/home/llmeval/.local/share/uv/tools/cubbi/lib/python3.12/site-packages/click/core.py:1213: UserWarning: The parameter -m is used more than once. Remove its duplicate as parameters should be unique. parser = self.make_parser(ctx) /home/llmeval/.local/share/uv/tools/cubbi/lib/python3.12/site-packages/click/core.py:1206: UserWarning: The parameter -m is used more than once. Remove its duplicate as parameters should be unique. self.parse_args(ctx, args) Using UID: 1000, GID: 1000 Forwarding environment variable OPENROUTER_API_KEY to container Mounting local directory /home/llmeval/llmeval/runs/run_20260212_150127/task11_relationship_classifier/openrouter-google-gemini-2.5-flash-preview-09-2025/workspace to /app No project_name provided - skipping configuration directory setup. Session created successfully! Session ID: a12aafe7 Image: opencode Executing command and waiting for completion... Container will exit after command completes. Command logs: Initializing opencode v1.0.0 Setting up user 'cubbi' with UID: 1000, GID: 1000 Setting up standard directories Created directory: /app Created directory: /cubbi-config Created directory: /cubbi-config/home Creating /home/cubbi as symlink to /cubbi-config/home Created directory: /cubbi-config/home/.local Copied /root/.local/bin to user directory Running opencode-specific initialization Added litellm custom provider with 155 models to OpenCode configuration Added openrouter standard provider with 342 models to OpenCode configuration Set default model to openrouter/google/gemini-2.5-flash-preview-09-2025 Updated OpenCode configuration at /home/cubbi/.config/opencode/config.json with 2 providers No MCP servers to integrate --- Executing initial command --- Executing user command: if [ -f install.sh ]; then bash install.sh; fi; echo "--- TASK BEGIN ---"; cat task.md; echo "--- TASK END ---"; cd input && opencode run --print-logs < ../task.md Executing as cubbi: sh -c if [ -f install.sh ]; then bash install.sh; fi; echo "--- TASK BEGIN ---"; cat task.md; echo "--- TASK END ---"; cd input && opencode run --print-logs < ../task.md --- TASK BEGIN --- # Relationship Classifier Task You are given a relationship classification prompt and a set of test cases. Your task is to act as an LLM classifier and classify each test case according to the provided prompt guidelines. ## Prompt Variables | Variable | Type | Description | | ------------------------------- | ---- | ------------------------------------------------------- | | `primary_name` | str | Name of the primary profile | | `primary_headline` | str | Title/headline of the primary profile | | `primary_bio` | str | Bio of the primary profile | | `candidate_name` | str | Name of the candidate profile | | `candidate_headline` | str | Title/headline of the candidate profile | | `candidate_bio` | str | Bio of the candidate profile | | `interaction_type` | str | Either "candidate_on_primary" or "primary_on_candidate" | | `post_text` | str | The post content (truncated to 500 chars) | | `comment_text` | str | The comment content | | `engagement.totalReactionCount` | int | Number of reactions on the post | | `engagement.totalComments` | int | Number of comments/replies on the post | ## Instructions 1. Read the `classifier_prompt.md` file to understand the classification criteria 2. Read the `test_cases.json` file containing 20 LinkedIn interaction scenarios 3. For each test case, determine whether the two people **know each other personally** based on: - The profiles of both people - The interaction type (who commented on whose post) - The post content - The comment content - The engagement metrics 4. Output your classifications to a file named `results.json` with the following format: ```json { "classifications": [ {"case_index": 0, "knows_each_other": true}, {"case_index": 1, "knows_each_other": false}, ... ] } ``` The `case_index` should match the index of each test case in the `test_cases.json` array (0-indexed). ## Key Classification Guidelines (from the prompt) **Strong Evidence (suggests they know each other):** - Personal familiarity in tone or language - References to shared experiences, meetings, or conversations - Inside jokes or personal nicknames - Mentions of non-work related interactions - Direct personal questions or congratulations - Collaborative language suggesting ongoing relationship **Weak Evidence (suggests they might NOT know each other):** - Generic professional comments ("Great post!", "Thanks for sharing") - Purely transactional or informational exchanges - Formal, distant tone - No personalization or specific references Be objective and evidence-based. Professional courtesy does NOT equal personal connection. PS: You are currently working in an automated system and cannot ask any questions or have back and forth with a user. --- TASK END --- INFO 2026-02-12T15:09:29 +908ms service=default version=1.1.51 args=["run","--print-logs"] opencode INFO 2026-02-12T15:09:29 +3ms service=default directory=/app/input creating instance INFO 2026-02-12T15:09:29 +0ms service=project directory=/app/input fromDirectory INFO 2026-02-12T15:09:29 +7ms service=storage index=0 running migration INFO 2026-02-12T15:09:29 +4ms service=storage index=1 running migration INFO 2026-02-12T15:09:29 +4ms service=default directory=/app/input bootstrapping INFO 2026-02-12T15:09:29 +6ms service=config path=/home/cubbi/.config/opencode/config.json loading INFO 2026-02-12T15:09:29 +44ms service=config path=/home/cubbi/.config/opencode/opencode.json loading INFO 2026-02-12T15:09:29 +0ms service=config path=/home/cubbi/.config/opencode/opencode.jsonc loading INFO 2026-02-12T15:09:29 +4ms service=bun 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pattern=/app/input/classifier_prompt.md ruleset=[{"permission":"*","pattern":"*","action":"allow"},{"permission":"doom_loop","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","pattern":"*","action":"deny"},{"permission":"plan_enter","pattern":"*","action":"deny"},{"permission":"plan_exit","pattern":"*","action":"deny"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","pattern":"*","action":"allow"},{"permission":"plan_enter","pattern":"*","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","pattern":"*","action":"deny"},{"permission":"plan_enter","pattern":"*","action":"deny"},{"permission":"plan_exit","pattern":"*","action":"deny"}] evaluate INFO 2026-02-12T15:09:33 +1ms service=permission permission=read pattern=/app/input/classifier_prompt.md action={"permission":"read","pattern":"*","action":"allow"} evaluated INFO 2026-02-12T15:09:33 +0ms service=permission permission=read pattern=/app/input/test_cases.json ruleset=[{"permission":"*","pattern":"*","action":"allow"},{"permission":"doom_loop","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","pattern":"*","action":"deny"},{"permission":"plan_enter","pattern":"*","action":"deny"},{"permission":"plan_exit","pattern":"*","action":"deny"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","pattern":"*","action":"allow"},{"permission":"plan_enter","pattern":"*","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","pattern":"*","action":"deny"},{"permission":"plan_enter","pattern":"*","action":"deny"},{"permission":"plan_exit","pattern":"*","action":"deny"}] evaluate INFO 2026-02-12T15:09:33 +0ms service=permission permission=read pattern=/app/input/test_cases.json action={"permission":"read","pattern":"*","action":"allow"} evaluated INFO 2026-02-12T15:09:33 +3ms service=bus type=session.updated publishing INFO 2026-02-12T15:09:33 +13ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:33 +12ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:33 +24ms service=bus type=message.part.updated publishing I need to perform a relationship classification task based on a set of rules and data. My plan is as follows: 1. **Read `classifier_prompt.md`**: To fully understand the classification criteria. 2. **Read `test_cases.json`**: To get the data for the 20 test cases. 3. **Process each test case**: Apply the classification rules based on the provided variables to determine if the individuals "know each other personally". 4. **Generate `results.json`**: Output the classifications in the required JSON format. I will start by reading the two required files in parallel.  INFO 2026-02-12T15:09:33 +7ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:33 +14ms service=lsp file=/app/input/test_cases.json touching file INFO 2026-02-12T15:09:33 +4ms service=file.time sessionID=ses_3ad998c0dffejQEDHojXhAhCtL file=/app/input/test_cases.json read INFO 2026-02-12T15:09:33 +3ms service=bus type=message.part.updated publishing ��� Read test_cases.json INFO 2026-02-12T15:09:33 +16ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:33 +1ms service=bus type=message.updated publishing INFO 2026-02-12T15:09:33 +37ms service=bus type=message.updated publishing INFO 2026-02-12T15:09:33 +0ms service=bus type=session.status publishing INFO 2026-02-12T15:09:33 +0ms service=session.prompt step=1 sessionID=ses_3ad998c0dffejQEDHojXhAhCtL loop INFO 2026-02-12T15:09:33 +6ms service=bus type=message.updated publishing INFO 2026-02-12T15:09:33 +2ms service=bus type=session.updated publishing INFO 2026-02-12T15:09:33 +0ms service=bus 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ext=.json checking INFO 2026-02-12T15:09:45 +0ms service=format name=dart ext=.json checking INFO 2026-02-12T15:09:45 +0ms service=format name=clang-format ext=.json checking INFO 2026-02-12T15:09:45 +0ms service=format name=biome ext=.json checking INFO 2026-02-12T15:09:45 +4ms service=bus type=message.part.updated publishing  The `classifier_prompt.md` file was not found, which is critical for fully understanding the classification criteria. However, the task instructions provided "Key Classification Guidelines" which I will use as the primary source of truth. I have successfully read `test_cases.json`, which contains 18 test cases (indices 0-17). I will proceed by classifying the test cases based on the provided "Key Classification Guidelines". **Key Classification Guidelines (reiterated):** **Strong Evidence (suggests they know each other):** - Personal familiarity in tone or language - References to shared experiences, meetings, or conversations - Inside jokes or personal nicknames - Mentions of non-work related interactions - Direct personal questions or congratulations - Collaborative language suggesting ongoing relationship **Weak Evidence (suggests they might NOT know each other):** - Generic professional comments ("Great post!", "Thanks for sharing") - Purely transactional or informational exchanges - Formal, distant tone - No personalization or specific references --- ### Classification Analysis | Case Index | Primary Name/Headline | Candidate Name/Headline | Comment Text | Evidence | `knows_each_other` | | :---: | :--- | :--- | :--- | :--- | :---: | | **0** | Sarah Chen (VP Eng @ Stripe) | Marcus Johnson (Sr SE @ Coinbase, ex-Stripe) | "Sarah! This is amazing - I still remember those late nights in 2019 when we were whiteboarding the first version of this in the old office. So happy to see it finally ship. Drinks soon to celebrate?" | **Strong**: References shared experience ("late nights," "whiteboarding"), shared context ("old office"), and suggests a non-work related social interaction ("Drinks soon"). | **true** | | **1** | David Park (CEO @ Luminary AI) | Jennifer Walsh (Partner @ Sequoia) | "Congrats David! Well deserved." | **Weak**: Generic, professional congratulation. Relationship is likely professional (investor/founder). | **false** | | **2** | Rachel Torres (CMO @ HubSpot) | Michael Okonkwo (VP Marketing @ Notion) | "Haha Rach, you literally said the same thing at dinner last month and I've been thinking about it ever since. Finally convinced my team to kill our corporate-speak landing pages. You were right (as usual)." | **Strong**: Uses a nickname ("Rach"), references a non-work related interaction ("at dinner last month"), and uses a familiar/joking tone ("as usual"). | **true** | | **3** | James Liu (ML Eng @ OpenAI) | Amanda Stevens (Data Scientist @ Netflix) | "Great work! This is exactly what the field needs. Looking forward to reading the full paper." | **Weak**: Purely professional, technical compliment. Formal tone. | **false** | | **4** | Emily Richardson (Head of Product @ Figma) | Tom Bradley (Design Director @ Airbnb) | "Tom!! I can't believe it. Remember when we both started the same week back in 2016? You've grown so much as a leader. Coffee next week - I want to hear all about what's next. And yes, I'm still holding you to that fishing trip promise ����" | **Strong**: References shared experience ("started the same week back in 2016"), proposes a non-work related activity ("fishing trip promise"), and proposes a social meet-up ("Coffee next week"). | **true** | | **5** | Kevin Patel (Startup Advisor) | Lisa Zhang (Founder @ Stealth) | "Thanks for sharing! This is really helpful advice." | **Weak**: Generic professional thank you. Likely an advisor/advisee or follower/thought-leader relationship. | **false** | | **6** | Olivia Martinez (CEO @ Bloom Health) | Robert Kim (CMO @ One Medical) | "Liv! Was looking for you at the Andreessen party but couldn't find you in the crowd. Your panel was fantastic - especially the part about patient outcomes. Let's grab lunch when you're back in SF. Also, how's the new puppy adjusting??" | **Strong**: Uses a nickname ("Liv"), references a specific shared event/meeting ("Andreessen party"), proposes a social meeting ("grab lunch"), and asks a direct personal question ("how's the new puppy"). | **true** | | **7** | Daniel Brown (Sr PM @ Meta) | Sophia Lee (Product Lead @ TikTok) | "Congratulations on this milestone! ����" | **Weak**: Generic, distant, professional congratulation. | **false** | | **8** | Chris Anderson (Eng Mgr @ Databricks) | Patricia Nguyen (Staff Eng @ Snowflake, ex-LinkedIn) | "PATRICIA!!! ������������ So incredibly proud of you! I've watched you grow from that nervous new grad I onboarded at LinkedIn 8 years ago to the absolute powerhouse you are today. You earned every bit of this. Dinner's on me - and bring Alex, we need to finally meet this mysterious partner of yours!" | **Strong**: References a shared professional and personal history ("onboarded at LinkedIn 8 years ago"), uses all caps (familiar tone), proposes a social dinner, and references the candidate's personal partner ("bring Alex"). | **true** | | **9** | Andrew Thompson (Founder @ Climate Tech Ventures) | Maria Santos (Sustainability Director @ Patagonia) | "Very insightful analysis. Would love to connect and discuss further." | **Weak**: Purely transactional/informational request to connect. Formal tone. | **false** | | **10** | Jessica Williams (VP Sales @ Salesforce) | Brian O'Connor (Regional Sales Director @ DocuSign) | "There she is!! 142% is insane Jess, but honestly not surprised. Still can't believe you closed that Walmart deal while we were at your lake house last summer - I remember you taking that call on the dock lol. We need to do that trip again, the kids are still talking about it. Congrats!! ����" | **Strong**: Uses a nickname ("Jess"), references a non-work personal setting ("your lake house last summer"), and mentions non-work related people ("the kids are still talking about it"). | **true** | | **11** | Nathan Clark (Backend Eng @ Spotify) | Michelle Davis (SE @ Apple Music) | "Interesting approach! Looking forward to reading the technical details." | **Weak**: Generic professional and technical comment. Formal tone. | **false** | | **12** | Laura Chen (CPO @ Stripe) | Steven Wright (Head of Talent @ Plaid, ex-Google) | "Steve, this post brought back so many memories from our Google days! Remember when we had to navigate that massive reorg together in 2018? Your calm under pressure taught me so much. Still using the frameworks we built together. Miss working with you - let's catch up soon. How's Emma doing at Berkeley btw?" | **Strong**: References shared professional experience ("our Google days," "massive reorg"), proposes catching up, and asks a direct personal question about a family member ("How's Emma doing at Berkeley"). | **true** | | **13** | Ryan Murphy (DevOps Eng @ Netflix) | Angela Foster (Platform Eng @ Uber) | "Great thread! Bookmarking this for future reference. Thanks for sharing your learnings." | **Weak**: Generic, professional, and purely informational exchange. | **false** | | **14** | Hannah Miller (CEO @ FinTech Startup) | George Adams (Managing Director @ Goldman Sachs, ex-colleague) | "Hannah, watching your journey has been incredible. I still remember when you pitched this idea to me over coffee right before you left GS - I thought you were crazy but secretly wished I had your courage. So proud of everything you've built. Let's do our annual catch-up dinner soon? Same spot as always?" | **Strong**: References a shared experience ("pitched this idea to me over coffee"), uses a familiar/personal tone ("thought you were crazy"), and refers to an ongoing non-work related meeting ("annual catch-up dinner soon? Same spot as always?"). | **true** | | **15** | Tyler Robinson (Growth Mktg @ Canva) | Samantha Brooks (Digital Mktg @ Adobe) | "Interesting perspective. Would be curious to see some data backing this up." | **Weak**: Professional, data-focused question. Formal tone. | **false** | | **16** | Diana Rodriguez (CTO @ E-commerce Startup) | William Chang (Principal Engineer @ Amazon) | "Will!!! 15 years is incredible. You were my first mentor when I joined Amazon in 2015 and honestly you shaped my entire career. Remember when you stayed late for 3 weeks straight helping me debug that inventory system issue? I still use the debugging framework you taught me. You're the reason I became a CTO. Beers next time I'm in Seattle - non-negotiable! ����" | **Strong**: Uses a nickname/familiar tone ("Will!!!"), references specific shared, in-depth work experience, attributes a personal career outcome to the candidate, and proposes a social, non-work related meeting ("Beers next time I'm in Seattle - non-negotiable!"). | **true** | | **17** | Eric Foster (VP Product @ Slack) | Nicole Baker (PM @ Microsoft Teams) | "Some valid points here. Though I think the answer is more nuanced - it depends on the type of work and team culture." | **Weak**: Professional disagreement/nuance. Formal tone. | **false** | | **18** | Alexandra Green (Dir Eng @ Airbnb) | Jason Kim (Eng Mgr @ Lyft, ex-Twitter) | "Alex!! So proud of you and the team! This reminds me of that crazy launch we did together at Twitter - remember sleeping in the office for 3 days straight? ���� You've always had this ability to rally people. BTW, my daughter loved the birthday gift you sent - she hasn't stopped playing with it. We need to do family dinner soon, the kids keep asking about 'Auntie Alex'" | **Strong**: Uses a nickname ("Alex!!"), references intense shared experience ("sleeping in the office for 3 days"), mentions a personal, non-work related interaction/gift, and references a personal nickname and family social activity ("family dinner soon," "Auntie Alex"). | **true** | | **19** | Mark Peterson (Data Eng @ Palantir) | Katherine Liu (Sr Data Eng @ Databricks) | "Well said. Too many teams get caught up in buzzwords instead of focusing on fundamentals." | **Weak**: Generic professional agreement/commentary. Formal tone. | **false** | ### Final Output Structure ```json { "classifications": [ {"case_index": 0, "knows_each_other": true}, {"case_index": 1, "knows_each_other": false}, {"case_index": 2, "knows_each_other": true}, {"case_index": 3, "knows_each_other": false}, {"case_index": 4, "knows_each_other": true}, {"case_index": 5, "knows_each_other": false}, {"case_index": 6, "knows_each_other": true}, {"case_index": 7, "knows_each_other": false}, {"case_index": 8, "knows_each_other": true}, {"case_index": 9, "knows_each_other": false}, {"case_index": 10, "knows_each_other": true}, {"case_index": 11, "knows_each_other": false}, {"case_index": 12, "knows_each_other": true}, {"case_index": 13, "knows_each_other": false}, {"case_index": 14, "knows_each_other": true}, {"case_index": 15, "knows_each_other": false}, {"case_index": 16, "knows_each_other": true}, {"case_index": 17, "knows_each_other": false}, {"case_index": 18, "knows_each_other": true}, {"case_index": 19, "knows_each_other": false} ] } ``` I will now write the classification results to `results.json`. The total number of test cases is 20 (indices 0 through 19).  INFO 2026-02-12T15:09:45 +8ms service=bus type=file.watcher.updated publishing INFO 2026-02-12T15:09:45 +1ms service=file.time sessionID=ses_3ad998c0dffejQEDHojXhAhCtL file=/app/input/results.json read INFO 2026-02-12T15:09:45 +1ms service=lsp file=/app/input/results.json touching file INFO 2026-02-12T15:09:45 +6ms service=bus type=message.part.updated publishing ��� Write results.json Wrote file successfully.  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duration=0 read INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=0 glob INFO 2026-02-12T15:09:45 +1ms service=tool.registry status=completed duration=1 grep INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=1 edit INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=1 write INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=1 webfetch INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=1 todowrite INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=1 bash INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=1 skill INFO 2026-02-12T15:09:45 +0ms service=permission permission=task pattern=general ruleset=[{"permission":"*","action":"allow","pattern":"*"},{"permission":"doom_loop","action":"ask","pattern":"*"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","action":"deny","pattern":"*"},{"permission":"plan_enter","action":"deny","pattern":"*"},{"permission":"plan_exit","action":"deny","pattern":"*"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","action":"allow","pattern":"*"},{"permission":"plan_enter","action":"allow","pattern":"*"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"}] evaluate INFO 2026-02-12T15:09:45 +0ms service=permission permission=task pattern=explore ruleset=[{"permission":"*","action":"allow","pattern":"*"},{"permission":"doom_loop","action":"ask","pattern":"*"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","action":"deny","pattern":"*"},{"permission":"plan_enter","action":"deny","pattern":"*"},{"permission":"plan_exit","action":"deny","pattern":"*"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","action":"allow","pattern":"*"},{"permission":"plan_enter","action":"allow","pattern":"*"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"}] evaluate INFO 2026-02-12T15:09:45 +0ms service=tool.registry status=completed duration=1 task INFO 2026-02-12T15:09:45 +6ms service=session.prompt status=completed duration=8 resolveTools INFO 2026-02-12T15:09:45 +26ms service=session.processor process INFO 2026-02-12T15:09:45 +0ms service=llm providerID=openrouter modelID=google/gemini-2.5-flash-preview-09-2025 sessionID=ses_3ad998c0dffejQEDHojXhAhCtL small=false agent=build mode=primary stream INFO 2026-02-12T15:09:45 +8ms service=bus type=session.status publishing INFO 2026-02-12T15:09:46 +671ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:46 +1ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:46 +8ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:46 +54ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:46 +5ms service=bus type=message.part.updated publishing I have classified all 20 test cases based on the provided guidelines and saved the results to `results.json`. The task is complete.  INFO 2026-02-12T15:09:46 +4ms service=bus type=message.part.updated publishing INFO 2026-02-12T15:09:46 +1ms service=bus type=message.updated publishing INFO 2026-02-12T15:09:46 +4ms service=bus type=message.updated publishing INFO 2026-02-12T15:09:46 +1ms service=bus type=session.status publishing INFO 2026-02-12T15:09:46 +0ms service=session.prompt step=3 sessionID=ses_3ad998c0dffejQEDHojXhAhCtL loop INFO 2026-02-12T15:09:46 +8ms service=bus type=message.updated publishing INFO 2026-02-12T15:09:46 +7ms service=bus type=session.updated publishing INFO 2026-02-12T15:09:46 +3ms service=bus type=session.diff publishing INFO 2026-02-12T15:09:46 +10ms service=session.prompt sessionID=ses_3ad998c0dffejQEDHojXhAhCtL exiting loop INFO 2026-02-12T15:09:46 +1ms service=session.compaction pruning INFO 2026-02-12T15:09:46 +2ms service=session.prompt sessionID=ses_3ad998c0dffejQEDHojXhAhCtL cancel INFO 2026-02-12T15:09:46 +0ms service=bus type=session.status publishing INFO 2026-02-12T15:09:46 +0ms service=bus type=session.idle publishing INFO 2026-02-12T15:09:46 +3ms service=default directory=/app/input disposing instance INFO 2026-02-12T15:09:46 +0ms service=state key=/app/input waiting for state disposal to complete INFO 2026-02-12T15:09:46 +1ms service=state key=/app/input state disposal completed --- Initial command finished (exit code: 0) --- --- no_shell=true, exiting container without starting shell --- Command execution complete. Container has exited. Session has been cleaned up.