifying just the first instruction.
• 😀 The revised instruction asks the model to revise its previous answer using new information, incorporate critiques, and ensure citations are included.
• 😀 The response should be revised to remove unnecessary details and adhere to a word limit of 250 words.
• 😀 The revised answer must include a reference section, which does not count toward the word limit, and should include numerical citations to ensure verifiability.
• 😀 The revisor is tasked with considering the original response, critique, and search results to generate a more refined version of the answer.
• 😀 A new class, called 'revise answer', is introduced to manage the revised response structure, inheriting properties from the answer question model.
• 😀 The revise answer class includes a list for citations that will motivate the updated answer and is structured similarly to the answer question model.
• 😀 Tools are bound to the prompt template, and the revisor chain is set up to use the 'revise answer' schema, ensuring that the response meets the required format.
• 😀 The connection of all components in the system (responder chain, reviser chain, and execution tools) is essential, and integrating these through an L graph will make the process smoother.
• 😀 The tutorial aims to teach the creation of a fully functional chain by gradually building each component, with the next section focusing on executing tools.

Q & A

What is the main focus of this video script?

The main focus of this video script is on building a reviser chain, which revises a previously generated response using critiques and new information. The process is described similarly to a responder chain but includes additional tasks such as adding citations and reference sections.

How is the reviser chain similar to the responder chain?

The reviser chain is built similarly to the responder chain. Both chains reuse the actor prompt template, but the reviser chain focuses on revising a response based on feedback and adding citations, while the responder chain simply generates a response based on the initial prompt.

What is the primary task of the reviser in this context?

The primary task of the reviser is to revise the original answer based on critiques, incorporating new information and ensuring that the response is verifiable through citations. The reviser also removes superfluous information and ensures the revised response does not exceed the word limit.

What is the role of citations in the reviser chain?

Citations play a crucial role in ensuring that the revised answer is verifiable. The reviser must include numerical citations to back up the new information in the revised response, which is also accompanied by a reference section at the end.

What steps are involved in building the reviser chain?

Building the reviser chain involves modifying the responder chain by changing the first instruction to focus on revising the original response. Additionally, a 'revise answer' class is created to inherit base properties and include references, and tools are bound to ensure the revised response is structured correctly.

How is the revised answer generated in the system?

The revised answer is generated by using the previous critique and new information, revising the original response to improve accuracy, conciseness, and clarity. The system also includes a reference section to cite sources and support the revised answer.

Why is it important to remove superfluous information from the answer?

Removing superfluous information helps streamline the answer, making it more focused and concise. It ensures that only the most relevant and valuable information remains, improving clarity and enhancing the overall quality of the response.

What is the purpose of the 'revise answer' class?

The 'revise answer' class is designed to inherit properties from the answer-question schema and include a list of references, which are citations motivating the updated answer. It ensures the revised response follows a structured format and contains the necessary supporting information.

What does the code do after defining the reviser chain?

After defining the reviser chain, the code binds tools to the system to ensure the revised response is based on the correct template. This involves piping the template with the tools, enforcing the use of the 'revise answer' schema, and providing citations for verification.

How does the process of binding tools work in the reviser chain?

Binding tools in the reviser chain involves linking the 'revise answer' schema to the system. This allows the reviser to generate a response based on the specified format and ensures that the revised answer includes citations and references, following the correct structure for the task.