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model-interaction-api

@aghyad-deeb/reward_seeker
1
0

Simple API for interacting with locally hosted models via vLLM. Use when you need to chat with a model, send messages, or generate responses from a local model server.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name model-interaction-api
description Simple API for interacting with locally hosted models via vLLM. Use when you need to chat with a model, send messages, or generate responses from a local model server.

Model Interaction API

A simple CLI for interacting with locally hosted models via vLLM.

CLI: python3 .claude/skills/model-interaction-api/scripts/eval_cli.py

Find model ID: curl -s http://localhost:8000/v1/models | python3 -c "import sys,json; print(json.load(sys.stdin)['data'][0]['id'])"

Commands

Command Description
CLI start MODEL_ID --label NAME Start a new session
CLI system "msg" Add a system message
CLI user "msg" Add a user message
CLI assistant "msg" Add an assistant message
CLI tool "output" Add tool output (auto-wrapped in <output> tags)
CLI generate Generate model response (auto-adds to conversation)
CLI show Print full conversation
CLI status Show session info
CLI clear Reset session

Session Checkpointing

Command Description
CLI save [PATH] Save session to checkpoint file (default: sessions/{label}/{date}/)
CLI load PATH Load a previously saved session checkpoint
CLI export PATH Copy the .eval log file to a destination path

Example

CLI=".claude/skills/model-interaction-api/scripts/eval_cli.py"

# Start session
python3 $CLI start "model-name" --label "my_chat"

# Add messages
python3 $CLI system "You are a helpful assistant."
python3 $CLI user "Hello!"

# Generate response
python3 $CLI generate

# Add tool output if model requested a command
python3 $CLI tool "command output here"

# Continue
python3 $CLI generate

# Save checkpoint (for later resumption)
python3 $CLI save

# Or save to specific path
python3 $CLI save /path/to/my_session.json

# Later: load a saved session
python3 $CLI load sessions/my_chat/2025-12-17/session_12-30-00.json

# Export .eval log to another location
python3 $CLI export /path/to/destination/

Logs

Conversations are saved in Inspect format to logs/. View with:

inspect view --log-dir logs/

Session Checkpoints

Session checkpoints are JSON files saved to sessions/ by default. They contain:

  • Full conversation history
  • Model ID and session metadata
  • Path to the associated .eval log file

Use checkpoints to:

  • Resume interrupted sessions
  • Branch conversations from a specific point
  • Archive sessions for later reference