feat(platform): add missing OpenAI API models (GPT-5.4, O4-mini, O3-pro, etc.)

Add 18 missing OpenAI models to the platform's LLM blocks:

- GPT-5.4 series (current flagship): gpt-5.4, gpt-5.4-mini, gpt-5.4-nano, gpt-5.4-pro
- O-series reasoning: o4-mini, o4-mini-deep-research, o3-pro, o3-deep-research
- GPT-5.3 series: gpt-5.3, gpt-5.3-codex
- Pro variants: gpt-5.2-pro, gpt-5-pro
- Codex models: gpt-5.1-codex
- Legacy: gpt-4.1-nano

Changes:
- LlmModel enum: added 18 new model entries with proper API model IDs
- MODEL_METADATA: added context window, max output tokens, and pricing tier
- block_cost_config.py: added credit costs for all new models
- codex.py: added GPT-5.3 Codex and updated default
- Updated DEFAULT_LLM_MODEL from GPT-5.2 to GPT-5.4

autogpt_platform/backend/backend/blocks/codex.py

@@ -35,6 +35,7 @@ class CodexCallResult:
 class CodexModel(str, Enum):
     """Codex-capable OpenAI models."""
 
+    GPT5_3_CODEX = "gpt-5.3-codex"
     GPT5_1_CODEX = "gpt-5.1-codex"
 
 
@@ -91,7 +92,7 @@ class CodeGenerationBlock(Block):
         )
         model: CodexModel = SchemaField(
             title="Codex Model",
-            default=CodexModel.GPT5_1_CODEX,
+            default=CodexModel.GPT5_3_CODEX,
             description="Codex-optimized model served via the Responses API.",
             advanced=False,
         )

autogpt_platform/backend/backend/blocks/llm.py

@@ -116,20 +116,39 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
                 return None
         return None
 
-    # OpenAI models
-    O3_MINI = "o3-mini"
+    # OpenAI models — O-series reasoning
+    O4_MINI = "o4-mini"
+    O4_MINI_DEEP_RESEARCH = "o4-mini-deep-research"
     O3 = "o3-2025-04-16"
+    O3_MINI = "o3-mini"
+    O3_PRO = "o3-pro"
+    O3_DEEP_RESEARCH = "o3-deep-research"
     O1 = "o1"
     O1_MINI = "o1-mini"
-    # GPT-5 models
+    # OpenAI models — GPT-5.4 series (current flagship)
+    GPT5_4 = "gpt-5.4-2026-03-05"
+    GPT5_4_MINI = "gpt-5.4-mini-2026-03-17"
+    GPT5_4_NANO = "gpt-5.4-nano-2026-03-17"
+    GPT5_4_PRO = "gpt-5.4-pro"
+    # OpenAI models — GPT-5.3 series
+    GPT5_3 = "gpt-5.3"
+    GPT5_3_CODEX = "gpt-5.3-codex"
+    # OpenAI models — GPT-5.2 series
     GPT5_2 = "gpt-5.2-2025-12-11"
+    GPT5_2_PRO = "gpt-5.2-pro"
+    # OpenAI models — GPT-5.1 series
     GPT5_1 = "gpt-5.1-2025-11-13"
+    GPT5_1_CODEX = "gpt-5.1-codex"
+    # OpenAI models — GPT-5 series
     GPT5 = "gpt-5-2025-08-07"
     GPT5_MINI = "gpt-5-mini-2025-08-07"
     GPT5_NANO = "gpt-5-nano-2025-08-07"
+    GPT5_PRO = "gpt-5-pro"
     GPT5_CHAT = "gpt-5-chat-latest"
+    # OpenAI models — GPT-4.x series
     GPT41 = "gpt-4.1-2025-04-14"
     GPT41_MINI = "gpt-4.1-mini-2025-04-14"
+    GPT41_NANO = "gpt-4.1-nano"
     GPT4O_MINI = "gpt-4o-mini"
     GPT4O = "gpt-4o"
     GPT4_TURBO = "gpt-4-turbo"
@@ -254,23 +273,64 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
 
 MODEL_METADATA = {
     # https://platform.openai.com/docs/models
+    # O-series reasoning models
+    LlmModel.O4_MINI: ModelMetadata(
+        "openai", 200000, 100000, "O4 Mini", "OpenAI", "OpenAI", 1
+    ),
+    LlmModel.O4_MINI_DEEP_RESEARCH: ModelMetadata(
+        "openai", 200000, 100000, "O4 Mini Deep Research", "OpenAI", "OpenAI", 2
+    ),
     LlmModel.O3: ModelMetadata("openai", 200000, 100000, "O3", "OpenAI", "OpenAI", 2),
     LlmModel.O3_MINI: ModelMetadata(
         "openai", 200000, 100000, "O3 Mini", "OpenAI", "OpenAI", 1
     ),  # o3-mini-2025-01-31
+    LlmModel.O3_PRO: ModelMetadata(
+        "openai", 200000, 100000, "O3 Pro", "OpenAI", "OpenAI", 3
+    ),
+    LlmModel.O3_DEEP_RESEARCH: ModelMetadata(
+        "openai", 200000, 100000, "O3 Deep Research", "OpenAI", "OpenAI", 3
+    ),
     LlmModel.O1: ModelMetadata(
         "openai", 200000, 100000, "O1", "OpenAI", "OpenAI", 3
     ),  # o1-2024-12-17
     LlmModel.O1_MINI: ModelMetadata(
         "openai", 128000, 65536, "O1 Mini", "OpenAI", "OpenAI", 2
     ),  # o1-mini-2024-09-12
-    # GPT-5 models
+    # GPT-5.4 models (current flagship, March 2026)
+    LlmModel.GPT5_4: ModelMetadata(
+        "openai", 1050000, 128000, "GPT-5.4", "OpenAI", "OpenAI", 2
+    ),
+    LlmModel.GPT5_4_MINI: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5.4 Mini", "OpenAI", "OpenAI", 1
+    ),
+    LlmModel.GPT5_4_NANO: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5.4 Nano", "OpenAI", "OpenAI", 1
+    ),
+    LlmModel.GPT5_4_PRO: ModelMetadata(
+        "openai", 1050000, 128000, "GPT-5.4 Pro", "OpenAI", "OpenAI", 3
+    ),
+    # GPT-5.3 models
+    LlmModel.GPT5_3: ModelMetadata(
+        "openai", 128000, 16384, "GPT-5.3", "OpenAI", "OpenAI", 2
+    ),
+    LlmModel.GPT5_3_CODEX: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5.3 Codex", "OpenAI", "OpenAI", 2
+    ),
+    # GPT-5.2 models
     LlmModel.GPT5_2: ModelMetadata(
         "openai", 400000, 128000, "GPT-5.2", "OpenAI", "OpenAI", 3
     ),
+    LlmModel.GPT5_2_PRO: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5.2 Pro", "OpenAI", "OpenAI", 3
+    ),
+    # GPT-5.1 models
     LlmModel.GPT5_1: ModelMetadata(
         "openai", 400000, 128000, "GPT-5.1", "OpenAI", "OpenAI", 2
     ),
+    LlmModel.GPT5_1_CODEX: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5.1 Codex", "OpenAI", "OpenAI", 2
+    ),
+    # GPT-5 models
     LlmModel.GPT5: ModelMetadata(
         "openai", 400000, 128000, "GPT-5", "OpenAI", "OpenAI", 1
     ),
@@ -280,15 +340,22 @@ MODEL_METADATA = {
     LlmModel.GPT5_NANO: ModelMetadata(
         "openai", 400000, 128000, "GPT-5 Nano", "OpenAI", "OpenAI", 1
     ),
+    LlmModel.GPT5_PRO: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5 Pro", "OpenAI", "OpenAI", 3
+    ),
     LlmModel.GPT5_CHAT: ModelMetadata(
         "openai", 400000, 16384, "GPT-5 Chat Latest", "OpenAI", "OpenAI", 2
     ),
+    # GPT-4.x models
     LlmModel.GPT41: ModelMetadata(
         "openai", 1047576, 32768, "GPT-4.1", "OpenAI", "OpenAI", 1
     ),
     LlmModel.GPT41_MINI: ModelMetadata(
         "openai", 1047576, 32768, "GPT-4.1 Mini", "OpenAI", "OpenAI", 1
     ),
+    LlmModel.GPT41_NANO: ModelMetadata(
+        "openai", 1047576, 32768, "GPT-4.1 Nano", "OpenAI", "OpenAI", 1
+    ),
     LlmModel.GPT4O_MINI: ModelMetadata(
         "openai", 128000, 16384, "GPT-4o Mini", "OpenAI", "OpenAI", 1
     ),  # gpt-4o-mini-2024-07-18
@@ -661,7 +728,7 @@ MODEL_METADATA = {
     LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000, "v0 1.0 MD", "V0", "V0", 1),
 }
 
-DEFAULT_LLM_MODEL = LlmModel.GPT5_2
+DEFAULT_LLM_MODEL = LlmModel.GPT5_4
 
 for model in LlmModel:
     if model not in MODEL_METADATA:

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -60,19 +60,33 @@ from backend.integrations.credentials_store import (
 # =============== Configure the cost for each LLM Model call =============== #
 
 MODEL_COST: dict[LlmModel, int] = {
+    LlmModel.O4_MINI: 2,
+    LlmModel.O4_MINI_DEEP_RESEARCH: 5,
     LlmModel.O3: 4,
     LlmModel.O3_MINI: 2,
+    LlmModel.O3_PRO: 30,
+    LlmModel.O3_DEEP_RESEARCH: 15,
     LlmModel.O1: 16,
     LlmModel.O1_MINI: 4,
     # GPT-5 models
+    LlmModel.GPT5_4: 5,
+    LlmModel.GPT5_4_MINI: 2,
+    LlmModel.GPT5_4_NANO: 1,
+    LlmModel.GPT5_4_PRO: 60,
+    LlmModel.GPT5_3: 5,
+    LlmModel.GPT5_3_CODEX: 5,
     LlmModel.GPT5_2: 6,
+    LlmModel.GPT5_2_PRO: 60,
     LlmModel.GPT5_1: 5,
+    LlmModel.GPT5_1_CODEX: 4,
     LlmModel.GPT5: 2,
     LlmModel.GPT5_MINI: 1,
     LlmModel.GPT5_NANO: 1,
+    LlmModel.GPT5_PRO: 30,
     LlmModel.GPT5_CHAT: 5,
     LlmModel.GPT41: 2,
     LlmModel.GPT41_MINI: 1,
+    LlmModel.GPT41_NANO: 1,
     LlmModel.GPT4O_MINI: 1,
     LlmModel.GPT4O: 3,
     LlmModel.GPT4_TURBO: 10,
@@ -285,6 +299,18 @@ BLOCK_COSTS: dict[Type[Block], list[BlockCost]] = {
     AITextSummarizerBlock: LLM_COST,
     AIListGeneratorBlock: LLM_COST,
     CodeGenerationBlock: [
+        BlockCost(
+            cost_type=BlockCostType.RUN,
+            cost_filter={
+                "model": CodexModel.GPT5_3_CODEX,
+                "credentials": {
+                    "id": openai_credentials.id,
+                    "provider": openai_credentials.provider,
+                    "type": openai_credentials.type,
+                },
+            },
+            cost_amount=5,
+        ),
         BlockCost(
             cost_type=BlockCostType.RUN,
             cost_filter={
@@ -296,7 +322,7 @@ BLOCK_COSTS: dict[Type[Block], list[BlockCost]] = {
                 },
             },
             cost_amount=5,
-        )
+        ),
     ],
     CreateTalkingAvatarVideoBlock: [
         BlockCost(