chore: release prep

Automated merge for release prep

Author: hyacinthus

.github/workflows/build.yml

@@ -144,8 +144,8 @@ jobs:
           kubectl set image -n testnet-dev deployment/intent-tg intent-tg=crestal/intentkit:${VERSION_NO_V}
           kubectl set image -n testnet-dev deployment/intent-checker intent-checker=crestal/intentkit:${VERSION_NO_V}
           #kubectl set image -n testnet-dev deployment/intent-singleton intent-singleton=crestal/intentkit:${VERSION_NO_V}
-          kubectl set image -n testnet-dev deployment/sandbox-open sandbox-open=crestal/intentkit:${VERSION_NO_V}
-          kubectl set image -n testnet-dev deployment/sandbox-autonomous sandbox-autonomous=crestal/intentkit:${VERSION_NO_V}
+          #kubectl set image -n testnet-dev deployment/sandbox-open sandbox-open=crestal/intentkit:${VERSION_NO_V}
+          #kubectl set image -n testnet-dev deployment/sandbox-autonomous sandbox-autonomous=crestal/intentkit:${VERSION_NO_V}
 
       - name: Deploy to Amazon EKS Prod
         if: ${{ github.event_name == 'release' && github.event.action == 'released' }}
@@ -160,8 +160,8 @@ jobs:
           kubectl set image -n testnet-prod deployment/intent-tg intent-tg=crestal/intentkit:${VERSION_NO_V}
           kubectl set image -n testnet-prod deployment/intent-checker intent-checker=crestal/intentkit:${VERSION_NO_V}
           #kubectl set image -n testnet-prod deployment/intent-singleton intent-singleton=crestal/intentkit:${VERSION_NO_V}
-          kubectl set image -n testnet-prod deployment/sandbox-open sandbox-open=crestal/intentkit:${VERSION_NO_V}
-          kubectl set image -n testnet-prod deployment/sandbox-autonomous sandbox-autonomous=crestal/intentkit:${VERSION_NO_V}
+          #kubectl set image -n testnet-prod deployment/sandbox-open sandbox-open=crestal/intentkit:${VERSION_NO_V}
+          #kubectl set image -n testnet-prod deployment/sandbox-autonomous sandbox-autonomous=crestal/intentkit:${VERSION_NO_V}
 
       - name: Build Success
         if: ${{ success() }}

intentkit/core/engine.py

@@ -67,6 +67,29 @@
 _agents_updated: dict[str, datetime] = {}
 
 
+def _extract_text_content(content: object) -> str:
+    if isinstance(content, list):
+        texts: list[str] = []
+        for item in content:
+            if isinstance(item, dict):
+                t = item.get("text")
+                ty = item.get("type")
+                if t is not None and (ty == "text" or ty is None):
+                    texts.append(t)
+            elif isinstance(item, str):
+                texts.append(item)
+        return "".join(texts)
+    if isinstance(content, dict):
+        if content.get("type") == "text" and "text" in content:
+            return content["text"]
+        if "text" in content:
+            return content["text"]
+        return ""
+    if isinstance(content, str):
+        return content
+    return ""
+
+
 async def build_agent(
     agent: Agent, agent_data: AgentData, custom_skills: list[BaseTool] = []
 ) -> CompiledStateGraph:
@@ -149,8 +172,8 @@ async def select_model(
                 if llm_model.info.provider == LLMProvider.OPENAI:
                     tools.append({"type": "web_search"})
                     private_tools.append({"type": "web_search"})
-                    if agent.model.startswith("gpt-5-"):
-                        llm_params["reasoning_effort"] = "low"
+                    if llm_model.info.model_name == "gpt-5-mini":
+                        llm_params["reasoning_effort"] = "medium"
                 if llm_model.info.provider == LLMProvider.XAI:
                     llm_params["search_parameters"] = {"mode": "auto"}
             # TODO: else use a search skill
@@ -431,31 +454,30 @@ async def stream_agent_raw(
 
     # super mode
     recursion_limit = 30
-    if re.search(r"\b@super\b", input_message):
+    if re.search(r"@super\b", input_message) or user_message.super_mode:
         recursion_limit = 300
         # Remove @super from the message
-        input_message = re.sub(r"\b@super\b", "", input_message).strip()
+        input_message = re.sub(r"@super\b", "", input_message).strip()
 
     # llm native search
-    search = False
-    if re.search(r"\b@search\b", input_message) or re.search(
-        r"\b@web\b", input_message
-    ):
+    search = user_message.search_mode if user_message.search_mode is not None else False
+    if re.search(r"@search\b", input_message) or re.search(r"@web\b", input_message):
         search = True
         if model.supports_search:
             input_message = re.sub(
-                r"\b@search\b",
+                r"@search\b",
                 "(You have native search tool, you can use it to get more recent information)",
                 input_message,
             ).strip()
             input_message = re.sub(
-                r"\b@web\b",
+                r"@web\b",
                 "(You have native search tool, you can use it to get more recent information)",
                 input_message,
             ).strip()
         else:
-            input_message = re.sub(r"\b@search\b", "", input_message).strip()
-            input_message = re.sub(r"\b@web\b", "", input_message).strip()
+            search = False
+            input_message = re.sub(r"@search\b", "", input_message).strip()
+            input_message = re.sub(r"@web\b", "", input_message).strip()
 
     # content to llm
     messages = [
@@ -526,16 +548,7 @@ def get_agent() -> Agent:
                     # tool calls, save for later use, if it is deleted by post_model_hook, will not be used.
                     cached_tool_step = msg
                 if hasattr(msg, "content") and msg.content:
-                    content = msg.content
-                    if isinstance(msg.content, list):
-                        # in new version, content item maybe a list
-                        content = msg.content[0]
-                    if isinstance(content, dict):
-                        if "text" in content:
-                            content = content["text"]
-                        else:
-                            content = str(content)
-                            logger.error(f"unexpected content type: {content}")
+                    content = _extract_text_content(msg.content)
                     # agent message
                     chat_message_create = ChatMessageCreate(
                         id=str(XID()),

intentkit/core/prompt.py

@@ -250,7 +250,7 @@ async def explain_prompt(message: str) -> str:
         str: The processed message with @skill patterns replaced
     """
     # Pattern to match @skill:category:config_name with word boundaries
-    pattern = r"\b@skill:([^:]+):([^\s]+)\b"
+    pattern = r"@skill:([^:]+):([^\s]+)\b"
 
     async def replace_skill_pattern(match):
         category = match.group(1)

intentkit/models/agent.py

@@ -958,6 +958,7 @@ class AgentPublicInfo(BaseModel):
             le=1.0,
             json_schema_extra={
                 "x-placeholder": "Enter agent price",
+                "x-step": 0.01,
             },
         ),
     ]

intentkit/models/llm.csv

@@ -5,8 +5,9 @@ google/gemini-2.5-flash,Gemini 2.5 Flash,gatewayz,FALSE,0.3,2.5,2,1050000,65000,
 google/gemini-2.5-pro,Gemini 2.5 Pro,gatewayz,FALSE,1.25,10,4,1050000,65000,4,2,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,https://api.gatewayz.ai/v1,300
 anthropic/claude-sonnet-4.5,Anthropic Claude Sonnet 4.5,gatewayz,FALSE,3,15,5,200000,64000,5,1,TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE,https://api.gatewayz.ai/v1,300
 gpt-5-nano,GPT-5 Nano,openai,TRUE,0.05,0.4,1,400000,128000,3,5,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,,180
-gpt-5-mini,GPT-5 Mini,openai,TRUE,0.25,2,2,400000,128000,4,4,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,,180
+gpt-5-mini,GPT-5 Mini,openai,TRUE,0.25,2,2,400000,128000,4,4,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,,180
 gpt-5,GPT-5,openai,TRUE,1.25,10,4,400000,128000,5,3,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,,180
+gpt-5-codex,GPT-5 Codex,openai,TRUE,1.25,10,4,400000,128000,5,3,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,,180
 gpt-4o,GPT-4o,openai,FALSE,2.5,10,4,128000,4096,4,3,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,,180
 gpt-4o-mini,GPT-4o Mini,openai,FALSE,0.15,0.6,1,128000,4096,3,4,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,,180
 gpt-4.1-nano,GPT-4.1 Nano,openai,TRUE,0.1,0.4,1,128000,4096,3,5,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,FALSE,,180
@@ -17,7 +18,8 @@ o4-mini,OpenAI o4-mini,openai,TRUE,1.1,4.4,3,128000,4096,4,3,FALSE,TRUE,TRUE,TRU
 deepseek-chat,Deepseek V3.2 Exp,deepseek,TRUE,0.28,0.42,2,128000,4096,4,3,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,https://api.deepseek.com,300
 deepseek-reasoner,DeepSeek V3.2 Exp (Thinking Mode),deepseek,TRUE,0.28,0.42,2,128000,32000,5,1,FALSE,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,TRUE,https://api.deepseek.com,300
 grok-4,Grok 4,xai,TRUE,3,15,4,256000,4096,5,3,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,,180
-grok-4-fast-non-reasoning,Grok 4 Fast,xai,TRUE,0.2,0.5,2,2000000,4096,3,4,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,,180
+grok-4-fast-non-reasoning,Grok 4 Fast,xai,TRUE,0.2,0.5,2,2000000,4096,3,4,TRUE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,,180
+grok-4-fast-reasoning,Grok 4 Fast Reasoning,xai,TRUE,0.2,0.5,2,2000000,4096,3,4,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,,180
 grok-code-fast-1,Grok Code Fast 1,xai,TRUE,0.2,1.5,3,256000,4096,4,4,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,,180
 grok-3,Grok 3,xai,TRUE,3,15,4,131072,4096,5,3,FALSE,TRUE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE,,180
 grok-3-mini,Grok 3 Mini,xai,TRUE,0.3,0.5,2,131072,4096,5,3,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,,180

intentkit/models/llm.py

@@ -403,6 +403,7 @@ async def create_instance(self, params: dict[str, Any] = {}) -> BaseChatModel:
             "model_name": self.model_name,
             "openai_api_key": config.openai_api_key,
             "timeout": info.timeout,
+            "use_responses_api": True,
         }
 
         # Add optional parameters based on model support
@@ -418,10 +419,12 @@ async def create_instance(self, params: dict[str, Any] = {}) -> BaseChatModel:
         if info.api_base:
             kwargs["openai_api_base"] = info.api_base
 
-        if self.model_name.startswith("gpt-5-"):
+        if self.model_name == "gpt-5-mini" or self.model_name == "gpt-5-nano":
             kwargs["reasoning_effort"] = "minimal"
         elif self.model_name == "gpt-5":
-            kwargs["reasoning_effort"] = "low"
+            kwargs["reasoning_effort"] = "medium"
+        elif self.model_name == "gpt-5-codex":
+            kwargs["reasoning_effort"] = "high"
 
         # Update kwargs with params to allow overriding
         kwargs.update(params)

tests/core/test_engine_content_extraction.py

@@ -0,0 +1,35 @@
+from intentkit.core.engine import _extract_text_content
+
+
+def test_extract_from_list_mixed_types():
+    content = [
+        {"id": "rs_x", "summary": [], "type": "reasoning"},
+        {
+            "id": "ws_x",
+            "action": {"query": "q", "type": "search"},
+            "status": "completed",
+            "type": "web_search_call",
+        },
+        {"type": "text", "text": "Hello"},
+        {"type": "text", "text": " World"},
+    ]
+    assert _extract_text_content(content) == "Hello World"
+
+
+def test_extract_from_dict_text_type():
+    content = {"type": "text", "text": "ABC"}
+    assert _extract_text_content(content) == "ABC"
+
+
+def test_extract_from_dict_with_text_without_type():
+    content = {"text": "XYZ"}
+    assert _extract_text_content(content) == "XYZ"
+
+
+def test_extract_from_dict_without_text():
+    content = {"type": "reasoning", "summary": []}
+    assert _extract_text_content(content) == ""
+
+
+def test_extract_from_string():
+    assert _extract_text_content("plain") == "plain"