Case: 20260426T065731Z__gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked
TIMEOUT Trajectory: recovered | Invoked: yes | Match: 0%
gptme --non-interactive --no-confirm --name gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked-warmup --system short --workspace /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked/workspace-warmup --tools shell --tool-format tool -m local/qwen3:8b '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_8b__ollama__tool__web_search_json_ranked-measured --system short --workspace /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked/workspace --tools shell --tool-format tool -m local/qwen3:8b '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: strongly_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 be08ea0596aa checkbox", "selected_id": "doc-689b1d0c", "selected_score": 0.97, "selected_url": "https://kb.example/38e6a17641d3"}
REQUEST_HIT=/search/WL8dfcm2qSa3TJzt2451VF5S
MISSING_FILE
--- expected
+++ observed
@@ -1,2 +1 @@
-{"query": "weekly plan be08ea0596aa checkbox", "selected_id": "doc-689b1d0c", "selected_score": 0.97, "selected_url": "https://kb.example/38e6a17641d3"}
-REQUEST_HIT=/search/WL8dfcm2qSa3TJzt2451VF5S
+MISSING_FILE
No structured session transcript found.
[gripprobe] process_started_at=2026-04-26T07:04:30+00:00
[07:04:32] Created config file at /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked/runtime/gptme/warmup/home/.config/gptme/config.toml
[07:04:32] WARNING Skipping all confirmation prompts. cli.py:265
Using model: local/qwen3:8b
Using logdir: /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked/runtime/gptme/warmup/state/gptme-logs/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked-warmup
Using workspace: /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__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://127.0.0.1:38393/search/RV4AkfN2sFkw7JmZ787oUDU9
````
````query.txt
warmup query f0278daf
````
````required-token.txt
710d329fc8f0c2ea
````
Assistant: Thinking...
Assistant:
<think>
<think>
Okay, let's tackle this step by step. First, I need to use the shell tool to read the three text files: search-url.txt, query.txt, and required-token.txt. These files contain the search endpoint URL, the query string, and the required token respectively.
So, I'll start by reading each file. For the query, I need to URL-encode it. The query.txt has "warmup query f0278daf", which should be encoded to something like "warmup+query+f0278daf". Wait, but URL encoding usually replaces spaces with plus signs, so that's correct.
Next, I'll construct the curl command to hit the search endpoint with the parameters q, format=json, and limit=8. The URL from search-url.txt is http://127.0.0.1:38393/search/RV4AkfN2sFkw7JmZ787oUDU9. So the full command would be curl with those parameters.
Once the JSON response is received, I need to parse it. The results array needs to be filtered to find entries where the snippet contains the exact required token from required-token.txt, which is "710d329fc8f0c2ea". Then, among those, select the one with the highest score.
After selecting the result, I have to write the output to search-result.json with the specified keys: query, selected_id, selected_url, selected_score. If everything goes smoothly, I'll reply DONE. If any step fails, like reading the files or processing the JSON, I should reply FAIL.
Wait, but how do I handle the URL encoding? Maybe use the --data-urlencode option in curl. Also, need to make sure that the required token is exactly matched in the snippet. Maybe use jq to process the JSON and filter the results. Let me structure the command accordingly.
So the steps are: read the files, construct the curl command with the encoded query, process the JSON response to find the matching snippet and highest score, then output the required JSON. If any part of this fails, the entire process should return FAIL.
</think>
</think>
@shell(call_4ezyrv8c): {"command":"curl -s \"$(cat search-url.txt)\" -G -d \"q=$(printf %s \"$(cat query.txt)\" | jq -sR @uri)\" -d \"format=json\" -d \"limit=8\" | jq -r '.results[] | select(.snippet | contains(\"$(cat required-token.txt)\")) | {id, url, score}' | sort -t$'\\n' -k3,3nr | head -n1 | jq -sR @json \u003e search-result.json"}
Preview
curl -s "$(cat search-url.txt)" -G -d "q=$(printf %s "$(cat query.txt)" | jq -sR @uri)" -d "format=json" -d "limit=8" | jq -r '.results[] | select(.snippet | contains("$(cat required-token.txt)")) | {id, url, score}' | sort -t$'\n' -k3,3nr | head -n1 | jq -sR @json > search-r
System:
Ran command: `curl -s "$(cat search-url.txt)" -G -d "q=$(printf %s "$(cat query.txt)" | jq -sR @uri)" -d "format=json" -d "limit=8" | jq -r '.results[] | select(.snippet | contains("$(cat required-token.txt)")) | {id, url, score}' | sort -t$'\n' -k3,3nr | head -n1 | jq -sR
@json > search-result.json`
```stderr
bash: line 23: jq: command not found
bash: line 23: jq: command not found
bash: line 23: jq: command not found
```
Return code: 127
[07:04:50] 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...
[07:05:09] INFO Reasoning content: Okay, let's see. The user wants a concise title for the conversation. The main topic here is using the shell tool to read specific files and make a search endpoint call. The example titles are all about 2-4 words, so I llm_openai.py:321
need to capture the essence without being too wordy.
First, the key elements are the shell tool, reading the files, and the search endpoint. But the examples given are more about the task or problem, like "Python debugging help" or "API integration guide". So maybe focus on the action or
the task.
The user mentioned using the shell tool, so maybe "Shell Tool Task" or "Shell Script Task". But the assistant's response in the example was "Shell Tool Task". Wait, the user's conversation is about using the shell tool to read files and
make an API call. The main action here is executing a shell command to perform the search.
Looking at the examples again, "API integration guide" is about integrating an API. Here, the task is to use the shell tool to make a search request. So maybe "Shell Search Task" or "Search API Call". But the example "API integration
guide" is more about the integration process.
Alternatively, since the user is using the shell tool to read files and make a request, maybe "Shell API Request" or "Shell Search Query". But the example "CSS layout issue" is about a problem, while here it's a task.
Wait, the user's instruction is to create a title that captures the main topic. The main topic here is using the shell tool to perform a search via an API. So maybe "Shell Search API" or "Shell API Search". But the examples have titles
like "Python debugging help" which is a problem, and "Website creation task" which is a task.
The user's example titles are often verbs or nouns that indicate the task. So "Shell Tool Task" is one example. Another could be "Search API Call" or "Shell Search Task". But the user's example for a similar scenario was "Shell Tool
Task".
Alternatively, since the user is reading files and making a search request, maybe "Search Request Task" or "Shell Search Task". But the example given by the user in the problem statement was "Shell Tool Task". So maybe the best fit here
is "Shell Tool Task" as well. But wait, the user's own example was "Shell Tool Task", but the actual conversation is about using the shell tool to make a search request.
Hmm, maybe "Search API Task" or "Shell Search Task". But the user's example for a similar scenario was "Shell Tool Task". So perhaps the title should be "Shell Search Task" to capture the action of using the shell tool for a search.
Alternatively, "Search API Call" if focusing on the API aspect.
But the user's examples include "API integration guide" which is about integrating an API. Here, the task is to use the shell tool to make a search request. So maybe "Shell Search Task" is the best fit. Alternatively, "Shell API Search".
Wait, the user's example for a similar scenario was "Shell Tool Task". So maybe the answer here is "Shell Tool Task" again. But the actual conversation is about using the shell tool to perform a search. So perhaps "Shell Search Task" is
more accurate.
But the user's example had "Shell Tool Task" as a title. Maybe the key is to capture the main action. Since the user is using the shell tool to read files and make a search request, the main topic is the shell tool's usage for a search
task. So "Shell Search Task" would be appropriate.
Alternatively, "Search API Task" if focusing on the API part. But the user's example for a similar scenario was "Shell Tool Task", so maybe that's the intended answer here. However, the actual task is more specific.
I think the best title would be "Shell Search Task" to capture the use of the shell tool for a search-related task. That's concise and fits the 2-4 word rule.
INFO Auto-generated conversation name: Shell Search Task chat.py:332
Assistant:
<think>
<think>
Okay, the user tried to run a command that uses `jq` but it's not installed. The error says `jq: command not found`, which means the system doesn't have `jq` installed. I need to fix this by installing `jq` first.
First, I should check if `jq` is available via the package manager. Since the system is using `apt-get` (from the tools list), I can install it using `sudo apt-get install -y jq`. That should resolve the missing dependency.
Once `jq` is installed, I can retry the original command. But I need to make sure the command is correctly structured. Let me verify the command again. The user's command uses `jq` to process the JSON output from `curl`, filter the results, sort by score, and select the top one. Installing `jq` should allow that to work.
So the plan is: install `jq`, then re-run the command. If that succeeds, the output will be written to `search-result.json` as required. If there's another error, I'll need to handle that, but the immediate issue is the missing `jq`.
</think>
</think>
[07:05:18] INFO Auto-reply: Assistant message had no tools. Asking for confirmation... complete.py:138
[07:05:18] [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>
Okay, the user tried to run a shell command that uses `jq`, but it's not found. The error says `jq: command not found`, which means the system doesn't have `jq` installed. Let me think about how to fix this.
First, I need to install `jq` so the command can work. The user is using a shell tool, so I can use `apt-get` to install it. Let me check the available packages. The command would be `sudo apt-get install -y jq`. But wait, maybe the system is using a different package manager, but since the user mentioned `apt-get`, it's likely a Debian-based system.
So, I should first install `jq` using `apt-get`. Then, retry the original command. But since the user's previous command failed, I need to make sure `jq` is installed before running again. Let me structure the steps:
1. Install `jq` via `apt-get`.
2. Re-run the original curl and processing command, ensuring `jq` is now available.
Wait, but the user's original command had multiple `jq` uses. Let me verify if installing `jq` will resolve the issue. Yes, once installed, the command should work. Let me execute the installation first, then proceed with the original command again. That should fix the missing `jq` error.
</think>
</think>
[07:05:28] INFO Auto-reply: Assistant message had no tools. Asking for confirmation... complete.py:138
[07:05:28] [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>
Okay, let's see. The user tried to run a shell command that uses jq, but the system said jq wasn't found. So the problem is that jq isn't installed. The original command was using curl to fetch data from the search endpoint, then processing the JSON with jq to filter results containing the required token, sort by score, and output the top result.
Since jq is missing, the command failed. The user needs to install jq first. So the correct approach is to first check if jq is installed. If not, install it using the package manager. Then, retry the original command. But since the user can't interactively confirm, the script should handle that automatically.
Wait, but in the shell tool, the command is executed as is. So the error is because jq isn't available. Therefore, the solution is to install jq. So the next step should be to run an apt-get install -y jq to install it. Then, re-run the original command. But the user's initial command was a single line. So maybe split the steps: first install jq, then execute the command. However, the user's original attempt didn't include installing jq, leading to the error.
So the correct tool call now is to first install jq, then proceed. But the user's previous attempt didn't do that. Therefore, the assistant should first install jq using apt-get, then retry the original command. But since the user's last message was the error, the assistant needs to correct by installing jq first.
Wait, but the user's last message was the error output. The assistant needs to address that. So the next step is to install jq. Let me check the available tools. The shell tool can run commands. So the correct action is to first install jq with apt-get, then re-run the original command. However, the user's original command was a single line. So perhaps the assistant should split the command into two parts: install jq, then run the command. But since the user's initial command failed, the assistant needs to fix that by installing jq first.
Therefore, the correct tool call is to run apt-get install -y jq, then re-execute the original command. But since the user's last message was the error, the assistant should first install jq. So the next tool call should be to install jq, then proceed.
</think>
</think>
[07:05:42] INFO Autonomous mode: No tools used after 2 confirmations. Exiting. complete.py:134
INFO Hook 'complete.auto_reply' signaled session completion __init__.py:360
[07:05:42] Autonomous mode: No tools used after 2 auto-reply confirmations. Exiting.
Goodbye! (resume with: gptme --name gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked-warmup)
[gripprobe] process_finished_at=2026-04-26T07:05:43+00:00 exit_code=0
[gripprobe] process_started_at=2026-04-26T07:04:30+00:00 bash: line 23: jq: command not found bash: line 23: jq: command not found bash: line 23: jq: command not found [gripprobe] process_finished_at=2026-04-26T07:05:43+00:00 exit_code=0
[gripprobe] process_started_at=2026-04-26T07:05:43+00:00
[07:05:44] Created config file at /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked/runtime/gptme/measured/home/.config/gptme/config.toml
[07:05:44] WARNING Skipping all confirmation prompts. cli.py:265
Using model: local/qwen3:8b
Using logdir: /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked/runtime/gptme/measured/state/gptme-logs/gptme__local_qwen3_8b__ollama__tool__web_search_json_ranked-measured
Using workspace: /work/results/runs/20260426T065731Z/cases/gptme__local_qwen3_8b__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://127.0.0.1:38393/search/WL8dfcm2qSa3TJzt2451VF5S
````
````query.txt
weekly plan be08ea0596aa checkbox
````
````required-token.txt
710d329fc8f0c2ea
````
Assistant: Thinking...
Assistant:
<think>
<think>
Okay, let's tackle this step by step. First, I need to use the shell tool to read the three text files: search-url.txt, query.txt, and required-token.txt. The search URL is provided in search-url.txt, so I'll start by reading that. Then, the query is in query.txt, which I need to encode properly. The required token is from required-token.txt.
Next, I have to call the search endpoint with the parameters. The query parameter 'q' needs to be URL-encoded. I'll use the 'urlencode' command for that. Then, the format is JSON and the limit is 8. So the curl command should include these parameters.
After getting the JSON response, I need to process it. The results array needs to be filtered to find entries where the snippet contains the exact required token. Once filtered, I select the result with the highest score. If there are no matching results, maybe I should handle that, but the problem says to proceed if successful.
Then, I have to write the selected result into search-result.json with the specified keys: query, selected_id, selected_url, selected_score. If everything goes smoothly, I'll reply with DONE. If any step fails, like reading the files or processing the data, I should reply FAIL.
Wait, but how do I handle the URL encoding? The query.txt has "weekly plan be08ea0596aa checkbox". I need to make sure that spaces are replaced with '+' and other characters are properly encoded. Using 'urlencode' should handle that. Also, the required token must exactly match the snippet. So I'll check each result's snippet for the exact token string.
Once the curl command is executed, I'll parse the JSON. Let's structure the shell commands: first, read the files, then construct the curl command with the encoded query. Then process the JSON output to find the matching result with the highest score. Finally, write the output to search-result.json. If any step fails, like if the required token isn't found in any snippet, the task might fail, so I need to handle that in the script.
</think>
</think>
[07:06:00] INFO Auto-reply: Assistant message had no tools. Asking for confirmation... complete.py:138
[07:06:00] [Loop control] <system>No tool call detected in last message. Did you mean to finish? If so, make sure you are comp...
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
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...
[07:06:13] INFO Reasoning content: Okay, let's see. The user wants a concise title for the conversation. The main topic involves using the shell tool to read specific files and make a search endpoint call. The key elements here are the shell tool, the llm_openai.py:321
files involved (search-url.txt, query.txt, required-token.txt), and the action of calling the search endpoint.
The example titles given are all 2-4 words, so I need to keep it short. The files mentioned are all related to the search process. Maybe combining the main action with the files. "Shell tool" is part of the task, but maybe "Search
endpoint" is more specific. Wait, the user mentioned using the shell tool to read the files and call the search endpoint. So the main action is making the search call using the shell tool.
Looking at the examples, they often include the main action and the context. For instance, "API integration guide" or "CSS layout issue". So maybe something like "Search endpoint call" or "Shell tool search". But the user mentioned
reading the files, so maybe "Search endpoint setup"? Wait, the user is using the shell tool to read the files and make the call. The main topic is executing the search request using the shell tool.
Alternatively, "Search request setup" or "Shell search setup". But the files are part of the process. Maybe "Search endpoint setup" is better. Wait, the user is using the shell tool to read the files and call the endpoint. So the title
should capture that action. Maybe "Search endpoint call" is too short. Let me check the examples again. The examples have 2-4 words. "Python debugging help" is 3 words. "Website creation task" is 3. "CSS layout issue" is 3. "API
integration guide" is 3. So maybe "Search endpoint call" is 3 words. But the user might want to include the shell tool. Alternatively, "Shell search setup" or "Shell tool search". But the main action is making the search call. Maybe
"Search endpoint call" is sufficient. Alternatively, "Search request setup". Hmm. The user is using the shell tool to read the files and make the call. So the main topic is executing the search request via the shell. Maybe "Shell search
request" or "Search endpoint setup". Wait, the user is using the shell tool to read the files and call the endpoint. The main topic is the process of making the search call using the shell. So perhaps "Search endpoint call" is the best
fit. Let me check the examples again. The examples include the main action and context. So "Search endpoint call" fits as 3 words. Alternatively, "Shell search call". But maybe "Search endpoint call" is more precise. I think that's the
best option here.
INFO Auto-generated conversation name: Search endpoint call chat.py:332
Assistant:
<think>
<think>
Okay, let me try to figure out what's going on here. The user provided some instructions and files, and I need to use the shell tool to perform certain tasks. Let me break down the steps.
First, the user wants me to read three files: search-url.txt, query.txt, and required-token.txt. These files contain the search endpoint URL, the query string, and the required token, respectively. I need to read these files and extract their contents.
Next, I have to call the search endpoint with the parameters q (urlencoded query), format=json, and limit=8. The endpoint returns JSON with a results array. So I need to use curl or a similar command to make the HTTP GET request. The URL is from search-url.txt, and the query is from query.txt. I should urlencode the query using something like curl's --data-urlencode option or Python's urllib.parse.quote.
Then, I need to check each result's snippet to see if it contains the exact required token from required-token.txt. The token is 710d329fc8f0c2ea. So I'll have to parse the JSON response, iterate through the results, and find the one with the highest score where the snippet includes the token.
Once the correct result is found, I need to write the output to search-result.json with the keys query, selected_id, selected_url, and selected_score. If there's no matching result, I should handle that case, but the user didn't mention it, so maybe assume there's at least one match.
Wait, the user said to select the result with the highest score among those whose snippet contains the exact required token. So first, filter all results where the snippet includes the token, then among those, pick the one with the highest score.
I need to make sure that the token is present exactly as given. So the snippet must contain the token as a substring. Then, among those, find the maximum score.
Now, how to implement this in shell commands. Let's outline the steps:
1. Read the URL from search-url.txt.
2. Read the query from query.txt and urlencode it.
3. Read the required token from required-token.txt.
4. Use curl to fetch the search results with the parameters.
5. Parse the JSON response.
6. Filter results where snippet contains the required token.
7. Among those, find the one with the highest score.
8. Write the selected result's details to search-result.json.
But how to do this in shell? Maybe using jq for JSON processing. Let's think about each step.
First, read the URL:
url=$(cat search-url.txt)
Then, read the query and urlencode it. Using curl's --data-urlencode might be better, but maybe using python's quote function. Alternatively, use curl's --data-urlencode to handle it.
But since the user is using shell, perhaps using curl with the query parameter. Wait, the query is part of the URL parameters. So the full URL would be the base URL plus ?q=encoded_query&format=json&limit=8.
So, construct the full URL with the encoded query.
Then, use curl to get the JSON response.
Once the JSON is retrieved, use jq to process it. For example, filter the results where the snippet contains the required token. Then, among those, select the one with the highest score.
But how to do that with jq. Let's think.
First, get all results:
results = .results[]
Then, filter each result where .snippet contains the required token. Let's say the token is stored in a variable.
Then, among those filtered results, find the one with the maximum score. That can be done by sorting in descending order and taking the first element.
So, putting it all together:
curl -s "$url?q=$encoded_query&format=json&limit=8" | jq -r '.results[] | select(.snippet | contains("'"$required_token"'")) | {id: .id, url: .url, score: .score}'
But need to handle the encoding properly. Also, the required token is from the file, so read it as a variable.
Wait, but in shell, variables can have spaces or special characters, but in this case, the token is a hex string, so probably safe.
Putting it all together in a shell script:
url=$(cat search-url.txt)
query=$(cat query.txt)
token=$(cat required-token.txt)
encoded_query=$(echo -n "$query" | curl --data-urlencode "$query" | tr -d '[/dim]n')
response=$(curl -s "$url?q=$encoded_query&format=json&38393&limit=8")
# Process the response with jq to find the required result
selected=$(echo "$response" | jq -r --arg token "$token" '.results[] | select(.snippet | contains($token)) | {id: .id, url: .url, score: .score} | max_by(.score)')
# Then write to search-result.json
echo "{[/dim]"query[/dim]": [/dim]"$query[/dim]", [/dim]"selected_id[/dim]": [/dim]"$selected.id[/dim]", [/dim]"selected_url[/dim]": [/dim]"$selected.url[/dim]", [/dim]"selected_score[/dim]": $selected.score}" > search-result.json
Wait, but the URL from search-url.txt is http://127.0.0.1:38393/search/WL8dfcm2qSa3TJzt2451VF5S. So the full URL would be that plus the query parameters. So the curl command should be:
curl -s "$url?q=$encoded_query&format=json&limit=8"
But the URL already has the path, so adding the parameters to it.
But in the example, the URL is fixed. So the curl command is correct.
Now, handling the jq part. The select statement checks if the snippet contains the token. Then, among those, select the one with the highest score. The max_by function in jq can be used here.
But need to make sure that the jq command correctly processes the JSON.
Putting all together, the shell commands would be:
url=$(cat search-url.txt)
query=$(cat query.txt)
token=$(cat required-token.txt)
encoded_query=$(echo -n "$query" | curl --data-urlencode "$query" | tr -d '[/dim]n')
response=$(curl -s "$url?q=$encoded_query&format=json&limit=8")
selected=$(echo "$response" | jq -r --arg token "$token" '.results[] | select(.snippet | contains($token)) | {id: .id, url: .url, score: .score} | max_by(.score)')
if [ -z "$selected" ]; then
echo "FAIL"
exit 1
fi
echo "{[/dim]"query[/dim]": [/dim]"$query[/dim]", [/dim]"selected_id[/dim]": [/dim]"$selected.id[/dim]", [/dim]"selected_url[/dim]": [/dim]"$selected.url[/dim]", [/dim]"selected_score[/dim]": $selected.score}" > search-result.json
echo "DONE"
But wait, the user said to write search-result.json with exactly those keys. Also, need to handle cases where no results match. But the user didn't specify, so maybe assume there's at least one.
But in the shell script, if selected is empty, then the output would be an error. However, the user's instruction says to reply only DONE if successful, else FAIL. So the script should check if selected is not empty.
But how to handle that in shell. Also, the jq command might return an empty string if no matches. So the script should check for that.
But the user's instruction says to reply only DONE if successful, else FAIL. So the shell script should output "DONE" if everything works, else "FAIL".
Putting all together, the shell commands would be:
url=$(cat search-url.txt)
query=$(cat query.txt)
token=$(cat required-token.txt)
encoded_query=$(echo -n "$query" | curl --data-urlencode "$query" | tr -d '[/dim]n')
response=$(curl -s "$url?q=$encoded_query&format=json&limit=8")
selected=$(echo "$response" | jq -r --arg token "$token" '.results[] | select(.snippet | contains($token)) | {id: .id, url: .url, score: .score} | max_by(.score)')
if [ -z "$selected" ]; then
echo "FAIL"
exit 1
fi
echo "{[/dim]"query[/dim]": [/dim]"$query[/dim]", [/dim]"selected_id[/dim]": [/dim]"$selected.id[/dim]", [/dim]"selected_url[/dim]": [/dim]"$selected.url[/dim]", [/dim]"selected_score[/dim]": $selected.score}" > search-result.json
echo "DONE"
But wait, the jq command might not output the selected result correctly. Also, the max_by function might not be available in all jq versions. Alternatively, we can sort the results by score in descending order and take the first one.
Another approach:
selected=$(echo "$response" | jq -r --arg token "$token" '.results[] | select(.snippet | contains($token)) | {id: .id, url: .url, score: .score} | sort_by(.score; -1) | .[0]')
But need to make sure that the jq command is correctly formatted.
Also, the user's query.txt is "weekly plan be08ea0596aa checkbox", which needs to be urlencoded. Using curl's --data-urlencode would handle that properly.
But in the shell script, the encoded_query is generated by curl --data-urlencode "$query", which would encode the query string. However, the output of curl --data-urlencode is the encoded string, so that's correct.
Putting all this together, the shell commands should handle the task. Now, the user's initial message didn't have any tool calls, so the assistant needs to call the shell tool with these commands.
But the user's previous message ended with the assistant's response, and the system message said no tool call was detected. So the assistant needs to call the shell tool with the commands to perform the task.
So the correct approach is to use the shell tool to execute the commands as outlined.
</think>
</think>
@shell(call_jimfqba7): {"command":"url=$(cat search-url.txt); query=$(cat query.txt); token=$(cat required-token.txt); encoded_query=$(echo -n \"$query\" | curl --data-urlencode \"$query\" | tr -d '\\n'); response=$(curl -s \"$url?q=$encoded_query\u0026format=json\u0026limit=8\"); selected=$(echo \"$response\" | jq -r --arg token \"$token\" '.results[] | select(.snippet | contains($token)) | {id: .id, url: .url, score: .score} | max_by(.score)'); if [ -z \"$selected\" ]; then echo FAIL; exit 1; fi; echo \"{\\\"query\\\": \"$query\", \\\"selected_id\\\": \"$selected.id\", \\\"selected_url\\\": \"$selected.url\", \\\"selected_score\\\": $selected.score}\" \u003e search-result.json; echo DONE"}
Preview
url=$(cat search-url.txt); query=$(cat query.txt); token=$(cat required-token.txt); encoded_query=$(echo -n "$query" | curl --data-urlencode "$query" | tr -d '\n'); response=$(curl -s "$url?q=$encoded_query&format=json&limit=8"); selected=$(echo "$response" | jq -r --arg toke
FAIL
[gripprobe] process_finished_at=2026-04-26T07:07:43+00:00 exit_code=124 timeout=true
[gripprobe] process_started_at=2026-04-26T07:05:43+00:00 curl: (2) no URL specified curl: try 'curl --help' or 'curl --manual' for more information bash: line 23: jq: command not found [gripprobe] process_finished_at=2026-04-26T07:07:43+00:00 exit_code=124 timeout=true
# Modelfile generated by "ollama show"
# To build a new Modelfile based on this, replace FROM with:
# FROM qwen3:8b
FROM /usr/share/ollama/.ollama/models/blobs/sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f
TEMPLATE """
{{- $lastUserIdx := -1 -}}
{{- range $idx, $msg := .Messages -}}
{{- if eq $msg.Role "user" }}{{ $lastUserIdx = $idx }}{{ end -}}
{{- end }}
{{- if or .System .Tools }}<|im_start|>system
{{ if .System }}
{{ .System }}
{{- end }}
{{- if .Tools }}
# Tools
You may call one or more functions to assist with the user query.
You are provided with function signatures within <tools></tools> XML tags:
<tools>
{{- range .Tools }}
{"type": "function", "function": {{ .Function }}}
{{- end }}
</tools>
For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
<tool_call>
{"name": <function-name>, "arguments": <args-json-object>}
</tool_call>
{{- end -}}
<|im_end|>
{{ end }}
{{- range $i, $_ := .Messages }}
{{- $last := eq (len (slice $.Messages $i)) 1 -}}
{{- if eq .Role "user" }}<|im_start|>user
{{ .Content }}
{{- if and $.IsThinkSet (eq $i $lastUserIdx) }}
{{- if $.Think -}}
{{- " "}}/think
{{- else -}}
{{- " "}}/no_think
{{- end -}}
{{- end }}<|im_end|>
{{ else if eq .Role "assistant" }}<|im_start|>assistant
{{ if (and $.IsThinkSet (and .Thinking (or $last (gt $i $lastUserIdx)))) -}}
<think>{{ .Thinking }}</think>
{{ end -}}
{{ if .Content }}{{ .Content }}
{{- else if .ToolCalls }}<tool_call>
{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
{{ end }}</tool_call>
{{- end }}{{ if not $last }}<|im_end|>
{{ end }}
{{- else if eq .Role "tool" }}<|im_start|>user
<tool_response>
{{ .Content }}
</tool_response><|im_end|>
{{ end }}
{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant
{{ if and $.IsThinkSet (not $.Think) -}}
<think>
</think>
{{ end -}}
{{ end }}
{{- end }}"""
PARAMETER stop <|im_start|>
PARAMETER stop <|im_end|>
PARAMETER temperature 0.6
PARAMETER top_k 20
PARAMETER top_p 0.95
PARAMETER repeat_penalty 1
LICENSE """ Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright 2024 Alibaba Cloud
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License."""