fix: use python3 in training Makefile for portability

Refs #680, closes #660

bin/nostr-agent-demo.py

@@ -1,3 +1,4 @@
+#!/usr/bin/env python3
 """
 Full Nostr agent-to-agent communication demo - FINAL WORKING
 """

bin/soul_eval_gate.py

@@ -1,3 +1,4 @@
+#!/usr/bin/env python3
 """
 Soul Eval Gate — The Conscience of the Training Pipeline
 

scripts/captcha_bypass_handler.py

@@ -1,3 +1,4 @@
+#!/usr/bin/env python3
 import json
 from hermes_tools import browser_navigate, browser_vision
 

scripts/diagram_meaning_extractor.py

@@ -1,3 +1,4 @@
+#!/usr/bin/env python3
 import json
 from hermes_tools import browser_navigate, browser_vision
 

scripts/visual_pr_reviewer.py

@@ -1,3 +1,4 @@
+#!/usr/bin/env python3
 import json
 from hermes_tools import browser_navigate, browser_vision
 

training/Makefile

@@ -15,6 +15,7 @@
 MODEL       ?= timmy:v0.1-q4
 BASELINE    ?= hermes3:latest
 OLLAMA_URL  ?= http://localhost:11434
+PYTHON      ?= python3
 OUTPUT      ?= output
 
 # ── Training ──────────────────────────────────────────────────────────
@@ -23,7 +24,7 @@ train-cloud: ## QLoRA fine-tune on cloud GPU (Axolotl)
 	axolotl train axolotl.yaml
 
 train-local: ## LoRA fine-tune on Apple Silicon (MLX)
-	python -m mlx_lm.lora --config mlx-lora.yaml
+	$(PYTHON) -m mlx_lm.lora --config mlx-lora.yaml
 
 # ── Evaluation ────────────────────────────────────────────────────────
 
@@ -45,7 +46,7 @@ vibes: ## Run vibes check — hand-picked prompts, human review
 	@echo "Date: $$(date '+%Y-%m-%d %H:%M')" > $(OUTPUT)/vibes-$(MODEL).md
 	@echo "Model: $(MODEL)" >> $(OUTPUT)/vibes-$(MODEL).md
 	@echo "" >> $(OUTPUT)/vibes-$(MODEL).md
-	@python -c "\
+	@$(PYTHON) -c "\
 	import yaml, subprocess, sys; \
 	prompts = yaml.safe_load(open('data/prompts_vibes.yaml'))['prompts']; \
 	f = open('$(OUTPUT)/vibes-$(MODEL).md', 'a'); \
@@ -69,19 +70,19 @@ vibes: ## Run vibes check — hand-picked prompts, human review
 # ── Data Pipeline ─────────────────────────────────────────────────────
 
 ingest: ## Pull heartbeat trajectories into training data
-	python ingest_trajectories.py \
+	$(PYTHON) ingest_trajectories.py \
 		--trajectories ~/.nexus/trajectories/ \
 		--curated data/curated_dataset.jsonl \
 		--output data/merged_training_data.jsonl
 	@echo "Merged dataset ready. Convert for MLX with: make convert"
 
 curated: ## Regenerate curated exemplar dataset
-	python build_curated.py
+	$(PYTHON) build_curated.py
 	@echo "Curated dataset regenerated."
 
 convert: ## Convert merged dataset to MLX format (train/valid split)
 	@mkdir -p data/mlx_curated
-	python -c "\
+	$(PYTHON) -c "\
 	import json; \
 	lines = open('data/merged_training_data.jsonl').readlines(); \
 	sessions = [json.loads(l) for l in lines]; \