community: add Valthera integration

[vselvarajijay]

**Description:**  
This PR integrates Valthera into LangChain, introducing an framework designed to send highly personalized nudges by an LLM agent. This is modeled after Dr. BJ Fogg's Behavior Model. This integration includes:

- Custom data connectors for HubSpot, PostHog, and Snowflake.
- A unified data aggregator that consolidates user data.
- Scoring configurations to compute motivation and ability scores.
- A reasoning engine that determines the appropriate user action.
- A trigger generator to create personalized messages for user engagement.

**Issue:**  
N/A

**Dependencies:**  
N/A

**Twitter handle:**  
- `@vselvarajijay`

**Tests and Docs:**  
- `docs/docs/integrations/tools/valthera` 
- `https://github.com/valthera/langchain-valthera/tree/main/tests`

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Name	Status	Preview	Comments	Updated (UTC)
langchain	✅ Ready (Inspect)	Visit Preview	💬 Add feedback	Mar 9, 2025 9:19pm

[vselvarajijay]

Hey @ccurme - I would really appreciate a review on my first PR to LangChain. Happy to make any refinements if I missed anything. Appreciate the review and feedback! 🙂

[ccurme]

Thanks for this. I left some in-line comments on the provider page. Remaining things to do:

• Add langchain-valthera to the package registry.
• Revert changes to the integration template in langchain-cli and uv.lock.
• Pypi page has some issues:
  • It documents ChatValthera, ValtheraEmbeddings, and other abstractions that do not appear to exist.
  • The homepage is the langchain monorepo instead of https://github.com/valthera/valthera.

[vselvarajijay]

@ccurme Thanks for the review! It looks like I had some old templates there, I cleared out the abstractions I wasn’t implementing.

1. langchain-valthera is now added to the package registry
2. Reverted template in langchain-cli and uv.lock
3. Fixed Pypi page:
   1. Removed references to unimplemented abstractions
   2. Fixed Homepage link
   3. Fixed Release Notes link
   4. Fixed Repository link
   5. Fixed Source code link
4. Corrected docs/docs/integrations/providers/valthera.mdx

[ccurme]

(nit) most likely to what?

[vselvarajijay]

Hmm yeah good call. Hopefully this is better:

Enable AI agents to engage users when they're most likely to respond.

[ccurme]

Suggest removing this and just keeping the langgraph example.

See the admonition on the API reference for create_react_agent here.

[vselvarajijay]

Ok - cleared out the LangGraph examples and only keeping LangChain

[vselvarajijay]

Hey @ccurme - a few more fixes on this PR as you suggested also a couple others I wanted to improve:

• Cleaned up integration tools doc
• Cleaned up provider doc
• Fixed up project structure of langchain-valthera (moved package to root of repo)
• Published new langchain-valthera package with updated links

Let me know if you think this is can be a good starting place for the Valthera tool. There is quite a bit more I would like to iterate on with the developer experience and capabilities that can help LLM Agents engage with people.