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fix speculative artifact persistence (#4211)

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This commit is contained in:
pedrohsdb
2025-12-05 08:39:36 -08:00
committed by GitHub
parent a2c9d88bbb
commit fadfe0848c
1 changed files with 103 additions and 78 deletions
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181
skyvern/forge/agent.py
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@@ -947,6 +947,12 @@ class ForgeAgent:
reuse_speculative_llm_response = json_response is not None
speculative_llm_metadata = speculative_plan.llm_metadata
prompt_name = speculative_plan.prompt_name
await self._persist_scrape_artifacts(
task=task,
step=step,
scraped_page=scraped_page,
context=context,
)
else:
(
scraped_page,
@@ -2371,10 +2377,11 @@ class ForgeAgent:
use_caching = False
if persist_artifacts:
await app.ARTIFACT_MANAGER.create_artifact(
await self._persist_scrape_artifacts(
task=task,
step=step,
artifact_type=ArtifactType.HTML_SCRAPE,
data=scraped_page.html.encode(),
scraped_page=scraped_page,
context=context,
)
LOG.info(
"Scraped website",
@@ -2383,54 +2390,6 @@ class ForgeAgent:
num_elements=len(scraped_page.elements),
url=task.url,
)
# TODO: we only use HTML element for now, introduce a way to switch in the future
enable_speed_optimizations = getattr(context, "enable_speed_optimizations", False)
element_tree_format = ElementTreeFormat.HTML
# OPTIMIZATION: Use economy tree (skip SVGs) when ENABLE_SPEED_OPTIMIZATIONS is enabled
# Economy tree removes all SVG elements from the DOM tree sent to LLM
# - SVGs are decorative (icons, logos, graphics) - not needed for action planning
# - Even for charts/graphs: LLM sees them in screenshots, not SVG code
# - Saves ~8s per SVG x ~15 SVGs = ~120s per workflow (30% speedup!)
#
# RETRY STRATEGY: Use economy tree on first attempt only
# - retry_index 0: Use economy tree (fast, no SVGs)
# - retry_index 1+: Use regular tree (SVGs loaded from existing 4-week cache)
# Note: SVG conversions are already cached globally with 4-week TTL, so retries are fast
#
# COORDINATION: The enable_speed_optimizations decision is made ONCE before scraping
# and stored in context. Both SVG conversion skip (agent_functions.py) and tree
# selection (here) use the SAME value, ensuring perfect coordination.
element_tree_in_prompt: str = ""
# Use the speed optimization decision from context (set before scraping)
enable_speed_optimizations = context.enable_speed_optimizations if context else False
if not enable_speed_optimizations:
# Optimization disabled - use regular tree always
element_tree_in_prompt = scraped_page.build_element_tree(element_tree_format)
elif step.retry_index == 0:
# First attempt - use economy tree (fast, no SVG conversion)
# Note: SVG conversion was already skipped in cleanup_element_tree_func
# based on the same context.enable_speed_optimizations value
element_tree_in_prompt = scraped_page.build_economy_elements_tree(element_tree_format)
LOG.info(
"Speed optimization: Using economy element tree (skipping SVGs)",
step_order=step.order,
step_retry=step.retry_index,
task_id=task.task_id,
workflow_run_id=task.workflow_run_id,
)
else:
# Retry 1+ - use regular tree (SVGs will be loaded from existing 4-week cache)
element_tree_in_prompt = scraped_page.build_element_tree(element_tree_format)
LOG.info(
"Speed optimization: Using regular tree on retry (SVGs from global cache)",
step_order=step.order,
step_retry=step.retry_index,
task_id=task.task_id,
workflow_run_id=task.workflow_run_id,
)
extract_action_prompt = ""
prompt_name = EXTRACT_ACTION_PROMPT_NAME # Default; overwritten below for non-CUA engines
if engine not in CUA_ENGINES:
@@ -2443,35 +2402,101 @@ class ForgeAgent:
expire_verification_code=True,
)
if persist_artifacts:
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_ID_CSS_MAP,
data=json.dumps(scraped_page.id_to_css_dict, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_ID_FRAME_MAP,
data=json.dumps(scraped_page.id_to_frame_dict, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_TREE,
data=json.dumps(scraped_page.element_tree, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_TREE_TRIMMED,
data=json.dumps(scraped_page.element_tree_trimmed, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_TREE_IN_PROMPT,
data=element_tree_in_prompt.encode(),
)
return scraped_page, extract_action_prompt, use_caching, prompt_name
async def _persist_scrape_artifacts(
self,
*,
task: Task,
step: Step,
scraped_page: ScrapedPage,
context: SkyvernContext | None,
) -> None:
"""
Persist the core scrape artifacts (HTML + element metadata) for a step.
This is used both for regular runs and when adopting a speculative plan.
"""
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.HTML_SCRAPE,
data=scraped_page.html.encode(),
)
element_tree_format = ElementTreeFormat.HTML
element_tree_in_prompt = self._build_element_tree_for_prompt(
scraped_page=scraped_page,
step=step,
task=task,
context=context,
element_tree_format=element_tree_format,
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_ID_CSS_MAP,
data=json.dumps(scraped_page.id_to_css_dict, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_ID_FRAME_MAP,
data=json.dumps(scraped_page.id_to_frame_dict, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_TREE,
data=json.dumps(scraped_page.element_tree, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_TREE_TRIMMED,
data=json.dumps(scraped_page.element_tree_trimmed, indent=2).encode(),
)
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
artifact_type=ArtifactType.VISIBLE_ELEMENTS_TREE_IN_PROMPT,
data=element_tree_in_prompt.encode(),
)
def _build_element_tree_for_prompt(
self,
*,
scraped_page: ScrapedPage,
step: Step,
task: Task,
context: SkyvernContext | None,
element_tree_format: ElementTreeFormat,
) -> str:
"""
Determine which element tree representation should be captured for the prompt/artifacts.
Mirrors the previous inline logic so that speculative runs can reuse it.
"""
enable_speed_optimizations = context.enable_speed_optimizations if context else False
if not enable_speed_optimizations:
return scraped_page.build_element_tree(element_tree_format)
if step.retry_index == 0:
element_tree_in_prompt = scraped_page.build_economy_elements_tree(element_tree_format)
LOG.info(
"Speed optimization: Using economy element tree (skipping SVGs)",
step_order=step.order,
step_retry=step.retry_index,
task_id=task.task_id,
workflow_run_id=task.workflow_run_id,
)
return element_tree_in_prompt
element_tree_in_prompt = scraped_page.build_element_tree(element_tree_format)
LOG.info(
"Speed optimization: Using regular tree on retry (SVGs from global cache)",
step_order=step.order,
step_retry=step.retry_index,
task_id=task.task_id,
workflow_run_id=task.workflow_run_id,
)
return element_tree_in_prompt
@staticmethod
def _build_extract_action_cache_variant(
verification_code_check: bool,