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Nahuel Defossé
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fix: pre-commit trailing whitespace issues
Signed-off-by: Nahuel Defossé <nahuel.deofsse@ibm.com>
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.github/actionlint-config.yaml

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rules:
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# Enable all rules by default
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all: true
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# Disable specific rules if needed
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# actions-have-safe-quotes: disable
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# expression-syntax: disable
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# Enable shellcheck for run steps
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enabled: true
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# Pyflakes configuration
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# Pyflakes configuration
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pyflakes:
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enabled: false

CONTRIBUTING.md

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```bash
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uv run pytest
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```
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Also, to ensure the [version is correctly computed from Git tags](#versioning-scheme)
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try running:
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```bash
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uvx --with uv-dynamic-versioning hatchling version
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```
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## Pre-commit Hooks
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We use pre-commit hooks to ensure code quality and consistency. These hooks automatically run checks before each commit.
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### Running Tests with Coverage
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**Code coverage** measures the percentage of your codebase that is exercised by tests.
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It's an important metric that helps you understand how thoroughly your how much code
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**Code coverage** measures the percentage of your codebase that is exercised by tests.
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It's an important metric that helps you understand how thoroughly your how much code
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is not exercised by your tests.
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README.md

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```bash
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uv pip install agentics-py
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```
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set up your .env using the required parameters for your LLM provider of choice. Use [.env_sample](.env_sample) as a reference.
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set up your .env using the required parameters for your LLM provider of choice. Use [.env_sample](.env_sample) as a reference.
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Find out more
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👉 **Getting Started**: [docs/getting_started.md](docs/getting_started.md)
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## 📘 Documentation and Notebooks
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Complete documentation available [here](./docs/index.md)
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Complete documentation available [here](./docs/index.md)
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| Notebook | Description |
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|---|---|
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## 👥 Authors
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**Project Lead**
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**Project Lead**
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- Alfio Massimiliano Gliozzo (IBM Research) — gliozzo@us.ibm.com
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**Core Contributors**
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- Nahuel Defosse (IBM Research) — nahuel.defosse@ibm.com
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- Junkyu Lee (IBM Research) — Junkyu.Lee@ibm.com
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- Naweed Aghmad Khan (IBM Research) — naweed.khan@ibm.com
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- Christodoulos Constantinides (IBM Watson) — Christodoulos.Constantinides@ibm.com
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- Mustafa Eyceoz (Red Hat) — Mustafa.Eyceoz@partner.ibm.com
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**Core Contributors**
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- Nahuel Defosse (IBM Research) — nahuel.defosse@ibm.com
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- Junkyu Lee (IBM Research) — Junkyu.Lee@ibm.com
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- Naweed Aghmad Khan (IBM Research) — naweed.khan@ibm.com
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- Christodoulos Constantinides (IBM Watson) — Christodoulos.Constantinides@ibm.com
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- Mustafa Eyceoz (Red Hat) — Mustafa.Eyceoz@partner.ibm.com
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---
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## 🧠 Conceptual Overview
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Most “agent frameworks” let untyped text flow through a pipeline. Agentics flips that: **types are the interface**.
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Most “agent frameworks” let untyped text flow through a pipeline. Agentics flips that: **types are the interface**.
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Workflows are expressed as transformations between structured states, with predictable schemas and composable operators.
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Because every step is a typed transformation, you can **compose** workflows safely (merge and compose types/instances, chain transductions, and reuse `@transducible` functions) without losing semantic structure.
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Because every step is a typed transformation, you can **compose** workflows safely (merge and compose types/instances, chain transductions, and reuse `@transducible` functions) without losing semantic structure.
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Agentics makes it natural to **scale out**: apply transformations over collections with async `amap`, and aggregate results with `areduce`.
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Agentics implements **Logical Transduction Algebra**, described in:
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- Alfio Gliozzo, Naweed Khan, Christodoulos Constantinides, Nandana Mihindukulasooriya, Nahuel Defosse, Junkyu Lee.
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*Transduction is All You Need for Structured Data Workflows* (August 2025).
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- Alfio Gliozzo, Naweed Khan, Christodoulos Constantinides, Nandana Mihindukulasooriya, Nahuel Defosse, Junkyu Lee.
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*Transduction is All You Need for Structured Data Workflows* (August 2025).
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arXiv:2508.15610 — https://arxiv.org/abs/2508.15610
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agentics_full_course/project_submission_guidelines.md

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Create a **5-minute recorded video** presenting your project.
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- Introduce the project goals, methods, and key results.
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- Optionally include a demo or short code walkthrough with slides.
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- Introduce the project goals, methods, and key results.
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- Optionally include a demo or short code walkthrough with slides.
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- You will present the same video **in person** during the student workshop.
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---
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Schedule a meeting with professors **at least two weeks before the final submission** to receive feedback on:
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- The draft of your short paper
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- Your runnable code and documentation
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- The draft of your short paper
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- Your runnable code and documentation
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- Your recorded video presentation
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## ✅ Submission Checklist
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- [ ] Conference-style project paper (PDF)
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- [ ] Runnable code in `applications/<project_name>`
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- [ ] `README.md` with install/test instructions
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- [ ] Documentation in `docs/` folder
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- [ ] 5-minute recorded presentation video
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- [ ] Faculty feedback meeting completed
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- [ ] Conference-style project paper (PDF)
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- [ ] Runnable code in `applications/<project_name>`
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- [ ] `README.md` with install/test instructions
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- [ ] Documentation in `docs/` folder
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- [ ] 5-minute recorded presentation video
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- [ ] Faculty feedback meeting completed
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---
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src/agentics/core/async_executor.py

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async def _execute(self, input: str) -> BaseModel:
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instructions = f"""
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You are a Logical Transducer. Your goal is to generate a JSON object that strictly
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You are a Logical Transducer. Your goal is to generate a JSON object that strictly
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conforms to the Output Pydantic schema below:
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{self.atype.model_json_schema()}

src/agentics/core/transducible_functions.py

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target_ag_template.instructions = f"""
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===============================================
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TASK :
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TASK :
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Input Type: {SourceModel.__name__}
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Input Type: {SourceModel.__name__}
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INSTRUCTIONS:
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instructions=f"""
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{type.model_json_schema()}.
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Generate list of {n_instances} random instances of the following type
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{type.model_json_schema()}.
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Try to fill most of the attributed for each generated instance as possible
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""",
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llm=llm,

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