langchain
for ai founders, dev teams
Steady0
signal score
1
live items
→ Steady
7-day est. ~0
Why this scored 0
every term, weightedEngagement per hour, normalized against the fastest item on its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities are talking about the same entity
Decays to zero over 14 days
Subtracted once something is big and old — we rank what's next, not what's peaked
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement. Full methodology
Outlook
low confidence · estimate, not a guarantee7-day
~0
range 0–0
14-day
~0
range 0–0
30-day
~0
range 0–0
Signal history
7-day window (free)— — projected trajectory (estimate, not a guarantee)
The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
- 19
@ai-sdk/langchain — The **[AI SDK](https://ai-sdk.dev)** LangChain adapter provides seamless integration between [LangChain](https://langcha
Ai sdk integration — for ai devs
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I Built a Local RAG Assistant with Ollama, ChromaDB and LangChain. Here's What I Learned
Local RAG assistant built — for ai founders, dev teams
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RAG vs Fine-Tuning: What Actually Solves Your Problem?
RAG vs fine-tuning — for ai devs
devtoaiSteady11d ago