sentence-transformers
English
agentweave_semantic_router
agentweave
agentic-ai
tool-routing
semantic-routing
function-calling
cpu
minilm
pre-inference-routing
Instructions to use sauravsingla08/AgentWeave-Router-MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sauravsingla08/AgentWeave-Router-MiniLM with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sauravsingla08/AgentWeave-Router-MiniLM") 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
Publish AgentWeave Router MiniLM from e4e9dce
Browse files
README.md
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license: apache-2.0
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library_name: sentence-transformers
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pipeline_tag: feature-extraction
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base_model: sentence-transformers/all-MiniLM-L6-v2
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tags:
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- agentweave
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- agentic-ai
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- minilm
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- sentence-transformers
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- pre-inference-routing
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language:
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- en
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---
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# AgentWeave Router MiniLM π§
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This repository is intentionally small: it publishes the AgentWeave routing configuration, route prototypes, and executable router code while reusing the upstream MiniLM encoder at runtime instead of copying its weights.
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## Why this exists
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Tool-rich agents can expose large action spaces to a language model. AgentWeave explores a complementary systems strategy: reduce the candidate action space *before* model reasoning. This model repository provides an experimental semantic routing companion to AgentWeave's default deterministic routing path.
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βΌ
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all-MiniLM-L6-v2
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## Quick start
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```bash
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pip install -r requirements.txt
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python router.py "research the latest protocol changes, verify the sources, and summarize the findings"
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| `router.py` | CPU semantic router implementation |
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| `route_prototypes.json` | Human-readable capability prototypes |
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| `config.json` |
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| `requirements.txt` | Minimal runtime dependencies |
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## Intended use
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- a calibrated confidence model
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- an authorization engine
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- a safety classifier
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- a replacement for downstream function-calling evaluation
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## Limitations
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- the route taxonomy is intentionally compact
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- domain-specific tools may need custom prototypes
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##
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AgentWeave source code and research artifacts are maintained at:
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`https://github.com/sauravsingla/AgentWeave`
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## License
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---
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license: apache-2.0
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tags:
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- agentweave
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- agentic-ai
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- minilm
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- sentence-transformers
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- pre-inference-routing
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- arxiv:2608.23078
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language:
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- en
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datasets:
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- sauravsingla08/AgentWeave-Tool-Routing
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---
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# AgentWeave Router MiniLM π§
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This repository is intentionally small: it publishes the AgentWeave routing configuration, route prototypes, and executable router code while reusing the upstream MiniLM encoder at runtime instead of copying its weights.
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## Artifact type and dependency boundary
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This Hub repository is a **routing artifact**, not a derived MiniLM checkpoint.
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- No MiniLM weights are included in this repository.
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- No fine-tuning, adapter training, quantization, merge, or weight transformation is claimed.
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- `sentence-transformers/all-MiniLM-L6-v2` is downloaded separately at runtime and used as a **frozen encoder dependency**.
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- AgentWeave-specific behavior comes from the route taxonomy, human-readable prototypes, and cosine-ranking logic published here.
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For that reason the Hub metadata intentionally does not declare this repository as a `base_model` derivative or as a standalone SentenceTransformers checkpoint.
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## Why this exists
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Tool-rich agents can expose large action spaces to a language model. AgentWeave explores a complementary systems strategy: reduce the candidate action space *before* model reasoning. This model repository provides an experimental semantic routing companion to AgentWeave's default deterministic routing path.
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β
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βΌ
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all-MiniLM-L6-v2
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frozen 384-d encoder
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β
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ββββββββββββββββ
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βΌ βΌ
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## Quick start
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Clone or download the files in this repository, then run:
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```bash
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pip install -r requirements.txt
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python router.py "research the latest protocol changes, verify the sources, and summarize the findings"
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|---|---|
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| `router.py` | CPU semantic router implementation |
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| `route_prototypes.json` | Human-readable capability prototypes |
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| `config.json` | Frozen encoder dependency and routing configuration |
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| `requirements.txt` | Minimal runtime dependencies |
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## Intended use
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- a calibrated confidence model
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- an authorization engine
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- a safety classifier
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- a standalone MiniLM or SentenceTransformers checkpoint
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- a replacement for downstream function-calling evaluation
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## Limitations
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- the route taxonomy is intentionally compact
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- domain-specific tools may need custom prototypes
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## Related research artifacts
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- Paper: https://arxiv.org/abs/2608.23078
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- Dataset: https://huggingface.co/datasets/sauravsingla08/AgentWeave-Tool-Routing
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- Interactive Space: https://huggingface.co/spaces/sauravsingla08/AgentWeave
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- Source: https://github.com/sauravsingla/agentweave
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## License
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