🐛 Fix some issues in new thought system

DysonNetwork.Insight/Thought/CLIENT_UPDATE_GUIDE.md

@@ -0,0 +1,155 @@
+# Client-Side Guide: Handling the New Message Structure
+
+This document outlines how to update your client application to support the new rich message structure for the thinking/chat feature. The backend now sends structured messages that can include plain text, function calls, and function results, allowing for a more interactive and transparent user experience.
+
+When using with gateway, all the response type are in snake case
+
+## 1. Data Models
+
+When you receive a complete message (a "thought"), it will be in the form of an `SnThinkingThought` object. The core of this object is the `Parts` array, which contains the different components of the message.
+
+Here are the primary data models you will be working with, represented here in a TypeScript-like format for clarity:
+
+```typescript
+// The main message object from the assistant or user
+interface SnThinkingThought {
+  id: string;
+  parts: SnThinkingMessagePart[];
+  role: 'Assistant' /*Value is (0)*/ | 'User' /*Value is (1)*/;
+  createdAt: string; // ISO 8601 date string
+  // ... other metadata
+}
+
+// A single part of a message
+interface SnThinkingMessagePart {
+  type: ThinkingMessagePartType;
+  text?: string;
+  functionCall?: SnFunctionCall;
+  functionResult?: SnFunctionResult;
+}
+
+// Enum for the different part types
+enum ThinkingMessagePartType {
+  Text = 0,
+  FunctionCall = 1,
+  FunctionResult = 2,
+}
+
+// Represents a function/tool call made by the assistant
+interface SnFunctionCall {
+  id: string;
+  name: string;
+  arguments: string; // A JSON string of the arguments
+}
+
+// Represents the result of a function call
+interface SnFunctionResult {
+  callId: string;      // The ID of the corresponding function call
+  result: any;         // The data returned by the function
+  isError: boolean;
+}
+```
+
+## 2. Handling the SSE Stream
+
+The response is streamed using Server-Sent Events (SSE). Your client should listen to this stream and process events as they arrive to build the UI in real-time.
+
+The stream sends different types of messages, identified by a `type` field in the JSON payload.
+
+| Event Type               | `data` Payload                               | Client-Side Action                                                                                                                            |
+| ------------------------ | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
+| `text`                   | `{ "type": "text", "data": "some text" }`    | Append the text content to the current message being displayed. This is the most common event.                                                |
+| `function_call_update`   | `{ "type": "function_call_update", "data": { ... } }` | This provides real-time updates as the AI decides on a function call. You can use this to show an advanced "thinking" state, but it's optional. The key events to handle are `function_call` and `function_result`. |
+| `function_call`          | `{ "type": "function_call", "data": SnFunctionCall }` | The AI has committed to using a tool. Display a "Using tool..." indicator. You can show the `name` of the tool for more clarity. |
+| `function_result`        | `{ "type": "function_result", "data": SnFunctionResult }` | The tool has finished running. You can hide the "thinking" indicator for this tool and optionally display a summary of the result. |
+| `topic`                  | `{ "type": "topic", "data": "A new topic" }` | If this is the first message in a new conversation, this event provides the auto-generated topic title. Update your UI accordingly. |
+| `thought`                | `{ "type": "thought", "data": SnThinkingThought }` | This is the **final event** in the stream. It contains the complete, persisted message object with all its `Parts`. You should use this final object to replace the incrementally-built message in your state to ensure consistency. |
+
+## 3. Rendering a Message from `SnThinkingThought`
+
+Once you have the final `SnThinkingThought` object (either from the `thought` event in the stream or by fetching conversation history), you can render it by iterating through the `parts` array.
+
+### Pseudocode for Rendering
+
+```javascript
+function renderThought(thought: SnThinkingThought) {
+  const messageContainer = document.createElement('div');
+  messageContainer.className = `message message-role-${thought.role}`;
+
+  // User messages are simple and will only have one text part
+  if (thought.role === 'User') {
+    const textPart = thought.parts[0];
+    messageContainer.innerText = textPart.text;
+    return messageContainer;
+  }
+
+  // Assistant messages can have multiple parts
+  let textBuffer = '';
+
+  thought.parts.forEach(part => {
+    switch (part.type) {
+      case ThinkingMessagePartType.Text:
+        // Buffer text to combine consecutive text parts
+        textBuffer += part.text;
+        break;
+
+      case ThinkingMessagePartType.FunctionCall:
+        // First, render any buffered text
+        if (textBuffer) {
+          messageContainer.appendChild(renderText(textBuffer));
+          textBuffer = '';
+        }
+        // Then, render the function call UI component
+        messageContainer.appendChild(renderFunctionCall(part.functionCall));
+        break;
+
+      case ThinkingMessagePartType.FunctionResult:
+        // Render buffered text
+        if (textBuffer) {
+          messageContainer.appendChild(renderText(textBuffer));
+          textBuffer = '';
+        }
+        // Then, render the function result UI component
+        messageContainer.appendChild(renderFunctionResult(part.functionResult));
+        break;
+    }
+  });
+
+  // Render any remaining text at the end
+  if (textBuffer) {
+    messageContainer.appendChild(renderText(textBuffer));
+  }
+
+  return messageContainer;
+}
+
+// Helper functions to create UI components
+function renderText(text) {
+  const p = document.createElement('p');
+  p.innerText = text;
+  return p;
+}
+
+function renderFunctionCall(functionCall) {
+  const el = document.createElement('div');
+  el.className = 'function-call-indicator';
+  el.innerHTML = `<i>Using tool: <strong>${functionCall.name}</strong>...</i>`;
+  // You could add a button to show functionCall.arguments
+  return el;
+}
+
+function renderFunctionResult(functionResult) {
+  const el = document.createElement('div');
+  el.className = 'function-result-indicator';
+  if (functionResult.isError) {
+    el.classList.add('error');
+    el.innerText = 'An error occurred while using the tool.';
+  } else {
+    el.innerText = 'Tool finished.';
+  }
+  // You could expand this to show a summary of functionResult.result
+  return el;
+}
+```
+
+This approach ensures that text and tool-use indicators are rendered inline and in the correct order, providing a clear and accurate representation of the assistant's actions.

DysonNetwork.Insight/Thought/ThoughtProvider.cs

@@ -4,6 +4,7 @@ using System.Text.Json;
 using DysonNetwork.Insight.Thought.Plugins;
 using DysonNetwork.Shared.Models;
 using DysonNetwork.Shared.Proto;
+using DysonNetwork.Shared.Registry;
 using Microsoft.SemanticKernel;
 using Microsoft.SemanticKernel.Connectors.Ollama;
 using Microsoft.SemanticKernel.Connectors.OpenAI;
@@ -72,6 +73,12 @@ public class ThoughtProvider
                 throw new IndexOutOfRangeException("Unknown thinking provider: " + ModelProviderType);
         }
 
+        // Add gRPC clients for Thought Plugins
+        builder.Services.AddServiceDiscoveryCore();
+        builder.Services.AddServiceDiscovery();
+        builder.Services.AddAccountService();
+        builder.Services.AddSphereService();
+        
         builder.Plugins.AddFromType<SnAccountKernelPlugin>();
         builder.Plugins.AddFromType<SnPostKernelPlugin>();