SUBMISSION.md

Build Small Submission Plan

Project

• Space: https://huggingface.co/spaces/build-small-hackathon/tiny-dispatch-coach
• Runtime: https://build-small-hackathon-tiny-dispatch-coach.hf.space/
• Submission collection: https://huggingface.co/collections/build-small-hackathon/tiny-dispatch-coach-build-small-submission-6a2a78cece4ba47b80282176
• Real demo video: https://huggingface.co/datasets/build-small-hackathon/tiny-dispatch-coach-media/blob/main/tiny-dispatch-coach-real-demo.webm
• Public sharing post: https://huggingface.co/spaces/build-small-hackathon/tiny-dispatch-coach/discussions/1
• Trace dataset: https://huggingface.co/datasets/build-small-hackathon/tiny-dispatch-coach-traces
• Track: Backyard AI
• Model: openbmb/MiniCPM5-1B-GGUF
• File: MiniCPM5-1B-Q4_K_M.gguf
• Parameters: 1.08B
• Runtime path: local GGUF through llama-cpp-python, enabled by checkbox

Why It Fits Build Small

Tiny Dispatch Coach solves a narrow operational problem: turn a small delivery sheet and messy dispatcher notes into an auditable route plan. The model does not invent routes. MiniCPM5 parses human instructions into a compact constraint schema, then deterministic code computes time windows, capacity, route splits, late minutes, waiting time, and baseline deltas.

This makes the small model useful because the task is bounded:

• Extract route constraints from natural language notes.
• Keep all route math deterministic and inspectable.
• Run without cloud LLM APIs.
• Use only synthetic demo data.

Bonus Quest Alignment

• OpenBMB Awards: uses openbmb/MiniCPM5-1B-GGUF.
• Off the Grid: no cloud LLM API or external inference service.
• Llama Champion: MiniCPM5 runs through llama-cpp-python when available.
• Field Notes: see FIELD_NOTES.md.
• Sharing is Caring: see agent_trace.json.

Demo Video Script

1. Open the Space and point to the OpenBMB MiniCPM5 badges.
2. Leave the CSV empty so the synthetic sample is used.
3. Read the default dispatcher note: start time, urgent school/clinic stops, fresh produce before lunch, van capacity 18.
4. Click Plan route.
5. Show the parser trace: MiniCPM5 path or explicit deterministic fallback.
6. Show the Dispatch Score:
   • Manual late minutes: 207.
   • Tiny Dispatch Coach late minutes: 0.
   • On-time rate: 100%.
   • Capacity split: 3 trips.
7. Show the driver cards and route map.
8. Close with the privacy stance: synthetic data, no API keys, no customer data, no cloud LLM API.

Social Post Draft

I built Tiny Dispatch Coach for the Build Small Hackathon:

Small delivery teams often have messy notes, tight windows, and a van capacity constraint. This Gradio Space uses a MiniCPM5-ready constraint parser plus a deterministic planner to create auditable driver routes. The OpenBMB MiniCPM5-1B-GGUF path runs locally through llama.cpp when enabled; default fast mode keeps the public CPU Basic demo responsive.

No cloud LLM API. Synthetic demo data only. 1.08B params.

Space: https://huggingface.co/spaces/build-small-hackathon/tiny-dispatch-coach

#BuildSmallHackathon #HuggingFace #Gradio #OpenBMB #MiniCPM

Published share post:

https://huggingface.co/spaces/build-small-hackathon/tiny-dispatch-coach/discussions/1

Demo Video

Real browser-captured demo:

https://huggingface.co/datasets/build-small-hackathon/tiny-dispatch-coach-media/blob/main/tiny-dispatch-coach-real-demo.webm

Submission Package

Public Hugging Face Collection:

https://huggingface.co/collections/build-small-hackathon/tiny-dispatch-coach-build-small-submission-6a2a78cece4ba47b80282176

Final Submission Checklist

• Public Hugging Face Space.
• Gradio app.
• Model under 32B parameters.
• OpenBMB model listed in README metadata.
• Synthetic sample data only.
• No secrets or real customer records.
• Field notes included.
• Agent trace included.
• Record short demo video.
• Publish social post.
• Package Space link, video link, and social post link before the deadline.