| --- |
| license: apache-2.0 |
| library_name: sklearn |
| pipeline_tag: text-classification |
| tags: |
| - ai-systems |
| - agents |
| - agent-tasks |
| - routing |
| - automation |
| - tool-use |
| - multi-agent |
| --- |
| |
| # Agent Task Classifier |
|
|
| **Agent Task Classifier** is a lightweight reference model that maps short agent-task descriptions to practical operational categories. |
|
|
| It is published under the **ai-systems** handle as a transparent example for agent routing, task decomposition, and AI-system prototyping. |
|
|
| ## Task Labels |
|
|
| - `browser` |
| - `coding` |
| - `communication` |
| - `control` |
| - `data-analysis` |
| - `memory` |
| - `multi-agent` |
| - `planning` |
| - `research` |
| - `retrieval` |
| - `tool-use` |
| - `verification` |
| - `workflow-automation` |
|
|
| ## Examples |
|
|
| Input: |
|
|
| ```text |
| Search the web for recent papers and summarize the findings. |
| ``` |
|
|
| Expected category: |
|
|
| ```text |
| research |
| ``` |
|
|
| Input: |
|
|
| ```text |
| Fix a bug in a Python project and run the tests. |
| ``` |
|
|
| Expected category: |
|
|
| ```text |
| coding |
| ``` |
|
|
| Input: |
|
|
| ```text |
| Require human approval before sending the final message. |
| ``` |
|
|
| Expected category: |
|
|
| ```text |
| control |
| ``` |
|
|
| ## Usage |
|
|
| ```python |
| from joblib import load |
| |
| classifier = load("agent-task-classifier.joblib") |
| |
| text = "Delegate subtasks to specialized agents and merge their results" |
| prediction = classifier.predict([text])[0] |
| |
| print(prediction) |
| ``` |
|
|
| ## Model Architecture |
|
|
| The model uses: |
|
|
| - TF-IDF text features |
| - unigram and bigram features |
| - logistic regression classification |
|
|
| It is intentionally small and easy to inspect. |
|
|
| ## Training Data |
|
|
| The reference model was trained on a small curated set of agent-task descriptions covering: |
|
|
| - research |
| - coding |
| - browser interaction |
| - data analysis |
| - retrieval |
| - communication |
| - workflow automation |
| - planning |
| - verification |
| - memory |
| - tool use |
| - multi-agent coordination |
| - control and approval |
|
|
| ## Intended Use |
|
|
| Suitable for: |
|
|
| - agent-routing demos |
| - task taxonomies |
| - educational examples |
| - workflow prototypes |
| - lightweight agent orchestration experiments |
| - AI-system documentation |
|
|
| ## Limitations |
|
|
| This is a **reference model**, not a production-grade task router. |
|
|
| The training set is intentionally small, so ambiguous or out-of-domain requests may be misclassified. |
|
|
| It should not be used to make medical, legal, financial, safety-critical, or other high-impact decisions. |
|
|
| ## Related Dataset |
|
|
| `ai-systems/ai-system-patterns` |
|
|
| ## Related Models |
|
|
| - `ai-systems/system-router` |
| - `ai-systems/capability-classifier` |
|
|
| ## License |
|
|
| Apache-2.0 |
|
|
