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feat(api): update search api & related documentation

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ItzCrazyKns
2025-12-27 13:07:59 +05:30
parent a31a4ab295
commit 50ca7ac73a
2 changed files with 90 additions and 84 deletions
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25
docs/API/SEARCH.md
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@@ -57,7 +57,7 @@ Use the `id` field as the `providerId` and the `key` field from the models array
### Request
The API accepts a JSON object in the request body, where you define the focus mode, chat models, embedding models, and your query.
The API accepts a JSON object in the request body, where you define the enabled search `sources`, chat models, embedding models, and your query.
#### Request Body Structure
@@ -72,7 +72,7 @@ The API accepts a JSON object in the request body, where you define the focus mo
"key": "text-embedding-3-large"
},
"optimizationMode": "speed",
"focusMode": "webSearch",
"sources": ["web"],
"query": "What is Perplexica",
"history": [
["human", "Hi, how are you?"],
@@ -87,24 +87,25 @@ The API accepts a JSON object in the request body, where you define the focus mo
### Request Parameters
- **`chatModel`** (object, optional): Defines the chat model to be used for the query. To get available providers and models, send a GET request to `http://localhost:3000/api/providers`.
- **`chatModel`** (object, required): Defines the chat model to be used for the query. To get available providers and models, send a GET request to `http://localhost:3000/api/providers`.
- `providerId` (string): The UUID of the provider. You can get this from the `/api/providers` endpoint response.
- `key` (string): The model key/identifier (e.g., `gpt-4o-mini`, `llama3.1:latest`). Use the `key` value from the provider's `chatModels` array, not the display name.
- **`embeddingModel`** (object, optional): Defines the embedding model for similarity-based searching. To get available providers and models, send a GET request to `http://localhost:3000/api/providers`.
- **`embeddingModel`** (object, required): Defines the embedding model for similarity-based searching. To get available providers and models, send a GET request to `http://localhost:3000/api/providers`.
- `providerId` (string): The UUID of the embedding provider. You can get this from the `/api/providers` endpoint response.
- `key` (string): The embedding model key (e.g., `text-embedding-3-large`, `nomic-embed-text`). Use the `key` value from the provider's `embeddingModels` array, not the display name.
- **`focusMode`** (string, required): Specifies which focus mode to use. Available modes:
- **`sources`** (array, required): Which search sources to enable. Available values:
- `webSearch`, `academicSearch`, `writingAssistant`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.
- `web`, `academic`, `discussions`.
- **`optimizationMode`** (string, optional): Specifies the optimization mode to control the balance between performance and quality. Available modes:
- `speed`: Prioritize speed and return the fastest answer.
- `balanced`: Provide a balanced answer with good speed and reasonable quality.
- `quality`: Prioritize answer quality (may be slower).
- **`query`** (string, required): The search query or question.
@@ -132,14 +133,14 @@ The response from the API includes both the final message and the sources used t
"message": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online. Here are some key features and characteristics of Perplexica:\n\n- **AI-Powered Technology**: It utilizes advanced machine learning algorithms to not only retrieve information but also to understand the context and intent behind user queries, providing more relevant results [1][5].\n\n- **Open-Source**: Being open-source, Perplexica offers flexibility and transparency, allowing users to explore its functionalities without the constraints of proprietary software [3][10].",
"sources": [
{
"pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
"content": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
"metadata": {
"title": "What is Perplexica, and how does it function as an AI-powered search ...",
"url": "https://askai.glarity.app/search/What-is-Perplexica--and-how-does-it-function-as-an-AI-powered-search-engine"
}
},
{
"pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
"content": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
"metadata": {
"title": "Sahar Mor's Post",
"url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
@@ -158,7 +159,7 @@ Example of streamed response objects:
```
{"type":"init","data":"Stream connected"}
{"type":"sources","data":[{"pageContent":"...","metadata":{"title":"...","url":"..."}},...]}
{"type":"sources","data":[{"content":"...","metadata":{"title":"...","url":"..."}},...]}
{"type":"response","data":"Perplexica is an "}
{"type":"response","data":"innovative, open-source "}
{"type":"response","data":"AI-powered search engine..."}
@@ -174,9 +175,9 @@ Clients should process each line as a separate JSON object. The different messag
### Fields in the Response
- **`message`** (string): The search result, generated based on the query and focus mode.
- **`message`** (string): The search result, generated based on the query and enabled `sources`.
- **`sources`** (array): A list of sources that were used to generate the search result. Each source includes:
- `pageContent`: A snippet of the relevant content from the source.
- `content`: A snippet of the relevant content from the source.
- `metadata`: Metadata about the source, including:
- `title`: The title of the webpage.
- `url`: The URL of the webpage.
@@ -185,5 +186,5 @@ Clients should process each line as a separate JSON object. The different messag
If an error occurs during the search process, the API will return an appropriate error message with an HTTP status code.
- **400**: If the request is malformed or missing required fields (e.g., no focus mode or query).
- **400**: If the request is malformed or missing required fields (e.g., no `sources` or `query`).
- **500**: If an internal server error occurs during the search.

149
src/app/api/search/route.ts
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@@ -1,12 +1,13 @@
import ModelRegistry from '@/lib/models/registry';
import { ModelWithProvider } from '@/lib/models/types';
import SessionManager from '@/lib/session';
import SearchAgent from '@/lib/agents/search';
import { ChatTurnMessage } from '@/lib/types';
import { SearchSources } from '@/lib/agents/search/types';
import APISearchAgent from '@/lib/agents/search/api';
interface ChatRequestBody {
optimizationMode: 'speed' | 'balanced';
focusMode: string;
optimizationMode: 'speed' | 'balanced' | 'quality';
sources: SearchSources[];
chatModel: ModelWithProvider;
embeddingModel: ModelWithProvider;
query: string;
@@ -19,15 +20,15 @@ export const POST = async (req: Request) => {
try {
const body: ChatRequestBody = await req.json();
if (!body.focusMode || !body.query) {
if (!body.sources || !body.query) {
return Response.json(
{ message: 'Missing focus mode or query' },
{ message: 'Missing sources or query' },
{ status: 400 },
);
}
body.history = body.history || [];
body.optimizationMode = body.optimizationMode || 'balanced';
body.optimizationMode = body.optimizationMode || 'speed';
body.stream = body.stream || false;
const registry = new ModelRegistry();
@@ -48,18 +49,21 @@ export const POST = async (req: Request) => {
const session = SessionManager.createSession();
const agent = new SearchAgent();
const agent = new APISearchAgent();
agent.searchAsync(session, {
chatHistory: history,
config: {
embedding: embeddings,
llm: llm,
sources: ['web', 'discussions', 'academic'],
mode: 'balanced',
sources: body.sources,
mode: body.optimizationMode,
fileIds: [],
systemInstructions: body.systemInstructions || '',
},
followUp: body.query,
chatId: crypto.randomUUID(),
messageId: crypto.randomUUID(),
});
if (!body.stream) {
@@ -71,36 +75,37 @@ export const POST = async (req: Request) => {
let message = '';
let sources: any[] = [];
session.addListener('data', (data: string) => {
try {
const parsedData = JSON.parse(data);
if (parsedData.type === 'response') {
message += parsedData.data;
} else if (parsedData.type === 'sources') {
sources = parsedData.data;
session.subscribe((event: string, data: Record<string, any>) => {
if (event === 'data') {
try {
if (data.type === 'response') {
message += data.data;
} else if (data.type === 'searchResults') {
sources = data.data;
}
} catch (error) {
reject(
Response.json(
{ message: 'Error parsing data' },
{ status: 500 },
),
);
}
} catch (error) {
}
if (event === 'end') {
resolve(Response.json({ message, sources }, { status: 200 }));
}
if (event === 'error') {
reject(
Response.json(
{ message: 'Error parsing data' },
{ message: 'Search error', error: data },
{ status: 500 },
),
);
}
});
session.addListener('end', () => {
resolve(Response.json({ message, sources }, { status: 200 }));
});
session.addListener('error', (error: any) => {
reject(
Response.json(
{ message: 'Search error', error },
{ status: 500 },
),
);
});
},
);
}
@@ -131,54 +136,54 @@ export const POST = async (req: Request) => {
} catch (error) {}
});
session.addListener('data', (data: string) => {
if (signal.aborted) return;
session.subscribe((event: string, data: Record<string, any>) => {
if (event === 'data') {
if (signal.aborted) return;
try {
const parsedData = JSON.parse(data);
if (parsedData.type === 'response') {
controller.enqueue(
encoder.encode(
JSON.stringify({
type: 'response',
data: parsedData.data,
}) + '\n',
),
);
} else if (parsedData.type === 'sources') {
sources = parsedData.data;
controller.enqueue(
encoder.encode(
JSON.stringify({
type: 'sources',
data: sources,
}) + '\n',
),
);
try {
if (data.type === 'response') {
controller.enqueue(
encoder.encode(
JSON.stringify({
type: 'response',
data: data.data,
}) + '\n',
),
);
} else if (data.type === 'searchResults') {
sources = data.data;
controller.enqueue(
encoder.encode(
JSON.stringify({
type: 'sources',
data: sources,
}) + '\n',
),
);
}
} catch (error) {
controller.error(error);
}
} catch (error) {
controller.error(error);
}
});
session.addListener('end', () => {
if (signal.aborted) return;
if (event === 'end') {
if (signal.aborted) return;
controller.enqueue(
encoder.encode(
JSON.stringify({
type: 'done',
}) + '\n',
),
);
controller.close();
});
controller.enqueue(
encoder.encode(
JSON.stringify({
type: 'done',
}) + '\n',
),
);
controller.close();
}
session.addListener('error', (error: any) => {
if (signal.aborted) return;
if (event === 'error') {
if (signal.aborted) return;
controller.error(error);
controller.error(data);
}
});
},
cancel() {