refactor(backend): Introduced Graph Input & Output Schema, Merge GraphMeta & Graph, Remove subgraph functionality

autogpt_platform/backend/backend/blocks/branching.py

@@ -71,11 +71,18 @@ def __init__(self):
         )
 
     def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        value1 = input_data.value1
         operator = input_data.operator
+
+        value1 = input_data.value1
+        if isinstance(value1, str):
+            value1 = float(value1.strip())
+
         value2 = input_data.value2
+        if isinstance(value2, str):
+            value2 = float(value2.strip())
+
         yes_value = input_data.yes_value if input_data.yes_value is not None else value1
-        no_value = input_data.no_value if input_data.no_value is not None else value1
+        no_value = input_data.no_value if input_data.no_value is not None else value2
 
         comparison_funcs = {
             ComparisonOperator.EQUAL: lambda a, b: a == b,
@@ -86,17 +93,11 @@ def run(self, input_data: Input, **kwargs) -> BlockOutput:
             ComparisonOperator.LESS_THAN_OR_EQUAL: lambda a, b: a <= b,
         }
 
-        try:
-            result = comparison_funcs[operator](value1, value2)
-
-            yield "result", result
+        result = comparison_funcs[operator](value1, value2)
 
-            if result:
-                yield "yes_output", yes_value
-            else:
-                yield "no_output", no_value
+        yield "result", result
 
-        except Exception:
-            yield "result", None
-            yield "yes_output", None
-            yield "no_output", None
+        if result:
+            yield "yes_output", yes_value
+        else:
+            yield "no_output", no_value

autogpt_platform/backend/backend/data/execution.py

@@ -9,14 +9,11 @@
     AgentNodeExecution,
     AgentNodeExecutionInputOutput,
 )
-from prisma.types import (
-    AgentGraphExecutionInclude,
-    AgentGraphExecutionWhereInput,
-    AgentNodeExecutionInclude,
-)
+from prisma.types import AgentGraphExecutionWhereInput
 from pydantic import BaseModel
 
 from backend.data.block import BlockData, BlockInput, CompletedBlockOutput
+from backend.data.includes import EXECUTION_RESULT_INCLUDE, GRAPH_EXECUTION_INCLUDE
 from backend.util import json, mock
 
 
@@ -110,24 +107,6 @@ def from_db(execution: AgentNodeExecution):
 
 # --------------------- Model functions --------------------- #
 
-EXECUTION_RESULT_INCLUDE: AgentNodeExecutionInclude = {
-    "Input": True,
-    "Output": True,
-    "AgentNode": True,
-    "AgentGraphExecution": True,
-}
-
-GRAPH_EXECUTION_INCLUDE: AgentGraphExecutionInclude = {
-    "AgentNodeExecutions": {
-        "include": {
-            "Input": True,
-            "Output": True,
-            "AgentNode": True,
-            "AgentGraphExecution": True,
-        }
-    }
-}
-
 
 async def create_graph_execution(
     graph_id: str,
@@ -268,21 +247,9 @@ async def update_graph_execution_start_time(graph_exec_id: str):
 
 async def update_graph_execution_stats(
     graph_exec_id: str,
-    error: Exception | None,
-    wall_time: float,
-    cpu_time: float,
-    node_count: int,
+    stats: dict[str, Any],
 ):
-    status = ExecutionStatus.FAILED if error else ExecutionStatus.COMPLETED
-    stats = (
-        {
-            "walltime": wall_time,
-            "cputime": cpu_time,
-            "nodecount": node_count,
-            "error": str(error) if error else None,
-        },
-    )
-
+    status = ExecutionStatus.FAILED if stats.get("error") else ExecutionStatus.COMPLETED
     await AgentGraphExecution.prisma().update(
         where={"id": graph_exec_id},
         data={