1 files changed, 0 insertions, 76 deletions
diff --git a/autogpt/core/planning/schema.py b/autogpt/core/planning/schema.py
deleted file mode 100644
index 4c19ea4b6..000000000
--- a/autogpt/core/planning/schema.py
+++ /dev/null
@@ -1,76 +0,0 @@
-import enum
-
-from pydantic import BaseModel, Field
-
-from autogpt.core.ability.schema import AbilityResult
-from autogpt.core.resource.model_providers.schema import (
-    LanguageModelFunction,
-    LanguageModelMessage,
-    LanguageModelProviderModelResponse,
-)
-
-
-class LanguageModelClassification(str, enum.Enum):
-    """The LanguageModelClassification is a functional description of the model.
-
-    This is used to determine what kind of model to use for a given prompt.
-    Sometimes we prefer a faster or cheaper model to accomplish a task when
-    possible.
-
-    """
-
-    FAST_MODEL: str = "fast_model"
-    SMART_MODEL: str = "smart_model"
-
-
-class LanguageModelPrompt(BaseModel):
-    messages: list[LanguageModelMessage]
-    functions: list[LanguageModelFunction] = Field(default_factory=list)
-
-    def __str__(self):
-        return "\n\n".join([f"{m.role.value}: {m.content}" for m in self.messages])
-
-
-class LanguageModelResponse(LanguageModelProviderModelResponse):
-    """Standard response struct for a response from a language model."""
-
-
-class TaskType(str, enum.Enum):
-    RESEARCH: str = "research"
-    WRITE: str = "write"
-    EDIT: str = "edit"
-    CODE: str = "code"
-    DESIGN: str = "design"
-    TEST: str = "test"
-    PLAN: str = "plan"
-
-
-class TaskStatus(str, enum.Enum):
-    BACKLOG: str = "backlog"
-    READY: str = "ready"
-    IN_PROGRESS: str = "in_progress"
-    DONE: str = "done"
-
-
-class TaskContext(BaseModel):
-    cycle_count: int = 0
-    status: TaskStatus = TaskStatus.BACKLOG
-    parent: "Task" = None
-    prior_actions: list[AbilityResult] = Field(default_factory=list)
-    memories: list = Field(default_factory=list)
-    user_input: list[str] = Field(default_factory=list)
-    supplementary_info: list[str] = Field(default_factory=list)
-    enough_info: bool = False
-
-
-class Task(BaseModel):
-    objective: str
-    type: str  # TaskType  FIXME: gpt does not obey the enum parameter in its schema
-    priority: int
-    ready_criteria: list[str]
-    acceptance_criteria: list[str]
-    context: TaskContext = Field(default_factory=TaskContext)
-
-
-# Need to resolve the circular dependency between Task and TaskContext once both models are defined.
-TaskContext.update_forward_refs()