Updated LLM Request node with improved UI, support for A Thousand Words VLM server, and other tweaks.

.env.example

@@ -50,6 +50,12 @@ OPENAI_COMPATIBLE_API_KEY=
 CLAUDE_CLI=
 CODEX_CLI=
 
+# --- A Thousand Words ---------------------------------------------------------
+# Local captioning server (server.bat). Only needed if it is not on the
+# default port.
+# default http://127.0.0.1:8585
+ATHOUSANDWORDS_URL=
+
 # --- Sanctum -------------------------------------------------------------------
 # Server address (http://host:port)
 SANCTUM_URL=

README.md

@@ -141,7 +141,7 @@ Visual bounding-box for Ideogram 4 with added automatic string input for each re
 Automatically generates random Ideogram 4 json-structured compositions with dictionary-sourced descriptions.
 <img width="2162" height="580" alt="image" src="https://github.com/user-attachments/assets/72b2eeeb-8d12-4525-991b-b284fd13d60d" />
 
-## ✨🧠 [LLM Request](./README/llm_api.md)
+## ✨ [LLM Request](./README/llm_request.md)
 
 One node for every LLM: ChatGPT, Claude, Gemini, Grok, Groq, OpenRouter, Mistral, DeepSeek, Ollama / LM Studio / any OpenAI-compatible server on your PC or your network, and your Claude Code or Codex subscription. Model browser, live streaming preview, vision, reasoning control, and live config support.
 

README/llm_request.md

@@ -1,4 +1,4 @@
-# ✨🧠 LLM Request
+# ✨ LLM Request
 
 One node for every language model: ChatGPT, Claude, Gemini, Grok, Groq,
 OpenRouter, Mistral, DeepSeek, local servers like Ollama and LM Studio (on

__init__.py

@@ -10,7 +10,7 @@ from .nodes.groq_api_llm import GroqAPILLM
 from .nodes.groq_api_vlm import GroqAPIVLM
 from .nodes.groq_api_alm_transcribe import GroqAPIALMTranscribe
 #from .nodes.groq_api_alm_translate import GroqAPIALMTranslate
-from .nodes.llm_api import LLMAPI
+from .nodes.llm_request import LLMAPI
 from .nodes.tiktoken_tokenizer import TiktokenTokenizer
 from .nodes.string_cleaning import StringCleaning
 from .nodes.generate_negative_prompt import GenerateNegativePrompt

nodes/__init__.py

@@ -5,7 +5,7 @@ from .get_file_path import GetFilePath
 from .groq_api_llm import GroqAPILLM
 from .groq_api_vlm import GroqAPIVLM
 from .groq_api_alm_transcribe import GroqAPIALMTranscribe
-from .llm_api import LLMAPI
+from .llm_request import LLMAPI
 from .tiktoken_tokenizer import TiktokenTokenizer
 from .string_cleaning import StringCleaning
 from .lora_tag_loader import LoraTagLoader

nodes/llm/DefaultEndpoints.json

@@ -30,7 +30,7 @@
             "description": "Any OpenAI-compatible server: llama.cpp, vLLM, KoboldCpp, text-generation-webui, LocalAI, Jan… Set OPENAI_COMPATIBLE_URL in .env (usually ending in /v1)."
         },
         {
-            "name": "Local Claude Code Subscription",
+            "name": "Claude Code Subscription",
             "provider": "claude_cli",
             "command": "${CLAUDE_CLI:-claude}",
             "options": {
@@ -39,7 +39,7 @@
             "description": "Runs the Claude Code CLI on this PC (claude -p) with your Claude subscription. Install Claude Code and sign in once by running `claude` in a terminal. Empty model uses Claude Code's default."
         },
         {
-            "name": "Local Codex Subscription",
+            "name": "Codex Subscription",
             "provider": "codex_cli",
             "command": "${CODEX_CLI:-codex}",
             "options": {
@@ -117,6 +117,12 @@
             "default_model": "deepseek-chat",
             "description": "DeepSeek's API. Key from platform.deepseek.com."
         },
+        {
+            "name": "A Thousand Words",
+            "provider": "athousandwords",
+            "base_url": "${ATHOUSANDWORDS_URL:-http://127.0.0.1:8585}",
+            "description": "A Thousand Words running on this PC (server.bat). A dedicated image/video captioning server: requires images or a video. No key needed."
+        },
         {
             "name": "Sanctum",
             "provider": "openai",

nodes/llm/UserEndpoints.example.json

@@ -1,5 +1,5 @@
 {
-    "_readme": "Your own endpoints for the ✨🧠 LLM Request node. Copied to UserEndpoints.json on first run; that copy is git-ignored and survives updates. Entries here are added to the built-in list; one with the same name as a built-in replaces it, and \"enabled\": false hides it. Never paste keys or private addresses here: put them in the .env file in the pack root and reference them as ${VAR}. Press R in ComfyUI (refresh node definitions) after editing.",
+    "_readme": "Your own endpoints for the ✨ LLM Request node. Copied to UserEndpoints.json on first run; that copy is git-ignored and survives updates. Entries here are added to the built-in list; one with the same name as a built-in replaces it, and \"enabled\": false hides it. Never paste keys or private addresses here: put them in the .env file in the pack root and reference them as ${VAR}. Press R in ComfyUI (refresh node definitions) after editing.",
     "endpoints": [
         {
             "name": "My llama.cpp box",

nodes/llm_request.py

@@ -101,12 +101,12 @@ class LLMAPI(io.ComfyNode):
 
         return io.Schema(
             node_id="MNeMiC_LLMAPI",
-            display_name="✨🧠 LLM Request",
+            display_name="✨ LLM Request",
             category="⚡ MNeMiC Nodes",
-            description="Sends a prompt, and optionally images, to any LLM: ChatGPT, Claude, Gemini, Grok, Groq, OpenRouter, or Ollama and LM Studio on this PC or your network.",
+            description="Sends a prompt, and optionally images or a video, to any LLM: ChatGPT, Claude, Gemini, Grok, Groq, OpenRouter, A Thousand Words, or Ollama and LM Studio on this PC or your network.",
             search_aliases=["llm", "chat", "ollama", "openai", "chatgpt", "gpt", "claude", "anthropic", "gemini",
                             "grok", "xai", "groq", "openrouter", "lm studio", "llama.cpp", "vllm", "vlm", "prompt generator",
-                            "universal llm api"],
+                            "universal llm api", "a thousand words", "caption", "video caption"],
             inputs=[
                 io.Combo.Input("endpoint", options=names, default=names[0],
                                tooltip="Which server to talk to. Endpoints are defined in nodes/llm/*.json; keys and private addresses come from .env and are never saved in the workflow."),
@@ -120,6 +120,8 @@ class LLMAPI(io.ComfyNode):
                                 tooltip="The request itself: what you want the model to write, rewrite or describe. May be empty: the system message or preset is then sent on its own."),
                 io.Image.Input("images", optional=True,
                                tooltip="Images to send along with the prompt, for vision models. Every image in the batch is sent."),
+                io.Video.Input("video", optional=True,
+                              tooltip="A Thousand Words only: a video to caption instead of, or alongside, images. Which models accept video depends on the server's own model list."),
                 io.Float.Input("temperature", default=0.8, min=0.0, max=2.0, step=0.05,
                                tooltip="Randomness. Low is focused and repeatable, high is varied and creative. Dropped automatically for models that only allow their default."),
                 io.Combo.Input("reasoning", options=REASONING_LEVELS, default="default", advanced=True,
@@ -167,7 +169,7 @@ class LLMAPI(io.ComfyNode):
     async def execute(cls, endpoint, model, preset, system_message, user_input, temperature,
                       reasoning="default", max_tokens=0, top_p=1.0, seed=42, stop="", json_mode=False,
                       unload_model_after=False, context_length=0, free_comfy_vram=False, max_retries=2,
-                      raise_on_error=True, custom_endpoint="", images=None) -> io.NodeOutput:
+                      raise_on_error=True, custom_endpoint="", images=None, video=None) -> io.NodeOutput:
         node_id = cls.hidden.unique_id if cls.hidden else None
         client_id = _current_client_id()
         console_log = is_llm_console_log_enabled()
@@ -180,7 +182,7 @@ class LLMAPI(io.ComfyNode):
             if raise_on_error:
                 # from None: the chained original error would otherwise be
                 # printed in ComfyUI's traceback.
-                raise RuntimeError(f"✨🧠 LLM Request — {message}") from None
+                raise RuntimeError(f"✨ LLM Request — {message}") from None
             return io.NodeOutput("", "", False, message,
                                  ui={"mnemic_llm": [{"ok": False, "error": message, "status": status}]})
 
@@ -196,6 +198,8 @@ class LLMAPI(io.ComfyNode):
         ep = ep_config.resolve()
         if not ep.ok:
             return fail(f"{endpoint}: {' '.join(ep.problems)}", "not configured")
+        if video is not None and ep_config.provider != "athousandwords":
+            return fail(f"{endpoint} can't take a video; only A Thousand Words can.")
 
         model = (model or "").strip() or ep_config.default_model
         # Local and network servers (Ollama, LM Studio, llama.cpp…) usually
@@ -231,7 +235,10 @@ class LLMAPI(io.ComfyNode):
             caption_block = "\n\n".join(f"[Image {i + 1} description]: {d}" for i, d in enumerate(descriptions) if d)
             user_input = f"{caption_block}\n\n{user_input}".strip() if user_input else caption_block
             pil_images = []
-        if not user_input and not pil_images:
+        has_media = bool(pil_images) or video is not None
+        if ep_config.provider == "athousandwords" and not has_media:
+            return fail("A Thousand Words requires at least one image or a video.")
+        if not user_input and not has_media:
             if not system_message:
                 return fail("There is nothing to send: system_message, user_input and images are all empty.")
             # Instructions alone are a valid request; most APIs need a user
@@ -243,6 +250,7 @@ class LLMAPI(io.ComfyNode):
             system=system_message,
             user=user_input,
             images=pil_images,
+            videos=[video] if video is not None else [],
             temperature=temperature,
             top_p=top_p,
             max_tokens=max_tokens,

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-mnemic-nodes"
-description = "Added LLM Request node and made the wildcard processor node show a preview, and colorize special inputs"
-version = "3.0.3"
+description = "Updated LLM Request node with improved UI, support for A Thousand Words VLM server, and other tweaks."
+version = "3.0.4"
 license = { file = "LICENSE" }
 dependencies = ["configparser", "groq", "transformers", "torch", "tiktoken", "imageio", "tqdm", "piexif", "requests", "colorama", "opencv-python", "python-dotenv"]
 

utils/llm_cli.py

@@ -397,27 +397,99 @@ def run_cli_chat(provider, command, req, result, **kwargs):
         raise CLIError(f"could not start the CLI ({type(e).__name__})", status="cli error") from None
 
 
+# Every model here is current-generation and accepts image input, so all are
+# marked vision: True. static: True marks a fixed list, not fetched live, for
+# the picker's "*" indicator. Only the rolling alias is listed for each model
+# (not also its current pinned full name, e.g. claude-sonnet-5): both resolve
+# to the same model today, and the alias is the one that keeps working as
+# Anthropic ships new versions.
 CLAUDE_MODELS = [
-    {"id": "sonnet", "detail": "alias for claude-sonnet-5"},
-    {"id": "claude-sonnet-5", "detail": "Sonnet 5"},
-    {"id": "opus", "detail": "alias for claude-opus-5-5"},
-    {"id": "claude-opus-5-5", "detail": "Opus 5.5"},
-    {"id": "haiku", "detail": "alias for claude-haiku-4-5-20251001"},
-    {"id": "claude-haiku-4-5-20251001", "detail": "Haiku 4.5"},
-    {"id": "fable", "detail": "alias for claude-fable-5-1"},
-    {"id": "claude-fable-5-1", "detail": "Fable 5.1"},
+    {"id": "sonnet", "detail": "", "vision": True, "static": True},
+    {"id": "opus", "detail": "", "vision": True, "static": True},
+    {"id": "haiku", "detail": "", "vision": True, "static": True},
+    {"id": "fable", "detail": "", "vision": True, "static": True},
 ]
 # Codex has no equivalent of `claude` picking up new releases under a fixed
-# alias, and no command to list what a given install supports (openai/codex#8871
-# asks for exactly this); these are current model names, not a live list.
+# alias. Its app-server does expose a live model/list RPC (see
+# _codex_model_list_rpc below), so this is only the fallback when that can't
+# be reached (CLI not installed, too old to speak the protocol, timed out…).
+# Matched against codex-cli 0.157.0's own live catalog, not a guess.
 CODEX_MODELS = [
-    {"id": "gpt-5.2-codex", "detail": "current Codex model"},
-    {"id": "gpt-5.1-codex-max", "detail": "previous Codex model"},
-    {"id": "gpt-5.1-codex-mini", "detail": "smaller, faster"},
+    {"id": "gpt-6-astra", "detail": "", "vision": True, "static": True},
+    {"id": "gpt-6-sol", "detail": "", "vision": True, "static": True},
+    {"id": "gpt-6-luna", "detail": "", "vision": True, "static": True},
+    {"id": "gpt-5.6-sol", "detail": "", "vision": True, "static": True},
+    {"id": "gpt-5.6-terra", "detail": "", "vision": True, "static": True},
+    {"id": "gpt-5.6-luna", "detail": "", "vision": True, "static": True},
+    {"id": "gpt-5.5", "detail": "", "vision": True, "static": True},
 ]
 
 
-def list_cli_models(provider):
-    """Neither CLI can list what a given install actually supports; these are
-    known model names/aliases, not fetched live."""
-    return list(CLAUDE_MODELS) if provider == CLAUDE else list(CODEX_MODELS)
+def _codex_model_list_rpc(command, timeout=6):
+    """The live model catalog from Codex's own `app-server` JSON-RPC daemon
+    (method "model/list"), so the picker matches what this install actually
+    offers. None on any failure (not installed, too old to speak this
+    protocol, no reply in time…).
+    """
+    try:
+        with _work_dir() as cwd:
+            proc = _popen([command, "app-server"], CODEX, cwd)
+            lines = queue.Queue()
+            threading.Thread(target=_read_lines, args=(proc.stdout, lines), daemon=True).start()
+            try:
+                proc.stdin.write((json.dumps({
+                    "jsonrpc": "2.0", "id": 1, "method": "initialize",
+                    "params": {"clientInfo": {"name": "ComfyUI-mnemic-nodes", "version": "1.0"}},
+                }) + "\n").encode())
+                proc.stdin.write((json.dumps({
+                    "jsonrpc": "2.0", "id": 2, "method": "model/list", "params": {},
+                }) + "\n").encode())
+                proc.stdin.flush()
+
+                deadline = time.monotonic() + timeout
+                while time.monotonic() < deadline:
+                    try:
+                        raw = lines.get(timeout=0.25)
+                    except queue.Empty:
+                        continue
+                    if raw is None:
+                        return None
+                    try:
+                        msg = json.loads(raw.decode("utf-8", errors="replace"))
+                    except ValueError:
+                        continue
+                    if msg.get("id") == 2:
+                        return (msg.get("result") or {}).get("data")
+                return None
+            finally:
+                _terminate(proc)
+    except OSError:
+        return None
+
+
+def _codex_models_from_catalog(data):
+    models = []
+    for m in data or []:
+        if m.get("hidden"):
+            continue
+        model_id = m.get("id") or m.get("model")
+        if not model_id:
+            continue
+        vision = "image" in (m.get("inputModalities") or ["text", "image"])
+        models.append({"id": model_id, "detail": "", "vision": vision})
+    return models
+
+
+def list_cli_models(provider, command=""):
+    """Claude Code has no documented way to enumerate installed models, so
+    CLAUDE_MODELS is a fixed list of current aliases/names. Codex exposes a
+    live catalog through its own app-server; that is queried directly, and
+    CODEX_MODELS is only the fallback when it can't be reached.
+    """
+    if provider == CLAUDE:
+        return list(CLAUDE_MODELS)
+    if command:
+        models = _codex_models_from_catalog(_codex_model_list_rpc(command))
+        if models:
+            return models
+    return list(CODEX_MODELS)

utils/llm_endpoints.py

@@ -25,7 +25,7 @@ DEFAULT_ENDPOINTS_FILE = os.path.join(LLM_DIR, "DefaultEndpoints.json")
 USER_ENDPOINTS_FILE = os.path.join(LLM_DIR, "UserEndpoints.json")
 USER_ENDPOINTS_EXAMPLE = os.path.join(LLM_DIR, "UserEndpoints.example.json")
 
-PROVIDERS = ("openai", "anthropic", "ollama", "claude_cli", "codex_cli")
+PROVIDERS = ("openai", "anthropic", "ollama", "claude_cli", "codex_cli", "athousandwords")
 CLI_PROVIDERS = ("claude_cli", "codex_cli")
 CUSTOM_ENDPOINT_NAME = "Custom Endpoint - WARNING"
 

utils/llm_providers.py

@@ -12,6 +12,10 @@ Each adapter turns a ChatRequest into (url, headers, body), and turns the
 reply — whole or streamed — back into text. `run_chat` does the HTTP around it:
 retries, backoff, live streaming, interrupts, and dropping parameters an
 endpoint rejects.
+
+`athousandwords` is not a chat API (one multipart POST /caption per request,
+no streaming, images/video only) and bypasses the adapter's build/parse: see
+_run_athousandwords. Its adapter only serves list_models.
 """
 
 import base64
@@ -61,6 +65,7 @@ class ChatRequest:
     system: str = ""
     user: str = ""
     images: list = field(default_factory=list)      # PIL images
+    videos: list = field(default_factory=list)      # VIDEO inputs; A Thousand Words only
     temperature: float | None = None
     top_p: float | None = None
     max_tokens: int = 0
@@ -90,8 +95,8 @@ class ChatResult:
 # Helpers
 # --------------------------------------------------------------------------
 
-def encode_images(images):
-    """PIL images → list of (mime, base64). Large images are scaled down."""
+def _encode_image_bytes(images):
+    """PIL images → list of (mime, raw bytes). Large images are scaled down."""
     encoded = []
     for image in images:
         image = image.convert("RGB")
@@ -99,10 +104,28 @@ def encode_images(images):
             image.thumbnail((MAX_IMAGE_SIDE, MAX_IMAGE_SIDE))
         buffer = BytesIO()
         image.save(buffer, format="JPEG", quality=92)
-        encoded.append(("image/jpeg", base64.b64encode(buffer.getvalue()).decode("ascii")))
+        encoded.append(("image/jpeg", buffer.getvalue()))
     return encoded
 
 
+def encode_images(images):
+    """PIL images → list of (mime, base64). Large images are scaled down."""
+    return [(mime, base64.b64encode(data).decode("ascii")) for mime, data in _encode_image_bytes(images)]
+
+
+_VIDEO_MIME = {"mp4": "video/mp4", "avi": "video/x-msvideo", "mov": "video/quicktime",
+               "matroska": "video/x-matroska", "webm": "video/webm"}
+
+
+def encode_video(video):
+    """A ComfyUI VIDEO input → (filename, raw bytes, mime), without re-encoding."""
+    fmt = (video.get_container_format() or "mp4").lower()
+    ext, mime = next(((e, m) for e, m in _VIDEO_MIME.items() if e in fmt), ("mp4", "video/mp4"))
+    source = video.get_stream_source()
+    data = open(source, "rb").read() if isinstance(source, str) else source.getvalue()
+    return f"video.{ext}", data, mime
+
+
 _THINK_BLOCK = re.compile(r"<(think|thinking|reasoning)>(.*?)</\1>", re.DOTALL | re.IGNORECASE)
 _THINK_OPEN_TAG = re.compile(r"<(think|thinking|reasoning)>", re.IGNORECASE)
 _THINK_OPEN_ONLY = re.compile(r"^\s*<(think|thinking|reasoning)>(.*)$", re.DOTALL | re.IGNORECASE)
@@ -470,7 +493,10 @@ class AnthropicAdapter:
     def list_models(self, ep, timeout):
         response = requests.get(f"{ep.base_url}/models", params={"limit": 1000}, headers=self.headers(ep), timeout=timeout, allow_redirects=False)
         _raise_for_status(response)
-        return [{"id": m["id"], "detail": m.get("display_name", "")} for m in response.json().get("data", [])]
+        # Every model the Anthropic API lists is a current Claude model, and
+        # all of them accept image input.
+        return [{"id": m["id"], "detail": m.get("display_name", ""), "vision": True}
+                for m in response.json().get("data", [])]
 
 
 class OllamaAdapter:
@@ -565,11 +591,38 @@ class OllamaAdapter:
             detail = [d for d in (details.get("parameter_size"), details.get("quantization_level")) if d]
             if item.get("size"):
                 detail.append(f"{item['size'] / 1e9:.1f} GB")
-            models.append({"id": item["name"], "detail": " · ".join(detail), "loaded": item["name"] in loaded})
+            vision = "vision" in (item.get("capabilities") or [])
+            models.append({"id": item["name"], "detail": " · ".join(detail),
+                           "loaded": item["name"] in loaded, "vision": vision})
         return sorted(models, key=lambda m: (not m["loaded"], m["id"].lower()))
 
 
-ADAPTERS = {a.name: a for a in (OpenAIAdapter(), AnthropicAdapter(), OllamaAdapter())}
+class AThousandWordsAdapter:
+    """A Thousand Words is a captioning server, not a chat API: one POST
+    /caption per request, multipart/form-data, no streaming. run_chat sends
+    it through _run_athousandwords instead of this adapter's build/parse; it
+    only serves list_models here."""
+    name = "athousandwords"
+
+    def headers(self, ep):
+        return dict(ep.headers)
+
+    def list_models(self, ep, timeout):
+        response = requests.get(f"{ep.base_url}/models", headers=self.headers(ep), timeout=timeout, allow_redirects=False)
+        _raise_for_status(response)
+        data = response.json()
+        batch_sizes = data.get("batch_sizes") or {}
+        models = []
+        for model_id in data.get("models", []):
+            recommended = (batch_sizes.get(model_id) or {}).get("recommended")
+            # The server doesn't say which models take video; every model here
+            # accepts the same /caption call, images or video, so both are marked.
+            models.append({"id": model_id, "detail": f"batch {recommended}" if recommended else "",
+                           "vision": True, "video": True})
+        return sorted(models, key=lambda m: m["id"].lower())
+
+
+ADAPTERS = {a.name: a for a in (OpenAIAdapter(), AnthropicAdapter(), OllamaAdapter(), AThousandWordsAdapter())}
 # CLI providers (claude_cli, codex_cli) have no HTTP adapter: see llm_cli.
 
 
@@ -692,6 +745,8 @@ def run_chat(ep, req, *, timeout=300, max_retries=2, on_delta=None, check_interr
     """
     if ep.endpoint.is_cli:
         return _run_cli(ep, req, timeout, on_delta, check_interrupt, log)
+    if ep.endpoint.provider == "athousandwords":
+        return _run_athousandwords(ep, req, timeout, check_interrupt, log)
     adapter = get_adapter(ep.endpoint.provider)
     url = adapter.chat_url(ep)
     headers = adapter.headers(ep)
@@ -858,11 +913,48 @@ def _run_cli(ep, req, timeout, on_delta, check_interrupt, log):
     return result
 
 
+def _run_athousandwords(ep, req, timeout, check_interrupt, log):
+    """POST /caption: multipart/form-data, one reply per call, no streaming."""
+    result = ChatResult()
+    started = time.monotonic()
+    files = [("files", (f"image{i}.jpg", data, mime))
+             for i, (mime, data) in enumerate(_encode_image_bytes(req.images))]
+    files += [("files", encode_video(video)) for video in req.videos]
+
+    form = {"model": req.model}
+    task_prompt = "\n\n".join(t for t in (req.system, req.user) if t)
+    if task_prompt:
+        form["task_prompt"] = task_prompt
+    if req.max_tokens:
+        form["max_tokens"] = str(req.max_tokens)
+    if req.temperature is not None:
+        form["temperature"] = str(req.temperature)
+
+    url = f"{ep.base_url}/caption"
+    if check_interrupt:
+        check_interrupt()
+    if log:
+        log(f"POST {url}\n{json.dumps({**form, 'files': f'{len(files)} file(s)'}, indent=2)}")
+    try:
+        response = requests.post(url, headers=ep.headers, data=form, files=files,
+                                 allow_redirects=False, timeout=(15, timeout))
+    except (requests.RequestException, LocationValueError) as e:
+        raise LLMError(f"Could not reach {ep.endpoint.name}: {_short_exception(e)}", status="connection error")
+    _raise_for_status(response)
+    try:
+        data = response.json()
+        result.text = "\n\n".join(r.get("caption", "") for r in data.get("results", []))
+    except (ValueError, AttributeError) as e:
+        raise LLMError(f"Bad response from {ep.endpoint.name}: {_short_exception(e)}", status="bad response")
+    result.seconds = time.monotonic() - started
+    return result
+
+
 def list_models(ep, timeout=15):
     """Models the endpoint reports, falling back to the configured list."""
     if ep.endpoint.is_cli:
         from .llm_cli import list_cli_models
-        return list_cli_models(ep.endpoint.provider)
+        return list_cli_models(ep.endpoint.provider, ep.base_url)
     adapter = get_adapter(ep.endpoint.provider)
     try:
         return adapter.list_models(ep, timeout)

utils/llm_routes.py

@@ -1,4 +1,4 @@
-"""HTTP routes behind the Universal LLM node's UI (web/js/llm_api.js).
+"""HTTP routes behind the Universal LLM node's UI (web/js/llm_request.js).
 
 Endpoints are addressed by name only; the browser never receives a key or a
 header value. Model listing happens here, server-side, because the key must

utils/settings_utils.py

@@ -149,8 +149,8 @@ LLM_ENDPOINT_VISIBILITY_IDS = {
     "Ollama (network)": "MNeMiC.LLM.ShowEndpoint.OllamaNetwork",
     "LM Studio (this PC)": "MNeMiC.LLM.ShowEndpoint.LMStudio",
     "OpenAI-compatible server": "MNeMiC.LLM.ShowEndpoint.OpenAICompatible",
-    "Local Claude Code Subscription": "MNeMiC.LLM.ShowEndpoint.ClaudeCodeSubscription",
-    "Local Codex Subscription": "MNeMiC.LLM.ShowEndpoint.CodexSubscription",
+    "Claude Code Subscription": "MNeMiC.LLM.ShowEndpoint.ClaudeCodeSubscription",
+    "Codex Subscription": "MNeMiC.LLM.ShowEndpoint.CodexSubscription",
     "OpenAI (ChatGPT)": "MNeMiC.LLM.ShowEndpoint.OpenAI",
     "Anthropic (Claude)": "MNeMiC.LLM.ShowEndpoint.Anthropic",
     "Google (Gemini)": "MNeMiC.LLM.ShowEndpoint.Gemini",
@@ -159,6 +159,7 @@ LLM_ENDPOINT_VISIBILITY_IDS = {
     "OpenRouter": "MNeMiC.LLM.ShowEndpoint.OpenRouter",
     "Mistral": "MNeMiC.LLM.ShowEndpoint.Mistral",
     "DeepSeek": "MNeMiC.LLM.ShowEndpoint.DeepSeek",
+    "A Thousand Words": "MNeMiC.LLM.ShowEndpoint.AThousandWords",
     "Sanctum": "MNeMiC.LLM.ShowEndpoint.Sanctum",
     "Custom Endpoint - WARNING": "MNeMiC.LLM.ShowEndpoint.CustomEndpoint",
 }

web/docs/MNeMiC_GroqAPILLM.md

@@ -15,7 +15,7 @@ GROQ_API_KEY=your_key_here
 ```
 
 Changes apply on the next run; no restart needed. The same key is used by the
-✨🧠 LLM Request node's Groq endpoint.
+✨ LLM Request node's Groq endpoint.
 
 ## Inputs
 
@@ -49,7 +49,7 @@ Advanced:
 
 Presets come from `nodes/groq/DefaultPrompts.json` (shipped) and
 `nodes/groq/UserPrompts.json` (yours). Each entry is `{"name": ..., "content":
-...}`; the name shows in the dropdown. They are shared with the ✨🧠 Universal
+...}`; the name shows in the dropdown. They are shared with the ✨ Universal
 LLM API node. Press R in ComfyUI (refresh node definitions) after editing.
 
 ## Notes

web/docs/MNeMiC_LLMAPI.md

@@ -1,10 +1,10 @@
-# ✨🧠 LLM Request
+# ✨ LLM Request
 
-Sends a prompt, and optionally images, to any language model and returns the
-reply. One node covers cloud APIs (ChatGPT, Claude, Gemini, Grok, Groq,
-OpenRouter, Mistral, DeepSeek) and local servers (Ollama and LM Studio on this
-PC, Ollama or any OpenAI-compatible server on your network). Presets are
-shared with the Groq nodes.
+Sends a prompt, and optionally images or a video, to any language model and
+returns the reply. One node covers cloud APIs (ChatGPT, Claude, Gemini, Grok,
+Groq, OpenRouter, Mistral, DeepSeek) and local servers (Ollama and LM Studio on
+this PC, Ollama or any OpenAI-compatible server on your network, A Thousand
+Words for image/video captioning). Presets are shared with the Groq nodes.
 
 ## Setup
 
@@ -27,22 +27,27 @@ and what is missing if not.
 
 ## Inputs
 
-- **endpoint** — Which server to call. The list comes from
-  `nodes/llm/DefaultEndpoints.json` and your `nodes/llm/UserEndpoints.json`.
-- **model** — Model name. Empty uses the endpoint's default model. Endpoints
-  on this PC or your network without one use the first chat model the
-  server lists, skipping embedding models (for Ollama, a model already in
-  memory if there is one, else the first installed one alphabetically);
-  cloud endpoints without one need a model chosen. Click **🔍 Models** to browse and search what the
-  endpoint offers; Ollama models already in memory are marked.
-- **preset** — A saved system prompt, or the first entry to use
-  `system_message`. Click **📜 Preset** to read the selected one.
-- **system_message** — The model's instructions. Ignored while a preset is
-  active; in the classic node view it is also greyed out and shows the
-  preset's text as a hint (📜 Preset shows it in either view).
+- **endpoint** — Which server to call. Click it (or the ▾) to browse and
+  search the list, in the order `nodes/llm/DefaultEndpoints.json` and your
+  `nodes/llm/UserEndpoints.json` define them.
+- **model** — Model name. Type one directly, or click the ▾ to browse and
+  search what the endpoint offers (Ollama models already in memory are
+  marked). Empty uses the endpoint's default model. Endpoints on this PC or
+  your network without one use the first chat model the server lists,
+  skipping embedding models (for Ollama, a model already in memory if there
+  is one, else the first installed one alphabetically); cloud endpoints
+  without one need a model chosen.
+- **preset** — A saved system prompt. Picking one copies its text into
+  `system_message` (asking first if that would overwrite something different)
+  and resets itself back to the first entry, so `system_message` stays a
+  plain, freely editable field afterward.
 - **user_input** — The request. May be empty: the system message (or preset)
   is then sent on its own as the request.
 - **images** — Optional. Every image in the batch is sent, for vision models.
+- **video** — Optional, A Thousand Words only. A single video to caption
+  instead of, or alongside, images. Sending it to any other endpoint fails:
+  no other protocol here accepts video. Which of the server's models actually
+  support video input is up to the server; it isn't in its model list.
 - **temperature** — Randomness. Dropped automatically for models that refuse
   anything but their default.
 
@@ -96,6 +101,7 @@ back in an error message is masked before it is shown or returned.
 | `ollama`     | Ollama's native API (for `keep_alive`, `num_ctx`, `think`)      |
 | `claude_cli` | The Claude Code CLI on this PC, with your Claude subscription   |
 | `codex_cli`  | The Codex CLI on this PC, with your ChatGPT subscription        |
+| `athousandwords` | A Thousand Words, a local image/video captioning server (not a chat API: one `POST /caption` per call, `system_message` and `user_input` are combined into its `task_prompt`, no streaming) |
 
 **Parameters that don't fit.** Models differ in what they accept: OpenAI's
 reasoning models refuse `temperature`, some servers don't know `seed`. For

web/js/llm_request.js

@@ -1,7 +1,7 @@
 import { app } from "../../../scripts/app.js";
 import { api } from "../../../scripts/api.js";
 
-// ✨🧠 LLM Request — node UI.
+// ✨ LLM Request — node UI.
 //
 // Adds a panel to the node with the endpoint's status (where it runs, whether
 // its key/address is set), a searchable model browser, a connection test, a
@@ -28,10 +28,10 @@ function defaultOutHeight() {
 }
 
 const LOCATION_LABEL = {
-    local: ["🖥", "This PC"],
-    network: ["🏠", "Network"],
-    cloud: ["☁", "Cloud"],
-    unknown: ["❔", "Not set"],
+    local: "This PC",
+    network: "Network",
+    cloud: "Cloud",
+    unknown: "Not configured",
 };
 
 const panels = new Set();
@@ -97,32 +97,6 @@ function splitInlineThinking(text) {
     return [text.slice(m[0].length).trimStart(), m[2].trim()];
 }
 
-// navigator.clipboard only exists in secure contexts; ComfyUI opened over
-// http://<LAN IP> is not one, so fall back to the old selection copy.
-async function copyText(text) {
-    try {
-        if (navigator.clipboard?.writeText) {
-            await navigator.clipboard.writeText(text);
-            return true;
-        }
-    } catch {
-        // fall through to the fallback
-    }
-    const area = document.createElement("textarea");
-    area.value = text;
-    area.style.cssText = "position:fixed;left:-9999px;top:0;opacity:0";
-    document.body.appendChild(area);
-    area.select();
-    let ok = false;
-    try {
-        ok = document.execCommand("copy");
-    } catch {
-        ok = false;
-    }
-    area.remove();
-    return ok;
-}
-
 // --------------------------------------------------------------------------
 // Styles
 // --------------------------------------------------------------------------
@@ -142,7 +116,20 @@ function addStylesheet() {
         .mnemic-llm-chip { padding:1px 7px; border-radius:10px; background:var(--comfy-input-bg); border:1px solid var(--border-color);
             white-space:nowrap; font-size:11px; }
         .mnemic-llm-chip.bad { border-color:#d29922; color:#d29922; }
-        .mnemic-llm-host { opacity:.6; font-size:11px; overflow:hidden; text-overflow:ellipsis; white-space:nowrap; min-width:0; flex:1; }
+        .mnemic-llm-host { opacity:.6; font-size:11px; overflow:hidden; text-overflow:ellipsis; white-space:nowrap; min-width:0; }
+        .mnemic-llm-test { flex:0 0 auto; min-width:0; margin-left:auto; padding:2px 8px; }
+        .mnemic-llm-pickrow { display:flex; gap:6px; }
+        .mnemic-llm-pick { flex:1; min-width:0; display:flex; align-items:center; gap:4px; padding:3px 6px; border-radius:5px;
+            background:var(--comfy-input-bg); color:var(--fg-color); border:1px solid var(--border-color); cursor:pointer; }
+        .mnemic-llm-pick:hover { border-color:#58a6ff; }
+        .mnemic-llm-pick.mnemic-llm-pick-combo { padding:0; cursor:default; }
+        .mnemic-llm-pick-value { flex:1; min-width:0; overflow:hidden; text-overflow:ellipsis; white-space:nowrap; text-align:left; font-size:11.5px; }
+        .mnemic-llm-pick-input { flex:1; min-width:0; padding:3px 0 3px 6px; border:none; background:none; color:var(--fg-color); font-size:11.5px; }
+        .mnemic-llm-pick-input:focus { outline:none; }
+        .mnemic-llm-arrow { opacity:.6; font-size:10px; flex:0 0 auto; }
+        .mnemic-llm-arrow-btn { flex:0 0 auto; padding:3px 6px; border:none; border-left:1px solid var(--border-color);
+            background:none; color:var(--fg-color); cursor:pointer; }
+        .mnemic-llm-arrow-btn:hover .mnemic-llm-arrow { opacity:1; }
         .mnemic-llm-buttons { display:flex; gap:4px; flex-wrap:wrap; }
         .mnemic-llm-btn { flex:1; min-width:60px; padding:3px 6px; border-radius:5px; cursor:pointer; font-size:11.5px;
             background:var(--comfy-input-bg); color:var(--fg-color); border:1px solid var(--border-color); white-space:nowrap; }
@@ -182,9 +169,11 @@ function addStylesheet() {
         .mnemic-llm-item { display:flex; align-items:baseline; gap:8px; padding:4px 12px; cursor:pointer; }
         .mnemic-llm-item.active { background:#58a6ff33; }
         .mnemic-llm-item.current .mnemic-llm-item-id::before { content:"✓ "; color:#3fb950; }
-        .mnemic-llm-item-id { flex:1; overflow:hidden; text-overflow:ellipsis; white-space:nowrap; }
-        .mnemic-llm-item-detail { opacity:.55; font-size:11px; white-space:nowrap; }
-        .mnemic-llm-loaded { color:#3fb950; font-size:10px; }
+        .mnemic-llm-item-id { flex:1; overflow:hidden; text-overflow:ellipsis; white-space:nowrap; color:#9198a1; }
+        .mnemic-llm-item-tags { flex:0 0 auto; display:flex; gap:8px; font-size:11px; }
+        .mnemic-llm-loaded { color:#3fb950; }
+        .mnemic-llm-vision { color:#d29922; }
+        .mnemic-llm-video { color:#58a6ff; }
         .mnemic-llm-note { padding:6px 12px; opacity:.75; font-size:11.5px; }
         .mnemic-llm-note.err { color:#f85149; opacity:1; }
         .mnemic-llm-pop pre { margin:0; padding:10px 12px; overflow:auto; white-space:pre-wrap; word-break:break-word; font:12px/1.45 ui-monospace, monospace; }
@@ -234,17 +223,18 @@ function createPopup(anchor, title) {
 function showModelPicker(panel, anchor) {
     const endpoint = panel.widget("endpoint")?.value;
     const pop = createPopup(anchor, `Models · ${endpoint}`);
+    const headTitle = pop.querySelector(".mnemic-llm-pop-head span");
     const refresh = document.createElement("b");
     refresh.className = "mnemic-llm-pop-refresh";
-    refresh.title = "Ask the endpoint again";
+    refresh.title = "Refresh: ask the endpoint for its model list again, instead of using the last one fetched (cached for 1 minute)";
     refresh.textContent = "⟳";
     pop.querySelector(".mnemic-llm-pop-head").insertBefore(refresh, pop.querySelector(".mnemic-llm-pop-close"));
 
     const search = document.createElement("input");
-    search.placeholder = "Search, or type any model name and press Enter…";
+    search.placeholder = "Search…";
     const note = document.createElement("div");
     note.className = "mnemic-llm-note";
-    note.textContent = "Asking the endpoint…";
+    note.hidden = true;
     const list = document.createElement("div");
     list.className = "mnemic-llm-list";
     pop.append(search, note, list);
@@ -254,7 +244,6 @@ function showModelPicker(panel, anchor) {
     let shown = [];
     let active = 0;
     const current = panel.widget("model")?.value ?? "";
-    const info = endpointCache.byName.get(endpoint);
 
     const choose = (id) => {
         panel.setModel(id);
@@ -265,9 +254,9 @@ function showModelPicker(panel, anchor) {
         const q = search.value.trim().toLowerCase();
         const terms = q.split(/\s+/).filter(Boolean);
         shown = models.filter((m) => terms.every((t) => `${m.id} ${m.detail ?? ""}`.toLowerCase().includes(t)));
-        const items = [{ id: "", label: `Endpoint default${info?.default_model ? ` (${info.default_model})` : ""}`, detail: "" }, ...shown];
+        const items = [...shown];
         if (q && !models.some((m) => m.id.toLowerCase() === q)) {
-            items.push({ id: search.value.trim(), label: `Use “${search.value.trim()}”`, detail: "custom" });
+            items.push({ id: search.value.trim(), label: `Use “${search.value.trim()}”` });
         }
         shown = items;
         active = Math.min(active, items.length - 1);
@@ -276,24 +265,33 @@ function showModelPicker(panel, anchor) {
                 const row = document.createElement("div");
                 row.className = "mnemic-llm-item";
                 if (i === active) row.classList.add("active");
-                if (m.id === current && (m.id !== "" || current === "")) row.classList.add("current");
+                if (m.id === current) row.classList.add("current");
                 const id = document.createElement("span");
                 id.className = "mnemic-llm-item-id";
                 id.textContent = m.label ?? m.id;
                 id.title = m.id;
                 row.append(id);
+                const tags = document.createElement("span");
+                tags.className = "mnemic-llm-item-tags";
                 if (m.loaded) {
                     const loaded = document.createElement("span");
                     loaded.className = "mnemic-llm-loaded";
-                    loaded.textContent = "● in memory";
-                    row.append(loaded);
+                    loaded.textContent = "in memory";
+                    tags.append(loaded);
                 }
-                if (m.detail) {
-                    const detail = document.createElement("span");
-                    detail.className = "mnemic-llm-item-detail";
-                    detail.textContent = m.detail;
-                    row.append(detail);
+                if (m.vision) {
+                    const vision = document.createElement("span");
+                    vision.className = "mnemic-llm-vision";
+                    vision.textContent = "vision";
+                    tags.append(vision);
                 }
+                if (m.video) {
+                    const video = document.createElement("span");
+                    video.className = "mnemic-llm-video";
+                    video.textContent = "video";
+                    tags.append(video);
+                }
+                if (tags.childNodes.length) row.append(tags);
                 row.addEventListener("mousemove", () => {
                     if (active === i) return;
                     list.querySelector(".active")?.classList.remove("active");
@@ -307,14 +305,16 @@ function showModelPicker(panel, anchor) {
     };
 
     const load = async (force) => {
-        note.className = "mnemic-llm-note";
-        note.textContent = "Asking the endpoint…";
         const data = await getModels(endpoint, force, panel.customId());
         if (openPopup !== pop) return;
         models = data.models ?? [];
+        const isStatic = models.length > 0 && models.every((m) => m.static);
+        headTitle.textContent = `Models · ${endpoint}${isStatic ? " *" : ""} (${models.length})`;
+        headTitle.title = isStatic ? "* a fixed list built into this pack, not fetched live from the endpoint" : "";
         if (data.ok) {
-            note.textContent = `${models.length} model${models.length === 1 ? "" : "s"} · ${data.ms} ms`;
+            note.hidden = true;
         } else {
+            note.hidden = false;
             note.className = "mnemic-llm-note err";
             note.textContent = `${data.error}${models.length ? " Showing models from the config instead." : ""}`;
         }
@@ -322,7 +322,7 @@ function showModelPicker(panel, anchor) {
     };
 
     search.addEventListener("input", () => {
-        active = search.value ? 1 : 0;
+        active = 0;
         render();
     });
     search.addEventListener("keydown", (e) => {
@@ -344,16 +344,73 @@ function showModelPicker(panel, anchor) {
     load(false);
 }
 
-async function showPreset(panel, anchor) {
-    const name = panel.widget("preset")?.value;
-    const pop = createPopup(anchor, name === DEFAULT_PRESET ? "No preset selected" : name);
-    const pre = document.createElement("pre");
-    if (name === DEFAULT_PRESET) {
-        pre.textContent = "The node is using its own system_message field.\n\nPick a preset to replace it with a saved system prompt. Presets are shared with the Groq nodes: nodes/groq/UserPrompts.json and UserPrompts_VLM.json.";
-    } else {
-        pre.textContent = (await getPresets(name))[name] ?? "(preset not found: it may have been removed from the preset files)";
-    }
-    pop.append(pre);
+function showEndpointPicker(panel, anchor) {
+    const widget = panel.widget("endpoint");
+    const names = widget?.options?.values ?? [];
+    const current = widget?.value ?? "";
+    const pop = createPopup(anchor, "Endpoints");
+
+    const search = document.createElement("input");
+    search.placeholder = "Search…";
+    const list = document.createElement("div");
+    list.className = "mnemic-llm-list";
+    pop.append(search, list);
+    search.focus();
+
+    const choose = (name) => {
+        panel.setEndpoint(name);
+        closePopup();
+    };
+
+    let shown = [];
+    let active = 0;
+
+    const render = () => {
+        const q = search.value.trim().toLowerCase();
+        shown = names.filter((name) => !q || name.toLowerCase().includes(q));
+        active = Math.min(active, shown.length - 1);
+        list.replaceChildren(
+            ...shown.map((name, i) => {
+                const row = document.createElement("div");
+                row.className = "mnemic-llm-item";
+                if (i === active) row.classList.add("active");
+                if (name === current) row.classList.add("current");
+                const id = document.createElement("span");
+                id.className = "mnemic-llm-item-id";
+                id.textContent = name;
+                row.append(id);
+                row.addEventListener("mousemove", () => {
+                    if (active === i) return;
+                    list.querySelector(".active")?.classList.remove("active");
+                    row.classList.add("active");
+                    active = i;
+                });
+                row.addEventListener("click", () => choose(name));
+                return row;
+            })
+        );
+    };
+
+    search.addEventListener("input", () => {
+        active = 0;
+        render();
+    });
+    search.addEventListener("keydown", (e) => {
+        if (e.key === "ArrowDown" || e.key === "ArrowUp") {
+            e.preventDefault();
+            active = (active + (e.key === "ArrowDown" ? 1 : -1) + shown.length) % shown.length;
+            render();
+            list.querySelector(".active")?.scrollIntoView({ block: "nearest" });
+        } else if (e.key === "Enter") {
+            e.preventDefault();
+            const pick = shown[active];
+            if (pick) choose(pick);
+        } else if (e.key === "Escape") {
+            closePopup();
+        }
+    });
+
+    render();
 }
 
 // --------------------------------------------------------------------------
@@ -372,16 +429,21 @@ class LLMPanel {
                 <span class="mnemic-llm-dot"></span>
                 <span class="mnemic-llm-chip" data-role="where"></span>
                 <span class="mnemic-llm-chip" data-role="key"></span>
-                <span class="mnemic-llm-host"></span>
+                <button class="mnemic-llm-btn mnemic-llm-test" data-act="test" title="Check that the endpoint answers">Test</button>
             </div>
-            <div class="mnemic-llm-buttons">
-                <button class="mnemic-llm-btn" data-act="models" title="Browse the models this endpoint offers">🔍 Models</button>
-                <button class="mnemic-llm-btn" data-act="test" title="Check that the endpoint answers">⚡ Test</button>
-                <button class="mnemic-llm-btn" data-act="preset" title="Show the selected preset's system prompt">📜 Preset</button>
-                <button class="mnemic-llm-btn" data-act="copy" title="Copy the last reply">📋 Copy</button>
+            <div class="mnemic-llm-host"></div>
+            <div class="mnemic-llm-pickrow">
+                <button class="mnemic-llm-pick" data-act="endpoints" title="Endpoint - click to choose">
+                    <span class="mnemic-llm-pick-value" data-role="endpoint-value"></span>
+                    <span class="mnemic-llm-arrow">▾</span>
+                </button>
+                <span class="mnemic-llm-pick mnemic-llm-pick-combo">
+                    <input class="mnemic-llm-pick-input" data-role="model-input" placeholder="Model" title="Model - type a name, or click ▾ to browse" spellcheck="false" autocomplete="off">
+                    <button class="mnemic-llm-arrow-btn" data-act="models" title="Browse the models this endpoint offers"><span class="mnemic-llm-arrow">▾</span></button>
+                </span>
             </div>
             <div class="mnemic-llm-custom" hidden>
-                <div class="mnemic-llm-warn"><b>⚠ Custom endpoint.</b> The address and key you enter are stored on this
+                <div class="mnemic-llm-warn"><b>Custom endpoint.</b> The address and key you enter are stored on this
                     ComfyUI machine only (nodes/llm/CustomEndpoints.local.json, plain text) and never in the workflow:
                     the workflow keeps just a random id, so shared workflows and images don't carry them.
                     Changing the address or protocol clears the saved key.
@@ -398,21 +460,21 @@ class LLMPanel {
                 </div>
                 <div class="mnemic-llm-row">
                     <input data-f="key" type="password" placeholder="API key (optional)" autocomplete="new-password">
-                    <button class="mnemic-llm-btn" data-act="custom-save" style="flex:0 0 auto">💾 Save</button>
+                    <button class="mnemic-llm-btn" data-act="custom-save" style="flex:0 0 auto">Save</button>
                 </div>
                 <div class="mnemic-llm-custom-status"></div>
             </div>
-            <div class="mnemic-llm-out empty">The reply will appear here.</div>
+            <div class="mnemic-llm-out empty">No reply yet.</div>
             <div class="mnemic-llm-stats"></div>
         `;
         this.dot = this.el.querySelector(".mnemic-llm-dot");
         this.where = this.el.querySelector('[data-role="where"]');
         this.key = this.el.querySelector('[data-role="key"]');
         this.host = this.el.querySelector(".mnemic-llm-host");
+        this.endpointValue = this.el.querySelector('[data-role="endpoint-value"]');
+        this.modelInput = this.el.querySelector('[data-role="model-input"]');
         this.out = this.el.querySelector(".mnemic-llm-out");
         this.stats = this.el.querySelector(".mnemic-llm-stats");
-        this.copyButton = this.el.querySelector('[data-act="copy"]');
-        this.copyButton.disabled = true;
         this.custom = this.el.querySelector(".mnemic-llm-custom");
         this.customStatus = this.el.querySelector(".mnemic-llm-custom-status");
         this.customField = (f) => this.custom.querySelector(`[data-f="${f}"]`);
@@ -425,10 +487,17 @@ class LLMPanel {
         // Typing in these fields must not trigger ComfyUI shortcuts.
         for (const type of ["keydown", "keyup", "keypress", "pointerdown", "wheel"]) {
             this.custom.addEventListener(type, (e) => e.stopPropagation());
+            this.modelInput.addEventListener(type, (e) => e.stopPropagation());
         }
+        this.modelInput.addEventListener("input", () => {
+            const w = this.widget("model");
+            if (!w) return;
+            w.value = this.modelInput.value;
+            w.callback?.(w.value);
+        });
 
         this.el.addEventListener("pointerdown", (e) => {
-            if (e.target.closest("button, .mnemic-llm-out")) e.stopPropagation();
+            if (e.target.closest("button, input, .mnemic-llm-out")) e.stopPropagation();
         });
         this.out.addEventListener("wheel", (e) => {
             if (this.out.scrollHeight > this.out.clientHeight) e.stopPropagation();
@@ -454,6 +523,10 @@ class LLMPanel {
         this.domWidget.computeLayoutSize = undefined;
         this.applyOutHeight();
 
+        this.hideRawWidgets();
+        this.syncEndpointValue();
+        this.syncModelInput();
+
         // Dragging the reply preview's resize handle persists the chosen
         // height on this node and resizes the node to match.
         new ResizeObserver(() => {
@@ -466,6 +539,31 @@ class LLMPanel {
         }).observe(this.out);
     }
 
+    // The endpoint and model widgets keep their value (workflows still store
+    // just the name/model string) but are never drawn: the pick button and
+    // the model input above are the only way to change them now.
+    hideRawWidgets() {
+        for (const name of ["endpoint", "model"]) {
+            const w = this.widget(name);
+            if (!w) continue;
+            w.hidden = true;
+            w.computeSize = () => [0, -4];
+            if (w.type !== "hidden") {
+                w.origType = w.origType || w.type;
+                w.type = "hidden";
+            }
+        }
+    }
+
+    syncEndpointValue() {
+        if (this.endpointValue) this.endpointValue.textContent = this.widget("endpoint")?.value ?? "";
+    }
+
+    syncModelInput() {
+        const w = this.widget("model");
+        if (w && this.modelInput && this.modelInput.value !== (w.value ?? "")) this.modelInput.value = w.value ?? "";
+    }
+
     outHeight() {
         return this.node.properties?.[OUT_HEIGHT_PROPERTY] ?? defaultOutHeight();
     }
@@ -581,20 +679,20 @@ class LLMPanel {
         }
         this.info = info;
         if (!info) {
-            this.setChip(this.where, "❔ Unknown endpoint", true);
+            this.setChip(this.where, "Unknown endpoint", true);
             this.setChip(this.key, "", false);
             this.host.textContent = "";
             if (this.state === "idle") this.setDot("warn");
             return;
         }
-        const [icon, label] = LOCATION_LABEL[info.location] ?? LOCATION_LABEL.unknown;
-        this.setChip(this.where, `${icon} ${label} · ${info.provider}`, info.location === "unknown");
+        const label = LOCATION_LABEL[info.location] ?? LOCATION_LABEL.unknown;
+        this.setChip(this.where, `${label} · ${info.provider}`, info.location === "unknown");
         if (info.is_custom) {
-            this.setChip(this.key, info.key_set ? "🔑 key saved" : "🔓 no key", false);
+            this.setChip(this.key, info.key_set ? "key saved" : "no key", false);
         } else if (info.key_env) {
-            this.setChip(this.key, info.key_set ? "🔑 key set" : info.key_optional ? "🔓 no key" : `🔑 ${info.key_env} missing`, !info.key_set && !info.key_optional);
+            this.setChip(this.key, info.key_set ? "key set" : info.key_optional ? "no key" : `${info.key_env} missing`, !info.key_set && !info.key_optional);
         } else {
-            this.setChip(this.key, "🔓 no key needed", false);
+            this.setChip(this.key, "no key needed", false);
         }
         this.host.title = [info.description, ...info.problems].filter(Boolean).join("\n\n");
         this.updateModelHint();
@@ -602,7 +700,7 @@ class LLMPanel {
             // Green once configured; ⚡ Test checks that it actually answers.
             this.setDot(info.ok ? "ok" : "warn");
             if (!info.ok && !this.result) this.showNote(info.problems.join(" "), false);
-            else if (info.ok && !this.result) this.showNote("The reply will appear here.", false);
+            else if (info.ok && !this.result) this.showNote("No reply yet.", false);
         }
     }
 
@@ -631,30 +729,47 @@ class LLMPanel {
                 : ["local", "network"].includes(this.info.location) ? "model: first the server lists"
                 : "no model chosen";
         }
-        this.host.textContent = [this.info.host, hint].filter(Boolean).join(" · ");
+        // The where-chip already names the CLI (e.g. "This PC · claude_cli");
+        // info.host would just repeat that in different words.
+        const hostPart = this.info.is_cli ? "" : this.info.host;
+        this.host.textContent = [hostPart, hint].filter(Boolean).join(" · ");
     }
 
     // ---- presets --------------------------------------------------------
 
-    async updatePresetState() {
-        const preset = this.widget("preset")?.value;
-        const presetButton = this.el.querySelector('[data-act="preset"]');
-        if (presetButton) presetButton.disabled = !preset || preset === DEFAULT_PRESET;
-        const system = this.widget("system_message");
-        const input = system?.inputEl;
-        if (!input) return;
-        if (preset && preset !== DEFAULT_PRESET) {
-            const text = (await getPresets(preset))[preset] ?? "";
-            if (this.widget("preset")?.value !== preset) return;
-            input.style.opacity = "0.45";
-            input.title = "Ignored while a preset is selected.";
-            input.dataset.mnemicPlaceholder ??= input.placeholder ?? "";
-            input.placeholder = `Preset “${preset}” is active:\n\n${text.slice(0, 600)}${text.length > 600 ? "…" : ""}`;
-        } else {
-            input.style.opacity = "";
-            input.title = "";
-            if (input.dataset.mnemicPlaceholder !== undefined) input.placeholder = input.dataset.mnemicPlaceholder;
+    // Picking a preset copies its text into system_message once, then resets
+    // the preset dropdown to default: a one-shot insert, not a persistent
+    // mode, so the field stays freely editable afterward.
+    async applyPreset() {
+        const w = this.widget("preset");
+        const name = w?.value;
+        if (!name || name === DEFAULT_PRESET) return;
+        const text = (await getPresets(name))[name] ?? "";
+        if (w.value !== name) return; // changed again while this was loading
+        const sys = this.widget("system_message");
+        const current = (sys?.value ?? "").trim();
+        if (current && current !== text.trim() && !window.confirm(`Replace the current system message with the "${name}" preset?`)) {
+            w.value = DEFAULT_PRESET;
+            w.callback?.(DEFAULT_PRESET);
+            return;
         }
+        if (sys) {
+            sys.value = text;
+            sys.callback?.(text);
+        }
+        w.value = DEFAULT_PRESET;
+        w.callback?.(DEFAULT_PRESET);
+        this.node.setDirtyCanvas(true, true);
+    }
+
+    // ---- endpoints --------------------------------------------------------
+
+    setEndpoint(name) {
+        const w = this.widget("endpoint");
+        if (!w || w.value === name) return;
+        w.value = name;
+        w.callback?.(name);
+        this.node.setDirtyCanvas(true, true);
     }
 
     // ---- models ---------------------------------------------------------
@@ -665,6 +780,7 @@ class LLMPanel {
         w.value = id;
         w.callback?.(id);
         this.rememberModel();
+        this.syncModelInput();
         this.node.setDirtyCanvas(true, true);
     }
 
@@ -688,9 +804,10 @@ class LLMPanel {
             w.value = remembered;
             this.node.setDirtyCanvas(true, true);
         }
+        this.syncEndpointValue();
+        this.syncModelInput();
         this.result = null;
         this.stats.textContent = "";
-        this.updateCopyState();
         this.refreshStatus();
     }
 
@@ -698,17 +815,8 @@ class LLMPanel {
 
     async onButton(act, button) {
         if (act === "custom-save") return this.saveCustom();
+        if (act === "endpoints") return showEndpointPicker(this, button);
         if (act === "models") return showModelPicker(this, button);
-        if (act === "preset") return showPreset(this, button);
-        if (act === "copy") {
-            // The reply on screen: the finished one, or what streamed in so far.
-            const text = this.result?.text ?? this.partial?.text ?? "";
-            if (!text) return;
-            const ok = await copyText(text);
-            button.textContent = ok ? "✓ Copied" : "Copy failed";
-            setTimeout(() => (button.textContent = "📋 Copy"), 1200);
-            return;
-        }
         if (act === "test") {
             button.disabled = true;
             const runId = this.runId;
@@ -736,10 +844,6 @@ class LLMPanel {
         this.out.textContent = text;
     }
 
-    updateCopyState() {
-        this.copyButton.disabled = !(this.result?.text ?? this.partial?.text ?? "");
-    }
-
     renderReply(text, thinking, streaming) {
         this.out.className = "mnemic-llm-out";
         const pinned = this.out.scrollHeight - this.out.scrollTop - this.out.clientHeight < 24;
@@ -788,7 +892,6 @@ class LLMPanel {
             this.showNote(msg.error, true);
             this.stats.textContent = "";
         }
-        this.updateCopyState();
     }
 
     onResult(summary) {
@@ -799,7 +902,6 @@ class LLMPanel {
             this.setDot("err");
             this.showNote(summary.error ?? summary.status, true);
             this.stats.textContent = "";
-            this.updateCopyState();
             return;
         }
         this.result = summary;
@@ -813,7 +915,6 @@ class LLMPanel {
         if (summary.output_tokens && summary.seconds > 0) parts.push(`${Math.round(summary.output_tokens / summary.seconds)} tok/s`);
         if (summary.status && summary.status !== "200 OK") parts.push(summary.status.replace(/^200 OK /, ""));
         this.stats.textContent = parts.join(" · ");
-        this.updateCopyState();
         // .env may have changed since the panel last looked (e.g. a key added).
         this.refreshStatus(true);
     }
@@ -825,7 +926,6 @@ class LLMPanel {
         // Keep what arrived, without the streaming caret.
         if (this.partial?.text || this.partial?.thinking) this.renderReply(this.partial.text, this.partial.thinking, false);
         this.stats.textContent = "interrupted";
-        this.updateCopyState();
     }
 }
 
@@ -854,7 +954,7 @@ function chainCallback(widget, fn) {
 }
 
 app.registerExtension({
-    name: "MNeMiC.LLMAPI",
+    name: "MNeMiC.LLMRequest",
 
     async beforeRegisterNodeDef(nodeType, nodeData) {
         if (nodeData.name !== NODE_ID) return;
@@ -866,18 +966,16 @@ app.registerExtension({
             this.mnemicLLM = panel;
 
             chainCallback(panel.widget("endpoint"), (_value, previous) => panel.onEndpointChanged(previous));
-            chainCallback(panel.widget("preset"), () => panel.updatePresetState());
+            chainCallback(panel.widget("preset"), () => panel.applyPreset());
             chainCallback(panel.widget("model"), () => {
                 panel.rememberModel();
+                panel.syncModelInput();
                 panel.updateModelHint();
             });
 
             const [w, h] = this.size;
             this.setSize([Math.max(w, 400), Math.max(h, this.computeSize()[1])]);
-            requestAnimationFrame(() => {
-                panel.refreshStatus();
-                panel.updatePresetState();
-            });
+            requestAnimationFrame(() => panel.refreshStatus());
             return r;
         };
 
@@ -890,6 +988,9 @@ app.registerExtension({
                     const w = panel.widget(name);
                     if (w) w._mnemicLast = w.value;
                 }
+                panel.hideRawWidgets();
+                panel.syncEndpointValue();
+                panel.syncModelInput();
                 requestAnimationFrame(() => {
                     // Undo/redo and tab switches rebuild the node, and
                     // onExecuted is not replayed: restore the last reply.
@@ -897,7 +998,6 @@ app.registerExtension({
                     const key = Object.keys(outputs).find((k) => panel.matches(k) && outputs[k]?.mnemic_llm?.[0]);
                     if (key && !panel.result) panel.onResult(outputs[key].mnemic_llm[0]);
                     panel.refreshStatus();
-                    panel.updatePresetState();
                     // A node saved before the reply box got a fixed height
                     // may carry a stale, oversized node height: correct it.
                     panel.fitNode();

web/js/settings.js

@@ -244,8 +244,8 @@ app.registerExtension({
     },
     {
       id: "MNeMiC.LLM.ShowEndpoint.ClaudeCodeSubscription",
-      name: "Local Claude Code Subscription",
-      category: ["⚡MNeMiC Nodes", "LLM Request", "Show Endpoints", "Local Claude Code Subscription"],
+      name: "Claude Code Subscription",
+      category: ["⚡MNeMiC Nodes", "LLM Request", "Show Endpoints", "Claude Code Subscription"],
       tooltip: "Show this endpoint in the LLM Request node's endpoint dropdown.",
       type: "boolean",
       defaultValue: true,
@@ -253,8 +253,8 @@ app.registerExtension({
     },
     {
       id: "MNeMiC.LLM.ShowEndpoint.CodexSubscription",
-      name: "Local Codex Subscription",
-      category: ["⚡MNeMiC Nodes", "LLM Request", "Show Endpoints", "Local Codex Subscription"],
+      name: "Codex Subscription",
+      category: ["⚡MNeMiC Nodes", "LLM Request", "Show Endpoints", "Codex Subscription"],
       tooltip: "Show this endpoint in the LLM Request node's endpoint dropdown.",
       type: "boolean",
       defaultValue: true,
@@ -332,6 +332,15 @@ app.registerExtension({
       defaultValue: true,
       sortOrder: -140,
     },
+    {
+      id: "MNeMiC.LLM.ShowEndpoint.AThousandWords",
+      name: "A Thousand Words",
+      category: ["⚡MNeMiC Nodes", "LLM Request", "Show Endpoints", "A Thousand Words"],
+      tooltip: "Show this endpoint in the LLM Request node's endpoint dropdown.",
+      type: "boolean",
+      defaultValue: true,
+      sortOrder: -145,
+    },
     {
       id: "MNeMiC.LLM.ShowEndpoint.Sanctum",
       name: "Sanctum",