mirror of
https://github.com/ggml-org/llama.cpp.git
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* refactor: unify reasoning handling via backend reasoning_content, drop frontend tag parsing - Updated the chat message component to surface backend-supplied reasoning via message.thinking while showing the raw assistant content without inline tag scrubbing - Simplified chat streaming to append content chunks directly, stream reasoning into the message model, and persist any partial reasoning when generation stops - Refactored the chat service SSE handler to rely on server-provided reasoning_content, removing legacy <think> parsing logic - Refreshed Storybook data and streaming flows to populate the thinking field explicitly for static and streaming assistant messages * refactor: implement streaming-aware universal reasoning parser Remove the streaming mode limitation from --reasoning-format by refactoring try_parse_reasoning() to handle incremental parsing of <think> tags across all formats. - Rework try_parse_reasoning() to track whitespace, partial tags, and multiple reasoning segments, allowing proper separation of reasoning_content and content in streaming mode - Parse reasoning tags before tool call handling in content-only and Llama 3.x formats to ensure inline <think> blocks are captured correctly - Change default reasoning_format from 'auto' to 'deepseek' for consistent behavior - Add 'deepseek-legacy' option to preserve old inline behavior when needed - Update CLI help and documentation to reflect streaming support - Add parser tests for inline <think>...</think> segments The parser now continues processing content after </think> closes instead of stopping, enabling proper message.reasoning_content and message.content separation in both streaming and non-streaming modes. Fixes the issue where streaming responses would dump everything (including post-thinking content) into reasoning_content while leaving content empty. * refactor: address review feedback from allozaur - Passed the assistant message content directly to ChatMessageAssistant to drop the redundant derived state in the chat message component - Simplified chat streaming updates by removing unused partial-thinking handling and persisting partial responses straight from currentResponse - Refreshed the ChatMessage stories to cover standard and reasoning scenarios without the old THINK-tag parsing examples Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com> * refactor: restore forced reasoning prefix to pass test-chat ([chat] All tests passed) - store the exact sequence seen on input when 'thinking_forced_open' enforces a reasoning block - inject this prefix before the first accumulated segment in 'reasoning_content', then clear it to avoid duplication - repeat the capture on every new 'start_think' detection to properly handle partial/streaming flows * refactor: address review feedback from ngxson * debug: say goodbye to curl -N, hello one-click raw stream - adds a new checkbox in the WebUI to display raw LLM output without backend parsing or frontend Markdown rendering * Update tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessage.svelte Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com> * webui: add Storybook example for raw LLM output and scope reasoning format toggle per story - Added a Storybook example that showcases the chat message component in raw LLM output mode with the provided trace sample - Updated every ChatMessage story to toggle the disableReasoningFormat setting so the raw-output rendering remains scoped to its own example * npm run format * chat-parser: address review feedback from ngxson Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> --------- Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com> Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
208 lines
6.2 KiB
Svelte
208 lines
6.2 KiB
Svelte
<script module lang="ts">
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import { defineMeta } from '@storybook/addon-svelte-csf';
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import ChatMessage from '$lib/components/app/chat/ChatMessages/ChatMessage.svelte';
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const { Story } = defineMeta({
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title: 'Components/ChatScreen/ChatMessage',
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component: ChatMessage,
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parameters: {
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layout: 'centered'
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}
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});
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// Mock messages for different scenarios
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const userMessage: DatabaseMessage = {
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id: '1',
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convId: 'conv-1',
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type: 'message',
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timestamp: Date.now() - 1000 * 60 * 5,
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role: 'user',
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content: 'What is the meaning of life, the universe, and everything?',
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parent: '',
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thinking: '',
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children: []
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};
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const assistantMessage: DatabaseMessage = {
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id: '2',
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convId: 'conv-1',
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type: 'message',
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timestamp: Date.now() - 1000 * 60 * 3,
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role: 'assistant',
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content:
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'The answer to the ultimate question of life, the universe, and everything is **42**.\n\nThis comes from Douglas Adams\' "The Hitchhiker\'s Guide to the Galaxy," where a supercomputer named Deep Thought calculated this answer over 7.5 million years. However, the question itself was never properly formulated, which is why the answer seems meaningless without context.',
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parent: '1',
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thinking: '',
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children: []
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};
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const assistantWithReasoning: DatabaseMessage = {
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id: '3',
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convId: 'conv-1',
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type: 'message',
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timestamp: Date.now() - 1000 * 60 * 2,
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role: 'assistant',
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content: "Here's the concise answer, now that I've thought it through carefully for you.",
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parent: '1',
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thinking:
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"Let's consider the user's question step by step:\\n\\n1. Identify the core problem\\n2. Evaluate relevant information\\n3. Formulate a clear answer\\n\\nFollowing this process ensures the final response stays focused and accurate.",
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children: []
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};
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const rawOutputMessage: DatabaseMessage = {
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id: '6',
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convId: 'conv-1',
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type: 'message',
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timestamp: Date.now() - 1000 * 60,
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role: 'assistant',
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content:
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'<|channel|>analysis<|message|>User greeted me. Initiating overcomplicated analysis: Is this a trap? No, just a normal hello. Respond calmly, act like a helpful assistant, and do not start explaining quantum physics again. Confidence 0.73. Engaging socially acceptable greeting protocol...<|end|>Hello there! How can I help you today?',
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parent: '1',
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thinking: '',
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children: []
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};
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let processingMessage = $state({
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id: '4',
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convId: 'conv-1',
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type: 'message',
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timestamp: 0, // No timestamp = processing
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role: 'assistant',
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content: '',
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parent: '1',
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thinking: '',
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children: []
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});
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let streamingMessage = $state({
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id: '5',
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convId: 'conv-1',
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type: 'message',
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timestamp: 0, // No timestamp = streaming
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role: 'assistant',
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content: '',
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parent: '1',
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thinking: '',
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children: []
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});
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</script>
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<Story
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name="User"
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args={{
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message: userMessage
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}}
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play={async () => {
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const { updateConfig } = await import('$lib/stores/settings.svelte');
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updateConfig('disableReasoningFormat', false);
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}}
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/>
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<Story
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name="Assistant"
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args={{
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class: 'max-w-[56rem] w-[calc(100vw-2rem)]',
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message: assistantMessage
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}}
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play={async () => {
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const { updateConfig } = await import('$lib/stores/settings.svelte');
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updateConfig('disableReasoningFormat', false);
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}}
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/>
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<Story
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name="AssistantWithReasoning"
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args={{
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class: 'max-w-[56rem] w-[calc(100vw-2rem)]',
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message: assistantWithReasoning
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}}
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play={async () => {
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const { updateConfig } = await import('$lib/stores/settings.svelte');
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updateConfig('disableReasoningFormat', false);
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}}
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/>
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<Story
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name="RawLlmOutput"
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args={{
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class: 'max-w-[56rem] w-[calc(100vw-2rem)]',
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message: rawOutputMessage
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}}
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play={async () => {
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const { updateConfig } = await import('$lib/stores/settings.svelte');
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updateConfig('disableReasoningFormat', true);
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}}
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/>
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<Story
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name="WithReasoningContent"
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args={{
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message: streamingMessage
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}}
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asChild
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play={async () => {
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const { updateConfig } = await import('$lib/stores/settings.svelte');
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updateConfig('disableReasoningFormat', false);
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// Phase 1: Stream reasoning content in chunks
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let reasoningText =
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'I need to think about this carefully. Let me break down the problem:\n\n1. The user is asking for help with something complex\n2. I should provide a thorough and helpful response\n3. I need to consider multiple approaches\n4. The best solution would be to explain step by step\n\nThis approach will ensure clarity and understanding.';
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let reasoningChunk = 'I';
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let i = 0;
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while (i < reasoningText.length) {
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const chunkSize = Math.floor(Math.random() * 5) + 3; // Random 3-7 characters
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const chunk = reasoningText.slice(i, i + chunkSize);
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reasoningChunk += chunk;
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// Update the reactive state directly
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streamingMessage.thinking = reasoningChunk;
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i += chunkSize;
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await new Promise((resolve) => setTimeout(resolve, 50));
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}
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const regularText =
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"Based on my analysis, here's the solution:\n\n**Step 1:** First, we need to understand the requirements clearly.\n\n**Step 2:** Then we can implement the solution systematically.\n\n**Step 3:** Finally, we test and validate the results.\n\nThis approach ensures we cover all aspects of the problem effectively.";
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let contentChunk = '';
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i = 0;
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while (i < regularText.length) {
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const chunkSize = Math.floor(Math.random() * 5) + 3; // Random 3-7 characters
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const chunk = regularText.slice(i, i + chunkSize);
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contentChunk += chunk;
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// Update the reactive state directly
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streamingMessage.content = contentChunk;
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i += chunkSize;
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await new Promise((resolve) => setTimeout(resolve, 50));
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}
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streamingMessage.timestamp = Date.now();
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}}
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>
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<div class="w-[56rem]">
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<ChatMessage message={streamingMessage} />
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</div>
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</Story>
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<Story
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name="Processing"
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args={{
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message: processingMessage
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}}
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play={async () => {
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const { updateConfig } = await import('$lib/stores/settings.svelte');
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updateConfig('disableReasoningFormat', false);
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// Import the chat store to simulate loading state
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const { chatStore } = await import('$lib/stores/chat.svelte');
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// Set loading state to true to trigger the processing UI
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chatStore.isLoading = true;
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// Simulate the processing state hook behavior
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// This will show the "Generating..." text and parameter details
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await new Promise((resolve) => setTimeout(resolve, 100));
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}}
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/>
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