envbert-agent 0.1.1

Agentic environmental due-diligence text classification using EnvBert and LangGraph

-- coding: utf-8 --

"""

EnvBert-Agent

EnvBert-Agent is an agentic AI pipeline for environmental due diligence text classification.

It combines:

• 🧠 EnvBert (domain-specific transformer backbone)
• 🤖 Optional LLM fallback
• 🔁 Agentic routing & confidence arbitration
• 📊 Quality control & explainability
• 🧩 Modular LangGraph orchestration

---

👩‍💻 Authors

• Afreen Aman
• Deepak John Reji

---

🚀 Features

• Environmental domain classification using EnvBert
• Confidence-based fallback to LLM
• Agentic workflow orchestration via LangGraph
• CLI interface for quick usage
• Python SDK interface for integration
• Designed for due diligence, remediation, and compliance workflows

---

📦 Installation

Install from PyPI:

pip install envbert-agent

⚙️ Requirements

• Python 3.9+
• Transformers (version constrained for TensorFlow compatibility)
• TensorFlow (required by EnvBert backbone)

🖥️ CLI Usage

After installation:

envbert-agent "BEHP was detected in groundwater"

Example output:

Label: Contaminated Media
Confidence: 0.87
Route: envbert

🧪 Python Usage

Basic Usage

from envbert_agent import run

text = "BEHP was detected in groundwater"
result = run(text)

print(result)

Direct CLI Invocation from Python

from envbert_agent.cli import main

main(["BEHP was detected in groundwater"])

Graph Edges & Flow

START
  ↓
[preprocess] ────────────────┐
  ↓                           │
[envbert] ────────────────────┤
  ↓                           │
[arbitrate]                   │  Conditional Router:
  ├─ (quality < 0.4)          │      route = "review"
  ├─ (confidence ≥ 0.75) ─────┼──────→ route = "accept"
  └─ (confidence < 0.75) ─────┘      route = "llm"
       ↓
    ┌──────────┬──────────┬──────────┐
    ↓          ↓          ↓
  (review)   (accept)   (llm)
    ↓          ↓          ↓
    │ ─────────→[llm]←─────
            ↓
        [evaluate]
            ↓
        [explain]
            ↓
        [monitor]
            ↓
           END

📜 License

MIT License

See the LICENSE file for details.

⚠️ Notes

• This package depends on the EnvBert backbone.

• Transformers version is constrained for TensorFlow compatibility.

• Future versions may migrate to a PyTorch backend for improved compatibility and lighter installation footprint.