DeepSeek Harness can answer a normal question through a custom model connection while failing as soon as a task requires web search.
That combination usually calls for a more specific investigation than replacing the model key again.
An agent's text-generation route, search provider, and page-fetching service can have separate configurations. A successful chat request validates only the path that produced that response.
This tutorial shows how to isolate those paths, test search independently, and reconnect the complete workflow without assuming that one Base URL controls every capability.
For the initial model configuration, use the agent harness model-connection guide. The steps below focus on the search failure that remains after ordinary chat works.
1. Identify the three operations
A web-assisted answer can involve:
- A model deciding that outside information is needed.
- A search service returning candidate pages.
- A fetch service retrieving the contents of selected pages.
The model then uses the retrieved material to draft an answer.
These operations can fail independently.
A search can succeed while a selected page cannot be retrieved. A page can be retrieved successfully while the model misinterprets it. A normal answer can also be generated without any search being attempted.
Before changing configuration, determine which event actually occurred.
| Evidence | What it establishes |
|---|---|
| Ordinary model response | The selected text-generation route worked |
| Search tool invocation | The agent attempted the tool |
| Search results | The search provider returned usable candidates |
| Retrieved page content | The fetch operation obtained source material |
| Supported final answer | The model used that material appropriately |
Do not collapse these checkpoints into a single “internet access works” status.
2. Record the effective providers
Write down the model provider, search provider, and fetch provider active in the failing session.
Also record the Harness version and profile. Configuration instructions from another release may not describe the fields or defaults in your installation.
The official model-provider guide describes model configuration. The search integration has its own package reference.
This matters when connecting DeepSeek Harness to other models. Changing the main model to a GPT, GLM, or another supported route does not establish which service handles web search.
Similarly, a successful TreeRouter model request does not demonstrate support for every independent search API exposed by an upstream provider.
Keep a small connection record:
Model provider:
Requested model:
Model API destination:
Search provider:
Search API destination:
Fetch provider:
Fetch API destination:
Harness version and profile:Record credential labels rather than secret values.
3. Check the selected search integration
DeepSeek Harness documents a dedicated Search and Fetch API integration in its web-deepseek-api package reference.
That integration registers separate search and fetch providers. Its API base includes the tools path, and the operation path is appended to that base.
For the direct DeepSeek service, the relevant distinction is:
Search/fetch base:
https://api.deepseek.com/v1/tools
Search operation:
https://api.deepseek.com/v1/tools/search
Fetch operation:
https://api.deepseek.com/v1/tools/fetchCheck whether the configuration field expects a base or a complete operation URL. Supplying the full search endpoint to a field that appends /search can produce an incorrect destination.
Also confirm which integration is enabled. A similarly named search option may use a different implementation and credential path.
4. Test the direct search API separately
The following request tests DeepSeek's direct Search API. It requires a credential issued for that service and the relevant account access.
It does not use a gateway credential.
curl --fail-with-body \
https://api.deepseek.com/v1/tools/search \
-H "Authorization: Bearer $DEEPSEEK_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "site:api-docs.deepseek.com Search Fetch API",
"count": 3,
"need_content": false
}'This is a Bash-style example. Supply the key through your environment's secret mechanism before running it.
The official Search and Fetch guide documents the endpoints and authentication.
Inspect whether the response contains search results or an error. Empty results can be a valid search outcome; they are different from a failed request.
Run this check only when the direct service is the integration you intend to use. Do not route production material through an additional provider merely for convenience.
5. Keep gateway credentials and direct-service credentials separate
An API key is scoped to the service that issued it.
A key for an API relay should not be assumed valid at DeepSeek's direct search endpoint. Conversely, a direct DeepSeek key should not be sent to an unrelated gateway address.
A mixed setup can be valid: the main model uses a gateway, while search uses a separately configured service. The important requirement is that each destination receives the correct credential.
Before consolidating both operations through one gateway, confirm support for the exact search schema and endpoint. General OpenAI compatibility is not sufficient evidence.
The TreeRouter API documentation is the starting point for checking the integration paths exposed by the platform. Verify your account's route before replacing a working direct-service configuration.
6. Use a small two-stage task
After the isolated search request works, test the agent workflow with a narrow instruction:
Find the official DeepSeek Search and Fetch documentation.
Return:
1. The selected official page.
2. Whether the search tool succeeded.
3. Whether page retrieval succeeded.
4. One endpoint supported by the retrieved documentation.
If either operation fails, identify the failed stage.
Do not substitute a remembered answer for a failed retrieval.Inspect the tool records as well as the final answer.
The agent may recognize the topic from training or prior context. A correct-looking URL alone does not demonstrate that search or retrieval worked during this run.
Use a new test session when old tool results could hide the failure.
7. Match the fix to the failed stage
| Symptom | First check |
|---|---|
| Search tool absent | Tool registration and active agent configuration |
| Tool called, credential missing | Search-provider credential source |
| Authentication rejected | Credential issuer, destination, and access |
| Unexpected path or not found | Base URL and appended operation |
| Search returns candidates, fetch fails | Selected URL and fetch-provider response |
| Tools work, answer lacks support | Context delivery and answer instructions |
| Repeated failures | Retry policy and the original error category |
Avoid changing every setting at once.
Preserve the successful model route while testing search. Preserve successful search while testing page retrieval. This makes each improvement attributable to a specific change.
Do not increase timeouts to repair an authentication failure. Do not rotate keys to repair a malformed operation path.
8. Keep the production workflow observable
For each web-assisted task, record the search outcome, retrieval outcome, model route, and final task status.
A model response can be successful while the overall research task remains incomplete. Your application should expose that distinction rather than presenting unsupported text as a completed lookup.
Store sanitized request identifiers and destinations where available. Avoid logging full credentials or unnecessary private search text.
When a service reports a temporary failure, use its documented retry guidance. Keep retry counts bounded so a configuration error does not become a loop of repeated calls.
Frequently asked questions
Does changing the main model change the search provider?
Do not assume it does. Inspect the selected provider for each capability in your installed version.
Can one API gateway handle both model calls and search?
Potentially, when it explicitly supports the required operations. Validate the model route and search route independently.
Does an empty results list mean authentication failed?
No. An empty successful search and a rejected request are different outcomes. Inspect the status and response structure.
Should I disable search when testing the model?
For the initial text-generation check, a task that requires no tools is useful. Re-enable and test the required capabilities before considering the full workflow ready.
Connect the complete task
Create a TreeRouter account and verify the model route required by your Harness workflow.
Then test model generation, search, and retrieval as separate capabilities. This gives you a clearer basis for deployment than treating one successful chat response as proof that every agent tool is connected.
