Integrate ComfyUI agents and video workflows
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@@ -14,12 +14,95 @@ import os
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import requests
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# ── Config ───────────────────────────────────────────────────────────────
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BOOSAPI_BASE = os.environ.get("BOOSAPI_BASE", "http://127.0.0.1:4000")
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BOOSAPI_BASE_RAW = os.environ.get("BOOSAPI_BASE", "http://127.0.0.1:4000")
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BOOSAPI_KEY = os.environ.get("BOOSAPI_KEY", "sk-boos4721")
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HEADERS = {
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"Authorization": f"Bearer {BOOSAPI_KEY}",
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"Content-Type": "application/json",
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}
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FALLBACK_CHAT_MODELS = ["gpt-5.5", "gpt-5.4", "gpt-5.4-mini", "gpt-5.3-codex", "gpt-5.2"]
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FALLBACK_IMAGE_MODELS = ["gpt-image-2", "gpt-image-1", "dall-e-3", "dall-e-2"]
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FALLBACK_ALL_MODELS = FALLBACK_IMAGE_MODELS + FALLBACK_CHAT_MODELS
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def normalize_boosapi_root(base):
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base = str(base or "http://127.0.0.1:4000").strip().rstrip("/")
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if base.endswith("/v1"):
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base = base[:-3].rstrip("/")
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return base or "http://127.0.0.1:4000"
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BOOSAPI_ROOT = normalize_boosapi_root(BOOSAPI_BASE_RAW)
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BOOSAPI_V1 = f"{BOOSAPI_ROOT}/v1"
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def raise_for_status_with_body(resp):
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try:
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resp.raise_for_status()
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except requests.HTTPError as e:
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body = (resp.text or "").strip()
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if body:
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print(f"[BoosAPI] HTTP {resp.status_code} response: {body[:2000]}")
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raise requests.HTTPError(f"{e}; response body: {body[:1000]}", response=resp)
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raise
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def _ordered_unique(values):
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seen = set()
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result = []
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for value in values:
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value = str(value or "").strip()
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if not value or value in seen:
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continue
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seen.add(value)
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result.append(value)
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return result
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def fetch_boosapi_models():
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"""Fetch models exposed by BoosAPI's own /v1/models route."""
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try:
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resp = requests.get(f"{BOOSAPI_V1}/models", headers=HEADERS, timeout=8)
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resp.raise_for_status()
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data = resp.json()
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models = []
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for item in data.get("data", []):
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if isinstance(item, dict):
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models.append(item.get("id") or item.get("name"))
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elif isinstance(item, str):
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models.append(item)
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return _ordered_unique(models)
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except Exception as e:
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print(f"[BoosAPI] model list fallback: {e}")
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return None
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def model_choices(kind="all"):
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models = fetch_boosapi_models()
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if models is None:
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if kind == "image":
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return FALLBACK_IMAGE_MODELS
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if kind == "chat":
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return FALLBACK_CHAT_MODELS
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return FALLBACK_ALL_MODELS
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if kind == "image":
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image_like = [
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model for model in models
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if any(token in model.lower() for token in ("image", "dall", "flux", "sd", "midjourney"))
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]
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return _ordered_unique(image_like + models) or FALLBACK_IMAGE_MODELS
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if kind == "chat":
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chat_like = [
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model for model in models
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if not any(token in model.lower() for token in ("image", "dall", "flux", "sd", "midjourney"))
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]
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return _ordered_unique(chat_like + models) or FALLBACK_CHAT_MODELS
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return _ordered_unique(models) or FALLBACK_ALL_MODELS
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def default_model(kind="all"):
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choices = model_choices(kind)
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return choices[0] if choices else FALLBACK_ALL_MODELS[0]
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# ── Node Mappings ────────────────────────────────────────────────────────
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NODE_CLASS_MAPPINGS = {}
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@@ -37,7 +120,7 @@ class BoosAPIImageGen:
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return {
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"required": {
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"prompt": ("STRING", {"multiline": True, "default": ""}),
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"model": (["dall-e-3", "dall-e-2", "gpt-image-2"], {"default": "gpt-image-2"}),
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"model": (model_choices("image"), {"default": default_model("image")}),
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"size": (["1024x1024", "1792x1024", "1024x1792"], {"default": "1024x1024"}),
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"quality": (["standard", "hd"], {"default": "standard"}),
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"n": ("INT", {"default": 1, "min": 1, "max": 4}),
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@@ -50,10 +133,11 @@ class BoosAPIImageGen:
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RETURN_TYPES = ("IMAGE", "STRING")
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RETURN_NAMES = ("image", "metadata")
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FUNCTION = "generate"
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OUTPUT_NODE = True
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CATEGORY = "BoosAPI"
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def generate(self, prompt, model, size, quality, n, style="vivid"):
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url = f"{BOOSAPI_BASE}/v1/images/generations"
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url = f"{BOOSAPI_V1}/images/generations"
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payload = {
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"model": model,
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"prompt": prompt,
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@@ -65,7 +149,7 @@ class BoosAPIImageGen:
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}
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try:
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resp = requests.post(url, headers=HEADERS, json=payload, timeout=120)
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resp.raise_for_status()
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raise_for_status_with_body(resp)
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data = resp.json()
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images = data.get("data", [])
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# Return first image as b64
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@@ -104,7 +188,7 @@ class BoosAPILLM:
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return {
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"required": {
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"prompt": ("STRING", {"multiline": True, "default": ""}),
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"model": ("STRING", {"default": "gpt-5.5"}),
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"model": (model_choices("chat"), {"default": default_model("chat")}),
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"system_prompt": ("STRING", {"multiline": True, "default": ""}),
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"temperature": ("FLOAT", {"default": 0.7, "min": 0.0, "max": 2.0}),
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"max_tokens": ("INT", {"default": 2048, "min": 1, "max": 16384}),
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@@ -114,10 +198,11 @@ class BoosAPILLM:
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("text",)
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FUNCTION = "chat"
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OUTPUT_NODE = True
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CATEGORY = "BoosAPI"
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def chat(self, prompt, model, system_prompt, temperature, max_tokens):
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url = f"{BOOSAPI_BASE}/v1/chat/completions"
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url = f"{BOOSAPI_V1}/chat/completions"
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messages = []
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if system_prompt:
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messages.append({"role": "system", "content": system_prompt})
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@@ -132,10 +217,10 @@ class BoosAPILLM:
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}
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try:
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resp = requests.post(url, headers=HEADERS, json=payload, timeout=120)
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resp.raise_for_status()
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raise_for_status_with_body(resp)
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data = resp.json()
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text = data["choices"][0]["message"]["content"]
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return (text,)
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return {"ui": {"text": (text,)}, "result": (text,)}
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except Exception as e:
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print(f"[BoosAPI] LLM chat failed: {e}")
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raise
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@@ -153,7 +238,7 @@ class BoosAPITextToImage:
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return {
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"required": {
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"positive": ("STRING", {"multiline": True, "default": ""}),
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"model": (["gpt-image-2", "dall-e-3"], {"default": "gpt-image-2"}),
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"model": (model_choices("image"), {"default": default_model("image")}),
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},
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"optional": {
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"negative": ("STRING", {"multiline": True, "default": ""}),
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@@ -163,6 +248,7 @@ class BoosAPITextToImage:
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "generate"
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OUTPUT_NODE = True
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CATEGORY = "BoosAPI"
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def generate(self, positive, model, negative="", size="1024x1024"):
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@@ -171,7 +257,7 @@ class BoosAPITextToImage:
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if negative:
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prompt = f"{positive}\n避免: {negative}"
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url = f"{BOOSAPI_BASE}/v1/images/generations"
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url = f"{BOOSAPI_V1}/images/generations"
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payload = {
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"model": model,
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"prompt": prompt,
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@@ -181,7 +267,7 @@ class BoosAPITextToImage:
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}
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try:
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resp = requests.post(url, headers=HEADERS, json=payload, timeout=120)
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resp.raise_for_status()
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raise_for_status_with_body(resp)
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data = resp.json()
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import base64
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