Improve visualizer output when invalid auth token is provided (#140)

This commit is contained in:
Suchintan
2024-04-01 00:36:04 -04:00
committed by GitHub
parent 0124764b6e
commit 14ea1e2417

View File

@@ -256,186 +256,202 @@ with visualizer_tab:
col_steps.markdown(f"#### Steps")
col_artifacts.markdown("#### Artifacts")
tasks_response = repository.get_tasks(task_page_number)
if "error" in tasks_response:
st.write(tasks_response)
# Display tasks in sidebar for selection
tasks = {task["task_id"]: task for task in tasks_response}
task_id_buttons = {
task_id: col_tasks.button(
f"{task_id}",
on_click=select_task,
args=(task,),
use_container_width=True,
type="primary" if selected_task and task_id == selected_task["task_id"] else "secondary",
)
for task_id, task in tasks.items()
}
# Display pagination buttons
task_page_prev, _, show_task_page_number, _, task_page_next = col_tasks.columns([1, 1, 1, 1, 1])
show_task_page_number.button(str(task_page_number), disabled=True)
if task_page_next.button("\>"):
st.session_state.task_page_number += 1
if task_page_prev.button("\<", disabled=task_page_number == 1):
st.session_state.task_page_number = max(1, st.session_state.task_page_number - 1)
(
tab_task,
tab_step,
tab_recording,
tab_screenshot,
tab_post_action_screenshot,
tab_id_to_xpath,
tab_element_tree,
tab_element_tree_trimmed,
tab_llm_prompt,
tab_llm_request,
tab_llm_response_parsed,
tab_llm_response_raw,
tab_html,
) = col_artifacts.tabs(
[
":green[Task]",
":blue[Step]",
":violet[Recording]",
":rainbow[Screenshot]",
":rainbow[Action Screenshots]",
":red[ID -> XPath]",
":orange[Element Tree]",
":blue[Element Tree (Trimmed)]",
":yellow[LLM Prompt]",
":green[LLM Request]",
":blue[LLM Response (Parsed)]",
":violet[LLM Response (Raw)]",
":rainbow[Html (Raw)]",
]
)
tab_task_details, tab_task_steps, tab_task_action_results = tab_task.tabs(["Details", "Steps", "Action Results"])
if selected_task:
tab_task_details.json(selected_task)
if selected_task_recording_uri:
streamlit_show_recording(tab_recording, selected_task_recording_uri)
if task_steps:
col_steps_prev, _, col_steps_next = col_steps.columns([3, 1, 3])
col_steps_prev.button(
"prev", on_click=go_to_previous_step, key="previous_step_button", use_container_width=True
if type(tasks_response) is not list:
st.error("Failed to fetch tasks.")
st.error(tasks_response)
if "Organization not found" in str(tasks_response) or "Could not validate credentials" in str(tasks_response):
st.error("Please check the organization credentials in .streamlit/secrets.toml.")
st.error(
"You can validate the credentials against the postgresql credentials by running\n\n"
'`psql -U skyvern -h localhost -d skyvern -c "SELECT o.organization_id, o.organization_name, token FROM organizations o JOIN organization_auth_tokens oat ON oat.organization_id = o.organization_id;"`.'
"\n\n NOTE: There might be multiple organizations -- each run of ./setup.sh creates a new one. Pick your favourite!"
)
col_steps_next.button("next", on_click=go_to_next_step, key="next_step_button", use_container_width=True)
step_id_buttons = {
step["step_id"]: col_steps.button(
f"{step['order']} - {step['retry_index']} - {step['step_id']}",
on_click=select_step,
args=(step,),
else:
# Display tasks in sidebar for selection
tasks = {task["task_id"]: task for task in tasks_response}
task_id_buttons = {
task_id: col_tasks.button(
f"{task_id}",
on_click=select_task,
args=(task,),
use_container_width=True,
type="primary" if selected_step and step["step_id"] == selected_step["step_id"] else "secondary",
type="primary" if selected_task and task_id == selected_task["task_id"] else "secondary",
)
for step in task_steps
for task_id, task in tasks.items()
}
df = pd.json_normalize(task_steps)
tab_task_steps.dataframe(df, use_container_width=True, height=1000)
# Display pagination buttons
task_page_prev, _, show_task_page_number, _, task_page_next = col_tasks.columns([1, 1, 1, 1, 1])
show_task_page_number.button(str(task_page_number), disabled=True)
if task_page_next.button("\>"):
st.session_state.task_page_number += 1
if task_page_prev.button("\<", disabled=task_page_number == 1):
st.session_state.task_page_number = max(1, st.session_state.task_page_number - 1)
task_action_results = []
for step in task_steps:
output = step.get("output")
step_id = step["step_id"]
if output:
step_action_results = output.get("action_results", [])
for action_result in step_action_results:
task_action_results.append(
{
"step_id": step_id,
"order": step["order"],
"retry_index": step["retry_index"],
**action_result,
}
)
df = pd.json_normalize(task_action_results)
df = df.reindex(sorted(df.columns), axis=1)
tab_task_action_results.dataframe(df, use_container_width=True, height=1000)
(
tab_task,
tab_step,
tab_recording,
tab_screenshot,
tab_post_action_screenshot,
tab_id_to_xpath,
tab_element_tree,
tab_element_tree_trimmed,
tab_llm_prompt,
tab_llm_request,
tab_llm_response_parsed,
tab_llm_response_raw,
tab_html,
) = col_artifacts.tabs(
[
":green[Task]",
":blue[Step]",
":violet[Recording]",
":rainbow[Screenshot]",
":rainbow[Action Screenshots]",
":red[ID -> XPath]",
":orange[Element Tree]",
":blue[Element Tree (Trimmed)]",
":yellow[LLM Prompt]",
":green[LLM Request]",
":blue[LLM Response (Parsed)]",
":violet[LLM Response (Raw)]",
":rainbow[Html (Raw)]",
]
)
if selected_step:
tab_step.json(selected_step)
tab_task_details, tab_task_steps, tab_task_action_results = tab_task.tabs(
["Details", "Steps", "Action Results"]
)
artifacts_response = repository.get_artifacts(selected_task["task_id"], selected_step["step_id"])
split_artifact_uris = [artifact["uri"].split("/") for artifact in artifacts_response]
file_name_to_uris = {split_uri[-1]: "/".join(split_uri) for split_uri in split_artifact_uris}
if selected_task:
tab_task_details.json(selected_task)
if selected_task_recording_uri:
streamlit_show_recording(tab_recording, selected_task_recording_uri)
for file_name, uri in file_name_to_uris.items():
file_name = file_name.lower()
if file_name.endswith("screenshot_llm.png") or file_name.endswith("screenshot.png"):
streamlit_content_safe(
tab_screenshot,
tab_screenshot.image,
read_artifact_safe(uri, is_image=True),
"No screenshot available.",
use_column_width=True,
)
elif file_name.endswith("screenshot_action.png"):
streamlit_content_safe(
tab_post_action_screenshot,
tab_post_action_screenshot.image,
read_artifact_safe(uri, is_image=True),
"No action screenshot available.",
use_column_width=True,
)
elif file_name.endswith("id_xpath_map.json"):
streamlit_content_safe(
tab_id_to_xpath, tab_id_to_xpath.json, read_artifact_safe(uri), "No ID -> XPath map available."
)
elif file_name.endswith("tree.json"):
streamlit_content_safe(
tab_element_tree,
tab_element_tree.json,
read_artifact_safe(uri),
"No element tree available.",
)
elif file_name.endswith("tree_trimmed.json"):
streamlit_content_safe(
tab_element_tree_trimmed,
tab_element_tree_trimmed.json,
read_artifact_safe(uri),
"No element tree trimmed available.",
)
elif file_name.endswith("llm_prompt.txt"):
content = read_artifact_safe(uri)
# this is a hacky way to call this generic method to get it working with st.text_area
streamlit_content_safe(
tab_llm_prompt,
tab_llm_prompt.text_area,
content,
"No LLM prompt available.",
value=content,
height=1000,
label_visibility="collapsed",
)
# tab_llm_prompt.text_area("collapsed", value=content, label_visibility="collapsed", height=1000)
elif file_name.endswith("llm_request.json"):
streamlit_content_safe(
tab_llm_request, tab_llm_request.json, read_artifact_safe(uri), "No LLM request available."
)
elif file_name.endswith("llm_response_parsed.json"):
streamlit_content_safe(
tab_llm_response_parsed,
tab_llm_response_parsed.json,
read_artifact_safe(uri),
"No parsed LLM response available.",
)
elif file_name.endswith("llm_response.json"):
streamlit_content_safe(
tab_llm_response_raw,
tab_llm_response_raw.json,
read_artifact_safe(uri),
"No raw LLM response available.",
)
elif file_name.endswith("html_scrape.html"):
streamlit_content_safe(tab_html, tab_html.text, read_artifact_safe(uri), "No html available.")
elif file_name.endswith("html_action.html"):
streamlit_content_safe(tab_html, tab_html.text, read_artifact_safe(uri), "No html available.")
else:
st.write(f"Artifact {file_name} not supported.")
if task_steps:
col_steps_prev, _, col_steps_next = col_steps.columns([3, 1, 3])
col_steps_prev.button(
"prev", on_click=go_to_previous_step, key="previous_step_button", use_container_width=True
)
col_steps_next.button(
"next", on_click=go_to_next_step, key="next_step_button", use_container_width=True
)
step_id_buttons = {
step["step_id"]: col_steps.button(
f"{step['order']} - {step['retry_index']} - {step['step_id']}",
on_click=select_step,
args=(step,),
use_container_width=True,
type="primary" if selected_step and step["step_id"] == selected_step["step_id"] else "secondary",
)
for step in task_steps
}
df = pd.json_normalize(task_steps)
tab_task_steps.dataframe(df, use_container_width=True, height=1000)
task_action_results = []
for step in task_steps:
output = step.get("output")
step_id = step["step_id"]
if output:
step_action_results = output.get("action_results", [])
for action_result in step_action_results:
task_action_results.append(
{
"step_id": step_id,
"order": step["order"],
"retry_index": step["retry_index"],
**action_result,
}
)
df = pd.json_normalize(task_action_results)
df = df.reindex(sorted(df.columns), axis=1)
tab_task_action_results.dataframe(df, use_container_width=True, height=1000)
if selected_step:
tab_step.json(selected_step)
artifacts_response = repository.get_artifacts(selected_task["task_id"], selected_step["step_id"])
split_artifact_uris = [artifact["uri"].split("/") for artifact in artifacts_response]
file_name_to_uris = {split_uri[-1]: "/".join(split_uri) for split_uri in split_artifact_uris}
for file_name, uri in file_name_to_uris.items():
file_name = file_name.lower()
if file_name.endswith("screenshot_llm.png") or file_name.endswith("screenshot.png"):
streamlit_content_safe(
tab_screenshot,
tab_screenshot.image,
read_artifact_safe(uri, is_image=True),
"No screenshot available.",
use_column_width=True,
)
elif file_name.endswith("screenshot_action.png"):
streamlit_content_safe(
tab_post_action_screenshot,
tab_post_action_screenshot.image,
read_artifact_safe(uri, is_image=True),
"No action screenshot available.",
use_column_width=True,
)
elif file_name.endswith("id_xpath_map.json"):
streamlit_content_safe(
tab_id_to_xpath,
tab_id_to_xpath.json,
read_artifact_safe(uri),
"No ID -> XPath map available.",
)
elif file_name.endswith("tree.json"):
streamlit_content_safe(
tab_element_tree,
tab_element_tree.json,
read_artifact_safe(uri),
"No element tree available.",
)
elif file_name.endswith("tree_trimmed.json"):
streamlit_content_safe(
tab_element_tree_trimmed,
tab_element_tree_trimmed.json,
read_artifact_safe(uri),
"No element tree trimmed available.",
)
elif file_name.endswith("llm_prompt.txt"):
content = read_artifact_safe(uri)
# this is a hacky way to call this generic method to get it working with st.text_area
streamlit_content_safe(
tab_llm_prompt,
tab_llm_prompt.text_area,
content,
"No LLM prompt available.",
value=content,
height=1000,
label_visibility="collapsed",
)
# tab_llm_prompt.text_area("collapsed", value=content, label_visibility="collapsed", height=1000)
elif file_name.endswith("llm_request.json"):
streamlit_content_safe(
tab_llm_request, tab_llm_request.json, read_artifact_safe(uri), "No LLM request available."
)
elif file_name.endswith("llm_response_parsed.json"):
streamlit_content_safe(
tab_llm_response_parsed,
tab_llm_response_parsed.json,
read_artifact_safe(uri),
"No parsed LLM response available.",
)
elif file_name.endswith("llm_response.json"):
streamlit_content_safe(
tab_llm_response_raw,
tab_llm_response_raw.json,
read_artifact_safe(uri),
"No raw LLM response available.",
)
elif file_name.endswith("html_scrape.html"):
streamlit_content_safe(tab_html, tab_html.text, read_artifact_safe(uri), "No html available.")
elif file_name.endswith("html_action.html"):
streamlit_content_safe(tab_html, tab_html.text, read_artifact_safe(uri), "No html available.")
else:
st.write(f"Artifact {file_name} not supported.")