antoinezambelli/forge

Health v2 · maintenance only

Adoption not part of the score

2227 stars · 174 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Forge is a Python framework providing a reliability layer for self-hosted LLM tool-calling, with guardrails like rescue parsing, retry nudges, and response validation. It can be used as a drop-in proxy server (OpenAI/Anthropic compatible), a WorkflowRunner for structured agent loops, or composable middleware inside your own orchestration loop.

Use cases

• make local 8B models reliable at tool calling
• run multi-step agentic workflows with self-hosted LLMs
• proxy Claude Code or aider through guardrails to a local model
• rescue malformed tool calls from small LLMs
• share one GPU inference slot across multiple agent workflows
• add guardrails to an existing agent orchestration loop
• connect OpenAI-compatible coding tools to Ollama or llama.cpp

When to choose

• you self-host models via Ollama, llama.cpp, Llamafile, or vLLM and need dependable tool calling
• you want a transparent proxy that upgrades existing coding agents without rewrites
• you need structured, constrained agent loops with required steps and validation
• you want composable reliability middleware rather than a full agent orchestrator

When to avoid

• you need multi-agent graphs, DAG planning, or cross-agent coordination
• you only use hosted APIs and don't care about local model reliability
• you want a full coding agent rather than a layer beneath one
• your project requires Python below 3.12

Facets

framework · maturity active

agent-framework llm-inference middleware http-server sdk artificial-intelligence large-language-models self-hosted developer-tools python self-hosted cli cross-platform tool-calling guardrails proxy-server ollama llama-cpp vllm function-calling agentic-workflows local-llm ai-agents

Member repositories

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markdown · JSON · MCP: product_card(name="antoinezambelli/forge")