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Author SHA1 Message Date
b99887f016 Merge 76ed952aa2 into 4c73caadf6 2025-02-17 15:01:07 +04:00
4c73caadf6 feat(custom-openai): save live changes 2025-02-17 16:24:41 +05:30
76ed952aa2 fix: update LMStudio endpoint from /health to /v1/models
- Replace health check endpoint with proper model listing endpoint
- Remove workaround that returned 200 for unexpected GET /v1/health
2025-02-16 15:21:28 +04:00
b20ea70089 Your commit message describing the changes 2025-02-16 03:04:54 +04:00
5220abae05 LM Studio Integration:
- Added LM Studio provider with OpenAI-compatible API support
- Dynamic model discovery via /v1/models endpoint
- Support for both chat and embeddings models
- Docker-compatible networking configuration
- Thinking Model Panel:

Added collapsible UI panel for model's chain of thought
-Parses responses with tags to separate reasoning
-Maintains backward compatibility with regular responses
-Styled consistently with app theme for light/dark modes
-Preserves all existing message functionality (sources, markdown, etc.)

These improvements enhance the app's compatibility with local LLMs and provide better visibility into model reasoning processes while maintaining existing functionality.
2025-02-16 02:43:13 +04:00
9668056554 save current changes 2025-02-16 02:34:21 +04:00
1d6ab2c90c feat: Add LM Studio Support and Thinking Model Panel
LM Studio Integration:
- Added LM Studio provider with OpenAI-compatible API support
- Dynamic model discovery via /v1/models endpoint
- Support for both chat and embeddings models
- Docker-compatible networking configuration

Thinking Model Panel:
- Added collapsible UI panel for model's chain of thought
- Parses responses with <think> tags to separate reasoning
- Maintains backward compatibility with regular responses
- Styled consistently with app theme for light/dark modes
- Preserves all existing message functionality (sources, markdown, etc.)

These improvements enhance the app's compatibility with local LLMs and
provide better visibility into model reasoning processes while maintaining
existing functionality.
2025-02-16 02:33:45 +04:00
115e6b2a71 Merge branch 'master' of https://github.com/ItzCrazyKns/Perplexica 2025-02-15 12:52:30 +05:30
a5c79c92ed feat(settings): add embedding provider settings 2025-02-15 12:52:27 +05:30
db3cea446e Update UPDATING.md 2025-02-15 12:33:43 +05:30
13 changed files with 7361 additions and 80 deletions

View File

@ -37,6 +37,7 @@ services:
args:
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
network: host
image: itzcrazykns1337/perplexica-frontend:main
depends_on:
- perplexica-backend

View File

@ -7,34 +7,43 @@ To update Perplexica to the latest version, follow these steps:
1. Clone the latest version of Perplexica from GitHub:
```bash
git clone https://github.com/ItzCrazyKns/Perplexica.git
git clone https://github.com/ItzCrazyKns/Perplexica.git
```
2. Navigate to the Project Directory.
2. Navigate to the project directory.
3. Pull latest images from registry.
3. Check for changes in the configuration files. If the `sample.config.toml` file contains new fields, delete your existing `config.toml` file, rename `sample.config.toml` to `config.toml`, and update the configuration accordingly.
4. Pull the latest images from the registry.
```bash
docker compose pull
```
4. Update and Recreate containers.
5. Update and recreate the containers.
```bash
docker compose up -d
```
5. Once the command completes running go to http://localhost:3000 and verify the latest changes.
6. Once the command completes, go to http://localhost:3000 and verify the latest changes.
## For non Docker users
## For non-Docker users
1. Clone the latest version of Perplexica from GitHub:
```bash
git clone https://github.com/ItzCrazyKns/Perplexica.git
git clone https://github.com/ItzCrazyKns/Perplexica.git
```
2. Navigate to the Project Directory
3. Execute `npm i` in both the `ui` folder and the root directory.
4. Once packages are updated, execute `npm run build` in both the `ui` folder and the root directory.
5. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.
2. Navigate to the project directory.
3. Check for changes in the configuration files. If the `sample.config.toml` file contains new fields, delete your existing `config.toml` file, rename `sample.config.toml` to `config.toml`, and update the configuration accordingly.
4. Execute `npm i` in both the `ui` folder and the root directory.
5. Once the packages are updated, execute `npm run build` in both the `ui` folder and the root directory.
6. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.
---

6912
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@ -15,12 +15,16 @@ API_KEY = ""
[MODELS.GEMINI]
API_KEY = ""
[MODELS.CUSTOM_OPENAI]
API_KEY = ""
API_URL = ""
[MODELS.OLLAMA]
API_URL = "" # Ollama API URL - http://host.docker.internal:11434
[MODELS.LMSTUDIO]
API_URL = "" # LM STUDIO API URL - http://host.docker.internal:1234
[MODELS.CUSTOM_OPENAI]
API_KEY = ""
API_URL = ""
MODEL_NAME = ""
[API_ENDPOINTS]
SEARXNG = "http://localhost:32768" # SearxNG API URL

View File

@ -26,6 +26,9 @@ interface Config {
OLLAMA: {
API_URL: string;
};
LMSTUDIO: {
API_URL: string;
};
CUSTOM_OPENAI: {
API_URL: string;
API_KEY: string;
@ -66,6 +69,8 @@ export const getSearxngApiEndpoint = () =>
export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
export const getLMStudioApiEndpoint = () => loadConfig().MODELS.LMSTUDIO.API_URL;
export const getCustomOpenaiApiKey = () =>
loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
@ -76,10 +81,6 @@ export const getCustomOpenaiModelName = () =>
loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
const mergeConfigs = (current: any, update: any): any => {
if (update === null || update === undefined) {
return current;
}
if (typeof current !== 'object' || current === null) {
return update;
}

1
src/lib/chat/service.ts Normal file
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@ -0,0 +1 @@

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@ -4,6 +4,7 @@ import { loadOpenAIChatModels, loadOpenAIEmbeddingsModels } from './openai';
import { loadAnthropicChatModels } from './anthropic';
import { loadTransformersEmbeddingsModels } from './transformers';
import { loadGeminiChatModels, loadGeminiEmbeddingsModels } from './gemini';
import { loadLMStudioChatModels, loadLMStudioEmbeddingsModels } from './lmstudio';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
@ -17,6 +18,7 @@ const chatModelProviders = {
ollama: loadOllamaChatModels,
anthropic: loadAnthropicChatModels,
gemini: loadGeminiChatModels,
lm_studio: loadLMStudioChatModels,
};
const embeddingModelProviders = {
@ -24,6 +26,7 @@ const embeddingModelProviders = {
local: loadTransformersEmbeddingsModels,
ollama: loadOllamaEmbeddingsModels,
gemini: loadGeminiEmbeddingsModels,
lm_studio: loadLMStudioEmbeddingsModels,
};
export const getAvailableChatModelProviders = async () => {

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@ -0,0 +1,125 @@
import { OpenAIEmbeddings } from '@langchain/openai';
import { ChatOpenAI } from '@langchain/openai';
import { getKeepAlive, getLMStudioApiEndpoint } from '../../config';
import logger from '../../utils/logger';
import axios from 'axios';
const ensureV1Endpoint = (endpoint: string): string => {
return endpoint.endsWith('/v1') ? endpoint : `${endpoint}/v1`;
};
interface LMStudioModel {
id: string;
// add other properties if LM Studio API provides them
}
interface ChatModelConfig {
displayName: string;
model: ChatOpenAI;
}
const checkLMStudioAvailability = async (endpoint: string): Promise<boolean> => {
const v1Endpoint = ensureV1Endpoint(endpoint);
try {
await axios.get(`${v1Endpoint}/models`, {
timeout: 1000, // 1 second timeout
headers: {
'Content-Type': 'application/json',
},
});
return true;
} catch (err) {
logger.debug(`LM Studio server not available at ${endpoint}`);
return false;
}
};
export const loadLMStudioChatModels = async (): Promise<Record<string, ChatModelConfig>> => {
const lmStudioEndpoint = getLMStudioApiEndpoint();
if (!lmStudioEndpoint) {
logger.debug('LM Studio endpoint not configured, skipping');
return {};
}
// Check if server is available before attempting to load models
const isAvailable = await checkLMStudioAvailability(lmStudioEndpoint);
if (!isAvailable) {
return {};
}
try {
const v1Endpoint = ensureV1Endpoint(lmStudioEndpoint);
const response = await axios.get<{ data: LMStudioModel[] }>(`${v1Endpoint}/models`, {
timeout: 5000, // 5 second timeout for model loading
headers: {
'Content-Type': 'application/json',
},
});
const lmStudioModels = response.data.data;
const chatModels = lmStudioModels.reduce<Record<string, ChatModelConfig>>((acc, model) => {
acc[model.id] = {
displayName: model.id,
model: new ChatOpenAI({
openAIApiKey: 'lm-studio',
configuration: {
baseURL: ensureV1Endpoint(lmStudioEndpoint),
},
modelName: model.id,
temperature: 0.7,
}),
};
return acc;
}, {});
return chatModels;
} catch (err) {
logger.error(`Error loading LM Studio models: ${err}`);
return {};
}
};
export const loadLMStudioEmbeddingsModels = async () => {
const lmStudioEndpoint = getLMStudioApiEndpoint();
if (!lmStudioEndpoint) return {};
// Check if server is available before attempting to load models
const isAvailable = await checkLMStudioAvailability(lmStudioEndpoint);
if (!isAvailable) {
return {};
}
try {
const v1Endpoint = ensureV1Endpoint(lmStudioEndpoint);
const response = await axios.get(`${v1Endpoint}/models`, {
timeout: 5000, // 5 second timeout for model loading
headers: {
'Content-Type': 'application/json',
},
});
const lmStudioModels = response.data.data;
const embeddingsModels = lmStudioModels.reduce((acc, model) => {
acc[model.id] = {
displayName: model.id,
model: new OpenAIEmbeddings({
openAIApiKey: 'lm-studio', // Dummy key required by LangChain
configuration: {
baseURL: ensureV1Endpoint(lmStudioEndpoint),
},
modelName: model.id,
}),
};
return acc;
}, {});
return embeddingsModels;
} catch (err) {
logger.error(`Error loading LM Studio embeddings model: ${err}`);
return {};
}
};

View File

@ -6,6 +6,7 @@ import {
import {
getGroqApiKey,
getOllamaApiEndpoint,
getLMStudioApiEndpoint,
getAnthropicApiKey,
getGeminiApiKey,
getOpenaiApiKey,
@ -54,12 +55,13 @@ router.get('/', async (_, res) => {
config['openaiApiKey'] = getOpenaiApiKey();
config['ollamaApiUrl'] = getOllamaApiEndpoint();
config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
config['anthropicApiKey'] = getAnthropicApiKey();
config['groqApiKey'] = getGroqApiKey();
config['geminiApiKey'] = getGeminiApiKey();
config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
config['customOpenaiModelName'] = getCustomOpenaiModelName();
config['customOpenaiModelName'] = getCustomOpenaiModelName()
res.status(200).json(config);
} catch (err: any) {
@ -88,6 +90,9 @@ router.post('/', async (req, res) => {
OLLAMA: {
API_URL: config.ollamaApiUrl,
},
LMSTUDIO: {
API_URL: config.lmStudioApiUrl,
},
CUSTOM_OPENAI: {
API_URL: config.customOpenaiApiUrl,
API_KEY: config.customOpenaiApiKey,

View File

@ -85,10 +85,12 @@ router.post('/', async (req, res) => {
if (body.chatModel?.provider === 'custom_openai') {
llm = new ChatOpenAI({
modelName: body.chatModel?.model || getCustomOpenaiModelName(),
openAIApiKey: body.chatModel?.customOpenAIKey || getCustomOpenaiApiKey(),
openAIApiKey:
body.chatModel?.customOpenAIKey || getCustomOpenaiApiKey(),
temperature: 0.7,
configuration: {
baseURL: body.chatModel?.customOpenAIBaseURL || getCustomOpenaiApiUrl(),
baseURL:
body.chatModel?.customOpenAIBaseURL || getCustomOpenaiApiUrl(),
},
}) as unknown as BaseChatModel;
} else if (

View File

@ -223,11 +223,11 @@ const Page = () => {
setChatModels(data.chatModelProviders || {});
setEmbeddingModels(data.embeddingModelProviders || {});
const currentProvider = selectedChatModelProvider;
const newProviders = Object.keys(data.chatModelProviders || {});
const currentChatProvider = selectedChatModelProvider;
const newChatProviders = Object.keys(data.chatModelProviders || {});
if (!currentProvider && newProviders.length > 0) {
const firstProvider = newProviders[0];
if (!currentChatProvider && newChatProviders.length > 0) {
const firstProvider = newChatProviders[0];
const firstModel = data.chatModelProviders[firstProvider]?.[0]?.name;
if (firstModel) {
@ -237,11 +237,11 @@ const Page = () => {
localStorage.setItem('chatModel', firstModel);
}
} else if (
currentProvider &&
currentChatProvider &&
(!data.chatModelProviders ||
!data.chatModelProviders[currentProvider] ||
!Array.isArray(data.chatModelProviders[currentProvider]) ||
data.chatModelProviders[currentProvider].length === 0)
!data.chatModelProviders[currentChatProvider] ||
!Array.isArray(data.chatModelProviders[currentChatProvider]) ||
data.chatModelProviders[currentChatProvider].length === 0)
) {
const firstValidProvider = Object.entries(
data.chatModelProviders || {},
@ -267,6 +267,55 @@ const Page = () => {
}
}
const currentEmbeddingProvider = selectedEmbeddingModelProvider;
const newEmbeddingProviders = Object.keys(
data.embeddingModelProviders || {},
);
if (!currentEmbeddingProvider && newEmbeddingProviders.length > 0) {
const firstProvider = newEmbeddingProviders[0];
const firstModel =
data.embeddingModelProviders[firstProvider]?.[0]?.name;
if (firstModel) {
setSelectedEmbeddingModelProvider(firstProvider);
setSelectedEmbeddingModel(firstModel);
localStorage.setItem('embeddingModelProvider', firstProvider);
localStorage.setItem('embeddingModel', firstModel);
}
} else if (
currentEmbeddingProvider &&
(!data.embeddingModelProviders ||
!data.embeddingModelProviders[currentEmbeddingProvider] ||
!Array.isArray(
data.embeddingModelProviders[currentEmbeddingProvider],
) ||
data.embeddingModelProviders[currentEmbeddingProvider].length === 0)
) {
const firstValidProvider = Object.entries(
data.embeddingModelProviders || {},
).find(
([_, models]) => Array.isArray(models) && models.length > 0,
)?.[0];
if (firstValidProvider) {
setSelectedEmbeddingModelProvider(firstValidProvider);
setSelectedEmbeddingModel(
data.embeddingModelProviders[firstValidProvider][0].name,
);
localStorage.setItem('embeddingModelProvider', firstValidProvider);
localStorage.setItem(
'embeddingModel',
data.embeddingModelProviders[firstValidProvider][0].name,
);
} else {
setSelectedEmbeddingModelProvider(null);
setSelectedEmbeddingModel(null);
localStorage.removeItem('embeddingModelProvider');
localStorage.removeItem('embeddingModel');
}
}
setConfig(data);
}
@ -278,6 +327,10 @@ const Page = () => {
localStorage.setItem('chatModelProvider', value);
} else if (key === 'chatModel') {
localStorage.setItem('chatModel', value);
} else if (key === 'embeddingModelProvider') {
localStorage.setItem('embeddingModelProvider', value);
} else if (key === 'embeddingModel') {
localStorage.setItem('embeddingModel', value);
}
} catch (err) {
console.error('Failed to save:', err);
@ -436,7 +489,6 @@ const Page = () => {
const value = e.target.value;
setSelectedChatModelProvider(value);
saveConfig('chatModelProvider', value);
// Auto-select first model of new provider
const firstModel =
config.chatModelProviders[value]?.[0]?.name;
if (firstModel) {
@ -511,12 +563,16 @@ const Page = () => {
<Input
type="text"
placeholder="Model name"
defaultValue={config.customOpenaiModelName}
onChange={(e) =>
setConfig({
...config,
value={config.customOpenaiModelName}
isSaving={savingStates['customOpenaiModelName']}
onChange={(e: React.ChangeEvent<HTMLInputElement>) => {
setConfig((prev) => ({
...prev!,
customOpenaiModelName: e.target.value,
})
}));
}}
onSave={(value) =>
saveConfig('customOpenaiModelName', value)
}
/>
</div>
@ -527,12 +583,16 @@ const Page = () => {
<Input
type="text"
placeholder="Custom OpenAI API Key"
defaultValue={config.customOpenaiApiKey}
onChange={(e) =>
setConfig({
...config,
value={config.customOpenaiApiKey}
isSaving={savingStates['customOpenaiApiKey']}
onChange={(e: React.ChangeEvent<HTMLInputElement>) => {
setConfig((prev) => ({
...prev!,
customOpenaiApiKey: e.target.value,
})
}));
}}
onSave={(value) =>
saveConfig('customOpenaiApiKey', value)
}
/>
</div>
@ -543,17 +603,96 @@ const Page = () => {
<Input
type="text"
placeholder="Custom OpenAI Base URL"
defaultValue={config.customOpenaiApiUrl}
onChange={(e) =>
setConfig({
...config,
value={config.customOpenaiApiUrl}
isSaving={savingStates['customOpenaiApiUrl']}
onChange={(e: React.ChangeEvent<HTMLInputElement>) => {
setConfig((prev) => ({
...prev!,
customOpenaiApiUrl: e.target.value,
})
}));
}}
onSave={(value) =>
saveConfig('customOpenaiApiUrl', value)
}
/>
</div>
</div>
)}
{config.embeddingModelProviders && (
<div className="flex flex-col space-y-4 mt-4 pt-4 border-t border-light-200 dark:border-dark-200">
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Embedding Model Provider
</p>
<Select
value={selectedEmbeddingModelProvider ?? undefined}
onChange={(e) => {
const value = e.target.value;
setSelectedEmbeddingModelProvider(value);
saveConfig('embeddingModelProvider', value);
const firstModel =
config.embeddingModelProviders[value]?.[0]?.name;
if (firstModel) {
setSelectedEmbeddingModel(firstModel);
saveConfig('embeddingModel', firstModel);
}
}}
options={Object.keys(config.embeddingModelProviders).map(
(provider) => ({
value: provider,
label:
provider.charAt(0).toUpperCase() +
provider.slice(1),
}),
)}
/>
</div>
{selectedEmbeddingModelProvider && (
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Embedding Model
</p>
<Select
value={selectedEmbeddingModel ?? undefined}
onChange={(e) => {
const value = e.target.value;
setSelectedEmbeddingModel(value);
saveConfig('embeddingModel', value);
}}
options={(() => {
const embeddingModelProvider =
config.embeddingModelProviders[
selectedEmbeddingModelProvider
];
return embeddingModelProvider
? embeddingModelProvider.length > 0
? embeddingModelProvider.map((model) => ({
value: model.name,
label: model.displayName,
}))
: [
{
value: '',
label: 'No models available',
disabled: true,
},
]
: [
{
value: '',
label:
'Invalid provider, please check backend logs',
disabled: true,
},
];
})()}
/>
</div>
)}
</div>
)}
</SettingsSection>
<SettingsSection title="API Keys">

View File

@ -11,6 +11,8 @@ import {
StopCircle,
Layers3,
Plus,
Brain,
ChevronDown,
} from 'lucide-react';
import Markdown from 'markdown-to-jsx';
import Copy from './MessageActions/Copy';
@ -41,26 +43,58 @@ const MessageBox = ({
}) => {
const [parsedMessage, setParsedMessage] = useState(message.content);
const [speechMessage, setSpeechMessage] = useState(message.content);
const [thinking, setThinking] = useState<string>('');
const [answer, setAnswer] = useState<string>('');
const [isThinkingExpanded, setIsThinkingExpanded] = useState(false);
useEffect(() => {
const regex = /\[(\d+)\]/g;
const thinkRegex = /<think>(.*?)(?:<\/think>|$)(.*)/s;
if (
message.role === 'assistant' &&
message?.sources &&
message.sources.length > 0
) {
return setParsedMessage(
message.content.replace(
regex,
(_, number) =>
`<a href="${message.sources?.[number - 1]?.metadata?.url}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${number}</a>`,
),
);
// Check for thinking content, including partial tags
const match = message.content.match(thinkRegex);
if (match) {
const [_, thinkingContent, answerContent] = match;
// Set thinking content even if </think> hasn't appeared yet
if (thinkingContent) {
setThinking(thinkingContent.trim());
setIsThinkingExpanded(true); // Auto-expand when thinking starts
}
// Only set answer content if we have it (after </think>)
if (answerContent) {
setAnswer(answerContent.trim());
// Process the answer part for sources if needed
if (message.role === 'assistant' && message?.sources && message.sources.length > 0) {
setParsedMessage(
answerContent.trim().replace(
regex,
(_, number) =>
`<a href="${message.sources?.[number - 1]?.metadata?.url}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${number}</a>`,
),
);
} else {
setParsedMessage(answerContent.trim());
}
setSpeechMessage(answerContent.trim().replace(regex, ''));
}
} else {
// No thinking content - process as before
if (message.role === 'assistant' && message?.sources && message.sources.length > 0) {
setParsedMessage(
message.content.replace(
regex,
(_, number) =>
`<a href="${message.sources?.[number - 1]?.metadata?.url}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${number}</a>`,
),
);
} else {
setParsedMessage(message.content);
}
setSpeechMessage(message.content.replace(regex, ''));
}
setSpeechMessage(message.content.replace(regex, ''));
setParsedMessage(message.content);
}, [message.content, message.sources, message.role]);
const { speechStatus, start, stop } = useSpeech({ text: speechMessage });
@ -92,27 +126,71 @@ const MessageBox = ({
<MessageSources sources={message.sources} />
</div>
)}
<div className="flex flex-col space-y-2">
<div className="flex flex-row items-center space-x-2">
<Disc3
className={cn(
'text-black dark:text-white',
isLast && loading ? 'animate-spin' : 'animate-none',
<div className="flex flex-col space-y-4">
{thinking && (
<div className="flex flex-col space-y-2 mb-4">
<button
onClick={() => setIsThinkingExpanded(!isThinkingExpanded)}
className="flex flex-row items-center space-x-2 group text-black/70 dark:text-white/70 hover:text-black dark:hover:text-white transition duration-200"
>
<Brain size={20} />
<h3 className="font-medium text-xl">Reasoning</h3>
<ChevronDown
size={16}
className={cn(
"transition-transform duration-200",
isThinkingExpanded ? "rotate-180" : ""
)}
/>
</button>
{isThinkingExpanded && (
<div className="rounded-lg bg-light-secondary/50 dark:bg-dark-secondary/50 p-4">
{thinking.split('\n\n').map((paragraph, index) => {
if (!paragraph.trim()) return null;
const content = paragraph.replace(/^[•\-\d.]\s*/, '');
return (
<div key={index} className="mb-2 last:mb-0">
<details className="group [&_summary::-webkit-details-marker]:hidden">
<summary className="flex items-center cursor-pointer list-none text-sm text-black/70 dark:text-white/70 hover:text-black dark:hover:text-white">
<span className="arrow mr-2 inline-block transition-transform duration-200 group-open:rotate-90 group-open:self-start group-open:mt-1"></span>
<p className="relative whitespace-normal line-clamp-1 group-open:line-clamp-none after:content-['...'] after:inline group-open:after:hidden transition-all duration-200 text-ellipsis overflow-hidden group-open:overflow-visible">
{content}
</p>
</summary>
</details>
</div>
);
})}
</div>
)}
size={20}
/>
<h3 className="text-black dark:text-white font-medium text-xl">
Answer
</h3>
</div>
)}
<div className="flex flex-col space-y-2">
<div className="flex flex-row items-center space-x-2">
<Disc3
className={cn(
'text-black dark:text-white',
isLast && loading ? 'animate-spin' : 'animate-none',
)}
size={20}
/>
<h3 className="text-black dark:text-white font-medium text-xl">
Answer
</h3>
</div>
<Markdown
className={cn(
'prose prose-h1:mb-3 prose-h2:mb-2 prose-h2:mt-6 prose-h2:font-[800] prose-h3:mt-4 prose-h3:mb-1.5 prose-h3:font-[600] dark:prose-invert prose-p:leading-relaxed prose-pre:p-0 font-[400]',
'max-w-none break-words text-black dark:text-white',
)}
>
{parsedMessage}
</Markdown>
</div>
<Markdown
className={cn(
'prose prose-h1:mb-3 prose-h2:mb-2 prose-h2:mt-6 prose-h2:font-[800] prose-h3:mt-4 prose-h3:mb-1.5 prose-h3:font-[600] dark:prose-invert prose-p:leading-relaxed prose-pre:p-0 font-[400]',
'max-w-none break-words text-black dark:text-white',
)}
>
{parsedMessage}
</Markdown>
{loading && isLast ? null : (
<div className="flex flex-row items-center justify-between w-full text-black dark:text-white py-4 -mx-2">
<div className="flex flex-row items-center space-x-1">

View File

@ -1,5 +1,6 @@
{
"compilerOptions": {
"target": "es2018",
"lib": ["dom", "dom.iterable", "esnext"],
"allowJs": true,
"skipLibCheck": true,