Instructions to use DriptoBhattacharyya/astranexus-mm-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DriptoBhattacharyya/astranexus-mm-encoder with PEFT:
Task type is invalid.
- sentence-transformers
How to use DriptoBhattacharyya/astranexus-mm-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DriptoBhattacharyya/astranexus-mm-encoder") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Add agent trace.json (LangGraph run on fixture)
Browse files- trace.json +74 -0
trace.json
ADDED
|
@@ -0,0 +1,74 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"agent": "AstraNexus",
|
| 3 |
+
"started": "2026-06-14T21:08:30.129791+00:00",
|
| 4 |
+
"finished": "2026-06-14T21:12:01.632546+00:00",
|
| 5 |
+
"graph": [
|
| 6 |
+
"fetch",
|
| 7 |
+
"embed",
|
| 8 |
+
"cluster",
|
| 9 |
+
"label",
|
| 10 |
+
"serialize"
|
| 11 |
+
],
|
| 12 |
+
"steps": [
|
| 13 |
+
{
|
| 14 |
+
"node": "fetch",
|
| 15 |
+
"ts": "2026-06-14T21:08:30.135879+00:00",
|
| 16 |
+
"duration_ms": 2.4,
|
| 17 |
+
"summary": {
|
| 18 |
+
"n_emails": 200,
|
| 19 |
+
"accounts": [
|
| 20 |
+
"alice.deals@gmail.com",
|
| 21 |
+
"alice.personal@gmail.com",
|
| 22 |
+
"alice@gmail.com",
|
| 23 |
+
"alice@startup.io"
|
| 24 |
+
]
|
| 25 |
+
}
|
| 26 |
+
},
|
| 27 |
+
{
|
| 28 |
+
"node": "embed",
|
| 29 |
+
"ts": "2026-06-14T21:11:26.620498+00:00",
|
| 30 |
+
"duration_ms": 176483.8,
|
| 31 |
+
"summary": {
|
| 32 |
+
"shape": [
|
| 33 |
+
200,
|
| 34 |
+
256
|
| 35 |
+
]
|
| 36 |
+
}
|
| 37 |
+
},
|
| 38 |
+
{
|
| 39 |
+
"node": "cluster",
|
| 40 |
+
"ts": "2026-06-14T21:12:01.628038+00:00",
|
| 41 |
+
"duration_ms": 35006.7,
|
| 42 |
+
"summary": {
|
| 43 |
+
"n_clusters": 7,
|
| 44 |
+
"noise": 49
|
| 45 |
+
}
|
| 46 |
+
},
|
| 47 |
+
{
|
| 48 |
+
"node": "label",
|
| 49 |
+
"ts": "2026-06-14T21:12:01.630534+00:00",
|
| 50 |
+
"duration_ms": 1.0,
|
| 51 |
+
"summary": {
|
| 52 |
+
"names": [
|
| 53 |
+
"Cosmic Dust",
|
| 54 |
+
"Weekly Digest",
|
| 55 |
+
"Our Latest",
|
| 56 |
+
"Invoice Thanks",
|
| 57 |
+
"Let Interview",
|
| 58 |
+
"Deploy Failed",
|
| 59 |
+
"Payment Due",
|
| 60 |
+
"Won Limited"
|
| 61 |
+
]
|
| 62 |
+
}
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"node": "serialize",
|
| 66 |
+
"ts": "2026-06-14T21:12:01.632103+00:00",
|
| 67 |
+
"duration_ms": 1.1,
|
| 68 |
+
"summary": {
|
| 69 |
+
"nodes": 200,
|
| 70 |
+
"wormholes": 16
|
| 71 |
+
}
|
| 72 |
+
}
|
| 73 |
+
]
|
| 74 |
+
}
|