fill the search quota by measuring instead of assuming a rate

searches_needed was computed once as (max - earned) // 5 and never re-checked. Two assumptions fail in practice: some markets award 3 points per search rather than 5, and the daily maximum itself is not stable, observed as 15, 30 and 60 on one account within a day with the counter resetting. The run therefore stopped around 18/30 and still reported success.

Search in rounds instead: measure, run a batch sized on the lower known rate, measure again, stop when the quota is full or a round gains nothing, and warn instead of claiming success when it is not filled.

Also give the ollama client a timeout and bound the empty-response retry, since both were unbounded and an unattended run hung for 14 minutes with 2.3 CPU-seconds. The bare while-not-response loop spins forever on empty responses.
This commit is contained in:
mardausdennis
2026-08-25 22:28:14 +02:00
parent 17830f0872
commit 77d9ec2a0f
2 changed files with 70 additions and 19 deletions
+23 -3
View File
@@ -31,14 +31,34 @@ DEFAULT_USER_PROMPT_FOR_SEARCH_POINTS_WITHOUT_DESC = """Generate the first searc
USER_PROMPT_FOR_SEARCH_QUERY_CONTINUATION = """Generate the next search query."""
# Without an explicit timeout a stalled or cold ollama backend blocks the whole
# run forever, which is fatal for an unattended scheduled run.
_CLIENT = ollama.Client(timeout=180)
MAX_EMPTY_RETRIES = 5
def get_ollama_response(messages: list[dict[str, str]], model: str="gemma4:cloud") -> str:
response = ollama.chat(
response = _CLIENT.chat(
model=model,
messages=messages
)
return response.message.content
def get_nonempty_ollama_response(messages: list[dict[str, str]]) -> str:
"""Retry a bounded number of times instead of spinning forever on empties."""
for attempt in range(MAX_EMPTY_RETRIES):
response = get_ollama_response(messages)
if response and response.strip():
return response
print(f"[WARNING] Empty LLM response, retry {attempt + 1}/{MAX_EMPTY_RETRIES}")
raise RuntimeError(f"LLM returned nothing usable after {MAX_EMPTY_RETRIES} attempts")
def get_search_query_from_task_description(task_description: str) -> str:
# compat
if "lyrics of your favorite song" in task_description.lower(): return "sweet caroline lyrics"
@@ -54,7 +74,7 @@ def get_search_query_from_task_description(task_description: str) -> str:
}
]
while not (response := get_ollama_response(messages)): pass # ensure non-empty response
response = get_nonempty_ollama_response(messages)
return response.lower()
@@ -71,7 +91,7 @@ def get_related_search_queries(seed_word: str, num_queries: int=20) -> Generator
]
for _ in range(num_queries):
while not (response := get_ollama_response(messages)): pass # ensure non-empty response
response = get_nonempty_ollama_response(messages)
yield response.lower()
+47 -16
View File
@@ -154,14 +154,57 @@ class RewardsTaskUtils:
for i in range(scroll_times):
ActionChains(self.driver).scroll_by_amount(0, -100).perform() # scroll back to top of page
def complete_required_searches(self):
def complete_required_searches(self, max_rounds: int = 6):
# Points per search are not fixed. Some markets award 3 rather than 5,
# the daily maximum itself changes (observed 15, 30 and 60 on the same
# account within one day, with the counter resetting), and daily set and
# card searches count towards the same quota. A single up front division
# therefore leaves points on the table and still reports success.
# Measure, search, measure again.
points_earned, max_pts = self.read_search_points()
print(f"[INFO] Search points before: {points_earned}/{max_pts}")
for round_number in range(1, max_rounds + 1):
if points_earned >= max_pts:
break
# Assume the lower known rate so a round never overshoots by much.
searches = max(1, (max_pts - points_earned) // 3)
self.run_search_batch(searches)
previous = points_earned
points_earned, max_pts = self.read_search_points()
print(f"[INFO] Round {round_number}: {searches} searches -> {points_earned}/{max_pts}")
if points_earned <= previous:
print("[WARNING] Round produced no points, stopping instead of searching pointlessly.")
break
if points_earned < max_pts:
print(f"[WARNING] Search quota not filled: {points_earned}/{max_pts}")
else:
print(f"Search quota complete: {points_earned}/{max_pts}")
def read_search_points(self):
"""Open the points breakdown, read the Bing search row, close it again."""
self.switch_to_earn_page()
self.wait_for_then_click(self.elements.get_points_breakdown_button)
self.wait_for_element(self.elements.get_close_button_on_points_breakdown) # make sure sidebar loads
close_btn = self.wait_for_element(self.elements.get_close_button_on_points_breakdown)
points_earned, max_pts = self.elements.get_points_earned_from_searches_on_points_breakdown()
searches_needed = (max_pts - points_earned) // 5
try:
self.move_to_and_click(close_btn)
except Exception:
pass
return points_earned, max_pts
def run_search_batch(self, count: int):
self.driver.get("https://www.bing.com/")
self.tab_utils.ensure_focus()
@@ -171,7 +214,7 @@ class RewardsTaskUtils:
for i, query in enumerate(
llm_utils.get_related_search_queries(
llm_utils.get_random_noun(), num_queries=searches_needed
llm_utils.get_random_noun(), num_queries=count
)
):
self.keyboard.send_keys(query+Keys.ENTER)
@@ -186,18 +229,6 @@ class RewardsTaskUtils:
self.driver.get("https://rewards.bing.com/")
self.tab_utils.ensure_focus()
self.switch_to_earn_page()
self.wait_for_then_click(self.elements.get_points_breakdown_button)
close_btn = self.wait_for_element(self.elements.get_close_button_on_points_breakdown)
points_earned, max_pts = self.elements.get_points_earned_from_searches_on_points_breakdown()
self.move_to_and_click(close_btn)
print(f"Points earned from {searches_needed} searches: {points_earned}/{max_pts}")
def claim_bonus_points(self):
self.switch_to_dashboard()