LMIS-ORG/ToolOrchestra_Slime_Agentic_Qwen3_8B

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library_name: transformers license: apache-2.0 license_link: https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE pipeline_tag: text-generation base_model:

• Qwen/Qwen3-8B-Base

ToolOrchestra — agentic/ToolOrchestra/

Our code hub is:https://github.com/LMIS-ORG/slime-agentic/tree/main

Reproduces the core idea of ToolOrchestra: an Orchestrator-Expert multi-agent framework for RL training. A central Orchestrator LLM learns to route tasks to the best specialized expert model and the corresponding tools through multi-turn tool calls. GRPO is applied to the Orchestrator's decision trajectory, enabling it to improve tool-use and routing capabilities without manually annotated intermediate steps.

Architecture

Input question
  │
  ▼
Orchestrator LLM                        ← Decide which tool to call (loss_mask=1)
  │
  └─► for turn in range(max_turns):
        │
        ├─ parse_tool_call()            ← Parse <tool_call> from model output
        │
        ├─ tool call                    ← Call retrieval / external tool (loss_mask=0)
        │    └─ FAISS retrieval service (port 8000)
        │
        ├─ call_expert ──────────────► Expert LLM routing (loss_mask=0)
        │                               └─ specialist models on separate ports
        │
        └─ answer ──────────────────► Final answer → stop loop
  │
  ▼
GenerationOutput
  - token_ids + log_probs  (all turns concatenated)
  - loss_mask: Orchestrator output = 1 / tool result = 0

Results

Model	Dataset	Baseline (Qwen3-8B)	ToolOrchestra (Ours)	Improvement
Qwen3-8B	τ²-Bench	0.278	0.388	+0.110