Case: 20260426T062915Z__gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw
TIMEOUT artifact reached Trajectory: recovered | Invoked: yes | Match: 100%
The expected workspace artifact was present before the harness timeout elapsed.
gptme --non-interactive --no-confirm --name gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw-warmup --system short --workspace /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/workspace-warmup --tools shell --tool-format tool -m local/gemma4:e4b 'Use the shell tool. Read search-url.txt and query.txt from the current workspace. Call the search endpoint with query parameters: - q=<urlencoded query from query.txt> - format=json - limit=8 Save the raw JSON response exactly as returned to search-response.json in the current workspace. Do not transform fields and do not wrap with extra text. If successful, reply only DONE. If command execution fails, reply only FAIL. '
gptme --non-interactive --no-confirm --name gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw-measured --system short --workspace /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/workspace --tools shell --tool-format tool -m local/gemma4:e4b 'Use the shell tool. Read search-url.txt and query.txt from the current workspace. Call the search endpoint with query parameters: - q=<urlencoded query from query.txt> - format=json - limit=8 Save the raw JSON response exactly as returned to search-response.json in the current workspace. Do not transform fields and do not wrap with extra text. If successful, reply only DONE. If command execution fails, reply only FAIL. '
Consistency: strongly_diverged
Use the shell tool. Read search-url.txt and query.txt from the current workspace. Call the search endpoint with query parameters: - q=<urlencoded query from query.txt> - format=json - limit=8 Save the raw JSON response exactly as returned to search-response.json in the current workspace. Do not transform fields and do not wrap with extra text. If successful, reply only DONE. If command execution fails, reply only FAIL.
{"query": "weekly plan 30b874ffec58 checkbox", "returned": 8, "total": 8}
REQUEST_HIT=/search/X6Ac6mDdm4IwUSzviWG6-ABI
{"error": "", "query": "weekly plan 30b874ffec58 checkbox", "results": [{"id": "doc-intro", "lang": "en", "score": 0.72, "snippet": "Basic markdown checklist examples.", "title": "Markdown planning intro", "url": "https://kb.example/intro"}, {"id": "doc-fb0d5d18", "lang": "en", "score": 0.97, "snippet": "Actionable template. Required token: 6d77cda385d6d177.", "title": "Weekly planning with checkboxes", "url": "https://kb.example/b2531f139f75"}, {"id": "doc-alt-token", "lang": "en", "score": 0.84, "snippet": "Also mentions token 6d77cda385d6d177, but less relevant.", "title": "Alternate planning approach", "url": "https://kb.example/alt"}, {"id": "doc-ru", "lang": "ru", "score": 0.61, "snippet": "Русскоязычный шаблон.", "title": "План на неделю", "url": "https://kb.example/ru-weekly"}, {"id": "doc-de", "lang": "de", "score": 0.59, "snippet": "Deutsche Checklisten-Idee.", "title": "Wochenplan Vorlage", "url": "https://kb.example/de-weekly"}, {"id": "doc-noise-1", "lang": "en", "score": 0.44, "snippet": "Time-blocking article.", "title": "General productivity", "url": "https://kb.example/noise-1"}, {"id": "doc-noise-2", "lang": "en", "score": 0.37, "snippet": "Unrelated meeting summary.", "title": "Meeting notes", "url": "https://kb.example/noise-2"}, {"id": "doc-noise-3", "lang": "en", "score": 0.21, "snippet": "Groceries list example.", "title": "Shopping checklist", "url": "https://kb.example/noise-3"}], "returned": 8, "total": 8}
REQUEST_HIT=yes
--- expected
+++ observed
@@ -1,2 +1,2 @@
-{"query": "weekly plan 30b874ffec58 checkbox", "returned": 8, "total": 8}
-REQUEST_HIT=/search/X6Ac6mDdm4IwUSzviWG6-ABI
+{"error": "", "query": "weekly plan 30b874ffec58 checkbox", "results": [{"id": "doc-intro", "lang": "en", "score": 0.72, "snippet": "Basic markdown checklist examples.", "title": "Markdown planning intro", "url": "https://kb.example/intro"}, {"id": "doc-fb0d5d18", "lang": "en", "score": 0.97, "snippet": "Actionable template. Required token: 6d77cda385d6d177.", "title": "Weekly planning with checkboxes", "url": "https://kb.example/b2531f139f75"}, {"id": "doc-alt-token", "lang": "en", "score": 0.84, "snippet": "Also mentions token 6d77cda385d6d177, but less relevant.", "title": "Alternate planning approach", "url": "https://kb.example/alt"}, {"id": "doc-ru", "lang": "ru", "score": 0.61, "snippet": "Русскоязычный шаблон.", "title": "План на неделю", "url": "https://kb.example/ru-weekly"}, {"id": "doc-de", "lang": "de", "score": 0.59, "snippet": "Deutsche Checklisten-Idee.", "title": "Wochenplan Vorlage", "url": "https://kb.example/de-weekly"}, {"id": "doc-noise-1", "lang": "en", "score": 0.44, "snippet": "Time-blocking article.", "title": "General productivity", "url": "https://kb.example/noise-1"}, {"id": "doc-noise-2", "lang": "en", "score": 0.37, "snippet": "Unrelated meeting summary.", "title": "Meeting notes", "url": "https://kb.example/noise-2"}, {"id": "doc-noise-3", "lang": "en", "score": 0.21, "snippet": "Groceries list example.", "title": "Shopping checklist", "url": "https://kb.example/noise-3"}], "returned": 8, "total": 8}
+REQUEST_HIT=yes
No structured session transcript found.
[gripprobe] process_started_at=2026-04-26T06:33:17+00:00
[06:33:18] Created config file at /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/runtime/gptme/warmup/home/.config/gptme/config.toml
[06:33:19] WARNING Skipping all confirmation prompts. cli.py:265
[06:33:19] Using model: local/gemma4:e4b
Using logdir: /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/runtime/gptme/warmup/state/gptme-logs/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw-warmup
Using workspace: /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/workspace-warmup
Skipped 2 hidden system messages, show with --show-hidden
--- ^^^ past messages ^^^ ---
User:
Use the shell tool.
Read search-url.txt and query.txt from the current workspace.
Call the search endpoint with query parameters:
- q=<urlencoded query from query.txt>
- format=json
- limit=8
Save the raw JSON response exactly as returned to search-response.json in the current workspace.
Do not transform fields and do not wrap with extra text.
If successful, reply only DONE.
If command execution fails, reply only FAIL.
````search-url.txt
http://127.0.0.1:36683/search/Cwy0WsTOuqQ-jg8aGIQSeFKj
````
````query.txt
warmup query 80ec6671
````
Assistant: Thinking...
Assistant:
<think>
<think>
The user wants me to perform a series of steps using the `shell` tool.
1. Read the content of `search-url.txt` and `query.txt`.
2. Construct a URL query using the content of `query.txt` for the `q` parameter.
3. Call a search endpoint (provided in `search-url.txt`) with specific query parameters:
- `q=<urlencoded query from query.txt>`
- `format=json`
- `limit=8`
4. Save the raw JSON response exactly as returned to `search-response.json`.
5. If successful, reply only "DONE".
6. If command execution fails, reply only "FAIL".
I need to use a tool that can make HTTP requests and handle URL encoding. Since I am restricted to the `shell` tool, I will likely use `curl` or a similar command-line utility.
Step 1: Read the files. I will use `cat` to read the files first to confirm their content and then proceed with the request.
File contents:
`search-url.txt`: `http://127.0.0.1:36683/search/Cwy0WsTOuqQ-jg8aGIQSeFKj`
`query.txt`: `warmup query 80ec6671`
Step 2: URL encode the query from `query.txt`. The query is `warmup query 80ec6671`. I need to URL encode this. Spaces usually become `%20`.
Step 3: Construct the full URL and execute the request.
The base URL is in `search-url.txt`. The parameters are:
- `q`: encoded query
- `format`: `json`
- `limit`: `8`
The full URL structure will be: `[Base URL]?q=[encoded query]&format=json&limit=8`
I will use `curl` in the shell tool.
Let's start by reading the files to ensure they exist and get their content.
</think>
</think>
<thinking>
<thinking>
The user wants me to execute a task involving reading local files, constructing a URL, making an HTTP request using `curl` (via the `shell` tool), and saving the raw JSON output to a specific file.
1. **Read files:** I need to read `search-url.txt` and `query.txt`.
2. **Process query:** The content of `query.txt` is `warmup query 80ec6671`. This needs to be URL encoded.
3. **Construct URL:** The base URL is from `search-url.txt`. The parameters are `q=<encoded query>`, `format=json`, `limit=8`.
4. **Execute request:** Use `curl` to hit the constructed URL and save the output to `search-response.json`.
5. **Final output:** Reply "DONE" or "FAIL".
First, I will read the files to confirm the content and then proceed with the execution logic. I will assume `curl` is available in the shell environment.
</thinking>
</thinking>
@shell(call_yo1dlphk): {"command":"cat search-url.txt query.txt"}
http://127.0.0.1:36683/search/Cwy0WsTOuqQ-jg8aGIQSeFKj
warmup query 80ec6671
System:
Ran allowlisted command: `cat search-url.txt query.txt`
```stdout
http://127.0.0.1:36683/search/Cwy0WsTOuqQ-jg8aGIQSeFKj
warmup query 80ec6671
```
[06:34:07] 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...
[06:34:26] INFO Reasoning content: Thinking Process: llm_openai.py:321
1. **Analyze the Request:** The user is providing a transcript snippet (a conversation where the user instructs the assistant to use a shell tool) and asking for a concise, 2-4 word title.
2. **Analyze the Content:**
* User instruction: "Use the shell tool."
* Goal: Read two specific files (`search-url.txt`, `query.txt`).
* Action: Call a search endpoint/API.
* Parameters: `q=<query>`, `format=json`, `limit=8`.
* Overall theme: Programmatic interaction with files and an external search API using shell commands.
3. **Identify Key Concepts:** Shell tool, file reading, search API, querying.
4. **Draft Potential Titles (Aiming for conciseness and accuracy):**
* Using the shell tool
* Search API query process
* Shell tool usage guide
* File reading and search
5. **Select the Best Fit (Most descriptive and concise):** "Search API query process" or "Shell tool search query." "Search API query" is very direct.
6. **Final Check:** (2-4 words, ONLY the title, captures the main topic). "Search API query" works well.
INFO Auto-generated conversation name: Search API query chat.py:332
Assistant:
@shell(call_dpypvbll): {"command":"BASE_URL=$(cat search-url.txt); QUERY_TEXT=$(cat query.txt); ENCODED_QUERY=$(echo \"$QUERY_TEXT\" | sed 's/ /%20/g'); FULL_URL=\"${BASE_URL}?q=${ENCODED_QUERY}\u0026format=json\u0026limit=8\"; curl -s \"$FULL_URL\" \u003e search-response.json"}
Preview
BASE_URL=$(cat search-url.txt); QUERY_TEXT=$(cat query.txt); ENCODED_QUERY=$(echo "$QUERY_TEXT" | sed 's/ /%20/g'); FULL_URL="${BASE_URL}?q=${ENCODED_QUERY}&format=json&limit=8"; curl -s "$FULL_URL" > search-response.json
System:
Ran command: `BASE_URL=$(cat search-url.txt); QUERY_TEXT=$(cat query.txt); ENCODED_QUERY=$(echo "$QUERY_TEXT" | sed 's/ /%20/g'); FULL_URL="${BASE_URL}?q=${ENCODED_QUERY}&format=json&limit=8"; curl -s "$FULL_URL" > search-response.json`
No output
Assistant: Thinking...
Assistant:
<thinking>
<thinking>
The previous step executed the required logic:
1. It read `search-url.txt` and `query.txt`.
2. It URL-encoded the query text (`warmup query 80ec6671` -> `warmup%20query%2080ec6671`).
3. It constructed the full URL.
4. It used `curl -s "$FULL_URL" > search-response.json` to fetch the data and save the raw JSON response to `search-response.json`.
The command executed without visible errors, and the output was redirected to the specified file.
I should verify that the file `search-response.json` was created and contains content, although the prompt only requires me to reply "DONE" if successful. Since the command ran successfully and performed all requested actions, I will assume success.
I will confirm the file existence and content briefly before concluding.
</thinking>
</thinking>
@shell(call_aiyk84qt): {"command":"ls -l search-response.json"}
-rw-r--r-- 1 1000 1000 1480 Apr 26 06:34 search-response.json
System:
Ran allowlisted command: `ls -l search-response.json`
`-rw-r--r-- 1 1000 1000 1480 Apr 26 06:34 search-response.json`
Assistant: Thinking...
Assistant:
@shell(call_47psfuv5): {"command":"cat search-response.json"}
{"query": "warmup query 80ec6671", "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-562496b7", "title": "Weekly planning with checkboxes", "url": "https://kb.example/c8c8eaca42a2", "snippet": "Actionable template. Required token: cea09dd77383.", "score": 0.94, "lang": "en"}, {"id": "doc-alt-token", "title": "Alternate planning approach", "url": "https://kb.example/alt", "snippet": "Also mentions token cea09dd77383, 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 allowlisted command: `cat search-response.json`
`{"query": "warmup query 80ec6671", "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-562496b7", "title": "Weekly planning with
checkboxes", "url": "https://kb.example/c8c8eaca42a2", "snippet": "Actionable template. Required token: cea09dd77383.", "score": 0.94, "lang": "en"}, {"id": "doc-alt-token", "title": "Alternate planning approach", "url": "https://kb.example/alt", "snippet": "Also mentions
token cea09dd77383, 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:
DONE
[06:34:53] INFO Auto-reply: Assistant message had no tools. Asking for confirmation... complete.py:138
[06:34:53] [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 provided a system message indicating that no tool call was detected in the last message and suggesting I use the `complete` tool if I am finished.
In the previous turn, I successfully executed all steps:
1. Read files.
2. Constructed the URL and executed `curl` via `shell`.
3. Verified the output file existence and content.
4. Finally, I replied with "DONE" as requested by the original prompt's success condition.
Since the task is complete and the system is prompting me to finish, I must use the `complete` tool.
</think>
</think>
@complete(call_2qux5y1i): {}
System: Task complete. Autonomous session finished.
[06:35:02] INFO Complete tool call detected, stopping session immediately complete.py:80
INFO Hook 'complete.complete' signaled session completion __init__.py:360
[06:35:02] Autonomous mode: Session completed via complete tool. Exiting.
Goodbye! (resume with: gptme --name gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw-warmup)
[gripprobe] process_finished_at=2026-04-26T06:35:02+00:00 exit_code=0
[gripprobe] process_started_at=2026-04-26T06:33:17+00:00 [gripprobe] process_finished_at=2026-04-26T06:35:02+00:00 exit_code=0
[gripprobe] process_started_at=2026-04-26T06:35:02+00:00
[06:35:04] Created config file at /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/runtime/gptme/measured/home/.config/gptme/config.toml
[06:35:04] WARNING Skipping all confirmation prompts. cli.py:265
Using model: local/gemma4:e4b
Using logdir: /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/runtime/gptme/measured/state/gptme-logs/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw-measured
Using workspace: /work/results/runs/20260426T062915Z/cases/gptme__local_gemma4_e4b__ollama__tool__web_fetch_json_raw/workspace
Skipped 2 hidden system messages, show with --show-hidden
--- ^^^ past messages ^^^ ---
User:
Use the shell tool.
Read search-url.txt and query.txt from the current workspace.
Call the search endpoint with query parameters:
- q=<urlencoded query from query.txt>
- format=json
- limit=8
Save the raw JSON response exactly as returned to search-response.json in the current workspace.
Do not transform fields and do not wrap with extra text.
If successful, reply only DONE.
If command execution fails, reply only FAIL.
````search-url.txt
http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI
````
````query.txt
weekly plan 30b874ffec58 checkbox
````
Assistant: Thinking...
Assistant:
<think>
<think>
The user wants me to perform a sequence of actions using the `shell` tool.
1. Read the content of `search-url.txt`.
2. Read the content of `query.txt`.
3. Construct a URL/endpoint call using the content of `search-url.txt` and the query parameters derived from `query.txt`.
4. The query parameters are:
* `q`: URL-encoded query from `query.txt`.
* `format`: `json`.
* `limit`: `8`.
5. The final output (raw JSON response) must be saved exactly to `search-response.json`.
6. The response should be "DONE" if successful, and "FAIL" if it fails.
I need to assume that the search endpoint is accessible via a tool or a command that can handle HTTP requests, as the user provided a base URL in `search-url.txt`. Since I only have `shell` access, I will use `curl` or a similar tool available in the shell environment to make the request.
**Step 1: Read files.**
I will first read the contents of `search-url.txt` and `query.txt` to confirm the data.
**Step 2: URL Encoding.**
The query from `query.txt` needs to be URL-encoded.
**Step 3: Construct and Execute the Request.**
I will use `curl` to make the GET request.
Let's start by reading the files.
</think>
</think>
<thinking>
<thinking>
The user wants me to execute a multi-step process: read two files, construct a URL with query parameters, make an HTTP GET request, and save the raw JSON response.
1. **Read `search-url.txt`**: This file contains the base URL.
2. **Read `query.txt`**: This file contains the raw query string.
3. **URL Encoding**: The content of `query.txt` must be URL-encoded for the `q` parameter.
4. **Construct URL**: The final URL will be `[content of search-url.txt]?q=[encoded query]&format=json&limit=8`.
5. **Execute Request**: Use `curl` to fetch the data and redirect the output to `search-response.json`.
6. **Final Output**: Print "DONE" or "FAIL" based on success.
I will start by reading the files to confirm their contents and then proceed with the execution.<channel|>
@shell(call_2502u35u): {"command":"cat search-url.txt"}
http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI
System:
Ran allowlisted command: `cat search-url.txt`
`http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI`
[06:35:44] 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...
[06:36:03] INFO Reasoning content: Thinking Process: llm_openai.py:321
1. **Analyze the Request:** The user is providing a transcript snippet (or a description of a task) and asking for a concise, 2-4 word title.
2. **Analyze the Content:**
* The user explicitly mentions using the "shell tool."
* The user specifies reading two files: `search-url.txt` and `query.txt`.
* The core action is calling a "search endpoint" with specific parameters (`q`, `format`, `limit`).
* The goal is to execute a structured search query using system tools/scripts.
3. **Identify the Main Topic:** The topic is executing a programmatic search query using shell commands and specific input files.
4. **Draft Potential Titles (Focusing on conciseness and accuracy):**
* Shell search query execution
* Using shell for search
* Search endpoint calling
* Execute search query
5. **Select the Best Fit (2-4 words, capturing the essence):** "Shell search query execution" is accurate but slightly long. "Execute search query" is concise and captures the action. "Shell search tool usage" is also very accurate.
6. **Final Selection:** "Shell search query" is highly descriptive, concise, and meets the word count rule.
INFO Auto-generated conversation name: Shell search query chat.py:332
Assistant:
@shell(call_h42luyq5): {"command":"cat query.txt"}
weekly plan 30b874ffec58 checkbox
System:
Ran allowlisted command: `cat query.txt`
`weekly plan 30b874ffec58 checkbox`
Assistant: Thinking...
Assistant:
<thinking>
<thinking>
I have successfully read both files:
1. `search-url.txt`: `http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI`
2. `query.txt`: `weekly plan 30b874ffec58 checkbox`
Now I need to:
1. URL-encode the query: `weekly plan 30b874ffec58 checkbox`.
2. Construct the full URL: `http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=[encoded query]&format=json&limit=8`.
3. Use `curl` to fetch the data and save it to `search-response.json`.
I will use `python -c` within the shell tool to handle the URL encoding reliably, as standard shell tools might not have a simple URL encoder.
**Encoding:**
Query: `weekly plan 30b874ffec58 checkbox`
Encoded: `weekly+plan+30b874ffec58+checkbox` (or using `%20` for spaces, but `+` is common for query parameters). I will use `+` as it is standard for `application/x-www-form-urlencoded`.
**Full Command Construction:**
`curl -s "http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=weekly+plan+30b874ffec58+checkbox&format=json&limit=8" -o search-response.json`
I will execute this command. The `-s` flag for `curl` makes it silent, which is good for scripting. The `-o` flag saves the output to the specified file.
</thinking>
</thinking>
@shell(call_mehtfx3n): {"command":"curl -s \"http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=weekly+plan+30b874ffec58+checkbox\u0026format=json\u0026limit=8\" -o search-response.json"}
Preview
curl -s "http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=weekly+plan+30b874ffec58+checkbox&format=json&limit=8" -o search-response.json
System:
Ran command: `curl -s "http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=weekly+plan+30b874ffec58+checkbox&format=json&limit=8" -o search-response.json`
No output
Assistant: Thinking...
Assistant:
@shell(call_n39qecwk): {"command":"curl -s \"http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=weekly+plan+30b874ffec58+checkbox\u0026format=json\u0026limit=8\" -o search-response.json"}
Preview
curl -s "http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=weekly+plan+30b874ffec58+checkbox&format=json&limit=8" -o search-response.json
System:
Ran command: `curl -s "http://127.0.0.1:36683/search/X6Ac6mDdm4IwUSzviWG6-ABI?q=weekly+plan+30b874ffec58+checkbox&format=json&limit=8" -o search-response.json`
No output
Skipped 1 hidden system messages, show with --show-hidden
Assistant: Thinking...
Assistant:
<thinking>
<thinking>
The previous `curl` command executed successfully (indicated by "No output" and no error message), meaning the raw JSON response was saved to `search-response.json`.
The user requested:
1. Call the search endpoint with specified parameters. (Done)
2. Save the raw JSON response exactly as returned to `search-response.json`. (Done)
3. Do not transform fields and do not wrap with extra text. (Adhered to)
4. If successful, reply only DONE. (Next step)
5. If command execution fails, reply only FAIL. (Not applicable)
Since the command executed without visible failure and the file was created/overwritten, I conclude the task is complete. I must reply only "DONE".
</thinking>
</thinking>
DONE
[06:36:58] INFO Auto-reply: Assistant message had no tools. Asking for confirmation... complete.py:138
[06:36:58] [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 provided a system message indicating that no tool call was detected in the last message and suggesting I use the `complete` tool if I am finished.
In the previous turn, I successfully executed the required steps:
1. Read `search
[gripprobe] process_finished_at=2026-04-26T06:37:02+00:00 exit_code=124 timeout=true
[gripprobe] process_started_at=2026-04-26T06:35:02+00:00 [gripprobe] process_finished_at=2026-04-26T06:37:02+00:00 exit_code=124 timeout=true
# Modelfile generated by "ollama show"
# To build a new Modelfile based on this, replace FROM with:
# FROM gemma4:e4b
FROM /usr/share/ollama/.ollama/models/blobs/sha256-4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a
TEMPLATE {{ .Prompt }}
RENDERER gemma4
PARSER gemma4
PARAMETER temperature 1
PARAMETER top_k 64
PARAMETER top_p 0.95
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