LLM completions and Lean4 theorem proving via scillm...
LLM completions and formal proofs via scillm (per SCILLM_PAVED_PATH_CONTRACT.md).
| Tool | Purpose |
|---|---|
batch.py |
Batch LLM completions via parallel_acompletions |
prove.py |
Lean4 theorem proving via certainly |
# Single completion
python .agents/skills/scillm/batch.py single "What is 2+2?"
# Single with JSON response
python .agents/skills/scillm/batch.py single "Return {answer: number}" --json
# Batch from file
python .agents/skills/scillm/batch.py batch --input prompts.jsonl --json
Single completion:
python .agents/skills/scillm/batch.py single "Your prompt" [--json] [--model MODEL]
Batch completions:
python .agents/skills/scillm/batch.py batch \
--input prompts.jsonl \
--output results.jsonl \
--json \
--concurrency 6
Input JSONL (one per line):
{"prompt": "Summarize..."}
{"prompt": "Translate..."}
Output JSONL:
{"index": 0, "content": "...", "ok": true}
{"index": 1, "error": "timeout", "status": 408}
| Variable | Required |
|---|---|
CHUTES_API_BASE |
Yes |
CHUTES_API_KEY |
Yes |
CHUTES_MODEL_ID |
Yes |
# Prove a claim
python .agents/skills/scillm/prove.py "Prove that n + 0 = n"
# With tactic hints
python .agents/skills/scillm/prove.py "Prove n < n + 1" --tactics omega
# Check availability
python .agents/skills/scillm/prove.py --check
Prove a claim:
python .agents/skills/scillm/prove.py "Your claim" [--tactics simp,omega] [--timeout 120]
Check if ready:
python .agents/skills/scillm/prove.py --check
Success:
{
"ok": true,
"lean4_code": "theorem add_zero (n : â„•) : n + 0 = n := by simp",
"compile_ms": 7406
}
Failure:
{
"ok": false,
"diagnosis": "mathematically false",
"suggestion": "Change to 'Prove that 2 + 2 = 4'"
}
| Tactic | Use for |
|---|---|
simp |
Identities, simplification |
omega |
Integer arithmetic |
ring |
Polynomial algebra |
linarith |
Linear inequalities |
The quick_completion function can be imported by sibling skills:
# Add scillm to path (for sibling skills)
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent / "scillm"))
from batch import quick_completion
# Simple completion
result = quick_completion("What is 2+2?")
# With JSON mode
result = quick_completion("Extract {name, age}", json_mode=True)
# With system prompt
result = quick_completion(
prompt="Translate to French: Hello",
system="You are a translator",
temperature=0.3,
)
Parameters:
| Param | Type | Default | Description |
|---|---|---|---|
prompt |
str | required | User prompt |
model |
str | env var | Model ID |
json_mode |
bool | False | Request JSON response |
max_tokens |
int | 1024 | Max tokens |
temperature |
float | 0.2 | Sampling temperature |
timeout |
int | 30 | Request timeout (s) |
system |
str | None | System prompt |
For more control, use scillm directly:
# Single completion (for one-off calls)
from scillm import acompletion
resp = await acompletion(model=..., messages=[...], api_base=..., api_key=...)
# Batch completions (for parallel processing)
from scillm import parallel_acompletions
reqs = [{"model": MODEL, "messages": [...]}]
results = await parallel_acompletions(reqs, api_base=..., api_key=...)
# Lean4 proofs
from scillm.integrations.certainly import prove_requirement
result = await prove_requirement("Prove n + 0 = n", tactics=["simp"])
See SCILLM_PAVED_PATH_CONTRACT.md for full reference.