fix(wizard): update DeepSeek provider models to v4 (#3939)

Update DeepSeek references from deprecated model names to the V4 lineup:
- deepseek-reasoner → deepseek-v4-pro
- deepseek-chat → deepseek-v4-flash

Keep docs and frontend mocks aligned with the wizard provider list.

backend/tests/test_patched_deepseek.py

@@ -18,7 +18,7 @@ def _make_model(**kwargs):
     from deerflow.models.patched_deepseek import PatchedChatDeepSeek
 
     return PatchedChatDeepSeek(
-        model="deepseek-reasoner",
+        model="deepseek-v4-pro",
         api_key="test-key",
         **kwargs,
     )
@@ -53,7 +53,7 @@ def test_to_json_produces_constructor_type():
 def test_to_json_kwargs_contains_model():
     model = _make_model()
     result = model.to_json()
-    assert result["kwargs"]["model_name"] == "deepseek-reasoner"
+    assert result["kwargs"]["model_name"] == "deepseek-v4-pro"
     assert result["kwargs"]["api_base"] == "https://api.deepseek.com/v1"
 
 

config.example.yaml

@@ -243,17 +243,17 @@ models:
   #       thinking:
   #         type: disabled
 
-  # Example: DeepSeek model (with thinking support)
-  # - name: deepseek-v3
-  #   display_name: DeepSeek V3 (Thinking)
+  # Example: DeepSeek V4 model (with thinking support)
+  # - name: deepseek-v4
+  #   display_name: DeepSeek V4 (Thinking)
   #   use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
-  #   model: deepseek-reasoner
+  #   model: deepseek-v4-pro
   #   api_key: $DEEPSEEK_API_KEY
   #   timeout: 600.0
   #   max_retries: 2
   #   max_tokens: 8192
   #   supports_thinking: true
-  #   supports_vision: false  # DeepSeek V3 does not support vision
+  #   supports_vision: false  # DeepSeek V4 does not support vision
   #   when_thinking_enabled:
   #     extra_body:
   #       thinking:

frontend/src/app/mock/api/models/route.ts

@@ -9,10 +9,10 @@ export function GET() {
         supports_thinking: true,
       },
       {
-        id: "deepseek-v3.2",
-        name: "deepseek-v3.2",
-        model: "deepseek-chat",
-        display_name: "DeepSeek v3.2",
+        id: "deepseek-v4",
+        name: "deepseek-v4",
+        model: "deepseek-v4-pro",
+        display_name: "DeepSeek V4",
         supports_thinking: true,
       },
       {

frontend/src/content/en/application/configuration.mdx

@@ -68,9 +68,9 @@ models:
   <Tabs.Tab>
 ```yaml
 models:
-  - name: deepseek-v3
+  - name: deepseek-v4
     use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
-    model: deepseek-reasoner
+    model: deepseek-v4-pro
     api_key: $DEEPSEEK_API_KEY
     timeout: 600.0
     max_retries: 2

frontend/src/content/en/harness/lead-agent.mdx

@@ -107,9 +107,9 @@ Thinking mode is controlled per-request through the `thinking_enabled` flag. If
 
 ```yaml
 models:
-  - name: deepseek-v3
+  - name: deepseek-v4
     use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
-    model: deepseek-reasoner
+    model: deepseek-v4-pro
     api_key: $DEEPSEEK_API_KEY
     supports_thinking: true
     when_thinking_enabled:

frontend/src/content/zh/application/configuration.mdx

@@ -75,9 +75,9 @@ models:
   <Tabs.Tab>
 ```yaml
 models:
-  - name: deepseek
+  - name: deepseek-v4
     use: langchain_openai:ChatOpenAI
-    model: deepseek-reasoner
+    model: deepseek-v4-pro
     api_key: $DEEPSEEK_API_KEY
     base_url: https://api.deepseek.com
     request_timeout: 600.0

scripts/wizard/providers.py

@@ -167,10 +167,10 @@ LLM_PROVIDERS: list[LLMProvider] = [
     LLMProvider(
         name="deepseek",
         display_name="DeepSeek",
-        description="DeepSeek Reasoner with thinking support",
+        description="DeepSeek V4 with thinking support",
         use="deerflow.models.patched_deepseek:PatchedChatDeepSeek",
-        models=["deepseek-reasoner", "deepseek-chat"],
-        default_model="deepseek-reasoner",
+        models=["deepseek-v4-pro", "deepseek-v4-flash"],
+        default_model="deepseek-v4-pro",
         env_var="DEEPSEEK_API_KEY",
         package="langchain-deepseek",
         extra_config={

scripts/wizard/writer.py

@@ -153,7 +153,7 @@ def _make_model_config_name(model_name: str) -> str:
 
     Replaces path separators and dots with hyphens so the result is a clean
     YAML-friendly identifier (e.g. "google/gemini-2.5-pro" → "gemini-2-5-pro",
-    "gpt-5.4" → "gpt-5-4", "deepseek-chat" → "deepseek-chat").
+    "gpt-5.4" → "gpt-5-4", "deepseek-v4-pro" → "deepseek-v4-pro").
     """
     # Take only the last path component for namespaced models (e.g. "org/model-name")
     base = model_name.split("/")[-1]