pr comments

autogpt_platform/backend/backend/api/features/v1.py

@@ -7,7 +7,6 @@ from collections import defaultdict
 from datetime import datetime, timezone
 from typing import Annotated, Any, Sequence, get_args
 
-import prisma.models
 import pydantic
 import stripe
 from autogpt_libs.auth import get_user_id, requires_user
@@ -829,43 +828,27 @@ async def update_graph(
     existing_versions = await graph_db.get_graph_all_versions(graph_id, user_id=user_id)
     if not existing_versions:
         # User doesn't own this graph -- check if they have it in their library
-        # (e.g. added from the marketplace). If so, fork it with their edits applied.
-        library_agent = await prisma.models.LibraryAgent.prisma().find_first(
-            where={
-                "userId": user_id,
-                "agentGraphId": graph_id,
-                "isDeleted": False,
-            }
+        # (e.g. added from the marketplace). If so, fork it and apply their edits.
+        library_agent = await library_db.get_library_agent_by_graph_id(
+            user_id=user_id, graph_id=graph_id
         )
         if not library_agent:
             raise HTTPException(404, detail=f"Graph #{graph_id} not found")
 
-        # Fork: apply the user's edits to a new user-owned graph
-        graph.version = 1
-        graph.is_active = True
-        forked = graph_db.make_graph_model(graph, user_id)
-        forked.forked_from_id = graph_id
-        forked.forked_from_version = library_agent.agentGraphVersion
-        forked.reassign_ids(user_id=user_id, reassign_graph_id=True)
-        forked.validate_graph(for_run=False)
-
-        new_graph_version = await graph_db.create_graph(forked, user_id=user_id)
-        new_graph_version = await on_graph_activate(new_graph_version, user_id=user_id)
+        # Fork the marketplace agent to create a user-owned copy
+        forked = await graph_db.fork_graph(
+            graph_id, library_agent.graph_version, user_id
+        )
+        forked = await on_graph_activate(forked, user_id=user_id)
         await graph_db.set_graph_active_version(
-            graph_id=new_graph_version.id,
-            version=new_graph_version.version,
-            user_id=user_id,
+            graph_id=forked.id, version=forked.version, user_id=user_id
         )
-        await library_db.create_library_agent(new_graph_version, user_id)
+        await library_db.create_library_agent(forked, user_id)
 
-        new_graph_with_subgraphs = await graph_db.get_graph(
-            new_graph_version.id,
-            new_graph_version.version,
-            user_id=user_id,
-            include_subgraphs=True,
-        )
-        assert new_graph_with_subgraphs
-        return new_graph_with_subgraphs
+        # Apply the user's edits on top of the fork via the normal update path
+        graph_id = forked.id
+        graph.id = forked.id
+        existing_versions = [forked]
 
     graph.version = max(g.version for g in existing_versions) + 1
     current_active_version = next((v for v in existing_versions if v.is_active), None)

autogpt_platform/backend/backend/blocks/llm.py

@@ -531,12 +531,12 @@ class LLMResponse(BaseModel):
 
 def convert_openai_tool_fmt_to_anthropic(
     openai_tools: list[dict] | None = None,
-) -> Iterable[ToolParam] | anthropic.Omit:
+) -> Iterable[ToolParam] | anthropic.NotGiven:
     """
     Convert OpenAI tool format to Anthropic tool format.
     """
     if not openai_tools or len(openai_tools) == 0:
-        return anthropic.omit
+        return anthropic.NOT_GIVEN
 
     anthropic_tools = []
     for tool in openai_tools:
@@ -596,10 +596,10 @@ def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
 
 def get_parallel_tool_calls_param(
     llm_model: LlmModel, parallel_tool_calls: bool | None
-) -> bool | openai.Omit:
+) -> bool | openai.NotGiven:
     """Get the appropriate parallel_tool_calls parameter for OpenAI-compatible APIs."""
     if llm_model.startswith("o") or parallel_tool_calls is None:
-        return openai.omit
+        return openai.NOT_GIVEN
     return parallel_tool_calls
 
 
@@ -676,7 +676,7 @@ async def llm_call(
             response_format=response_format,  # type: ignore
             max_completion_tokens=max_tokens,
             tools=tools_param,  # type: ignore
-            parallel_tool_calls=parallel_tool_calls,
+            parallel_tool_calls=parallel_tool_calls,  # type: ignore
         )
 
         tool_calls = extract_openai_tool_calls(response)
@@ -722,7 +722,7 @@ async def llm_call(
                 system=sysprompt,
                 messages=messages,
                 max_tokens=max_tokens,
-                tools=an_tools,
+                tools=an_tools,  # type: ignore
                 timeout=600,
             )
 
@@ -838,7 +838,7 @@ async def llm_call(
             messages=prompt,  # type: ignore
             max_tokens=max_tokens,
             tools=tools_param,  # type: ignore
-            parallel_tool_calls=parallel_tool_calls_param,
+            parallel_tool_calls=parallel_tool_calls_param,  # type: ignore
         )
 
         # If there's no response, raise an error
@@ -880,7 +880,7 @@ async def llm_call(
             messages=prompt,  # type: ignore
             max_tokens=max_tokens,
             tools=tools_param,  # type: ignore
-            parallel_tool_calls=parallel_tool_calls_param,
+            parallel_tool_calls=parallel_tool_calls_param,  # type: ignore
         )
 
         # If there's no response, raise an error
@@ -951,7 +951,7 @@ async def llm_call(
             response_format=response_format,  # type: ignore
             max_tokens=max_tokens,
             tools=tools_param,  # type: ignore
-            parallel_tool_calls=parallel_tool_calls_param,
+            parallel_tool_calls=parallel_tool_calls_param,  # type: ignore
         )
 
         tool_calls = extract_openai_tool_calls(response)