Fixed image extraction.

Author: srtab

daiv/automation/agents/image_url_extractor/schemas.py

@@ -21,7 +21,7 @@ class ImageTemplate(BaseModel):
 
     @staticmethod
     def from_images(
-        images: list[Image], repo_client_slug: str | None = None, project_id: int | None = None
+        images: list[Image], repo_client_slug: ClientType | None = None, project_id: int | None = None
     ) -> list[dict]:
         """
         Create a list of image templates from a list of images.
@@ -47,7 +47,7 @@ def from_images(
                 and not parsed_url.scheme
                 and repo_client_slug == ClientType.GITLAB
                 and project_id
-                and parsed_url.path.startswith("uploads/")
+                and parsed_url.path.startswith(("/uploads/", "uploads/"))
             ):
                 _repo_image_url = build_uri(f"{settings.GITLAB_URL}api/v4/projects/{project_id}/", image.url)
                 image_url = url_to_data_url(

daiv/automation/agents/issue_addressor/agent.py

@@ -103,14 +103,13 @@ def prepare_data(self, state: OverallState, config: RunnableConfig) -> Command[L
         return Command(
             goto="plan_and_execute",
             update={
-                "image_templates": extracted_images,
                 "messages": HumanMessagePromptTemplate.from_template(
                     [issue_addressor_human] + extracted_images, "jinja2"
                 ).format_messages(
                     issue_title=state["issue_title"],
                     issue_description=state["issue_description"],
                     project_description=repo_config.repository_description,
-                ),
+                )
             },
         )
 

daiv/automation/agents/issue_addressor/state.py

@@ -16,8 +16,3 @@ class OverallState(MessagesState):
     """
     Whether the issue is a request for changes.
     """
-
-    image_templates: list[dict]
-    """
-    The image templates to be used in the issue addressor.
-    """

daiv/automation/agents/plan_and_execute/agent.py

@@ -156,7 +156,7 @@ def execute_plan(
             store=store,
             prompt=ChatPromptTemplate.from_messages([
                 execute_plan_system,
-                HumanMessagePromptTemplate.from_template([execute_plan_human] + state["image_templates"], "jinja2"),
+                HumanMessagePromptTemplate.from_template(execute_plan_human, "jinja2"),
                 MessagesPlaceholder("messages"),
             ]).partial(current_date_time=timezone.now().strftime("%d %B, %Y %H:%M")),
             checkpointer=False,  # Disable checkpointer to avoid storing the execution in the store

daiv/automation/agents/plan_and_execute/prompts.py

@@ -32,6 +32,7 @@
 
 <making_the_plan>
 When creating the plan, you must ensure that changes are broken down so that they can be applied in parallel and independently. Each change SHOULD be self-contained and actionable, focusing only on the changes that need to be made to address the user request. Be sure to include all details and describe code locations by pattern. Do not include preambles or post-amble changes, focus only on the user request. When providing the plan only describe the changes to be made using natural language, don't implement the changes yourself, you're the architect, not the engineer.
+If images are provided, describe them in detail, but only what's relevant to the user request. Use the `think` tool in a separate step to analyze the images.
 
 REMEMBER: You're the architect, so be detailed and specific about the changes that need to be made to ensure that user requirements are met and codebase quality is maintained; the engineer will be doing the actual implementation and writing of the code, and their success depends on the plan you provide.
 </making_the_plan>

daiv/automation/agents/plan_and_execute/state.py

@@ -26,11 +26,6 @@ class PlanAndExecuteState(MessagesState):
     The state of the overall plan and execute agent.
     """
 
-    image_templates: list[dict]
-    """
-    The image templates to be used in the plan and execute agent.
-    """
-
     plan_questions: list[str]
     """
     The questions to be answered by the human to clarify it's intent.

daiv/codebase/managers/issue_addressor.py

@@ -117,7 +117,7 @@ def _process_issue(self, should_reset_plan: bool):
                 "source_repo_id": self.repo_id,
                 "source_ref": self.ref,
                 "issue_id": self.issue.iid,
-                "repo_client": str(self.client.client_slug),
+                "repo_client": self.client.client_slug,
             },
         )