Initial commit: autonomous AI talk show (Leonard + Charlie)

- Autonomous agent runtime (JSONL + fcntl locking, no token caps) - Moltbook-style prompts: agents share what they built, not scripted turns - Episodes 001-008 transcripts, conversation logs, system prompts - Producer brief for Hermes v0.18
2026-07-09 03:26:37 +00:00
parent e02d1c00ee
commit 772ef4f6fd
38 changed files with 2942 additions and 0 deletions
@@ -0,0 +1,140 @@
+#!/usr/bin/env python3
+"""
+AI Talk Show — Episode Orchestrator
+Manages turn-taking between two autonomous agents (Leonard & Charlie).
+Each agent gets its own system prompt and sees the full conversation history.
+"""
+
+import json
+import time
+import sys
+import requests
+from pathlib import Path
+
+# ── Config ──────────────────────────────────────────────────────────
+BASE_URL = "http://100.64.0.2:39195/v1/chat/completions"
+MODEL = "qwen36-27b-nvfp4-mtp-gguf"
+TEMPERATURE = 0.8
+MAX_TURNS = 8  # 4 exchanges each (Leonard opens)
+MAX_TOKENS_OPENING = 250
+MAX_TOKENS_TURN = 180
+PROJECT_DIR = Path(__file__).parent.parent
+OUTPUT_DIR = PROJECT_DIR / "outputs"
+OUTPUT_DIR.mkdir(exist_ok=True)
+
+# ── Load prompts ────────────────────────────────────────────────────
+LEONARD_SYSTEM = (PROJECT_DIR / "prompts" / "leonard_system.md").read_text().strip()
+CHARLIE_SYSTEM = (PROJECT_DIR / "prompts" / "charlie_system.md").read_text().strip()
+PRODUCER_BRIEF = (PROJECT_DIR / "prompts" / "producer_brief_003.md").read_text().strip()
+
+# ── Helpers ─────────────────────────────────────────────────────────
+def call_agent(system: str, messages: list, max_tokens: int) -> str:
+    """Call the model API with the agent's system prompt and conversation history."""
+    payload = {
+        "model": MODEL,
+        "messages": [{"role": "system", "content": system}] + messages,
+        "max_tokens": max_tokens,
+        "temperature": TEMPERATURE,
+    }
+    resp = requests.post(BASE_URL, json=payload, timeout=120)
+    resp.raise_for_status()
+    data = resp.json()
+    content = data["choices"][0]["message"]["content"].strip()
+    usage = data.get("usage", {})
+    return content, usage
+
+def call_agent_turn(agent_name: str, conversation: list, is_opening: bool) -> dict:
+    """Run one turn for an agent."""
+    system = LEONARD_SYSTEM if agent_name == "Leonard" else CHARLIE_SYSTEM
+    max_tokens = MAX_TOKENS_OPENING if is_opening else MAX_TOKENS_TURN
+
+    # Build conversation history
+    history = []
+    for turn in conversation:
+        speaker = turn["agent"]
+        history.append({"role": "user", "content": f"{speaker}: {turn['content']}"})
+
+    # Leonard's opening: give him the raw brief and let him start naturally
+    if agent_name == "Leonard" and is_opening:
+        history.insert(0, {"role": "user", "content": f"Here's what's new in Hermes v0.18:\n\n{PRODUCER_BRIEF}"})
+
+    content, usage = call_agent(system, history, max_tokens)
+
+    # Word count check
+    word_count = len(content.split())
+    print(f"  {agent_name} turn {len(conversation)+1}: {word_count} words "
+          f"(prompt: {usage.get('prompt_tokens', '?')}, "
+          f"completion: {usage.get('completion_tokens', '?')})", flush=True)
+
+    return {
+        "agent": agent_name,
+        "content": content,
+        "word_count": word_count,
+        "turn": len(conversation) + 1,
+        "tokens": usage,
+    }
+
+# ── Main ────────────────────────────────────────────────────────────
+def main():
+    episode_id = "003"
+    topic = "hermes-v018"
+    print(f"=== AI Talk Show — Episode {episode_id}: {topic} ===\n", flush=True)
+
+    conversation = []
+    turn = 0
+
+    while turn < MAX_TURNS:
+        # Determine speaker: Leonard opens, then alternate
+        if turn == 0:
+            speaker = "Leonard"
+            is_opening = True
+        elif turn % 2 == 1:
+            speaker = "Charlie"
+            is_opening = False
+        else:
+            speaker = "Leonard"
+            is_opening = False
+
+        print(f"\n--- Turn {turn+1}/{MAX_TURNS}: {speaker} ---", flush=True)
+        result = call_agent_turn(speaker, conversation, is_opening)
+        conversation.append(result)
+
+        # Print a short excerpt
+        excerpt = result["content"][:120].replace("\n", " ")
+        print(f"  → {excerpt}...", flush=True)
+
+        turn += 1
+        if turn < MAX_TURNS:
+            time.sleep(0.5)  # Brief pause between turns
+
+    # ── Save transcript ────────────────────────────────────────────
+    transcript_path = OUTPUT_DIR / f"ep{episode_id}_{topic}_transcript.json"
+    transcript_data = {
+        "episode": episode_id,
+        "topic": topic,
+        "turns": len(conversation),
+        "conversation": conversation,
+    }
+    transcript_path.write_text(json.dumps(transcript_data, indent=2))
+    print(f"\n✅ Transcript saved: {transcript_path}", flush=True)
+
+    # ── Save readable transcript ───────────────────────────────────
+    readable_path = OUTPUT_DIR / f"ep{episode_id}_{topic}_readable.txt"
+    lines = []
+    lines.append(f"AI TALK SHOW — Episode {episode_id}\n")
+    lines.append(f"Topic: Hermes v0.18\n")
+    lines.append("=" * 60 + "\n\n")
+    for t in conversation:
+        lines.append(f"**{t['agent']}**\n")
+        lines.append(t["content"] + "\n\n")
+    readable_path.write_text("\n".join(lines))
+    print(f"✅ Readable transcript: {readable_path}", flush=True)
+
+    # ── Word count summary ─────────────────────────────────────────
+    total_words = sum(t["word_count"] for t in conversation)
+    print(f"\n📊 Total: {total_words} words across {len(conversation)} turns", flush=True)
+    estimated_minutes = total_words / 150
+    print(f"   Estimated runtime: {estimated_minutes:.1f} minutes", flush=True)
+
+if __name__ == "__main__":
+    main()