e5e1ad8dee
Give the agent recall of things said beyond the verbatim window, without breaking the RAM-only philosophy — nothing is persisted to disk. - MemoryIndex: a capped, in-memory pool of embedded messages with pure-Python cosine search (no numpy). Retains far more than the rolling transcript so old lines can be surfaced on demand; oldest evicted past the cap to bound RAM. - OllamaEmbedder: local embeddings via nomic-embed-text, on by default and independent of the chat provider (reuses the Ollama host when chat is Ollama). - Bridge: captured room messages (live + backfilled) are embedded on a background worker so a slow embedder can't stall frame draining. On a /ai question the agent retrieves top-k relevant lines, drops weak (<min_score) and windowed-duplicate hits, and prepends them as a clearly-fenced "recalled context" preamble — kept at user role, never elevated to system, so untrusted room text informs without instructing. Falls back to recency-only if the embedder is unreachable. - CLI: --no-rag, --embed-model, --embed-host, --rag-top-k. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
147 lines
6.4 KiB
Python
147 lines
6.4 KiB
Python
"""CLI: run an AI agent that joins a hack-house room.
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Examples
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--------
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# local Ollama (default, recommended)
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python -m cmd_chat.agent 127.0.0.1 3000 --name oracle \
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--password hunter2 --model llama3 --no-tls
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# cloud, opt-in
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python -m cmd_chat.agent 127.0.0.1 3000 --name claude \
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--provider anthropic --model claude-opus-4-6 --password hunter2 --no-tls
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# any OpenAI-compatible endpoint (Groq, Together, local vLLM…)
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python -m cmd_chat.agent 127.0.0.1 3000 --provider openai \
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--base-url https://api.groq.com/openai/v1 --model llama-3.1-70b --password hunter2
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# a named profile from models.toml (provider + model + endpoint + key env)
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python -m cmd_chat.agent 127.0.0.1 3000 --profile groq-llama --password hunter2
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# a custom provider you wrote
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python -m cmd_chat.agent 127.0.0.1 3000 --provider mypkg.mod:MyProvider
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# discovery / preflight (no room join)
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python -m cmd_chat.agent --profile groq-llama --list-models
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python -m cmd_chat.agent --profile groq-llama --check
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"""
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from __future__ import annotations
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import argparse
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import sys
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from .bridge import AgentBridge
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from .profiles import load_profiles, provider_from_profile
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from .providers import OllamaEmbedder, make_provider, preflight
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def _build_provider(args, ap):
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"""Resolve a Provider from either --profile or the explicit flags."""
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if args.profile:
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profiles = load_profiles(args.models_file)
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if args.profile not in profiles:
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known = ", ".join(profiles) or "(none — create models.toml)"
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ap.error(f"unknown profile '{args.profile}'. known: {known}")
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prof = profiles[args.profile]
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provider = provider_from_profile(
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prof, name=args.profile, model=args.model, base_url=args.base_url
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)
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# Profile may also supply non-provider defaults.
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if args.system is None and prof.get("system"):
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args.system = prof["system"]
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if args.context_window == 12 and prof.get("context_window"):
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args.context_window = int(prof["context_window"])
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return provider
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opts: dict = {}
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if args.base_url and (args.provider == "openai" or ":" in args.provider):
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opts["base_url"] = args.base_url
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return make_provider(args.provider, model=args.model, **opts)
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def main() -> None:
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ap = argparse.ArgumentParser(
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prog="cmd_chat.agent", description="hack-house AI agent bridge (PoC)"
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)
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ap.add_argument("server", nargs="?", help="room host (omit with --list-models/--check)")
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ap.add_argument("port", type=int, nargs="?", help="room port")
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ap.add_argument("--name", default="oracle", help="agent's room display name")
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ap.add_argument("--password", default=None, help="room password")
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ap.add_argument("--provider", default="ollama",
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help="ollama | anthropic | openai | module:Class")
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ap.add_argument("--profile", default=None,
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help="named profile from models.toml (overrides --provider/--model)")
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ap.add_argument("--models-file", default=None,
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help="path to models.toml (default: $HH_MODELS_FILE, ./models.toml, ~/.config/hh/models.toml)")
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ap.add_argument("--model", default=None, help="model name (provider default if omitted)")
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ap.add_argument("--base-url", default=None, help="endpoint for openai-compatible providers")
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ap.add_argument("--system", default=None, help="override the system prompt")
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ap.add_argument("--context-window", type=int, default=12,
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help="max prior messages fed to the model per reply")
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ap.add_argument("--token-budget", type=int, default=3000,
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help="approx token cap on the context window (whichever is smaller wins)")
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ap.add_argument("--no-rag", action="store_true",
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help="disable in-RAM semantic recall (recency-only context)")
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ap.add_argument("--embed-model", default="nomic-embed-text",
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help="Ollama model used to embed messages for recall")
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ap.add_argument("--embed-host", default=None,
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help="Ollama host for embeddings (default: chat host or $OLLAMA_HOST)")
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ap.add_argument("--rag-top-k", type=int, default=4,
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help="how many recalled messages to surface per reply")
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ap.add_argument("--list-models", action="store_true",
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help="list models the backend can serve, then exit")
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ap.add_argument("--check", action="store_true",
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help="run a reachability/model preflight, then exit (0 ok, 1 fail)")
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ap.add_argument("--insecure", action="store_true", help="skip TLS cert verification")
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ap.add_argument("--no-tls", action="store_true", help="plain ws/http (local/Tailscale)")
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args = ap.parse_args()
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provider = _build_provider(args, ap)
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# Discovery / preflight modes never join a room.
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if args.list_models:
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discover = getattr(provider, "available_models", None)
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if discover is None:
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ap.error(f"provider '{provider.name}' has no model discovery")
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for m in discover():
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print(m)
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return
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if args.check:
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ok, msg = preflight(provider)
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print(("ok: " if ok else "FAIL: ") + msg, file=sys.stderr if not ok else sys.stdout)
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sys.exit(0 if ok else 1)
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if args.server is None or args.port is None:
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ap.error("server and port are required to join a room")
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# Non-fatal preflight: warn early, but still try (discovery may be blocked
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# while completion works).
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ok, msg = preflight(provider)
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if not ok:
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print(f"⚠ preflight: {msg}", file=sys.stderr)
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# In-RAM semantic recall is on by default and local (Ollama embeddings),
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# independent of which provider answers chat. Reuse the chat host if it's an
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# Ollama provider so a single --host/profile covers both.
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embedder = None
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if not args.no_rag:
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embedder = OllamaEmbedder(
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model=args.embed_model,
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host=args.embed_host or getattr(provider, "host", None),
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)
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bridge = AgentBridge(
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args.server, args.port, name=args.name, provider=provider,
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password=args.password, insecure=args.insecure, no_tls=args.no_tls,
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system_prompt=args.system, context_window=args.context_window,
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token_budget=args.token_budget, embedder=embedder, rag_top_k=args.rag_top_k,
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)
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try:
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bridge.run()
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except KeyboardInterrupt:
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print("\nagent stopped")
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if __name__ == "__main__":
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main()
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