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fix(agent): use provider registry for claw402, echo reasoning_content for thinking models, add Beta badge

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- Agent now uses mcp.NewAIClientByProvider() for claw402 provider, ensuring
  x402 payment signing works correctly instead of generic HTTP client
- Added ReasoningContent field to Message/LLMResponse structs and wired
  serialization/parsing so DeepSeek thinking models work in multi-turn
- Added Beta badge to Agent nav tab in HeaderBar

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
shinchan-zhai
2026-05-11 20:22:32 +08:00
parent b8cde34e67
commit 9f25bf49bf
5 changed files with 38 additions and 12 deletions
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14
mcp/request.go
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@@ -6,10 +6,11 @@ import "context"
// Supports plain messages (Role+Content), assistant tool-call messages (ToolCalls),
// and tool result messages (Role="tool", ToolCallID, Content).
type Message struct {
Role string `json:"role"` // "system", "user", "assistant", "tool"
Content string `json:"content,omitempty"` // Text content (omitted when ToolCalls present)
ToolCalls []ToolCall `json:"tool_calls,omitempty"` // Set by assistant when calling tools
ToolCallID string `json:"tool_call_id,omitempty"` // Set on role="tool" result messages
Role string `json:"role"` // "system", "user", "assistant", "tool"
Content string `json:"content,omitempty"` // Text content (omitted when ToolCalls present)
ReasoningContent string `json:"reasoning_content,omitempty"` // Thinking-model reasoning (must be echoed back in multi-turn)
ToolCalls []ToolCall `json:"tool_calls,omitempty"` // Set by assistant when calling tools
ToolCallID string `json:"tool_call_id,omitempty"` // Set on role="tool" result messages
}
// ToolCall is a single function call requested by the LLM.
@@ -29,8 +30,9 @@ type ToolCallFunction struct {
// text reply (Content) and any structured tool calls (ToolCalls).
// Exactly one of the two fields will be non-empty for a well-formed response.
type LLMResponse struct {
Content string // Plain-text reply (final answer)
ToolCalls []ToolCall // Structured tool invocations
Content string // Plain-text reply (final answer)
ReasoningContent string // Thinking-model reasoning content
ToolCalls []ToolCall // Structured tool invocations
}
// Tool represents a tool/function that AI can call