Python Guide
Python is the Forge surface for orchestration, data workflows, ML-adjacent systems, automation, and analyst tooling. Read this tab when the agent lives near notebooks, pipelines, warehouses, embeddings, or evaluation code.
Language perspective
Python users should focus on fast iteration without losing runtime structure. Forge gives Python workflows identity, capability control, provider boundaries, and telemetry so scripts can grow into accountable agents.
Primary surfaces:
forge-py/src/forge/coreforge-py/src/forge/agentforge-py/src/forge/identityforge-py/src/forge/authforge-py/src/forge/mcp- data, memory, embedding, and provider helpers
Follow this path
- Start with Quickstart.
- Read Memory, Embeddings and RAG, and Media.
- Add Agents, Tools, and Capabilities.
- Read Provider Capability Matrix before choosing models.
- Use Examples to map patterns into pipelines.
PYTHONPATH=src pytest
python3 tools/release_gate.py --root .
Contract focus
| Contract | Python reading lens |
|---|---|
| Memory | Keep storage and retrieval tied to identity and telemetry. |
| Embeddings | Treat vector operations as provider-backed runtime work, not side-channel state. |
| Tools | Scope data access tools explicitly with Arsenal ACTs. |
| Providers | Keep model choice configurable and observable. |
| Telemetry | Make pipeline and model steps replayable through spans and audit entries. |
What to read next
Memory →
Runtime memory patterns with identity and capability context.
Embeddings and RAG →
Retrieval workflows without bypassing Forge accountability.
Media →
Multimodal workflows through the same agent contract.
Examples →
Copyable patterns for orchestration and data-heavy agents.
Current guidance
Use Python for data and orchestration, but keep public claims tied to the same release gate as every other SDK.