Context Big (rgthree)

rgthree

Context Big (rgthree)

Example

JSON Example

{
  "class_type": "Context Big (rgthree)",
  "inputs": {}
}

This example shows required inputs only. Connection values like ["node_id", 0] should reference actual node IDs from your workflow.

Inputs

Name	Type	Status	Constraints	Default
base_ctx	RGTHREE_CONTEXT	optional	-	-
model	MODEL	optional	-	-
clip	CLIP	optional	-	-
vae	VAE	optional	-	-
positive	CONDITIONING	optional	-	-
negative	CONDITIONING	optional	-	-
latent	LATENT	optional	-	-
images	IMAGE	optional	-	-
seed	INT	optional	-	-
steps	INT	optional	-	-
step_refiner	INT	optional	-	-
cfg	FLOAT	optional	-	-
ckpt_name	ENUM 0 options URL: Checkpoint	optional	-	-
sampler	ENUM 44 options euler euler_cfg_pp euler_ancestral euler_ancestral_cfg_pp heun heunpp2 exp_heun_2_x0 exp_heun_2_x0_sde dpm_2 dpm_2_ancestral lms dpm_fast dpm_adaptive dpmpp_2s_ancestral dpmpp_2s_ancestral_cfg_pp dpmpp_sde dpmpp_sde_gpu dpmpp_2m dpmpp_2m_cfg_pp dpmpp_2m_sde dpmpp_2m_sde_gpu dpmpp_2m_sde_heun dpmpp_2m_sde_heun_gpu dpmpp_3m_sde dpmpp_3m_sde_gpu ddpm lcm ipndm ipndm_v deis res_multistep res_multistep_cfg_pp res_multistep_ancestral res_multistep_ancestral_cfg_pp gradient_estimation gradient_estimation_cfg_pp er_sde seeds_2 seeds_3 sa_solver sa_solver_pece ddim uni_pc uni_pc_bh2	optional	-	-
scheduler	ENUM 9 options simple sgm_uniform karras exponential ddim_uniform beta normal linear_quadratic kl_optimal	optional	-	-
clip_width	INT	optional	-	-
clip_height	INT	optional	-	-
text_pos_g	STRING	optional	-	-
text_pos_l	STRING	optional	-	-
text_neg_g	STRING	optional	-	-
text_neg_l	STRING	optional	-	-
mask	MASK	optional	-	-
control_net	CONTROL_NET	optional	-	-

Outputs

Index	Name	Type	Is List	Connection Reference
0	CONTEXT	RGTHREE_CONTEXT	No	["{node_id}", 0]
1	MODEL	MODEL	No	["{node_id}", 1]
2	CLIP	CLIP	No	["{node_id}", 2]
3	VAE	VAE	No	["{node_id}", 3]
4	POSITIVE	CONDITIONING	No	["{node_id}", 4]
5	NEGATIVE	CONDITIONING	No	["{node_id}", 5]
6	LATENT	LATENT	No	["{node_id}", 6]
7	IMAGE	IMAGE	No	["{node_id}", 7]
8	SEED	INT	No	["{node_id}", 8]
9	STEPS	INT	No	["{node_id}", 9]
10	STEP_REFINER	INT	No	["{node_id}", 10]
11	CFG	FLOAT	No	["{node_id}", 11]
12	CKPT_NAME		No	["{node_id}", 12]
13	SAMPLER	eulereuler_cfg_ppeuler_ancestraleuler_ancestral_cfg_ppheunheunpp2exp_heun_2_x0exp_heun_2_x0_sdedpm_2dpm_2_ancestrallmsdpm_fastdpm_adaptivedpmpp_2s_ancestraldpmpp_2s_ancestral_cfg_ppdpmpp_sdedpmpp_sde_gpudpmpp_2mdpmpp_2m_cfg_ppdpmpp_2m_sdedpmpp_2m_sde_gpudpmpp_2m_sde_heundpmpp_2m_sde_heun_gpudpmpp_3m_sdedpmpp_3m_sde_gpuddpmlcmipndmipndm_vdeisres_multistepres_multistep_cfg_ppres_multistep_ancestralres_multistep_ancestral_cfg_ppgradient_estimationgradient_estimation_cfg_pper_sdeseeds_2seeds_3sa_solversa_solver_peceddimuni_pcuni_pc_bh2	No	["{node_id}", 13]
14	SCHEDULER	simplesgm_uniformkarrasexponentialddim_uniformbetanormallinear_quadratickl_optimal	No	["{node_id}", 14]
15	CLIP_WIDTH	INT	No	["{node_id}", 15]
16	CLIP_HEIGHT	INT	No	["{node_id}", 16]
17	TEXT_POS_G	STRING	No	["{node_id}", 17]
18	TEXT_POS_L	STRING	No	["{node_id}", 18]
19	TEXT_NEG_G	STRING	No	["{node_id}", 19]
20	TEXT_NEG_L	STRING	No	["{node_id}", 20]
21	MASK	MASK	No	["{node_id}", 21]
22	CONTROL_NET	CONTROL_NET	No	["{node_id}", 22]

How to connect to these outputs

To connect another node's input to an output from this node, use the connection reference format:

["node_id", output_index]

Where node_id is the ID of this Context Big (rgthree) node in your workflow, and output_index is the index from the table above.

Example

If this node has ID "5" in your workflow:

• CONTEXT (RGTHREE_CONTEXT): ["5", 0]
• MODEL (MODEL): ["5", 1]
• CLIP (CLIP): ["5", 2]

Package: rgthree-comfy