Case: 20260501T141352Z__gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked
PASS Trajectory: recovered | Invoked: yes | Match: 100%
gptme --non-interactive --no-confirm --name gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked-warmup --system short --workspace /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/workspace-warmup --tools shell --tool-format tool -m local/qwen3.5:9b 'Use the shell tool. Read search-url.txt, query.txt, and required-token.txt from the current workspace. Call the search endpoint with query parameters: - q=<urlencoded query from query.txt> - format=json - limit=8 The endpoint returns JSON with a results array. Select the result with the highest score among results whose snippet contains the exact required token. Write search-result.json in the current workspace as JSON with exactly these keys: - query - selected_id - selected_url - selected_score If successful, reply only DONE. If command execution fails, reply only FAIL. '
gptme --non-interactive --no-confirm --name gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked-measured --system short --workspace /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/workspace --tools shell --tool-format tool -m local/qwen3.5:9b 'Use the shell tool. Read search-url.txt, query.txt, and required-token.txt from the current workspace. Call the search endpoint with query parameters: - q=<urlencoded query from query.txt> - format=json - limit=8 The endpoint returns JSON with a results array. Select the result with the highest score among results whose snippet contains the exact required token. Write search-result.json in the current workspace as JSON with exactly these keys: - query - selected_id - selected_url - selected_score If successful, reply only DONE. If command execution fails, reply only FAIL. '
Consistency: diverged
Use the shell tool. Read search-url.txt, query.txt, and required-token.txt from the current workspace. Call the search endpoint with query parameters: - q=<urlencoded query from query.txt> - format=json - limit=8 The endpoint returns JSON with a results array. Select the result with the highest score among results whose snippet contains the exact required token. Write search-result.json in the current workspace as JSON with exactly these keys: - query - selected_id - selected_url - selected_score If successful, reply only DONE. If command execution fails, reply only FAIL.
{"query": "weekly plan 43818acfb3df checkbox", "selected_id": "doc-a461fa09", "selected_score": 0.97, "selected_url": "https://kb.example/7cf50cf9ad27"}
REQUEST_HIT=/search/Ba_VCwR3vWVmv3rktQJIVLc9
{"query": "weekly plan 43818acfb3df checkbox", "selected_id": "doc-a461fa09", "selected_score": 0.97, "selected_url": "https://kb.example/7cf50cf9ad27"}
REQUEST_HIT=yes
--- expected
+++ observed
@@ -1,2 +1,2 @@
{"query": "weekly plan 43818acfb3df checkbox", "selected_id": "doc-a461fa09", "selected_score": 0.97, "selected_url": "https://kb.example/7cf50cf9ad27"}
-REQUEST_HIT=/search/Ba_VCwR3vWVmv3rktQJIVLc9
+REQUEST_HIT=yes
No structured session transcript found.
[gripprobe] process_started_at=2026-05-01T14:39:35+00:00
[14:39:37] Created config file at /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/runtime/gptme/warmup/home/.config/gptme/config.toml
[14:39:37] WARNING Skipping all confirmation prompts. cli.py:265
Using model: local/qwen3.5:9b
Using logdir: /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/runtime/gptme/warmup/state/gptme-logs/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked-warmup
Using workspace: /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/workspace-warmup
Skipped 2 hidden system messages, show with --show-hidden
--- ^^^ past messages ^^^ ---
User:
Use the shell tool.
Read search-url.txt, query.txt, and required-token.txt from the current workspace.
Call the search endpoint with query parameters:
- q=<urlencoded query from query.txt>
- format=json
- limit=8
The endpoint returns JSON with a results array.
Select the result with the highest score among results whose snippet contains the exact required token.
Write search-result.json in the current workspace as JSON with exactly these keys:
- query
- selected_id
- selected_url
- selected_score
If successful, reply only DONE.
If command execution fails, reply only FAIL.
````search-url.txt
http://127.0.0.1:33765/search/N7ozKtPolz3VvKQ8teND6fkd
````
````query.txt
warmup query dffb0b13
````
````required-token.txt
f40eb84a2e0612fe
````
Assistant: Thinking...
Assistant:
<think>
<think>
The user wants me to:
1. Read three files: search-url.txt, query.txt, and required-token.txt
2. Call a search endpoint with the query from query.txt
3. Filter results whose snippet contains the exact token from required-token.txt
4. Select the result with the highest score
5. Write the result to search-result.json
Let me start by reading the files to understand the content.
</think>
</think>
@shell(call_kdwsqg6r): {"command":"cat search-url.txt query.txt required-token.txt"}
http://127.0.0.1:33765/search/N7ozKtPolz3VvKQ8teND6fkd
warmup query dffb0b13
f40eb84a2e0612fe
System:
Ran allowlisted command: `cat search-url.txt query.txt required-token.txt`
```stdout
http://127.0.0.1:33765/search/N7ozKtPolz3VvKQ8teND6fkd
warmup query dffb0b13
f40eb84a2e0612fe
```
[14:39:52] ERROR exception during auto-name auto_naming.py:100
Traceback (most recent call last):
File "/opt/venvs/gptme/lib/python3.12/site-packages/gptme/util/auto_naming.py", line 97, in _generate_llm_name
summary_model_name = get_summary_model(current_model.provider)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/venvs/gptme/lib/python3.12/site-packages/gptme/llm/models.py", line 576, in get_summary_model
raise ValueError(f"Provider {provider} did not have a summary model")
ValueError: Provider local did not have a summary model
Assistant: Thinking...
[14:40:05] INFO Reasoning content: The user is asking me to create a 2-4 word title for this conversation. Looking at the conversation, it's about using a shell tool to read files and call a search endpoint. llm_openai.py:321
The main topic is about shell tool usage and file operations for a search task.
Let me create a concise title:
- "Shell tool search task"
- "File reading and search"
- "Search endpoint integration"
- "Shell script search query"
I'll go with something that captures the essence - it's about using shell tools for a search operation.
"Shell search task" or "Search endpoint task" or "File search operation"
Let me pick: "Shell search task"
INFO Auto-generated conversation name: Shell search task chat.py:332
Assistant:
<think>
<think>
Now I have:
- search-url: http://127.0.0.1:33765/search/N7ozKtPolz3VvKQ8teND6fkd
- query: warmup query dffb0b13
- required-token: f40eb84a2e0612fe
I need to call the search endpoint with:
- q=warmup%20query%20dffb0b13 (URL encoded)
- format=json
- limit=8
Let me make the curl request.
</think>
</think>
@shell(call_dscw7n8j): {"command":"curl -s \"http://127.0.0.1:33765/search/N7ozKtPolz3VvKQ8teND6fkd?q=warmup%20query%20dffb0b13\u0026format=json\u0026limit=8\""}
Preview
curl -s "http://127.0.0.1:33765/search/N7ozKtPolz3VvKQ8teND6fkd?q=warmup%20query%20dffb0b13&format=json&limit=8"
{"query": "warmup query dffb0b13", "results": [{"id": "doc-intro", "title": "Markdown planning intro", "url": "https://kb.example/intro", "snippet": "Basic markdown checklist examples.", "score": 0.72, "lang": "en"}, {"id": "doc-b5a7b086", "title": "Weekly planning with checkboxes", "url": "https://kb.example/794a6369aa62", "snippet": "Actionable template. Required token: 077c1c2882cd.", "score": 0.94, "lang": "en"}, {"id": "doc-alt-token", "title": "Alternate planning approach", "url": "https://kb.example/alt", "snippet": "Also mentions token 077c1c2882cd, but less relevant.", "score": 0.8099999999999999, "lang": "en"}, {"id": "doc-ru", "title": "План на неделю", "url": "https://kb.example/ru-weekly", "snippet": "Русскоязычный шаблон.", "score": 0.61, "lang": "ru"}, {"id": "doc-de", "title": "Wochenplan Vorlage", "url": "https://kb.example/de-weekly", "snippet": "Deutsche Checklisten-Idee.", "score": 0.59, "lang": "de"}, {"id": "doc-noise-1", "title": "General productivity", "url": "https://kb.example/noise-1", "snippet": "Time-blocking article.", "score": 0.44, "lang": "en"}, {"id": "doc-noise-2", "title": "Meeting notes", "url": "https://kb.example/noise-2", "snippet": "Unrelated meeting summary.", "score": 0.37, "lang": "en"}, {"id": "doc-noise-3", "title": "Shopping checklist", "url": "https://kb.example/noise-3", "snippet": "Groceries list example.", "score": 0.21, "lang": "en"}], "total": 8, "returned": 8, "error": ""}System:
Ran command: `curl -s "http://127.0.0.1:33765/search/N7ozKtPolz3VvKQ8teND6fkd?q=warmup%20query%20dffb0b13&format=json&limit=8"`
`{"query": "warmup query dffb0b13", "results": [{"id": "doc-intro", "title": "Markdown planning intro", "url": "https://kb.example/intro", "snippet": "Basic markdown checklist examples.", "score": 0.72, "lang": "en"}, {"id": "doc-b5a7b086", "title": "Weekly planning with
checkboxes", "url": "https://kb.example/794a6369aa62", "snippet": "Actionable template. Required token: 077c1c2882cd.", "score": 0.94, "lang": "en"}, {"id": "doc-alt-token", "title": "Alternate planning approach", "url": "https://kb.example/alt", "snippet": "Also mentions
token 077c1c2882cd, but less relevant.", "score": 0.8099999999999999, "lang": "en"}, {"id": "doc-ru", "title": "План на неделю", "url": "https://kb.example/ru-weekly", "snippet": "Русскоязычный шаблон.", "score": 0.61, "lang": "ru"}, {"id": "doc-de", "title": "Wochenplan
Vorlage", "url": "https://kb.example/de-weekly", "snippet": "Deutsche Checklisten-Idee.", "score": 0.59, "lang": "de"}, {"id": "doc-noise-1", "title": "General productivity", "url": "https://kb.example/noise-1", "snippet": "Time-blocking article.", "score": 0.44, "lang":
"en"}, {"id": "doc-noise-2", "title": "Meeting notes", "url": "https://kb.example/noise-2", "snippet": "Unrelated meeting summary.", "score": 0.37, "lang": "en"}, {"id": "doc-noise-3", "title": "Shopping checklist", "url": "https://kb.example/noise-3", "snippet": "Groceries
list example.", "score": 0.21, "lang": "en"}], "total": 8, "returned": 8, "error": ""}`
Assistant: Thinking...
Assistant:
<think>
<think>
Now I need to filter results whose snippet contains the exact required token "f40eb84a2e0612fe".
Looking at the results:
1. doc-intro: "Basic markdown checklist examples." - no token
2. doc-b5a7b086: "Actionable template. Required token: 077c1c2882cd." - has token 077c1c2882cd, not f40eb84a2e0612fe
3. doc-alt-token: "Also mentions token 077c1c2882cd, but less relevant." - has token 077c1c2882cd, not f40eb84a2e0612fe
4. doc-ru: "Русскоязычный шаблон." - no token
5. doc-de: "Deutsche Checklisten-Idee." - no token
6. doc-noise-1: "Time-blocking article." - no token
7. doc-noise-2: "Unrelated meeting summary." - no token
8. doc-noise-3: "Groceries list example." - no token
None of the snippets contain the exact required token "f40eb84a2e0612fe". They all contain "077c1c2882cd" instead.
Wait, let me re-read the requirement: "Select the result with the highest score among results whose snippet contains the exact required token."
Since none of the results contain the exact token "f40eb84a2e0612fe", there are no matching results. This could mean:
1. The search should fail
2. Or I should report that no results match
But the instructions say "If command execution fails, reply only FAIL." This is not a command execution failure - it's a data filtering issue.
Let me think about this more carefully. The task says to select the result with the highest score among results whose snippet contains the exact required token. If no results match, then there's no valid selection.
Since no results contain the exact token, I should probably report FAIL. But wait - maybe I should double-check the token. The required token is "f40eb84a2e0612fe" and none of the snippets contain this exact string. They all contain "077c1c2882cd" instead. So there are no matching results, and I should report FAIL.
</think>
</think>
@shell(call_ppq3z42f): {"command":"echo '{\"query\": \"warmup query dffb0b13\", \"selected_id\": null, \"selected_url\": null, \"selected_score\": null}' \u003e search-result.json"}
Preview
echo '{"query": "warmup query dffb0b13", "selected_id": null, "selected_url": null, "selected_score": null}' > search-result.json
System:
Ran command: `echo '{"query": "warmup query dffb0b13", "selected_id": null, "selected_url": null, "selected_score": null}' > search-result.json`
No output
Skipped 1 hidden system messages, show with --show-hidden
Assistant: Thinking...
Assistant:
<think>
<think>
Wait, I need to reconsider. The task says to select the result with the highest score among results whose snippet contains the exact required token. If no results match, then there's no valid selection.
But looking at the instructions again: "If command execution fails, reply only FAIL."
This is not a command execution failure - the curl command succeeded. The issue is that no results match the filter criteria.
However, I think the expected behavior when no results match is to report FAIL since there's no valid result to select.
Actually, let me re-read the task more carefully. It says:
- "Select the result with the highest score among results whose snippet contains the exact required token."
- "If command execution fails, reply only FAIL."
The command execution didn't fail - the curl succeeded. But there are no matching results. In this case, I should probably still write the JSON with null values or indicate no match.
But wait - maybe I should interpret "command execution fails" more broadly. If the task cannot be completed (no matching results), then it's a failure.
Let me write FAIL as the response since
[gripprobe] process_finished_at=2026-05-01T14:41:35+00:00 exit_code=124 timeout=true
[gripprobe] process_started_at=2026-05-01T14:39:35+00:00 [gripprobe] process_finished_at=2026-05-01T14:41:35+00:00 exit_code=124 timeout=true
[gripprobe] process_started_at=2026-05-01T14:41:35+00:00
[14:41:37] Created config file at /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/runtime/gptme/measured/home/.config/gptme/config.toml
[14:41:37] WARNING Skipping all confirmation prompts. cli.py:265
Using model: local/qwen3.5:9b
Using logdir: /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/runtime/gptme/measured/state/gptme-logs/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked-measured
Using workspace: /work/results/runs/20260501T141352Z/cases/gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked/workspace
Skipped 2 hidden system messages, show with --show-hidden
--- ^^^ past messages ^^^ ---
User:
Use the shell tool.
Read search-url.txt, query.txt, and required-token.txt from the current workspace.
Call the search endpoint with query parameters:
- q=<urlencoded query from query.txt>
- format=json
- limit=8
The endpoint returns JSON with a results array.
Select the result with the highest score among results whose snippet contains the exact required token.
Write search-result.json in the current workspace as JSON with exactly these keys:
- query
- selected_id
- selected_url
- selected_score
If successful, reply only DONE.
If command execution fails, reply only FAIL.
````search-url.txt
http://127.0.0.1:33765/search/Ba_VCwR3vWVmv3rktQJIVLc9
````
````query.txt
weekly plan 43818acfb3df checkbox
````
````required-token.txt
f40eb84a2e0612fe
````
Assistant: Thinking...
Assistant:
<think>
<think>
The user wants me to:
1. Read three files: search-url.txt, query.txt, and required-token.txt
2. Call a search endpoint with the query from query.txt
3. Filter results whose snippet contains the exact token from required-token.txt
4. Select the result with the highest score
5. Write the result to search-result.json
Let me start by reading the files to understand the content.
</think>
</think>
@shell(call_aglmq70v): {"command":"cat search-url.txt query.txt required-token.txt"}
http://127.0.0.1:33765/search/Ba_VCwR3vWVmv3rktQJIVLc9
weekly plan 43818acfb3df checkbox
f40eb84a2e0612fe
System:
Ran allowlisted command: `cat search-url.txt query.txt required-token.txt`
```stdout
http://127.0.0.1:33765/search/Ba_VCwR3vWVmv3rktQJIVLc9
weekly plan 43818acfb3df checkbox
f40eb84a2e0612fe
```
Assistant: Thinking...
[14:41:52] ERROR exception during auto-name auto_naming.py:100
Traceback (most recent call last):
File "/opt/venvs/gptme/lib/python3.12/site-packages/gptme/util/auto_naming.py", line 97, in _generate_llm_name
summary_model_name = get_summary_model(current_model.provider)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/venvs/gptme/lib/python3.12/site-packages/gptme/llm/models.py", line 576, in get_summary_model
raise ValueError(f"Provider {provider} did not have a summary model")
ValueError: Provider local did not have a summary model
[14:42:04] INFO Reasoning content: The user is asking me to create a 2-4 word title for this conversation. Looking at the conversation, it's about using a shell tool to read files and call a search endpoint. llm_openai.py:321
The main topic is about shell tool usage and file operations for a search task.
Let me create a concise title:
- "Shell tool search task"
- "File reading and search"
- "Search endpoint integration"
- "Shell script search query"
I'll go with something that captures the essence - it's about using shell tools for a search operation.
"Shell search task" or "Search endpoint task" or "File search operation"
Let me pick: "Shell search task"
INFO Auto-generated conversation name: Shell search task chat.py:332
Assistant:
<think>
<think>
Now I have:
- search-url: http://127.0.0.1:33765/search/Ba_VCwR3vWVmv3rktQJIVLc9
- query: weekly plan 43818acfb3df checkbox
- required-token: f40eb84a2e0612fe
I need to call the search endpoint with:
- q=weekly+plan+43818acfb3df+checkbox (URL encoded)
- format=json
- limit=8
Let me make the curl request.
</think>
</think>
@shell(call_btspqnn8): {"command":"curl -s \"http://127.0.0.1:33765/search/Ba_VCwR3vWVmv3rktQJIVLc9?q=weekly+plan+43818acfb3df+checkbox\u0026format=json\u0026limit=8\""}
Preview
curl -s "http://127.0.0.1:33765/search/Ba_VCwR3vWVmv3rktQJIVLc9?q=weekly+plan+43818acfb3df+checkbox&format=json&limit=8"
{"query": "weekly plan 43818acfb3df checkbox", "results": [{"id": "doc-intro", "title": "Markdown planning intro", "url": "https://kb.example/intro", "snippet": "Basic markdown checklist examples.", "score": 0.72, "lang": "en"}, {"id": "doc-a461fa09", "title": "Weekly planning with checkboxes", "url": "https://kb.example/7cf50cf9ad27", "snippet": "Actionable template. Required token: f40eb84a2e0612fe.", "score": 0.97, "lang": "en"}, {"id": "doc-alt-token", "title": "Alternate planning approach", "url": "https://kb.example/alt", "snippet": "Also mentions token f40eb84a2e0612fe, but less relevant.", "score": 0.84, "lang": "en"}, {"id": "doc-ru", "title": "План на неделю", "url": "https://kb.example/ru-weekly", "snippet": "Русскоязычный шаблон.", "score": 0.61, "lang": "ru"}, {"id": "doc-de", "title": "Wochenplan Vorlage", "url": "https://kb.example/de-weekly", "snippet": "Deutsche Checklisten-Idee.", "score": 0.59, "lang": "de"}, {"id": "doc-noise-1", "title": "General productivity", "url": "https://kb.example/noise-1", "snippet": "Time-blocking article.", "score": 0.44, "lang": "en"}, {"id": "doc-noise-2", "title": "Meeting notes", "url": "https://kb.example/noise-2", "snippet": "Unrelated meeting summary.", "score": 0.37, "lang": "en"}, {"id": "doc-noise-3", "title": "Shopping checklist", "url": "https://kb.example/noise-3", "snippet": "Groceries list example.", "score": 0.21, "lang": "en"}], "total": 8, "returned": 8, "error": ""}System:
Ran command: `curl -s "http://127.0.0.1:33765/search/Ba_VCwR3vWVmv3rktQJIVLc9?q=weekly+plan+43818acfb3df+checkbox&format=json&limit=8"`
`{"query": "weekly plan 43818acfb3df checkbox", "results": [{"id": "doc-intro", "title": "Markdown planning intro", "url": "https://kb.example/intro", "snippet": "Basic markdown checklist examples.", "score": 0.72, "lang": "en"}, {"id": "doc-a461fa09", "title": "Weekly
planning with checkboxes", "url": "https://kb.example/7cf50cf9ad27", "snippet": "Actionable template. Required token: f40eb84a2e0612fe.", "score": 0.97, "lang": "en"}, {"id": "doc-alt-token", "title": "Alternate planning approach", "url": "https://kb.example/alt", "snippet":
"Also mentions token f40eb84a2e0612fe, but less relevant.", "score": 0.84, "lang": "en"}, {"id": "doc-ru", "title": "План на неделю", "url": "https://kb.example/ru-weekly", "snippet": "Русскоязычный шаблон.", "score": 0.61, "lang": "ru"}, {"id": "doc-de", "title": "Wochenplan
Vorlage", "url": "https://kb.example/de-weekly", "snippet": "Deutsche Checklisten-Idee.", "score": 0.59, "lang": "de"}, {"id": "doc-noise-1", "title": "General productivity", "url": "https://kb.example/noise-1", "snippet": "Time-blocking article.", "score": 0.44, "lang":
"en"}, {"id": "doc-noise-2", "title": "Meeting notes", "url": "https://kb.example/noise-2", "snippet": "Unrelated meeting summary.", "score": 0.37, "lang": "en"}, {"id": "doc-noise-3", "title": "Shopping checklist", "url": "https://kb.example/noise-3", "snippet": "Groceries
list example.", "score": 0.21, "lang": "en"}], "total": 8, "returned": 8, "error": ""}`
Assistant: Thinking...
Assistant:
<think>
<think>
Now I need to:
1. Filter results whose snippet contains the exact required token "f40eb84a2e0612fe"
2. Select the result with the highest score
Looking at the results:
- doc-intro: snippet "Basic markdown checklist examples." - does NOT contain "f40eb84a2e0612fe"
- doc-a461fa09: snippet "Actionable template. Required token: f40eb84a2e0612fe." - CONTAINS the token, score 0.97
- doc-alt-token: snippet "Also mentions token f40eb84a2e0612fe, but less relevant." - CONTAINS the token, score 0.84
- doc-ru: snippet "Русскоязычный шаблон." - does NOT contain the token
- doc-de: snippet "Deutsche Checklisten-Idee." - does NOT contain the token
- doc-noise-1: snippet "Time-blocking article." - does NOT contain the token
- doc-noise-2: snippet "Unrelated meeting summary." - does NOT contain the token
- doc-noise-3: snippet "Groceries list example." - does NOT contain the token
Results containing the token:
- doc-a461fa09: score 0.97
- doc-alt-token: score 0.84
The highest score is 0.97 for doc-a461fa09.
Now I need to write search-result.json with:
- query: "weekly plan 43818acfb3df checkbox"
- selected_id: "doc-a461fa09"
- selected_url: "https://kb.example/7cf50cf9ad27"
- selected_score: 0.97
</think>
</think>
@shell(call_ip6qx69a): {"command":"echo '{\"query\": \"weekly plan 43818acfb3df checkbox\", \"selected_id\": \"doc-a461fa09\", \"selected_url\": \"https://kb.example/7cf50cf9ad27\", \"selected_score\": 0.97}' \u003e search-result.json"}
Preview
echo '{"query": "weekly plan 43818acfb3df checkbox", "selected_id": "doc-a461fa09", "selected_url": "https://kb.example/7cf50cf9ad27", "selected_score": 0.97}' > search-result.json
System:
Ran command: `echo '{"query": "weekly plan 43818acfb3df checkbox", "selected_id": "doc-a461fa09", "selected_url": "https://kb.example/7cf50cf9ad27", "selected_score": 0.97}' > search-result.json`
No output
Skipped 1 hidden system messages, show with --show-hidden
Assistant: Thinking...
Assistant:
<think>
<think>
The file was created successfully. Let me verify it was written correctly.
</think>
</think>
@shell(call_pmuhelzm): {"command":"cat search-result.json"}
{"query": "weekly plan 43818acfb3df checkbox", "selected_id": "doc-a461fa09", "selected_url": "https://kb.example/7cf50cf9ad27", "selected_score": 0.97}
System:
Ran allowlisted command: `cat search-result.json`
`{"query": "weekly plan 43818acfb3df checkbox", "selected_id": "doc-a461fa09", "selected_url": "https://kb.example/7cf50cf9ad27", "selected_score": 0.97}`
Assistant: Thinking...
Assistant:
<think>
<think>
The file was created correctly with all the required fields. The task is complete.
</think>
</think>
DONE
[14:43:15] INFO Auto-reply: Assistant message had no tools. Asking for confirmation... complete.py:138
[14:43:15] [Loop control] <system>No tool call detected in last message. Did you mean to finish? If so, make sure you are comp...
User: <system>No tool call detected in last message. Did you mean to finish? If so, make sure you are completely done and then use the `complete` tool to end the session.</system>
Assistant: Thinking...
Assistant:
<think>
<think>
The user is asking me to use the complete tool to end the session. I have completed the task - I read the files, called the search endpoint, selected the result with the highest score that contains the required token, and wrote the search-result.json file. I should now use the complete tool.
</think>
</think>
@complete(call_2s5afequ): {}
System: Task complete. Autonomous session finished.
[14:43:24] INFO Complete tool call detected, stopping session immediately complete.py:80
INFO Hook 'complete.complete' signaled session completion __init__.py:360
[14:43:24] Autonomous mode: Session completed via complete tool. Exiting.
Goodbye! (resume with: gptme --name gptme__local_qwen3_5_9b__ollama__tool__web_search_json_ranked-measured)
[gripprobe] process_finished_at=2026-05-01T14:43:24+00:00 exit_code=0
[gripprobe] process_started_at=2026-05-01T14:41:35+00:00 [gripprobe] process_finished_at=2026-05-01T14:43:24+00:00 exit_code=0
# Modelfile generated by "ollama show"
# To build a new Modelfile based on this, replace FROM with:
# FROM qwen3.5:9b
FROM /usr/share/ollama/.ollama/models/blobs/sha256-dec52a44569a2a25341c4e4d3fee25846eed4f6f0b936278e3a3c900bb99d37c
TEMPLATE {{ .Prompt }}
RENDERER qwen3.5
PARSER qwen3.5
PARAMETER temperature 1
PARAMETER top_k 20
PARAMETER top_p 0.95
PARAMETER presence_penalty 1.5
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