March 2024 Plans

[jacoblee93]

(X-posted and adapted from Harrison's Python discussion here)

Hi all! Trying something new here. I wanted to share some of our priorities and roadmap for the upcoming month. We would love feedback on these issues - are we tackling the right things? Are there things that are missing? Are there places you would want to help?

Note that beside these main themes, we will also continue to focus on core things like integrations, chain examples, templates, bug fixes, LangSmith integration etc

Theme 1: Structured Outputs

Continue to document usage of with_structured_output on LLMs
Continue to add with_structured_output to more LLMs that support function calling
Add benchmarks for extraction
Improve extraction use case page
Add extraction use case accelerant (standalone github repo)
Add utilities for constructing few shot example messages
Support streaming of structured outputs in more places
Support retries with context

Theme 2: Retrieval

Improve docs for query analysis
Add query analysis use case accelerant (standalone github repo)
Add abstraction for "index"

Theme 3: Agents

Continue to add more examples of using LangGraph
Specifically, add a few examples of complex chatbots

Theme 4: Documentation

✅ Add feedback buttons for each page
Fix all broken links
Based on feedback left on pages and other feedback, think about how to improve architecture of docs

Theme 5: Streaming improvements

make it easier to implement streaming when creating a custom chat model
add more info to the output of astream_events()

[jacob-israel-turner]

Thanks for the update @jacoblee93!

I appreciate the focus on both structured outputs and agents. I've found both to be remarkably impactful while building my LLM app. I have, however, found virtually zero support for integrating agents and structured outputs together. In fact, I've had to scrap my agent plans because I was unable to make structured output work with it.

Are there any plans to add better support for structured output with agents?