Merge branch 'ItzCrazyKns:master' into gluetun
This commit is contained in:
bigsk1
GitHub
commit
be3bb569dc
54 changed files with 2025 additions and 2808 deletions
1
.github/FUNDING.yml
vendored
1
.github/FUNDING.yml
vendored
|
|
@ -1 +0,0 @@
|
|||
patreon: itzcrazykns
|
||||
73
.github/workflows/docker-build.yaml
vendored
Normal file
73
.github/workflows/docker-build.yaml
vendored
Normal file
|
|
@ -0,0 +1,73 @@
|
|||
name: Build & Push Docker Images
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- master
|
||||
release:
|
||||
types: [published]
|
||||
|
||||
jobs:
|
||||
build-and-push:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
service: [backend, app]
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v3
|
||||
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v2
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v2
|
||||
with:
|
||||
install: true
|
||||
|
||||
- name: Log in to DockerHub
|
||||
uses: docker/login-action@v2
|
||||
with:
|
||||
username: ${{ secrets.DOCKER_USERNAME }}
|
||||
password: ${{ secrets.DOCKER_PASSWORD }}
|
||||
|
||||
- name: Extract version from release tag
|
||||
if: github.event_name == 'release'
|
||||
id: version
|
||||
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/tags/}" >> $GITHUB_ENV
|
||||
|
||||
- name: Build and push Docker image for ${{ matrix.service }}
|
||||
if: github.ref == 'refs/heads/master' && github.event_name == 'push'
|
||||
run: |
|
||||
docker buildx create --use
|
||||
if [[ "${{ matrix.service }}" == "backend" ]]; then \
|
||||
DOCKERFILE=backend.dockerfile; \
|
||||
IMAGE_NAME=perplexica-backend; \
|
||||
else \
|
||||
DOCKERFILE=app.dockerfile; \
|
||||
IMAGE_NAME=perplexica-frontend; \
|
||||
fi
|
||||
docker buildx build --platform linux/amd64,linux/arm64 \
|
||||
--cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:main \
|
||||
--cache-to=type=inline \
|
||||
-f $DOCKERFILE \
|
||||
-t itzcrazykns1337/${IMAGE_NAME}:main \
|
||||
--push .
|
||||
|
||||
- name: Build and push release Docker image for ${{ matrix.service }}
|
||||
if: github.event_name == 'release'
|
||||
run: |
|
||||
docker buildx create --use
|
||||
if [[ "${{ matrix.service }}" == "backend" ]]; then \
|
||||
DOCKERFILE=backend.dockerfile; \
|
||||
IMAGE_NAME=perplexica-backend; \
|
||||
else \
|
||||
DOCKERFILE=app.dockerfile; \
|
||||
IMAGE_NAME=perplexica-frontend; \
|
||||
fi
|
||||
docker buildx build --platform linux/amd64,linux/arm64 \
|
||||
--cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }} \
|
||||
--cache-to=type=inline \
|
||||
-f $DOCKERFILE \
|
||||
-t itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }} \
|
||||
--push .
|
||||
1
.gitignore
vendored
1
.gitignore
vendored
|
|
@ -36,3 +36,4 @@ Thumbs.db
|
|||
|
||||
# Db
|
||||
db.sqlite
|
||||
/searxng
|
||||
|
|
|
|||
22
README.md
22
README.md
|
|
@ -12,6 +12,8 @@
|
|||
- [Non-Docker Installation](#non-docker-installation)
|
||||
- [Ollama Connection Errors](#ollama-connection-errors)
|
||||
- [Using as a Search Engine](#using-as-a-search-engine)
|
||||
- [Using Perplexica's API](#using-perplexicas-api)
|
||||
- [Expose Perplexica to a network](#expose-perplexica-to-network)
|
||||
- [One-Click Deployment](#one-click-deployment)
|
||||
- [Upcoming Features](#upcoming-features)
|
||||
- [Support Us](#support-us)
|
||||
|
|
@ -45,6 +47,7 @@ Want to know more about its architecture and how it works? You can read it [here
|
|||
- **Wolfram Alpha Search Mode:** Answers queries that need calculations or data analysis using Wolfram Alpha.
|
||||
- **Reddit Search Mode:** Searches Reddit for discussions and opinions related to the query.
|
||||
- **Current Information:** Some search tools might give you outdated info because they use data from crawling bots and convert them into embeddings and store them in a index. Unlike them, Perplexica uses SearxNG, a metasearch engine to get the results and rerank and get the most relevant source out of it, ensuring you always get the latest information without the overhead of daily data updates.
|
||||
- **API**: Integrate Perplexica into your existing applications and make use of its capibilities.
|
||||
|
||||
It has many more features like image and video search. Some of the planned features are mentioned in [upcoming features](#upcoming-features).
|
||||
|
||||
|
|
@ -125,6 +128,16 @@ If you wish to use Perplexica as an alternative to traditional search engines li
|
|||
3. Add a new site search with the following URL: `http://localhost:3000/?q=%s`. Replace `localhost` with your IP address or domain name, and `3000` with the port number if Perplexica is not hosted locally.
|
||||
4. Click the add button. Now, you can use Perplexica directly from your browser's search bar.
|
||||
|
||||
## Using Perplexica's API
|
||||
|
||||
Perplexica also provides an API for developers looking to integrate its powerful search engine into their own applications. You can run searches, use multiple models and get answers to your queries.
|
||||
|
||||
For more details, check out the full documentation [here](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/API/SEARCH.md).
|
||||
|
||||
## Expose Perplexica to network
|
||||
|
||||
You can access Perplexica over your home network by following our networking guide [here](https://github.com/ItzCrazyKns/Perplexica/blob/master/docs/installation/NETWORKING.md).
|
||||
|
||||
## One-Click Deployment
|
||||
|
||||
[](https://repocloud.io/details/?app_id=267)
|
||||
|
|
@ -135,8 +148,9 @@ If you wish to use Perplexica as an alternative to traditional search engines li
|
|||
- [x] Adding support for local LLMs
|
||||
- [x] History Saving features
|
||||
- [x] Introducing various Focus Modes
|
||||
- [x] Adding API support
|
||||
- [x] Adding Discover
|
||||
- [ ] Finalizing Copilot Mode
|
||||
- [ ] Adding Discover
|
||||
|
||||
## Support Us
|
||||
|
||||
|
|
@ -146,9 +160,9 @@ If you find Perplexica useful, consider giving us a star on GitHub. This helps m
|
|||
|
||||
We also accept donations to help sustain our project. If you would like to contribute, you can use the following options to donate. Thank you for your support!
|
||||
|
||||
| Cards | Ethereum |
|
||||
| ----------------------------------- | ----------------------------------------------------- |
|
||||
| https://www.patreon.com/itzcrazykns | Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD` |
|
||||
| Ethereum |
|
||||
| ----------------------------------------------------- |
|
||||
| Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD` |
|
||||
|
||||
## Contribution
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
FROM node:alpine
|
||||
|
||||
ARG NEXT_PUBLIC_WS_URL
|
||||
ARG NEXT_PUBLIC_API_URL
|
||||
ARG NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
|
||||
ARG NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
|
||||
ENV NEXT_PUBLIC_WS_URL=${NEXT_PUBLIC_WS_URL}
|
||||
ENV NEXT_PUBLIC_API_URL=${NEXT_PUBLIC_API_URL}
|
||||
|
||||
|
|
@ -9,7 +9,7 @@ WORKDIR /home/perplexica
|
|||
|
||||
COPY ui /home/perplexica/
|
||||
|
||||
RUN yarn install
|
||||
RUN yarn install --frozen-lockfile
|
||||
RUN yarn build
|
||||
|
||||
CMD ["yarn", "start"]
|
||||
|
|
@ -1,21 +1,16 @@
|
|||
FROM node:slim
|
||||
|
||||
ARG SEARXNG_API_URL
|
||||
FROM node:18-slim
|
||||
|
||||
WORKDIR /home/perplexica
|
||||
|
||||
COPY src /home/perplexica/src
|
||||
COPY tsconfig.json /home/perplexica/
|
||||
COPY config.toml /home/perplexica/
|
||||
COPY drizzle.config.ts /home/perplexica/
|
||||
COPY package.json /home/perplexica/
|
||||
COPY yarn.lock /home/perplexica/
|
||||
|
||||
RUN sed -i "s|SEARXNG = \".*\"|SEARXNG = \"${SEARXNG_API_URL}\"|g" /home/perplexica/config.toml
|
||||
|
||||
RUN mkdir /home/perplexica/data
|
||||
|
||||
RUN yarn install
|
||||
RUN yarn install --frozen-lockfile --network-timeout 600000
|
||||
RUN yarn build
|
||||
|
||||
CMD ["yarn", "start"]
|
||||
|
|
@ -13,14 +13,16 @@ services:
|
|||
build:
|
||||
context: .
|
||||
dockerfile: backend.dockerfile
|
||||
args:
|
||||
- SEARXNG_API_URL=http://searxng:8080
|
||||
image: itzcrazykns1337/perplexica-backend:main
|
||||
environment:
|
||||
- SEARXNG_API_URL=http://searxng:8080
|
||||
depends_on:
|
||||
- searxng
|
||||
ports:
|
||||
- 3001:3001
|
||||
volumes:
|
||||
- backend-dbstore:/home/perplexica/data
|
||||
- ./config.toml:/home/perplexica/config.toml
|
||||
extra_hosts:
|
||||
- 'host.docker.internal:host-gateway'
|
||||
networks:
|
||||
|
|
@ -34,6 +36,7 @@ services:
|
|||
args:
|
||||
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
|
||||
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
|
||||
image: itzcrazykns1337/perplexica-frontend:main
|
||||
depends_on:
|
||||
- perplexica-backend
|
||||
ports:
|
||||
|
|
|
|||
117
docs/API/SEARCH.md
Normal file
117
docs/API/SEARCH.md
Normal file
|
|
@ -0,0 +1,117 @@
|
|||
# Perplexica Search API Documentation
|
||||
|
||||
## Overview
|
||||
|
||||
Perplexica’s Search API makes it easy to use our AI-powered search engine. You can run different types of searches, pick the models you want to use, and get the most recent info. Follow the following headings to learn more about Perplexica's search API.
|
||||
|
||||
## Endpoint
|
||||
|
||||
### **POST** `http://localhost:3001/api/search`
|
||||
|
||||
**Note**: Replace `3001` with any other port if you've changed the default PORT
|
||||
|
||||
### Request
|
||||
|
||||
The API accepts a JSON object in the request body, where you define the focus mode, chat models, embedding models, and your query.
|
||||
|
||||
#### Request Body Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"chatModel": {
|
||||
"provider": "openai",
|
||||
"model": "gpt-4o-mini"
|
||||
},
|
||||
"embeddingModel": {
|
||||
"provider": "openai",
|
||||
"model": "text-embedding-3-large"
|
||||
},
|
||||
"optimizationMode": "speed",
|
||||
"focusMode": "webSearch",
|
||||
"query": "What is Perplexica",
|
||||
"history": [
|
||||
["human", "Hi, how are you?"],
|
||||
["assistant", "I am doing well, how can I help you today?"]
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### Request Parameters
|
||||
|
||||
- **`chatModel`** (object, optional): Defines the chat model to be used for the query. For model details you can send a GET request at `http://localhost:3001/api/models`. Make sure to use the key value (For example "gpt-4o-mini" instead of the display name "GPT 4 omni mini").
|
||||
|
||||
- `provider`: Specifies the provider for the chat model (e.g., `openai`, `ollama`).
|
||||
- `model`: The specific model from the chosen provider (e.g., `gpt-4o-mini`).
|
||||
- Optional fields for custom OpenAI configuration:
|
||||
- `customOpenAIBaseURL`: If you’re using a custom OpenAI instance, provide the base URL.
|
||||
- `customOpenAIKey`: The API key for a custom OpenAI instance.
|
||||
|
||||
- **`embeddingModel`** (object, optional): Defines the embedding model for similarity-based searching. For model details you can send a GET request at `http://localhost:3001/api/models`. Make sure to use the key value (For example "text-embedding-3-large" instead of the display name "Text Embedding 3 Large").
|
||||
|
||||
- `provider`: The provider for the embedding model (e.g., `openai`).
|
||||
- `model`: The specific embedding model (e.g., `text-embedding-3-large`).
|
||||
|
||||
- **`focusMode`** (string, required): Specifies which focus mode to use. Available modes:
|
||||
|
||||
- `webSearch`, `academicSearch`, `writingAssistant`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.
|
||||
|
||||
- **`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.
|
||||
|
||||
- **`query`** (string, required): The search query or question.
|
||||
|
||||
- **`history`** (array, optional): An array of message pairs representing the conversation history. Each pair consists of a role (either 'human' or 'assistant') and the message content. This allows the system to use the context of the conversation to refine results. Example:
|
||||
|
||||
```json
|
||||
[
|
||||
["human", "What is Perplexica?"],
|
||||
["assistant", "Perplexica is an AI-powered search engine..."]
|
||||
]
|
||||
```
|
||||
|
||||
### Response
|
||||
|
||||
The response from the API includes both the final message and the sources used to generate that message.
|
||||
|
||||
#### Example Response
|
||||
|
||||
```json
|
||||
{
|
||||
"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.",
|
||||
"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.",
|
||||
"metadata": {
|
||||
"title": "Sahar Mor's Post",
|
||||
"url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
|
||||
}
|
||||
}
|
||||
....
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### Fields in the Response
|
||||
|
||||
- **`message`** (string): The search result, generated based on the query and focus mode.
|
||||
- **`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.
|
||||
- `metadata`: Metadata about the source, including:
|
||||
- `title`: The title of the webpage.
|
||||
- `url`: The URL of the webpage.
|
||||
|
||||
### Error Handling
|
||||
|
||||
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).
|
||||
- **500**: If an internal server error occurs during the search.
|
||||
|
|
@ -10,14 +10,21 @@ To update Perplexica to the latest version, follow these steps:
|
|||
git clone https://github.com/ItzCrazyKns/Perplexica.git
|
||||
```
|
||||
|
||||
2. Navigate to the Project Directory
|
||||
2. Navigate to the Project Directory.
|
||||
|
||||
3. Update and Rebuild Docker Containers:
|
||||
3. Pull latest images from registry.
|
||||
|
||||
```bash
|
||||
docker compose up -d --build
|
||||
docker compose pull
|
||||
```
|
||||
4. Once the command completes running go to http://localhost:3000 and verify the latest changes.
|
||||
|
||||
4. Update and Recreate containers.
|
||||
|
||||
```bash
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
5. Once the command completes running go to http://localhost:3000 and verify the latest changes.
|
||||
|
||||
## For non Docker users
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "perplexica-backend",
|
||||
"version": "1.8.0",
|
||||
"version": "1.9.1",
|
||||
"license": "MIT",
|
||||
"author": "ItzCrazyKns",
|
||||
"scripts": {
|
||||
|
|
@ -15,7 +15,10 @@
|
|||
"@types/better-sqlite3": "^7.6.10",
|
||||
"@types/cors": "^2.8.17",
|
||||
"@types/express": "^4.17.21",
|
||||
"@types/html-to-text": "^9.0.4",
|
||||
"@types/pdf-parse": "^1.1.4",
|
||||
"@types/readable-stream": "^4.0.11",
|
||||
"@types/ws": "^8.5.12",
|
||||
"drizzle-kit": "^0.22.7",
|
||||
"nodemon": "^3.1.0",
|
||||
"prettier": "^3.2.5",
|
||||
|
|
@ -36,7 +39,9 @@
|
|||
"dotenv": "^16.4.5",
|
||||
"drizzle-orm": "^0.31.2",
|
||||
"express": "^4.19.2",
|
||||
"html-to-text": "^9.0.5",
|
||||
"langchain": "^0.1.30",
|
||||
"pdf-parse": "^1.1.1",
|
||||
"winston": "^3.13.0",
|
||||
"ws": "^8.17.1",
|
||||
"zod": "^3.22.4"
|
||||
|
|
|
|||
2345
searxng/settings.yml
2345
searxng/settings.yml
File diff suppressed because it is too large
Load diff
|
|
@ -19,6 +19,7 @@ import formatChatHistoryAsString from '../utils/formatHistory';
|
|||
import eventEmitter from 'events';
|
||||
import computeSimilarity from '../utils/computeSimilarity';
|
||||
import logger from '../utils/logger';
|
||||
import { IterableReadableStream } from '@langchain/core/utils/stream';
|
||||
|
||||
const basicAcademicSearchRetrieverPrompt = `
|
||||
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
|
||||
|
|
@ -66,7 +67,7 @@ const basicAcademicSearchResponsePrompt = `
|
|||
const strParser = new StringOutputParser();
|
||||
|
||||
const handleStream = async (
|
||||
stream: AsyncGenerator<StreamEvent, any, unknown>,
|
||||
stream: IterableReadableStream<StreamEvent>,
|
||||
emitter: eventEmitter,
|
||||
) => {
|
||||
for await (const event of stream) {
|
||||
|
|
@ -114,12 +115,7 @@ const createBasicAcademicSearchRetrieverChain = (llm: BaseChatModel) => {
|
|||
|
||||
const res = await searchSearxng(input, {
|
||||
language: 'en',
|
||||
engines: [
|
||||
'arxiv',
|
||||
'google scholar',
|
||||
'internetarchivescholar',
|
||||
'pubmed',
|
||||
],
|
||||
engines: ['arxiv', 'google scholar', 'pubmed'],
|
||||
});
|
||||
|
||||
const documents = res.results.map(
|
||||
|
|
@ -142,6 +138,7 @@ const createBasicAcademicSearchRetrieverChain = (llm: BaseChatModel) => {
|
|||
const createBasicAcademicSearchAnsweringChain = (
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const basicAcademicSearchRetrieverChain =
|
||||
createBasicAcademicSearchRetrieverChain(llm);
|
||||
|
|
@ -167,26 +164,32 @@ const createBasicAcademicSearchAnsweringChain = (
|
|||
(doc) => doc.pageContent && doc.pageContent.length > 0,
|
||||
);
|
||||
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
if (optimizationMode === 'speed') {
|
||||
return docsWithContent.slice(0, 15);
|
||||
} else if (optimizationMode === 'balanced') {
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(
|
||||
docsWithContent.map((doc) => doc.pageContent),
|
||||
),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
|
||||
const sortedDocs = similarity
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.slice(0, 15)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
const sortedDocs = similarity
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.slice(0, 15)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
|
||||
return sortedDocs;
|
||||
return sortedDocs;
|
||||
}
|
||||
};
|
||||
|
||||
return RunnableSequence.from([
|
||||
|
|
@ -223,12 +226,17 @@ const basicAcademicSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = new eventEmitter();
|
||||
|
||||
try {
|
||||
const basicAcademicSearchAnsweringChain =
|
||||
createBasicAcademicSearchAnsweringChain(llm, embeddings);
|
||||
createBasicAcademicSearchAnsweringChain(
|
||||
llm,
|
||||
embeddings,
|
||||
optimizationMode,
|
||||
);
|
||||
|
||||
const stream = basicAcademicSearchAnsweringChain.streamEvents(
|
||||
{
|
||||
|
|
@ -257,8 +265,15 @@ const handleAcademicSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = basicAcademicSearch(message, history, llm, embeddings);
|
||||
const emitter = basicAcademicSearch(
|
||||
message,
|
||||
history,
|
||||
llm,
|
||||
embeddings,
|
||||
optimizationMode,
|
||||
);
|
||||
return emitter;
|
||||
};
|
||||
|
||||
|
|
|
|||
|
|
@ -19,6 +19,7 @@ import formatChatHistoryAsString from '../utils/formatHistory';
|
|||
import eventEmitter from 'events';
|
||||
import computeSimilarity from '../utils/computeSimilarity';
|
||||
import logger from '../utils/logger';
|
||||
import { IterableReadableStream } from '@langchain/core/utils/stream';
|
||||
|
||||
const basicRedditSearchRetrieverPrompt = `
|
||||
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
|
||||
|
|
@ -66,7 +67,7 @@ const basicRedditSearchResponsePrompt = `
|
|||
const strParser = new StringOutputParser();
|
||||
|
||||
const handleStream = async (
|
||||
stream: AsyncGenerator<StreamEvent, any, unknown>,
|
||||
stream: IterableReadableStream<StreamEvent>,
|
||||
emitter: eventEmitter,
|
||||
) => {
|
||||
for await (const event of stream) {
|
||||
|
|
@ -137,6 +138,7 @@ const createBasicRedditSearchRetrieverChain = (llm: BaseChatModel) => {
|
|||
const createBasicRedditSearchAnsweringChain = (
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const basicRedditSearchRetrieverChain =
|
||||
createBasicRedditSearchRetrieverChain(llm);
|
||||
|
|
@ -162,27 +164,33 @@ const createBasicRedditSearchAnsweringChain = (
|
|||
(doc) => doc.pageContent && doc.pageContent.length > 0,
|
||||
);
|
||||
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
if (optimizationMode === 'speed') {
|
||||
return docsWithContent.slice(0, 15);
|
||||
} else if (optimizationMode === 'balanced') {
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(
|
||||
docsWithContent.map((doc) => doc.pageContent),
|
||||
),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
|
||||
const sortedDocs = similarity
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.slice(0, 15)
|
||||
.filter((sim) => sim.similarity > 0.3)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
const sortedDocs = similarity
|
||||
.filter((sim) => sim.similarity > 0.3)
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.slice(0, 15)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
|
||||
return sortedDocs;
|
||||
return sortedDocs;
|
||||
}
|
||||
};
|
||||
|
||||
return RunnableSequence.from([
|
||||
|
|
@ -219,12 +227,13 @@ const basicRedditSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = new eventEmitter();
|
||||
|
||||
try {
|
||||
const basicRedditSearchAnsweringChain =
|
||||
createBasicRedditSearchAnsweringChain(llm, embeddings);
|
||||
createBasicRedditSearchAnsweringChain(llm, embeddings, optimizationMode);
|
||||
const stream = basicRedditSearchAnsweringChain.streamEvents(
|
||||
{
|
||||
chat_history: history,
|
||||
|
|
@ -252,8 +261,15 @@ const handleRedditSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = basicRedditSearch(message, history, llm, embeddings);
|
||||
const emitter = basicRedditSearch(
|
||||
message,
|
||||
history,
|
||||
llm,
|
||||
embeddings,
|
||||
optimizationMode,
|
||||
);
|
||||
return emitter;
|
||||
};
|
||||
|
||||
|
|
|
|||
|
|
@ -19,34 +19,83 @@ import formatChatHistoryAsString from '../utils/formatHistory';
|
|||
import eventEmitter from 'events';
|
||||
import computeSimilarity from '../utils/computeSimilarity';
|
||||
import logger from '../utils/logger';
|
||||
import LineListOutputParser from '../lib/outputParsers/listLineOutputParser';
|
||||
import { getDocumentsFromLinks } from '../lib/linkDocument';
|
||||
import LineOutputParser from '../lib/outputParsers/lineOutputParser';
|
||||
import { IterableReadableStream } from '@langchain/core/utils/stream';
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
|
||||
const basicSearchRetrieverPrompt = `
|
||||
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
|
||||
If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
|
||||
You are an AI question rephraser. You will be given a conversation and a follow-up question, you will have to rephrase the follow up question so it is a standalone question and can be used by another LLM to search the web for information to answer it.
|
||||
If it is a smple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
|
||||
If the user asks some question from some URL or wants you to summarize a PDF or a webpage (via URL) you need to return the links inside the \`links\` XML block and the question inside the \`question\` XML block. If the user wants to you to summarize the webpage or the PDF you need to return \`summarize\` inside the \`question\` XML block in place of a question and the link to summarize in the \`links\` XML block.
|
||||
You must always return the rephrased question inside the \`question\` XML block, if there are no links in the follow-up question then don't insert a \`links\` XML block in your response.
|
||||
|
||||
Example:
|
||||
1. Follow up question: What is the capital of France?
|
||||
Rephrased: Capital of france
|
||||
There are several examples attached for your reference inside the below \`examples\` XML block
|
||||
|
||||
2. Follow up question: What is the population of New York City?
|
||||
Rephrased: Population of New York City
|
||||
<examples>
|
||||
1. Follow up question: What is the capital of France
|
||||
Rephrased question:\`
|
||||
<question>
|
||||
Capital of france
|
||||
</question>
|
||||
\`
|
||||
|
||||
2. Hi, how are you?
|
||||
Rephrased question\`
|
||||
<question>
|
||||
not_needed
|
||||
</question>
|
||||
\`
|
||||
|
||||
3. Follow up question: What is Docker?
|
||||
Rephrased: What is Docker
|
||||
Rephrased question: \`
|
||||
<question>
|
||||
What is Docker
|
||||
</question>
|
||||
\`
|
||||
|
||||
Conversation:
|
||||
4. Follow up question: Can you tell me what is X from https://example.com
|
||||
Rephrased question: \`
|
||||
<question>
|
||||
Can you tell me what is X?
|
||||
</question>
|
||||
|
||||
<links>
|
||||
https://example.com
|
||||
</links>
|
||||
\`
|
||||
|
||||
5. Follow up question: Summarize the content from https://example.com
|
||||
Rephrased question: \`
|
||||
<question>
|
||||
summarize
|
||||
</question>
|
||||
|
||||
<links>
|
||||
https://example.com
|
||||
</links>
|
||||
\`
|
||||
</examples>
|
||||
|
||||
Anything below is the part of the actual conversation and you need to use conversation and the follow-up question to rephrase the follow-up question as a standalone question based on the guidelines shared above.
|
||||
|
||||
<conversation>
|
||||
{chat_history}
|
||||
</conversation>
|
||||
|
||||
Follow up question: {query}
|
||||
Rephrased question:
|
||||
`;
|
||||
|
||||
const basicWebSearchResponsePrompt = `
|
||||
You are Perplexica, an AI model who is expert at searching the web and answering user's queries.
|
||||
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are also an expert at summarizing web pages or documents and searching for content in them.
|
||||
|
||||
Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
|
||||
You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
|
||||
You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
|
||||
If the query contains some links and the user asks to answer from those links you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to answer the user's query.
|
||||
If the user asks to summarize content from some links, you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to summarize the text. The content provided inside the \`context\` block will be already summarized by another model so you just need to use that content to answer the user's query.
|
||||
Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
|
||||
You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
|
||||
Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
|
||||
|
|
@ -59,14 +108,14 @@ const basicWebSearchResponsePrompt = `
|
|||
{context}
|
||||
</context>
|
||||
|
||||
If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
|
||||
If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'. You do not need to do this for summarization tasks.
|
||||
Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
|
||||
`;
|
||||
|
||||
const strParser = new StringOutputParser();
|
||||
|
||||
const handleStream = async (
|
||||
stream: AsyncGenerator<StreamEvent, any, unknown>,
|
||||
stream: IterableReadableStream<StreamEvent>,
|
||||
emitter: eventEmitter,
|
||||
) => {
|
||||
for await (const event of stream) {
|
||||
|
|
@ -103,32 +152,162 @@ type BasicChainInput = {
|
|||
};
|
||||
|
||||
const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => {
|
||||
(llm as unknown as ChatOpenAI).temperature = 0;
|
||||
|
||||
return RunnableSequence.from([
|
||||
PromptTemplate.fromTemplate(basicSearchRetrieverPrompt),
|
||||
llm,
|
||||
strParser,
|
||||
RunnableLambda.from(async (input: string) => {
|
||||
if (input === 'not_needed') {
|
||||
const linksOutputParser = new LineListOutputParser({
|
||||
key: 'links',
|
||||
});
|
||||
|
||||
const questionOutputParser = new LineOutputParser({
|
||||
key: 'question',
|
||||
});
|
||||
|
||||
const links = await linksOutputParser.parse(input);
|
||||
let question = await questionOutputParser.parse(input);
|
||||
|
||||
if (question === 'not_needed') {
|
||||
return { query: '', docs: [] };
|
||||
}
|
||||
|
||||
const res = await searchSearxng(input, {
|
||||
language: 'en',
|
||||
});
|
||||
if (links.length > 0) {
|
||||
if (question.length === 0) {
|
||||
question = 'summarize';
|
||||
}
|
||||
|
||||
const documents = res.results.map(
|
||||
(result) =>
|
||||
new Document({
|
||||
pageContent: result.content,
|
||||
metadata: {
|
||||
title: result.title,
|
||||
url: result.url,
|
||||
...(result.img_src && { img_src: result.img_src }),
|
||||
},
|
||||
let docs = [];
|
||||
|
||||
const linkDocs = await getDocumentsFromLinks({ links });
|
||||
|
||||
const docGroups: Document[] = [];
|
||||
|
||||
linkDocs.map((doc) => {
|
||||
const URLDocExists = docGroups.find(
|
||||
(d) =>
|
||||
d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
|
||||
);
|
||||
|
||||
if (!URLDocExists) {
|
||||
docGroups.push({
|
||||
...doc,
|
||||
metadata: {
|
||||
...doc.metadata,
|
||||
totalDocs: 1,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
const docIndex = docGroups.findIndex(
|
||||
(d) =>
|
||||
d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
|
||||
);
|
||||
|
||||
if (docIndex !== -1) {
|
||||
docGroups[docIndex].pageContent =
|
||||
docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
|
||||
docGroups[docIndex].metadata.totalDocs += 1;
|
||||
}
|
||||
});
|
||||
|
||||
await Promise.all(
|
||||
docGroups.map(async (doc) => {
|
||||
const res = await llm.invoke(`
|
||||
You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the
|
||||
text into a detailed, 2-4 paragraph explanation that captures the main ideas and provides a comprehensive answer to the query.
|
||||
If the query is \"summarize\", you should provide a detailed summary of the text. If the query is a specific question, you should answer it in the summary.
|
||||
|
||||
- **Journalistic tone**: The summary should sound professional and journalistic, not too casual or vague.
|
||||
- **Thorough and detailed**: Ensure that every key point from the text is captured and that the summary directly answers the query.
|
||||
- **Not too lengthy, but detailed**: The summary should be informative but not excessively long. Focus on providing detailed information in a concise format.
|
||||
|
||||
The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
|
||||
|
||||
<example>
|
||||
1. \`<text>
|
||||
Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers.
|
||||
It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications
|
||||
by using containers.
|
||||
</text>
|
||||
|
||||
<query>
|
||||
What is Docker and how does it work?
|
||||
</query>
|
||||
|
||||
Response:
|
||||
Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application
|
||||
deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in
|
||||
any environment. Released in 2013, Docker has transformed the way applications are built, deployed, and managed.
|
||||
\`
|
||||
2. \`<text>
|
||||
The theory of relativity, or simply relativity, encompasses two interrelated theories of Albert Einstein: special relativity and general
|
||||
relativity. However, the word "relativity" is sometimes used in reference to Galilean invariance. The term "theory of relativity" was based
|
||||
on the expression "relative theory" used by Max Planck in 1906. The theory of relativity usually encompasses two interrelated theories by
|
||||
Albert Einstein: special relativity and general relativity. Special relativity applies to all physical phenomena in the absence of gravity.
|
||||
General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical
|
||||
realm, including astronomy.
|
||||
</text>
|
||||
|
||||
<query>
|
||||
summarize
|
||||
</query>
|
||||
|
||||
Response:
|
||||
The theory of relativity, developed by Albert Einstein, encompasses two main theories: special relativity and general relativity. Special
|
||||
relativity applies to all physical phenomena in the absence of gravity, while general relativity explains the law of gravitation and its
|
||||
relation to other forces of nature. The theory of relativity is based on the concept of "relative theory," as introduced by Max Planck in
|
||||
1906. It is a fundamental theory in physics that has revolutionized our understanding of the universe.
|
||||
\`
|
||||
</example>
|
||||
|
||||
Everything below is the actual data you will be working with. Good luck!
|
||||
|
||||
<query>
|
||||
${question}
|
||||
</query>
|
||||
|
||||
<text>
|
||||
${doc.pageContent}
|
||||
</text>
|
||||
|
||||
Make sure to answer the query in the summary.
|
||||
`);
|
||||
|
||||
const document = new Document({
|
||||
pageContent: res.content as string,
|
||||
metadata: {
|
||||
title: doc.metadata.title,
|
||||
url: doc.metadata.url,
|
||||
},
|
||||
});
|
||||
|
||||
docs.push(document);
|
||||
}),
|
||||
);
|
||||
);
|
||||
|
||||
return { query: input, docs: documents };
|
||||
return { query: question, docs: docs };
|
||||
} else {
|
||||
const res = await searchSearxng(question, {
|
||||
language: 'en',
|
||||
});
|
||||
|
||||
const documents = res.results.map(
|
||||
(result) =>
|
||||
new Document({
|
||||
pageContent: result.content,
|
||||
metadata: {
|
||||
title: result.title,
|
||||
url: result.url,
|
||||
...(result.img_src && { img_src: result.img_src }),
|
||||
},
|
||||
}),
|
||||
);
|
||||
|
||||
return { query: question, docs: documents };
|
||||
}
|
||||
}),
|
||||
]);
|
||||
};
|
||||
|
|
@ -136,6 +315,7 @@ const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => {
|
|||
const createBasicWebSearchAnsweringChain = (
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const basicWebSearchRetrieverChain = createBasicWebSearchRetrieverChain(llm);
|
||||
|
||||
|
|
@ -156,31 +336,41 @@ const createBasicWebSearchAnsweringChain = (
|
|||
return docs;
|
||||
}
|
||||
|
||||
if (query.toLocaleLowerCase() === 'summarize') {
|
||||
return docs;
|
||||
}
|
||||
|
||||
const docsWithContent = docs.filter(
|
||||
(doc) => doc.pageContent && doc.pageContent.length > 0,
|
||||
);
|
||||
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
if (optimizationMode === 'speed') {
|
||||
return docsWithContent.slice(0, 15);
|
||||
} else if (optimizationMode === 'balanced') {
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(
|
||||
docsWithContent.map((doc) => doc.pageContent),
|
||||
),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
|
||||
const sortedDocs = similarity
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.filter((sim) => sim.similarity > 0.5)
|
||||
.slice(0, 15)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
const sortedDocs = similarity
|
||||
.filter((sim) => sim.similarity > 0.3)
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.slice(0, 15)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
|
||||
return sortedDocs;
|
||||
return sortedDocs;
|
||||
}
|
||||
};
|
||||
|
||||
return RunnableSequence.from([
|
||||
|
|
@ -217,6 +407,7 @@ const basicWebSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = new eventEmitter();
|
||||
|
||||
|
|
@ -224,6 +415,7 @@ const basicWebSearch = (
|
|||
const basicWebSearchAnsweringChain = createBasicWebSearchAnsweringChain(
|
||||
llm,
|
||||
embeddings,
|
||||
optimizationMode,
|
||||
);
|
||||
|
||||
const stream = basicWebSearchAnsweringChain.streamEvents(
|
||||
|
|
@ -253,8 +445,15 @@ const handleWebSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = basicWebSearch(message, history, llm, embeddings);
|
||||
const emitter = basicWebSearch(
|
||||
message,
|
||||
history,
|
||||
llm,
|
||||
embeddings,
|
||||
optimizationMode,
|
||||
);
|
||||
return emitter;
|
||||
};
|
||||
|
||||
|
|
|
|||
|
|
@ -18,6 +18,7 @@ import type { Embeddings } from '@langchain/core/embeddings';
|
|||
import formatChatHistoryAsString from '../utils/formatHistory';
|
||||
import eventEmitter from 'events';
|
||||
import logger from '../utils/logger';
|
||||
import { IterableReadableStream } from '@langchain/core/utils/stream';
|
||||
|
||||
const basicWolframAlphaSearchRetrieverPrompt = `
|
||||
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
|
||||
|
|
@ -65,7 +66,7 @@ const basicWolframAlphaSearchResponsePrompt = `
|
|||
const strParser = new StringOutputParser();
|
||||
|
||||
const handleStream = async (
|
||||
stream: AsyncGenerator<StreamEvent, any, unknown>,
|
||||
stream: IterableReadableStream<StreamEvent>,
|
||||
emitter: eventEmitter,
|
||||
) => {
|
||||
for await (const event of stream) {
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ import eventEmitter from 'events';
|
|||
import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import type { Embeddings } from '@langchain/core/embeddings';
|
||||
import logger from '../utils/logger';
|
||||
import { IterableReadableStream } from '@langchain/core/utils/stream';
|
||||
|
||||
const writingAssistantPrompt = `
|
||||
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query.
|
||||
|
|
@ -19,7 +20,7 @@ Since you are a writing assistant, you would not perform web searches. If you th
|
|||
const strParser = new StringOutputParser();
|
||||
|
||||
const handleStream = async (
|
||||
stream: AsyncGenerator<StreamEvent, any, unknown>,
|
||||
stream: IterableReadableStream<StreamEvent>,
|
||||
emitter: eventEmitter,
|
||||
) => {
|
||||
for await (const event of stream) {
|
||||
|
|
|
|||
|
|
@ -19,6 +19,7 @@ import formatChatHistoryAsString from '../utils/formatHistory';
|
|||
import eventEmitter from 'events';
|
||||
import computeSimilarity from '../utils/computeSimilarity';
|
||||
import logger from '../utils/logger';
|
||||
import { IterableReadableStream } from '@langchain/core/utils/stream';
|
||||
|
||||
const basicYoutubeSearchRetrieverPrompt = `
|
||||
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
|
||||
|
|
@ -66,7 +67,7 @@ const basicYoutubeSearchResponsePrompt = `
|
|||
const strParser = new StringOutputParser();
|
||||
|
||||
const handleStream = async (
|
||||
stream: AsyncGenerator<StreamEvent, any, unknown>,
|
||||
stream: IterableReadableStream<StreamEvent>,
|
||||
emitter: eventEmitter,
|
||||
) => {
|
||||
for await (const event of stream) {
|
||||
|
|
@ -137,6 +138,7 @@ const createBasicYoutubeSearchRetrieverChain = (llm: BaseChatModel) => {
|
|||
const createBasicYoutubeSearchAnsweringChain = (
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const basicYoutubeSearchRetrieverChain =
|
||||
createBasicYoutubeSearchRetrieverChain(llm);
|
||||
|
|
@ -162,27 +164,33 @@ const createBasicYoutubeSearchAnsweringChain = (
|
|||
(doc) => doc.pageContent && doc.pageContent.length > 0,
|
||||
);
|
||||
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
if (optimizationMode === 'speed') {
|
||||
return docsWithContent.slice(0, 15);
|
||||
} else {
|
||||
const [docEmbeddings, queryEmbedding] = await Promise.all([
|
||||
embeddings.embedDocuments(
|
||||
docsWithContent.map((doc) => doc.pageContent),
|
||||
),
|
||||
embeddings.embedQuery(query),
|
||||
]);
|
||||
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
const similarity = docEmbeddings.map((docEmbedding, i) => {
|
||||
const sim = computeSimilarity(queryEmbedding, docEmbedding);
|
||||
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
return {
|
||||
index: i,
|
||||
similarity: sim,
|
||||
};
|
||||
});
|
||||
|
||||
const sortedDocs = similarity
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.slice(0, 15)
|
||||
.filter((sim) => sim.similarity > 0.3)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
const sortedDocs = similarity
|
||||
.filter((sim) => sim.similarity > 0.3)
|
||||
.sort((a, b) => b.similarity - a.similarity)
|
||||
.slice(0, 15)
|
||||
.map((sim) => docsWithContent[sim.index]);
|
||||
|
||||
return sortedDocs;
|
||||
return sortedDocs;
|
||||
}
|
||||
};
|
||||
|
||||
return RunnableSequence.from([
|
||||
|
|
@ -219,12 +227,13 @@ const basicYoutubeSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = new eventEmitter();
|
||||
|
||||
try {
|
||||
const basicYoutubeSearchAnsweringChain =
|
||||
createBasicYoutubeSearchAnsweringChain(llm, embeddings);
|
||||
createBasicYoutubeSearchAnsweringChain(llm, embeddings, optimizationMode);
|
||||
|
||||
const stream = basicYoutubeSearchAnsweringChain.streamEvents(
|
||||
{
|
||||
|
|
@ -253,8 +262,15 @@ const handleYoutubeSearch = (
|
|||
history: BaseMessage[],
|
||||
llm: BaseChatModel,
|
||||
embeddings: Embeddings,
|
||||
optimizationMode: 'speed' | 'balanced' | 'quality',
|
||||
) => {
|
||||
const emitter = basicYoutubeSearch(message, history, llm, embeddings);
|
||||
const emitter = basicYoutubeSearch(
|
||||
message,
|
||||
history,
|
||||
llm,
|
||||
embeddings,
|
||||
optimizationMode,
|
||||
);
|
||||
return emitter;
|
||||
};
|
||||
|
||||
|
|
|
|||
|
|
@ -28,3 +28,11 @@ server.listen(port, () => {
|
|||
});
|
||||
|
||||
startWebSocketServer(server);
|
||||
|
||||
process.on('uncaughtException', (err, origin) => {
|
||||
logger.error(`Uncaught Exception at ${origin}: ${err}`);
|
||||
});
|
||||
|
||||
process.on('unhandledRejection', (reason, promise) => {
|
||||
logger.error(`Unhandled Rejection at: ${promise}, reason: ${reason}`);
|
||||
});
|
||||
|
|
|
|||
|
|
@ -40,7 +40,8 @@ export const getGroqApiKey = () => loadConfig().API_KEYS.GROQ;
|
|||
|
||||
export const getAnthropicApiKey = () => loadConfig().API_KEYS.ANTHROPIC;
|
||||
|
||||
export const getSearxngApiEndpoint = () => loadConfig().API_ENDPOINTS.SEARXNG;
|
||||
export const getSearxngApiEndpoint = () =>
|
||||
process.env.SEARXNG_API_URL || loadConfig().API_ENDPOINTS.SEARXNG;
|
||||
|
||||
export const getOllamaApiEndpoint = () => loadConfig().API_ENDPOINTS.OLLAMA;
|
||||
|
||||
|
|
|
|||
99
src/lib/linkDocument.ts
Normal file
99
src/lib/linkDocument.ts
Normal file
|
|
@ -0,0 +1,99 @@
|
|||
import axios from 'axios';
|
||||
import { htmlToText } from 'html-to-text';
|
||||
import { RecursiveCharacterTextSplitter } from 'langchain/text_splitter';
|
||||
import { Document } from '@langchain/core/documents';
|
||||
import pdfParse from 'pdf-parse';
|
||||
import logger from '../utils/logger';
|
||||
|
||||
export const getDocumentsFromLinks = async ({ links }: { links: string[] }) => {
|
||||
const splitter = new RecursiveCharacterTextSplitter();
|
||||
|
||||
let docs: Document[] = [];
|
||||
|
||||
await Promise.all(
|
||||
links.map(async (link) => {
|
||||
link =
|
||||
link.startsWith('http://') || link.startsWith('https://')
|
||||
? link
|
||||
: `https://${link}`;
|
||||
|
||||
try {
|
||||
const res = await axios.get(link, {
|
||||
responseType: 'arraybuffer',
|
||||
});
|
||||
|
||||
const isPdf = res.headers['content-type'] === 'application/pdf';
|
||||
|
||||
if (isPdf) {
|
||||
const pdfText = await pdfParse(res.data);
|
||||
const parsedText = pdfText.text
|
||||
.replace(/(\r\n|\n|\r)/gm, ' ')
|
||||
.replace(/\s+/g, ' ')
|
||||
.trim();
|
||||
|
||||
const splittedText = await splitter.splitText(parsedText);
|
||||
const title = 'PDF Document';
|
||||
|
||||
const linkDocs = splittedText.map((text) => {
|
||||
return new Document({
|
||||
pageContent: text,
|
||||
metadata: {
|
||||
title: title,
|
||||
url: link,
|
||||
},
|
||||
});
|
||||
});
|
||||
|
||||
docs.push(...linkDocs);
|
||||
return;
|
||||
}
|
||||
|
||||
const parsedText = htmlToText(res.data.toString('utf8'), {
|
||||
selectors: [
|
||||
{
|
||||
selector: 'a',
|
||||
options: {
|
||||
ignoreHref: true,
|
||||
},
|
||||
},
|
||||
],
|
||||
})
|
||||
.replace(/(\r\n|\n|\r)/gm, ' ')
|
||||
.replace(/\s+/g, ' ')
|
||||
.trim();
|
||||
|
||||
const splittedText = await splitter.splitText(parsedText);
|
||||
const title = res.data
|
||||
.toString('utf8')
|
||||
.match(/<title>(.*?)<\/title>/)?.[1];
|
||||
|
||||
const linkDocs = splittedText.map((text) => {
|
||||
return new Document({
|
||||
pageContent: text,
|
||||
metadata: {
|
||||
title: title || link,
|
||||
url: link,
|
||||
},
|
||||
});
|
||||
});
|
||||
|
||||
docs.push(...linkDocs);
|
||||
} catch (err) {
|
||||
logger.error(
|
||||
`Error at generating documents from links: ${err.message}`,
|
||||
);
|
||||
docs.push(
|
||||
new Document({
|
||||
pageContent: `Failed to retrieve content from the link: ${err.message}`,
|
||||
metadata: {
|
||||
title: 'Failed to retrieve content',
|
||||
url: link,
|
||||
},
|
||||
}),
|
||||
);
|
||||
}
|
||||
}),
|
||||
);
|
||||
|
||||
return docs;
|
||||
};
|
||||
46
src/lib/outputParsers/lineOutputParser.ts
Normal file
46
src/lib/outputParsers/lineOutputParser.ts
Normal file
|
|
@ -0,0 +1,46 @@
|
|||
import { BaseOutputParser } from '@langchain/core/output_parsers';
|
||||
|
||||
interface LineOutputParserArgs {
|
||||
key?: string;
|
||||
}
|
||||
|
||||
class LineOutputParser extends BaseOutputParser<string> {
|
||||
private key = 'questions';
|
||||
|
||||
constructor(args?: LineOutputParserArgs) {
|
||||
super();
|
||||
this.key = args.key ?? this.key;
|
||||
}
|
||||
|
||||
static lc_name() {
|
||||
return 'LineOutputParser';
|
||||
}
|
||||
|
||||
lc_namespace = ['langchain', 'output_parsers', 'line_output_parser'];
|
||||
|
||||
async parse(text: string): Promise<string> {
|
||||
const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
|
||||
const startKeyIndex = text.indexOf(`<${this.key}>`);
|
||||
const endKeyIndex = text.indexOf(`</${this.key}>`);
|
||||
|
||||
if (startKeyIndex === -1 || endKeyIndex === -1) {
|
||||
return '';
|
||||
}
|
||||
|
||||
const questionsStartIndex =
|
||||
startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
|
||||
const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;
|
||||
const line = text
|
||||
.slice(questionsStartIndex, questionsEndIndex)
|
||||
.trim()
|
||||
.replace(regex, '');
|
||||
|
||||
return line;
|
||||
}
|
||||
|
||||
getFormatInstructions(): string {
|
||||
throw new Error('Not implemented.');
|
||||
}
|
||||
}
|
||||
|
||||
export default LineOutputParser;
|
||||
|
|
@ -22,6 +22,11 @@ class LineListOutputParser extends BaseOutputParser<string[]> {
|
|||
const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
|
||||
const startKeyIndex = text.indexOf(`<${this.key}>`);
|
||||
const endKeyIndex = text.indexOf(`</${this.key}>`);
|
||||
|
||||
if (startKeyIndex === -1 || endKeyIndex === -1) {
|
||||
return [];
|
||||
}
|
||||
|
||||
const questionsStartIndex =
|
||||
startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
|
||||
const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;
|
||||
|
|
|
|||
|
|
@ -9,26 +9,38 @@ export const loadAnthropicChatModels = async () => {
|
|||
|
||||
try {
|
||||
const chatModels = {
|
||||
'Claude 3.5 Sonnet': new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-5-sonnet-20240620',
|
||||
}),
|
||||
'Claude 3 Opus': new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-opus-20240229',
|
||||
}),
|
||||
'Claude 3 Sonnet': new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-sonnet-20240229',
|
||||
}),
|
||||
'Claude 3 Haiku': new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-haiku-20240307',
|
||||
}),
|
||||
'claude-3-5-sonnet-20240620': {
|
||||
displayName: 'Claude 3.5 Sonnet',
|
||||
model: new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-5-sonnet-20240620',
|
||||
}),
|
||||
},
|
||||
'claude-3-opus-20240229': {
|
||||
displayName: 'Claude 3 Opus',
|
||||
model: new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-opus-20240229',
|
||||
}),
|
||||
},
|
||||
'claude-3-sonnet-20240229': {
|
||||
displayName: 'Claude 3 Sonnet',
|
||||
model: new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-sonnet-20240229',
|
||||
}),
|
||||
},
|
||||
'claude-3-haiku-20240307': {
|
||||
displayName: 'Claude 3 Haiku',
|
||||
model: new ChatAnthropic({
|
||||
temperature: 0.7,
|
||||
anthropicApiKey: anthropicApiKey,
|
||||
model: 'claude-3-haiku-20240307',
|
||||
}),
|
||||
},
|
||||
};
|
||||
|
||||
return chatModels;
|
||||
|
|
|
|||
|
|
@ -9,56 +9,136 @@ export const loadGroqChatModels = async () => {
|
|||
|
||||
try {
|
||||
const chatModels = {
|
||||
'LLaMA3 8b': new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama3-8b-8192',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
'LLaMA3 70b': new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama3-70b-8192',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
'Mixtral 8x7b': new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'mixtral-8x7b-32768',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
'Gemma 7b': new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'gemma-7b-it',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
'Gemma2 9b': new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'gemma2-9b-it',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
'llama-3.2-3b-preview': {
|
||||
displayName: 'Llama 3.2 3B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama-3.2-3b-preview',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'llama-3.2-11b-vision-preview': {
|
||||
displayName: 'Llama 3.2 11B Vision',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama-3.2-11b-vision-preview',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'llama-3.2-90b-vision-preview': {
|
||||
displayName: 'Llama 3.2 90B Vision',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama-3.2-90b-vision-preview',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'llama-3.1-70b-versatile': {
|
||||
displayName: 'Llama 3.1 70B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama-3.1-70b-versatile',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'llama-3.1-8b-instant': {
|
||||
displayName: 'Llama 3.1 8B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama-3.1-8b-instant',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'llama3-8b-8192': {
|
||||
displayName: 'LLaMA3 8B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama3-8b-8192',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'llama3-70b-8192': {
|
||||
displayName: 'LLaMA3 70B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'llama3-70b-8192',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'mixtral-8x7b-32768': {
|
||||
displayName: 'Mixtral 8x7B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'mixtral-8x7b-32768',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'gemma-7b-it': {
|
||||
displayName: 'Gemma 7B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'gemma-7b-it',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
'gemma2-9b-it': {
|
||||
displayName: 'Gemma2 9B',
|
||||
model: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: groqApiKey,
|
||||
modelName: 'gemma2-9b-it',
|
||||
temperature: 0.7,
|
||||
},
|
||||
{
|
||||
baseURL: 'https://api.groq.com/openai/v1',
|
||||
},
|
||||
),
|
||||
},
|
||||
};
|
||||
|
||||
return chatModels;
|
||||
|
|
|
|||
|
|
@ -18,11 +18,15 @@ export const loadOllamaChatModels = async () => {
|
|||
const { models: ollamaModels } = (await response.json()) as any;
|
||||
|
||||
const chatModels = ollamaModels.reduce((acc, model) => {
|
||||
acc[model.model] = new ChatOllama({
|
||||
baseUrl: ollamaEndpoint,
|
||||
model: model.model,
|
||||
temperature: 0.7,
|
||||
});
|
||||
acc[model.model] = {
|
||||
displayName: model.name,
|
||||
model: new ChatOllama({
|
||||
baseUrl: ollamaEndpoint,
|
||||
model: model.model,
|
||||
temperature: 0.7,
|
||||
}),
|
||||
};
|
||||
|
||||
return acc;
|
||||
}, {});
|
||||
|
||||
|
|
@ -48,10 +52,14 @@ export const loadOllamaEmbeddingsModels = async () => {
|
|||
const { models: ollamaModels } = (await response.json()) as any;
|
||||
|
||||
const embeddingsModels = ollamaModels.reduce((acc, model) => {
|
||||
acc[model.model] = new OllamaEmbeddings({
|
||||
baseUrl: ollamaEndpoint,
|
||||
model: model.model,
|
||||
});
|
||||
acc[model.model] = {
|
||||
displayName: model.name,
|
||||
model: new OllamaEmbeddings({
|
||||
baseUrl: ollamaEndpoint,
|
||||
model: model.model,
|
||||
}),
|
||||
};
|
||||
|
||||
return acc;
|
||||
}, {});
|
||||
|
||||
|
|
|
|||
|
|
@ -9,31 +9,46 @@ export const loadOpenAIChatModels = async () => {
|
|||
|
||||
try {
|
||||
const chatModels = {
|
||||
'GPT-3.5 turbo': new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-3.5-turbo',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
'GPT-4': new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
'GPT-4 turbo': new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4-turbo',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
'GPT-4 omni': new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4o',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
'GPT-4 omni mini': new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4o-mini',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
'gpt-3.5-turbo': {
|
||||
displayName: 'GPT-3.5 Turbo',
|
||||
model: new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-3.5-turbo',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
},
|
||||
'gpt-4': {
|
||||
displayName: 'GPT-4',
|
||||
model: new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
},
|
||||
'gpt-4-turbo': {
|
||||
displayName: 'GPT-4 turbo',
|
||||
model: new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4-turbo',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
},
|
||||
'gpt-4o': {
|
||||
displayName: 'GPT-4 omni',
|
||||
model: new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4o',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
},
|
||||
'gpt-4o-mini': {
|
||||
displayName: 'GPT-4 omni mini',
|
||||
model: new ChatOpenAI({
|
||||
openAIApiKey,
|
||||
modelName: 'gpt-4o-mini',
|
||||
temperature: 0.7,
|
||||
}),
|
||||
},
|
||||
};
|
||||
|
||||
return chatModels;
|
||||
|
|
@ -50,14 +65,20 @@ export const loadOpenAIEmbeddingsModels = async () => {
|
|||
|
||||
try {
|
||||
const embeddingModels = {
|
||||
'Text embedding 3 small': new OpenAIEmbeddings({
|
||||
openAIApiKey,
|
||||
modelName: 'text-embedding-3-small',
|
||||
}),
|
||||
'Text embedding 3 large': new OpenAIEmbeddings({
|
||||
openAIApiKey,
|
||||
modelName: 'text-embedding-3-large',
|
||||
}),
|
||||
'text-embedding-3-small': {
|
||||
displayName: 'Text Embedding 3 Small',
|
||||
model: new OpenAIEmbeddings({
|
||||
openAIApiKey,
|
||||
modelName: 'text-embedding-3-small',
|
||||
}),
|
||||
},
|
||||
'text-embedding-3-large': {
|
||||
displayName: 'Text Embedding 3 Large',
|
||||
model: new OpenAIEmbeddings({
|
||||
openAIApiKey,
|
||||
modelName: 'text-embedding-3-large',
|
||||
}),
|
||||
},
|
||||
};
|
||||
|
||||
return embeddingModels;
|
||||
|
|
|
|||
|
|
@ -4,15 +4,24 @@ import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
|
|||
export const loadTransformersEmbeddingsModels = async () => {
|
||||
try {
|
||||
const embeddingModels = {
|
||||
'BGE Small': new HuggingFaceTransformersEmbeddings({
|
||||
modelName: 'Xenova/bge-small-en-v1.5',
|
||||
}),
|
||||
'GTE Small': new HuggingFaceTransformersEmbeddings({
|
||||
modelName: 'Xenova/gte-small',
|
||||
}),
|
||||
'Bert Multilingual': new HuggingFaceTransformersEmbeddings({
|
||||
modelName: 'Xenova/bert-base-multilingual-uncased',
|
||||
}),
|
||||
'xenova-bge-small-en-v1.5': {
|
||||
displayName: 'BGE Small',
|
||||
model: new HuggingFaceTransformersEmbeddings({
|
||||
modelName: 'Xenova/bge-small-en-v1.5',
|
||||
}),
|
||||
},
|
||||
'xenova-gte-small': {
|
||||
displayName: 'GTE Small',
|
||||
model: new HuggingFaceTransformersEmbeddings({
|
||||
modelName: 'Xenova/gte-small',
|
||||
}),
|
||||
},
|
||||
'xenova-bert-base-multilingual-uncased': {
|
||||
displayName: 'Bert Multilingual',
|
||||
model: new HuggingFaceTransformersEmbeddings({
|
||||
modelName: 'Xenova/bert-base-multilingual-uncased',
|
||||
}),
|
||||
},
|
||||
};
|
||||
|
||||
return embeddingModels;
|
||||
|
|
|
|||
|
|
@ -10,38 +10,54 @@ import {
|
|||
getOpenaiApiKey,
|
||||
updateConfig,
|
||||
} from '../config';
|
||||
import logger from '../utils/logger';
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
router.get('/', async (_, res) => {
|
||||
const config = {};
|
||||
try {
|
||||
const config = {};
|
||||
|
||||
const [chatModelProviders, embeddingModelProviders] = await Promise.all([
|
||||
getAvailableChatModelProviders(),
|
||||
getAvailableEmbeddingModelProviders(),
|
||||
]);
|
||||
const [chatModelProviders, embeddingModelProviders] = await Promise.all([
|
||||
getAvailableChatModelProviders(),
|
||||
getAvailableEmbeddingModelProviders(),
|
||||
]);
|
||||
|
||||
config['chatModelProviders'] = {};
|
||||
config['embeddingModelProviders'] = {};
|
||||
config['chatModelProviders'] = {};
|
||||
config['embeddingModelProviders'] = {};
|
||||
|
||||
for (const provider in chatModelProviders) {
|
||||
config['chatModelProviders'][provider] = Object.keys(
|
||||
chatModelProviders[provider],
|
||||
);
|
||||
for (const provider in chatModelProviders) {
|
||||
config['chatModelProviders'][provider] = Object.keys(
|
||||
chatModelProviders[provider],
|
||||
).map((model) => {
|
||||
return {
|
||||
name: model,
|
||||
displayName: chatModelProviders[provider][model].displayName,
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
for (const provider in embeddingModelProviders) {
|
||||
config['embeddingModelProviders'][provider] = Object.keys(
|
||||
embeddingModelProviders[provider],
|
||||
).map((model) => {
|
||||
return {
|
||||
name: model,
|
||||
displayName: embeddingModelProviders[provider][model].displayName,
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
config['openaiApiKey'] = getOpenaiApiKey();
|
||||
config['ollamaApiUrl'] = getOllamaApiEndpoint();
|
||||
config['anthropicApiKey'] = getAnthropicApiKey();
|
||||
config['groqApiKey'] = getGroqApiKey();
|
||||
|
||||
res.status(200).json(config);
|
||||
} catch (err: any) {
|
||||
res.status(500).json({ message: 'An error has occurred.' });
|
||||
logger.error(`Error getting config: ${err.message}`);
|
||||
}
|
||||
|
||||
for (const provider in embeddingModelProviders) {
|
||||
config['embeddingModelProviders'][provider] = Object.keys(
|
||||
embeddingModelProviders[provider],
|
||||
);
|
||||
}
|
||||
|
||||
config['openaiApiKey'] = getOpenaiApiKey();
|
||||
config['ollamaApiUrl'] = getOllamaApiEndpoint();
|
||||
config['anthropicApiKey'] = getAnthropicApiKey();
|
||||
config['groqApiKey'] = getGroqApiKey();
|
||||
|
||||
res.status(200).json(config);
|
||||
});
|
||||
|
||||
router.post('/', async (req, res) => {
|
||||
|
|
|
|||
48
src/routes/discover.ts
Normal file
48
src/routes/discover.ts
Normal file
|
|
@ -0,0 +1,48 @@
|
|||
import express from 'express';
|
||||
import { searchSearxng } from '../lib/searxng';
|
||||
import logger from '../utils/logger';
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
router.get('/', async (req, res) => {
|
||||
try {
|
||||
const data = (
|
||||
await Promise.all([
|
||||
searchSearxng('site:businessinsider.com AI', {
|
||||
engines: ['bing news'],
|
||||
pageno: 1,
|
||||
}),
|
||||
searchSearxng('site:www.exchangewire.com AI', {
|
||||
engines: ['bing news'],
|
||||
pageno: 1,
|
||||
}),
|
||||
searchSearxng('site:yahoo.com AI', {
|
||||
engines: ['bing news'],
|
||||
pageno: 1,
|
||||
}),
|
||||
searchSearxng('site:businessinsider.com tech', {
|
||||
engines: ['bing news'],
|
||||
pageno: 1,
|
||||
}),
|
||||
searchSearxng('site:www.exchangewire.com tech', {
|
||||
engines: ['bing news'],
|
||||
pageno: 1,
|
||||
}),
|
||||
searchSearxng('site:yahoo.com tech', {
|
||||
engines: ['bing news'],
|
||||
pageno: 1,
|
||||
}),
|
||||
])
|
||||
)
|
||||
.map((result) => result.results)
|
||||
.flat()
|
||||
.sort(() => Math.random() - 0.5);
|
||||
|
||||
return res.json({ blogs: data });
|
||||
} catch (err: any) {
|
||||
logger.error(`Error in discover route: ${err.message}`);
|
||||
return res.status(500).json({ message: 'An error has occurred' });
|
||||
}
|
||||
});
|
||||
|
||||
export default router;
|
||||
|
|
@ -26,7 +26,7 @@ router.post('/', async (req, res) => {
|
|||
let llm: BaseChatModel | undefined;
|
||||
|
||||
if (chatModels[provider] && chatModels[provider][chatModel]) {
|
||||
llm = chatModels[provider][chatModel] as BaseChatModel | undefined;
|
||||
llm = chatModels[provider][chatModel].model as BaseChatModel | undefined;
|
||||
}
|
||||
|
||||
if (!llm) {
|
||||
|
|
|
|||
|
|
@ -5,6 +5,8 @@ import configRouter from './config';
|
|||
import modelsRouter from './models';
|
||||
import suggestionsRouter from './suggestions';
|
||||
import chatsRouter from './chats';
|
||||
import searchRouter from './search';
|
||||
import discoverRouter from './discover';
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
|
|
@ -14,5 +16,7 @@ router.use('/config', configRouter);
|
|||
router.use('/models', modelsRouter);
|
||||
router.use('/suggestions', suggestionsRouter);
|
||||
router.use('/chats', chatsRouter);
|
||||
router.use('/search', searchRouter);
|
||||
router.use('/discover', discoverRouter);
|
||||
|
||||
export default router;
|
||||
|
|
|
|||
|
|
@ -14,6 +14,18 @@ router.get('/', async (req, res) => {
|
|||
getAvailableEmbeddingModelProviders(),
|
||||
]);
|
||||
|
||||
Object.keys(chatModelProviders).forEach((provider) => {
|
||||
Object.keys(chatModelProviders[provider]).forEach((model) => {
|
||||
delete chatModelProviders[provider][model].model;
|
||||
});
|
||||
});
|
||||
|
||||
Object.keys(embeddingModelProviders).forEach((provider) => {
|
||||
Object.keys(embeddingModelProviders[provider]).forEach((model) => {
|
||||
delete embeddingModelProviders[provider][model].model;
|
||||
});
|
||||
});
|
||||
|
||||
res.status(200).json({ chatModelProviders, embeddingModelProviders });
|
||||
} catch (err) {
|
||||
res.status(500).json({ message: 'An error has occurred.' });
|
||||
|
|
|
|||
158
src/routes/search.ts
Normal file
158
src/routes/search.ts
Normal file
|
|
@ -0,0 +1,158 @@
|
|||
import express from 'express';
|
||||
import logger from '../utils/logger';
|
||||
import { BaseChatModel } from 'langchain/chat_models/base';
|
||||
import { Embeddings } from 'langchain/embeddings/base';
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
import {
|
||||
getAvailableChatModelProviders,
|
||||
getAvailableEmbeddingModelProviders,
|
||||
} from '../lib/providers';
|
||||
import { searchHandlers } from '../websocket/messageHandler';
|
||||
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
interface chatModel {
|
||||
provider: string;
|
||||
model: string;
|
||||
customOpenAIBaseURL?: string;
|
||||
customOpenAIKey?: string;
|
||||
}
|
||||
|
||||
interface embeddingModel {
|
||||
provider: string;
|
||||
model: string;
|
||||
}
|
||||
|
||||
interface ChatRequestBody {
|
||||
optimizationMode: 'speed' | 'balanced';
|
||||
focusMode: string;
|
||||
chatModel?: chatModel;
|
||||
embeddingModel?: embeddingModel;
|
||||
query: string;
|
||||
history: Array<[string, string]>;
|
||||
}
|
||||
|
||||
router.post('/', async (req, res) => {
|
||||
try {
|
||||
const body: ChatRequestBody = req.body;
|
||||
|
||||
if (!body.focusMode || !body.query) {
|
||||
return res.status(400).json({ message: 'Missing focus mode or query' });
|
||||
}
|
||||
|
||||
body.history = body.history || [];
|
||||
body.optimizationMode = body.optimizationMode || 'balanced';
|
||||
|
||||
const history: BaseMessage[] = body.history.map((msg) => {
|
||||
if (msg[0] === 'human') {
|
||||
return new HumanMessage({
|
||||
content: msg[1],
|
||||
});
|
||||
} else {
|
||||
return new AIMessage({
|
||||
content: msg[1],
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
const [chatModelProviders, embeddingModelProviders] = await Promise.all([
|
||||
getAvailableChatModelProviders(),
|
||||
getAvailableEmbeddingModelProviders(),
|
||||
]);
|
||||
|
||||
const chatModelProvider =
|
||||
body.chatModel?.provider || Object.keys(chatModelProviders)[0];
|
||||
const chatModel =
|
||||
body.chatModel?.model ||
|
||||
Object.keys(chatModelProviders[chatModelProvider])[0];
|
||||
|
||||
const embeddingModelProvider =
|
||||
body.embeddingModel?.provider || Object.keys(embeddingModelProviders)[0];
|
||||
const embeddingModel =
|
||||
body.embeddingModel?.model ||
|
||||
Object.keys(embeddingModelProviders[embeddingModelProvider])[0];
|
||||
|
||||
let llm: BaseChatModel | undefined;
|
||||
let embeddings: Embeddings | undefined;
|
||||
|
||||
if (body.chatModel?.provider === 'custom_openai') {
|
||||
if (
|
||||
!body.chatModel?.customOpenAIBaseURL ||
|
||||
!body.chatModel?.customOpenAIKey
|
||||
) {
|
||||
return res
|
||||
.status(400)
|
||||
.json({ message: 'Missing custom OpenAI base URL or key' });
|
||||
}
|
||||
|
||||
llm = new ChatOpenAI({
|
||||
modelName: body.chatModel.model,
|
||||
openAIApiKey: body.chatModel.customOpenAIKey,
|
||||
temperature: 0.7,
|
||||
configuration: {
|
||||
baseURL: body.chatModel.customOpenAIBaseURL,
|
||||
},
|
||||
}) as unknown as BaseChatModel;
|
||||
} else if (
|
||||
chatModelProviders[chatModelProvider] &&
|
||||
chatModelProviders[chatModelProvider][chatModel]
|
||||
) {
|
||||
llm = chatModelProviders[chatModelProvider][chatModel]
|
||||
.model as unknown as BaseChatModel | undefined;
|
||||
}
|
||||
|
||||
if (
|
||||
embeddingModelProviders[embeddingModelProvider] &&
|
||||
embeddingModelProviders[embeddingModelProvider][embeddingModel]
|
||||
) {
|
||||
embeddings = embeddingModelProviders[embeddingModelProvider][
|
||||
embeddingModel
|
||||
].model as Embeddings | undefined;
|
||||
}
|
||||
|
||||
if (!llm || !embeddings) {
|
||||
return res.status(400).json({ message: 'Invalid model selected' });
|
||||
}
|
||||
|
||||
const searchHandler = searchHandlers[body.focusMode];
|
||||
|
||||
if (!searchHandler) {
|
||||
return res.status(400).json({ message: 'Invalid focus mode' });
|
||||
}
|
||||
|
||||
const emitter = searchHandler(
|
||||
body.query,
|
||||
history,
|
||||
llm,
|
||||
embeddings,
|
||||
body.optimizationMode,
|
||||
);
|
||||
|
||||
let message = '';
|
||||
let sources = [];
|
||||
|
||||
emitter.on('data', (data) => {
|
||||
const parsedData = JSON.parse(data);
|
||||
if (parsedData.type === 'response') {
|
||||
message += parsedData.data;
|
||||
} else if (parsedData.type === 'sources') {
|
||||
sources = parsedData.data;
|
||||
}
|
||||
});
|
||||
|
||||
emitter.on('end', () => {
|
||||
res.status(200).json({ message, sources });
|
||||
});
|
||||
|
||||
emitter.on('error', (data) => {
|
||||
const parsedData = JSON.parse(data);
|
||||
res.status(500).json({ message: parsedData.data });
|
||||
});
|
||||
} catch (err: any) {
|
||||
logger.error(`Error in getting search results: ${err.message}`);
|
||||
res.status(500).json({ message: 'An error has occurred.' });
|
||||
}
|
||||
});
|
||||
|
||||
export default router;
|
||||
|
|
@ -26,7 +26,7 @@ router.post('/', async (req, res) => {
|
|||
let llm: BaseChatModel | undefined;
|
||||
|
||||
if (chatModels[provider] && chatModels[provider][chatModel]) {
|
||||
llm = chatModels[provider][chatModel] as BaseChatModel | undefined;
|
||||
llm = chatModels[provider][chatModel].model as BaseChatModel | undefined;
|
||||
}
|
||||
|
||||
if (!llm) {
|
||||
|
|
|
|||
|
|
@ -26,7 +26,7 @@ router.post('/', async (req, res) => {
|
|||
let llm: BaseChatModel | undefined;
|
||||
|
||||
if (chatModels[provider] && chatModels[provider][chatModel]) {
|
||||
llm = chatModels[provider][chatModel] as BaseChatModel | undefined;
|
||||
llm = chatModels[provider][chatModel].model as BaseChatModel | undefined;
|
||||
}
|
||||
|
||||
if (!llm) {
|
||||
|
|
|
|||
|
|
@ -45,9 +45,8 @@ export const handleConnection = async (
|
|||
chatModelProviders[chatModelProvider][chatModel] &&
|
||||
chatModelProvider != 'custom_openai'
|
||||
) {
|
||||
llm = chatModelProviders[chatModelProvider][chatModel] as unknown as
|
||||
| BaseChatModel
|
||||
| undefined;
|
||||
llm = chatModelProviders[chatModelProvider][chatModel]
|
||||
.model as unknown as BaseChatModel | undefined;
|
||||
} else if (chatModelProvider == 'custom_openai') {
|
||||
llm = new ChatOpenAI({
|
||||
modelName: chatModel,
|
||||
|
|
@ -65,7 +64,7 @@ export const handleConnection = async (
|
|||
) {
|
||||
embeddings = embeddingModelProviders[embeddingModelProvider][
|
||||
embeddingModel
|
||||
] as Embeddings | undefined;
|
||||
].model as Embeddings | undefined;
|
||||
}
|
||||
|
||||
if (!llm || !embeddings) {
|
||||
|
|
@ -79,6 +78,18 @@ export const handleConnection = async (
|
|||
ws.close();
|
||||
}
|
||||
|
||||
const interval = setInterval(() => {
|
||||
if (ws.readyState === ws.OPEN) {
|
||||
ws.send(
|
||||
JSON.stringify({
|
||||
type: 'signal',
|
||||
data: 'open',
|
||||
}),
|
||||
);
|
||||
clearInterval(interval);
|
||||
}
|
||||
}, 5);
|
||||
|
||||
ws.on(
|
||||
'message',
|
||||
async (message) =>
|
||||
|
|
|
|||
|
|
@ -10,8 +10,8 @@ import type { BaseChatModel } from '@langchain/core/language_models/chat_models'
|
|||
import type { Embeddings } from '@langchain/core/embeddings';
|
||||
import logger from '../utils/logger';
|
||||
import db from '../db';
|
||||
import { chats, messages } from '../db/schema';
|
||||
import { eq } from 'drizzle-orm';
|
||||
import { chats, messages as messagesSchema } from '../db/schema';
|
||||
import { eq, asc, gt } from 'drizzle-orm';
|
||||
import crypto from 'crypto';
|
||||
|
||||
type Message = {
|
||||
|
|
@ -22,13 +22,13 @@ type Message = {
|
|||
|
||||
type WSMessage = {
|
||||
message: Message;
|
||||
copilot: boolean;
|
||||
optimizationMode: string;
|
||||
type: string;
|
||||
focusMode: string;
|
||||
history: Array<[string, string]>;
|
||||
};
|
||||
|
||||
const searchHandlers = {
|
||||
export const searchHandlers = {
|
||||
webSearch: handleWebSearch,
|
||||
academicSearch: handleAcademicSearch,
|
||||
writingAssistant: handleWritingAssistant,
|
||||
|
|
@ -71,7 +71,7 @@ const handleEmitterEvents = (
|
|||
emitter.on('end', () => {
|
||||
ws.send(JSON.stringify({ type: 'messageEnd', messageId: messageId }));
|
||||
|
||||
db.insert(messages)
|
||||
db.insert(messagesSchema)
|
||||
.values({
|
||||
content: recievedMessage,
|
||||
chatId: chatId,
|
||||
|
|
@ -106,7 +106,9 @@ export const handleMessage = async (
|
|||
const parsedWSMessage = JSON.parse(message) as WSMessage;
|
||||
const parsedMessage = parsedWSMessage.message;
|
||||
|
||||
const id = crypto.randomBytes(7).toString('hex');
|
||||
const humanMessageId =
|
||||
parsedMessage.messageId ?? crypto.randomBytes(7).toString('hex');
|
||||
const aiMessageId = crypto.randomBytes(7).toString('hex');
|
||||
|
||||
if (!parsedMessage.content)
|
||||
return ws.send(
|
||||
|
|
@ -138,9 +140,10 @@ export const handleMessage = async (
|
|||
history,
|
||||
llm,
|
||||
embeddings,
|
||||
parsedWSMessage.optimizationMode,
|
||||
);
|
||||
|
||||
handleEmitterEvents(emitter, ws, id, parsedMessage.chatId);
|
||||
handleEmitterEvents(emitter, ws, aiMessageId, parsedMessage.chatId);
|
||||
|
||||
const chat = await db.query.chats.findFirst({
|
||||
where: eq(chats.id, parsedMessage.chatId),
|
||||
|
|
@ -158,18 +161,29 @@ export const handleMessage = async (
|
|||
.execute();
|
||||
}
|
||||
|
||||
await db
|
||||
.insert(messages)
|
||||
.values({
|
||||
content: parsedMessage.content,
|
||||
chatId: parsedMessage.chatId,
|
||||
messageId: id,
|
||||
role: 'user',
|
||||
metadata: JSON.stringify({
|
||||
createdAt: new Date(),
|
||||
}),
|
||||
})
|
||||
.execute();
|
||||
const messageExists = await db.query.messages.findFirst({
|
||||
where: eq(messagesSchema.messageId, humanMessageId),
|
||||
});
|
||||
|
||||
if (!messageExists) {
|
||||
await db
|
||||
.insert(messagesSchema)
|
||||
.values({
|
||||
content: parsedMessage.content,
|
||||
chatId: parsedMessage.chatId,
|
||||
messageId: humanMessageId,
|
||||
role: 'user',
|
||||
metadata: JSON.stringify({
|
||||
createdAt: new Date(),
|
||||
}),
|
||||
})
|
||||
.execute();
|
||||
} else {
|
||||
await db
|
||||
.delete(messagesSchema)
|
||||
.where(gt(messagesSchema.id, messageExists.id))
|
||||
.execute();
|
||||
}
|
||||
} else {
|
||||
ws.send(
|
||||
JSON.stringify({
|
||||
|
|
|
|||
112
ui/app/discover/page.tsx
Normal file
112
ui/app/discover/page.tsx
Normal file
|
|
@ -0,0 +1,112 @@
|
|||
'use client';
|
||||
|
||||
import { Search } from 'lucide-react';
|
||||
import { useEffect, useState } from 'react';
|
||||
import Link from 'next/link';
|
||||
import { toast } from 'sonner';
|
||||
|
||||
interface Discover {
|
||||
title: string;
|
||||
content: string;
|
||||
url: string;
|
||||
thumbnail: string;
|
||||
}
|
||||
|
||||
const Page = () => {
|
||||
const [discover, setDiscover] = useState<Discover[] | null>(null);
|
||||
const [loading, setLoading] = useState(true);
|
||||
|
||||
useEffect(() => {
|
||||
const fetchData = async () => {
|
||||
try {
|
||||
const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/discover`, {
|
||||
method: 'GET',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
});
|
||||
|
||||
const data = await res.json();
|
||||
|
||||
if (!res.ok) {
|
||||
throw new Error(data.message);
|
||||
}
|
||||
|
||||
data.blogs = data.blogs.filter((blog: Discover) => blog.thumbnail);
|
||||
|
||||
setDiscover(data.blogs);
|
||||
} catch (err: any) {
|
||||
console.error('Error fetching data:', err.message);
|
||||
toast.error('Error fetching data');
|
||||
} finally {
|
||||
setLoading(false);
|
||||
}
|
||||
};
|
||||
|
||||
fetchData();
|
||||
}, []);
|
||||
|
||||
return loading ? (
|
||||
<div className="flex flex-row items-center justify-center min-h-screen">
|
||||
<svg
|
||||
aria-hidden="true"
|
||||
className="w-8 h-8 text-light-200 fill-light-secondary dark:text-[#202020] animate-spin dark:fill-[#ffffff3b]"
|
||||
viewBox="0 0 100 101"
|
||||
fill="none"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
>
|
||||
<path
|
||||
d="M100 50.5908C100.003 78.2051 78.1951 100.003 50.5908 100C22.9765 99.9972 0.997224 78.018 1 50.4037C1.00281 22.7993 22.8108 0.997224 50.4251 1C78.0395 1.00281 100.018 22.8108 100 50.4251ZM9.08164 50.594C9.06312 73.3997 27.7909 92.1272 50.5966 92.1457C73.4023 92.1642 92.1298 73.4365 92.1483 50.6308C92.1669 27.8251 73.4392 9.0973 50.6335 9.07878C27.8278 9.06026 9.10003 27.787 9.08164 50.594Z"
|
||||
fill="currentColor"
|
||||
/>
|
||||
<path
|
||||
d="M93.9676 39.0409C96.393 38.4037 97.8624 35.9116 96.9801 33.5533C95.1945 28.8227 92.871 24.3692 90.0681 20.348C85.6237 14.1775 79.4473 9.36872 72.0454 6.45794C64.6435 3.54717 56.3134 2.65431 48.3133 3.89319C45.869 4.27179 44.3768 6.77534 45.014 9.20079C45.6512 11.6262 48.1343 13.0956 50.5786 12.717C56.5073 11.8281 62.5542 12.5399 68.0406 14.7911C73.527 17.0422 78.2187 20.7487 81.5841 25.4923C83.7976 28.5886 85.4467 32.059 86.4416 35.7474C87.1273 38.1189 89.5423 39.6781 91.9676 39.0409Z"
|
||||
fill="currentFill"
|
||||
/>
|
||||
</svg>
|
||||
</div>
|
||||
) : (
|
||||
<>
|
||||
<div>
|
||||
<div className="flex flex-col pt-4">
|
||||
<div className="flex items-center">
|
||||
<Search />
|
||||
<h1 className="text-3xl font-medium p-2">Discover</h1>
|
||||
</div>
|
||||
<hr className="border-t border-[#2B2C2C] my-4 w-full" />
|
||||
</div>
|
||||
|
||||
<div className="grid lg:grid-cols-3 sm:grid-cols-2 grid-cols-1 gap-4 pb-28 lg:pb-8 w-full justify-items-center lg:justify-items-start">
|
||||
{discover &&
|
||||
discover?.map((item, i) => (
|
||||
<Link
|
||||
href={`/?q=Summary: ${item.url}`}
|
||||
key={i}
|
||||
className="max-w-sm rounded-lg overflow-hidden bg-light-secondary dark:bg-dark-secondary hover:-translate-y-[1px] transition duration-200"
|
||||
>
|
||||
<img
|
||||
className="object-cover w-full aspect-video"
|
||||
src={
|
||||
new URL(item.thumbnail).origin +
|
||||
new URL(item.thumbnail).pathname +
|
||||
`?id=${new URL(item.thumbnail).searchParams.get('id')}`
|
||||
}
|
||||
alt={item.title}
|
||||
/>
|
||||
<div className="px-6 py-4">
|
||||
<div className="font-bold text-lg mb-2">
|
||||
{item.title.slice(0, 100)}...
|
||||
</div>
|
||||
<p className="text-black-70 dark:text-white/70 text-sm">
|
||||
{item.content.slice(0, 100)}...
|
||||
</p>
|
||||
</div>
|
||||
</Link>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
</>
|
||||
);
|
||||
};
|
||||
|
||||
export default Page;
|
||||
|
|
@ -34,7 +34,7 @@ export default function RootLayout({
|
|||
unstyled: true,
|
||||
classNames: {
|
||||
toast:
|
||||
'bg-light-primary dark:bg-dark-primary text-white rounded-lg p-4 flex flex-row items-center space-x-2',
|
||||
'bg-light-primary dark:bg-dark-secondary dark:text-white/70 text-black-70 rounded-lg p-4 flex flex-row items-center space-x-2',
|
||||
},
|
||||
}}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
'use client';
|
||||
|
||||
import DeleteChat from '@/components/DeleteChat';
|
||||
import { formatTimeDifference } from '@/lib/utils';
|
||||
import { cn, formatTimeDifference } from '@/lib/utils';
|
||||
import { BookOpenText, ClockIcon, Delete, ScanEye } from 'lucide-react';
|
||||
import Link from 'next/link';
|
||||
import { useEffect, useState } from 'react';
|
||||
|
|
@ -58,13 +58,12 @@ const Page = () => {
|
|||
</div>
|
||||
) : (
|
||||
<div>
|
||||
<div className="fixed z-40 top-0 left-0 right-0 lg:pl-[104px] lg:pr-6 lg:px-8 px-4 py-4 lg:py-6 border-b border-light-200 dark:border-dark-200">
|
||||
<div className="flex flex-row items-center space-x-2 max-w-screen-lg lg:mx-auto">
|
||||
<div className="flex flex-col pt-4">
|
||||
<div className="flex items-center">
|
||||
<BookOpenText />
|
||||
<h2 className="text-black dark:text-white lg:text-3xl lg:font-medium">
|
||||
Library
|
||||
</h2>
|
||||
<h1 className="text-3xl font-medium p-2">Library</h1>
|
||||
</div>
|
||||
<hr className="border-t border-[#2B2C2C] my-4 w-full" />
|
||||
</div>
|
||||
{chats.length === 0 && (
|
||||
<div className="flex flex-row items-center justify-center min-h-screen">
|
||||
|
|
@ -74,10 +73,15 @@ const Page = () => {
|
|||
</div>
|
||||
)}
|
||||
{chats.length > 0 && (
|
||||
<div className="flex flex-col pt-16 lg:pt-24">
|
||||
<div className="flex flex-col pb-20 lg:pb-2">
|
||||
{chats.map((chat, i) => (
|
||||
<div
|
||||
className="flex flex-col space-y-4 border-b border-white-200 dark:border-dark-200 py-6 lg:mx-4"
|
||||
className={cn(
|
||||
'flex flex-col space-y-4 py-6',
|
||||
i !== chats.length - 1
|
||||
? 'border-b border-white-200 dark:border-dark-200'
|
||||
: '',
|
||||
)}
|
||||
key={i}
|
||||
>
|
||||
<Link
|
||||
|
|
|
|||
|
|
@ -38,43 +38,56 @@ const useSocket = (
|
|||
'embeddingModelProvider',
|
||||
);
|
||||
|
||||
const providers = await fetch(
|
||||
`${process.env.NEXT_PUBLIC_API_URL}/models`,
|
||||
{
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
},
|
||||
).then(async (res) => await res.json());
|
||||
|
||||
if (
|
||||
!chatModel ||
|
||||
!chatModelProvider ||
|
||||
!embeddingModel ||
|
||||
!embeddingModelProvider
|
||||
) {
|
||||
const providers = await fetch(
|
||||
`${process.env.NEXT_PUBLIC_API_URL}/models`,
|
||||
{
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
},
|
||||
).then(async (res) => await res.json());
|
||||
if (!chatModel || !chatModelProvider) {
|
||||
const chatModelProviders = providers.chatModelProviders;
|
||||
|
||||
const chatModelProviders = providers.chatModelProviders;
|
||||
const embeddingModelProviders = providers.embeddingModelProviders;
|
||||
chatModelProvider = Object.keys(chatModelProviders)[0];
|
||||
|
||||
if (
|
||||
!chatModelProviders ||
|
||||
Object.keys(chatModelProviders).length === 0
|
||||
)
|
||||
return toast.error('No chat models available');
|
||||
if (chatModelProvider === 'custom_openai') {
|
||||
toast.error(
|
||||
'Seems like you are using the custom OpenAI provider, please open the settings and configure the API key and base URL',
|
||||
);
|
||||
setError(true);
|
||||
return;
|
||||
} else {
|
||||
chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
|
||||
if (
|
||||
!chatModelProviders ||
|
||||
Object.keys(chatModelProviders).length === 0
|
||||
)
|
||||
return toast.error('No chat models available');
|
||||
}
|
||||
}
|
||||
|
||||
if (
|
||||
!embeddingModelProviders ||
|
||||
Object.keys(embeddingModelProviders).length === 0
|
||||
)
|
||||
return toast.error('No embedding models available');
|
||||
if (!embeddingModel || !embeddingModelProvider) {
|
||||
const embeddingModelProviders = providers.embeddingModelProviders;
|
||||
|
||||
chatModelProvider = Object.keys(chatModelProviders)[0];
|
||||
chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
|
||||
if (
|
||||
!embeddingModelProviders ||
|
||||
Object.keys(embeddingModelProviders).length === 0
|
||||
)
|
||||
return toast.error('No embedding models available');
|
||||
|
||||
embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
|
||||
embeddingModel = Object.keys(
|
||||
embeddingModelProviders[embeddingModelProvider],
|
||||
)[0];
|
||||
embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
|
||||
embeddingModel = Object.keys(
|
||||
embeddingModelProviders[embeddingModelProvider],
|
||||
)[0];
|
||||
}
|
||||
|
||||
localStorage.setItem('chatModel', chatModel!);
|
||||
localStorage.setItem('chatModelProvider', chatModelProvider);
|
||||
|
|
@ -84,15 +97,6 @@ const useSocket = (
|
|||
embeddingModelProvider,
|
||||
);
|
||||
} else {
|
||||
const providers = await fetch(
|
||||
`${process.env.NEXT_PUBLIC_API_URL}/models`,
|
||||
{
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
},
|
||||
).then(async (res) => await res.json());
|
||||
|
||||
const chatModelProviders = providers.chatModelProviders;
|
||||
const embeddingModelProviders = providers.embeddingModelProviders;
|
||||
|
||||
|
|
@ -106,6 +110,7 @@ const useSocket = (
|
|||
|
||||
if (
|
||||
chatModelProvider &&
|
||||
chatModelProvider != 'custom_openai' &&
|
||||
!chatModelProviders[chatModelProvider][chatModel]
|
||||
) {
|
||||
chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
|
||||
|
|
@ -160,20 +165,28 @@ const useSocket = (
|
|||
|
||||
const timeoutId = setTimeout(() => {
|
||||
if (ws.readyState !== 1) {
|
||||
ws.close();
|
||||
setError(true);
|
||||
toast.error(
|
||||
'Failed to connect to the server. Please try again later.',
|
||||
);
|
||||
}
|
||||
}, 10000);
|
||||
|
||||
ws.onopen = () => {
|
||||
console.log('[DEBUG] open');
|
||||
clearTimeout(timeoutId);
|
||||
setError(false);
|
||||
setIsWSReady(true);
|
||||
};
|
||||
ws.addEventListener('message', (e) => {
|
||||
const data = JSON.parse(e.data);
|
||||
if (data.type === 'signal' && data.data === 'open') {
|
||||
const interval = setInterval(() => {
|
||||
if (ws.readyState === 1) {
|
||||
setIsWSReady(true);
|
||||
clearInterval(interval);
|
||||
}
|
||||
}, 5);
|
||||
clearTimeout(timeoutId);
|
||||
console.log('[DEBUG] opened');
|
||||
}
|
||||
if (data.type === 'error') {
|
||||
toast.error(data.data);
|
||||
}
|
||||
});
|
||||
|
||||
ws.onerror = () => {
|
||||
clearTimeout(timeoutId);
|
||||
|
|
@ -192,13 +205,6 @@ const useSocket = (
|
|||
|
||||
connectWs();
|
||||
}
|
||||
|
||||
return () => {
|
||||
if (ws?.readyState === 1) {
|
||||
ws?.close();
|
||||
console.log('[DEBUG] closed');
|
||||
}
|
||||
};
|
||||
}, [ws, url, setIsWSReady, setError]);
|
||||
|
||||
return ws;
|
||||
|
|
@ -276,6 +282,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
|||
const [messages, setMessages] = useState<Message[]>([]);
|
||||
|
||||
const [focusMode, setFocusMode] = useState('webSearch');
|
||||
const [optimizationMode, setOptimizationMode] = useState('speed');
|
||||
|
||||
const [isMessagesLoaded, setIsMessagesLoaded] = useState(false);
|
||||
|
||||
|
|
@ -304,6 +311,15 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
|||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, []);
|
||||
|
||||
useEffect(() => {
|
||||
return () => {
|
||||
if (ws?.readyState === 1) {
|
||||
ws.close();
|
||||
console.log('[DEBUG] closed');
|
||||
}
|
||||
};
|
||||
}, []);
|
||||
|
||||
const messagesRef = useRef<Message[]>([]);
|
||||
|
||||
useEffect(() => {
|
||||
|
|
@ -313,11 +329,13 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
|||
useEffect(() => {
|
||||
if (isMessagesLoaded && isWSReady) {
|
||||
setIsReady(true);
|
||||
console.log('[DEBUG] ready');
|
||||
}
|
||||
}, [isMessagesLoaded, isWSReady]);
|
||||
|
||||
const sendMessage = async (message: string) => {
|
||||
const sendMessage = async (message: string, messageId?: string) => {
|
||||
if (loading) return;
|
||||
|
||||
setLoading(true);
|
||||
setMessageAppeared(false);
|
||||
|
||||
|
|
@ -325,16 +343,18 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
|||
let recievedMessage = '';
|
||||
let added = false;
|
||||
|
||||
const messageId = crypto.randomBytes(7).toString('hex');
|
||||
messageId = messageId ?? crypto.randomBytes(7).toString('hex');
|
||||
|
||||
ws?.send(
|
||||
JSON.stringify({
|
||||
type: 'message',
|
||||
message: {
|
||||
messageId: messageId,
|
||||
chatId: chatId!,
|
||||
content: message,
|
||||
},
|
||||
focusMode: focusMode,
|
||||
optimizationMode: optimizationMode,
|
||||
history: [...chatHistory, ['human', message]],
|
||||
}),
|
||||
);
|
||||
|
|
@ -456,15 +476,15 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
|||
return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
|
||||
});
|
||||
|
||||
sendMessage(message.content);
|
||||
sendMessage(message.content, message.messageId);
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
if (isReady && initialMessage) {
|
||||
if (isReady && initialMessage && ws?.readyState === 1) {
|
||||
sendMessage(initialMessage);
|
||||
}
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [isReady, initialMessage]);
|
||||
}, [ws?.readyState, isReady, initialMessage, isWSReady]);
|
||||
|
||||
if (hasError) {
|
||||
return (
|
||||
|
|
@ -497,6 +517,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
|||
sendMessage={sendMessage}
|
||||
focusMode={focusMode}
|
||||
setFocusMode={setFocusMode}
|
||||
optimizationMode={optimizationMode}
|
||||
setOptimizationMode={setOptimizationMode}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,5 +1,13 @@
|
|||
import { Delete, Trash } from 'lucide-react';
|
||||
import { Dialog, Transition } from '@headlessui/react';
|
||||
import { Trash } from 'lucide-react';
|
||||
import {
|
||||
Description,
|
||||
Dialog,
|
||||
DialogBackdrop,
|
||||
DialogPanel,
|
||||
DialogTitle,
|
||||
Transition,
|
||||
TransitionChild,
|
||||
} from '@headlessui/react';
|
||||
import { Fragment, useState } from 'react';
|
||||
import { toast } from 'sonner';
|
||||
import { Chat } from '@/app/library/page';
|
||||
|
|
@ -64,10 +72,10 @@ const DeleteChat = ({
|
|||
}
|
||||
}}
|
||||
>
|
||||
<Dialog.Backdrop className="fixed inset-0 bg-black/30" />
|
||||
<DialogBackdrop className="fixed inset-0 bg-black/30" />
|
||||
<div className="fixed inset-0 overflow-y-auto">
|
||||
<div className="flex min-h-full items-center justify-center p-4 text-center">
|
||||
<Transition.Child
|
||||
<TransitionChild
|
||||
as={Fragment}
|
||||
enter="ease-out duration-200"
|
||||
enterFrom="opacity-0 scale-95"
|
||||
|
|
@ -76,13 +84,13 @@ const DeleteChat = ({
|
|||
leaveFrom="opacity-100 scale-200"
|
||||
leaveTo="opacity-0 scale-95"
|
||||
>
|
||||
<Dialog.Panel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
|
||||
<Dialog.Title className="text-lg font-medium leading-6 dark:text-white">
|
||||
<DialogPanel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
|
||||
<DialogTitle className="text-lg font-medium leading-6 dark:text-white">
|
||||
Delete Confirmation
|
||||
</Dialog.Title>
|
||||
<Dialog.Description className="text-sm dark:text-white/70 text-black/70">
|
||||
</DialogTitle>
|
||||
<Description className="text-sm dark:text-white/70 text-black/70">
|
||||
Are you sure you want to delete this chat?
|
||||
</Dialog.Description>
|
||||
</Description>
|
||||
<div className="flex flex-row items-end justify-end space-x-4 mt-6">
|
||||
<button
|
||||
onClick={() => {
|
||||
|
|
@ -101,8 +109,8 @@ const DeleteChat = ({
|
|||
Delete
|
||||
</button>
|
||||
</div>
|
||||
</Dialog.Panel>
|
||||
</Transition.Child>
|
||||
</DialogPanel>
|
||||
</TransitionChild>
|
||||
</div>
|
||||
</div>
|
||||
</Dialog>
|
||||
|
|
|
|||
|
|
@ -4,10 +4,14 @@ const EmptyChat = ({
|
|||
sendMessage,
|
||||
focusMode,
|
||||
setFocusMode,
|
||||
optimizationMode,
|
||||
setOptimizationMode,
|
||||
}: {
|
||||
sendMessage: (message: string) => void;
|
||||
focusMode: string;
|
||||
setFocusMode: (mode: string) => void;
|
||||
optimizationMode: string;
|
||||
setOptimizationMode: (mode: string) => void;
|
||||
}) => {
|
||||
return (
|
||||
<div className="relative">
|
||||
|
|
@ -19,6 +23,8 @@ const EmptyChat = ({
|
|||
sendMessage={sendMessage}
|
||||
focusMode={focusMode}
|
||||
setFocusMode={setFocusMode}
|
||||
optimizationMode={optimizationMode}
|
||||
setOptimizationMode={setOptimizationMode}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -3,29 +3,41 @@ import { useEffect, useRef, useState } from 'react';
|
|||
import TextareaAutosize from 'react-textarea-autosize';
|
||||
import CopilotToggle from './MessageInputActions/Copilot';
|
||||
import Focus from './MessageInputActions/Focus';
|
||||
import Optimization from './MessageInputActions/Optimization';
|
||||
|
||||
const EmptyChatMessageInput = ({
|
||||
sendMessage,
|
||||
focusMode,
|
||||
setFocusMode,
|
||||
optimizationMode,
|
||||
setOptimizationMode,
|
||||
}: {
|
||||
sendMessage: (message: string) => void;
|
||||
focusMode: string;
|
||||
setFocusMode: (mode: string) => void;
|
||||
optimizationMode: string;
|
||||
setOptimizationMode: (mode: string) => void;
|
||||
}) => {
|
||||
const [copilotEnabled, setCopilotEnabled] = useState(false);
|
||||
const [message, setMessage] = useState('');
|
||||
|
||||
const inputRef = useRef<HTMLTextAreaElement | null>(null);
|
||||
|
||||
const handleKeyDown = (e: KeyboardEvent) => {
|
||||
if (e.key === '/') {
|
||||
e.preventDefault();
|
||||
inputRef.current?.focus();
|
||||
}
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
const handleKeyDown = (e: KeyboardEvent) => {
|
||||
const activeElement = document.activeElement;
|
||||
|
||||
const isInputFocused =
|
||||
activeElement?.tagName === 'INPUT' ||
|
||||
activeElement?.tagName === 'TEXTAREA' ||
|
||||
activeElement?.hasAttribute('contenteditable');
|
||||
|
||||
if (e.key === '/' && !isInputFocused) {
|
||||
e.preventDefault();
|
||||
inputRef.current?.focus();
|
||||
}
|
||||
};
|
||||
|
||||
document.addEventListener('keydown', handleKeyDown);
|
||||
|
||||
return () => {
|
||||
|
|
@ -59,14 +71,13 @@ const EmptyChatMessageInput = ({
|
|||
placeholder="Ask anything..."
|
||||
/>
|
||||
<div className="flex flex-row items-center justify-between mt-4">
|
||||
<div className="flex flex-row items-center space-x-1 -mx-2">
|
||||
<div className="flex flex-row items-center space-x-4">
|
||||
<Focus focusMode={focusMode} setFocusMode={setFocusMode} />
|
||||
{/* <Attach /> */}
|
||||
</div>
|
||||
<div className="flex flex-row items-center space-x-4 -mx-2">
|
||||
<CopilotToggle
|
||||
copilotEnabled={copilotEnabled}
|
||||
setCopilotEnabled={setCopilotEnabled}
|
||||
<div className="flex flex-row items-center space-x-1 sm:space-x-4">
|
||||
<Optimization
|
||||
optimizationMode={optimizationMode}
|
||||
setOptimizationMode={setOptimizationMode}
|
||||
/>
|
||||
<button
|
||||
disabled={message.trim().length === 0}
|
||||
|
|
|
|||
|
|
@ -27,14 +27,21 @@ const MessageInput = ({
|
|||
|
||||
const inputRef = useRef<HTMLTextAreaElement | null>(null);
|
||||
|
||||
const handleKeyDown = (e: KeyboardEvent) => {
|
||||
if (e.key === '/') {
|
||||
e.preventDefault();
|
||||
inputRef.current?.focus();
|
||||
}
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
const handleKeyDown = (e: KeyboardEvent) => {
|
||||
const activeElement = document.activeElement;
|
||||
|
||||
const isInputFocused =
|
||||
activeElement?.tagName === 'INPUT' ||
|
||||
activeElement?.tagName === 'TEXTAREA' ||
|
||||
activeElement?.hasAttribute('contenteditable');
|
||||
|
||||
if (e.key === '/' && !isInputFocused) {
|
||||
e.preventDefault();
|
||||
inputRef.current?.focus();
|
||||
}
|
||||
};
|
||||
|
||||
document.addEventListener('keydown', handleKeyDown);
|
||||
|
||||
return () => {
|
||||
|
|
|
|||
|
|
@ -7,7 +7,12 @@ import {
|
|||
SwatchBook,
|
||||
} from 'lucide-react';
|
||||
import { cn } from '@/lib/utils';
|
||||
import { Popover, Transition } from '@headlessui/react';
|
||||
import {
|
||||
Popover,
|
||||
PopoverButton,
|
||||
PopoverPanel,
|
||||
Transition,
|
||||
} from '@headlessui/react';
|
||||
import { SiReddit, SiYoutube } from '@icons-pack/react-simple-icons';
|
||||
import { Fragment } from 'react';
|
||||
|
||||
|
|
@ -70,10 +75,10 @@ const Focus = ({
|
|||
setFocusMode: (mode: string) => void;
|
||||
}) => {
|
||||
return (
|
||||
<Popover className="fixed w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
|
||||
<Popover.Button
|
||||
<Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
|
||||
<PopoverButton
|
||||
type="button"
|
||||
className="p-2 text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary active:scale-95 transition duration-200 hover:text-black dark:hover:text-white"
|
||||
className=" text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary active:scale-95 transition duration-200 hover:text-black dark:hover:text-white"
|
||||
>
|
||||
{focusMode !== 'webSearch' ? (
|
||||
<div className="flex flex-row items-center space-x-1">
|
||||
|
|
@ -86,7 +91,7 @@ const Focus = ({
|
|||
) : (
|
||||
<ScanEye />
|
||||
)}
|
||||
</Popover.Button>
|
||||
</PopoverButton>
|
||||
<Transition
|
||||
as={Fragment}
|
||||
enter="transition ease-out duration-150"
|
||||
|
|
@ -96,10 +101,10 @@ const Focus = ({
|
|||
leaveFrom="opacity-100 translate-y-0"
|
||||
leaveTo="opacity-0 translate-y-1"
|
||||
>
|
||||
<Popover.Panel className="absolute z-10 w-full">
|
||||
<div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-1 bg-light-primary dark:bg-dark-primary border rounded-lg border-light-200 dark:border-dark-200 w-full p-2 max-h-[200px] md:max-h-none overflow-y-auto">
|
||||
<PopoverPanel className="absolute z-10 w-64 md:w-[500px] left-0">
|
||||
<div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-2 bg-light-primary dark:bg-dark-primary border rounded-lg border-light-200 dark:border-dark-200 w-full p-4 max-h-[200px] md:max-h-none overflow-y-auto">
|
||||
{focusModes.map((mode, i) => (
|
||||
<Popover.Button
|
||||
<PopoverButton
|
||||
onClick={() => setFocusMode(mode.key)}
|
||||
key={i}
|
||||
className={cn(
|
||||
|
|
@ -123,10 +128,10 @@ const Focus = ({
|
|||
<p className="text-black/70 dark:text-white/70 text-xs">
|
||||
{mode.description}
|
||||
</p>
|
||||
</Popover.Button>
|
||||
</PopoverButton>
|
||||
))}
|
||||
</div>
|
||||
</Popover.Panel>
|
||||
</PopoverPanel>
|
||||
</Transition>
|
||||
</Popover>
|
||||
);
|
||||
|
|
|
|||
104
ui/components/MessageInputActions/Optimization.tsx
Normal file
104
ui/components/MessageInputActions/Optimization.tsx
Normal file
|
|
@ -0,0 +1,104 @@
|
|||
import { ChevronDown, Sliders, Star, Zap } from 'lucide-react';
|
||||
import { cn } from '@/lib/utils';
|
||||
import {
|
||||
Popover,
|
||||
PopoverButton,
|
||||
PopoverPanel,
|
||||
Transition,
|
||||
} from '@headlessui/react';
|
||||
import { Fragment } from 'react';
|
||||
|
||||
const OptimizationModes = [
|
||||
{
|
||||
key: 'speed',
|
||||
title: 'Speed',
|
||||
description: 'Prioritize speed and get the quickest possible answer.',
|
||||
icon: <Zap size={20} className="text-[#FF9800]" />,
|
||||
},
|
||||
{
|
||||
key: 'balanced',
|
||||
title: 'Balanced',
|
||||
description: 'Find the right balance between speed and accuracy',
|
||||
icon: <Sliders size={20} className="text-[#4CAF50]" />,
|
||||
},
|
||||
{
|
||||
key: 'quality',
|
||||
title: 'Quality (Soon)',
|
||||
description: 'Get the most thorough and accurate answer',
|
||||
icon: (
|
||||
<Star
|
||||
size={16}
|
||||
className="text-[#2196F3] dark:text-[#BBDEFB] fill-[#BBDEFB] dark:fill-[#2196F3]"
|
||||
/>
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
const Optimization = ({
|
||||
optimizationMode,
|
||||
setOptimizationMode,
|
||||
}: {
|
||||
optimizationMode: string;
|
||||
setOptimizationMode: (mode: string) => void;
|
||||
}) => {
|
||||
return (
|
||||
<Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
|
||||
<PopoverButton
|
||||
type="button"
|
||||
className="p-2 text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary active:scale-95 transition duration-200 hover:text-black dark:hover:text-white"
|
||||
>
|
||||
<div className="flex flex-row items-center space-x-1">
|
||||
{
|
||||
OptimizationModes.find((mode) => mode.key === optimizationMode)
|
||||
?.icon
|
||||
}
|
||||
<p className="text-xs font-medium">
|
||||
{
|
||||
OptimizationModes.find((mode) => mode.key === optimizationMode)
|
||||
?.title
|
||||
}
|
||||
</p>
|
||||
<ChevronDown size={20} />
|
||||
</div>
|
||||
</PopoverButton>
|
||||
<Transition
|
||||
as={Fragment}
|
||||
enter="transition ease-out duration-150"
|
||||
enterFrom="opacity-0 translate-y-1"
|
||||
enterTo="opacity-100 translate-y-0"
|
||||
leave="transition ease-in duration-150"
|
||||
leaveFrom="opacity-100 translate-y-0"
|
||||
leaveTo="opacity-0 translate-y-1"
|
||||
>
|
||||
<PopoverPanel className="absolute z-10 w-64 md:w-[250px] right-0">
|
||||
<div className="flex flex-col gap-2 bg-light-primary dark:bg-dark-primary border rounded-lg border-light-200 dark:border-dark-200 w-full p-4 max-h-[200px] md:max-h-none overflow-y-auto">
|
||||
{OptimizationModes.map((mode, i) => (
|
||||
<PopoverButton
|
||||
onClick={() => setOptimizationMode(mode.key)}
|
||||
key={i}
|
||||
disabled={mode.key === 'quality'}
|
||||
className={cn(
|
||||
'p-2 rounded-lg flex flex-col items-start justify-start text-start space-y-1 duration-200 cursor-pointer transition',
|
||||
optimizationMode === mode.key
|
||||
? 'bg-light-secondary dark:bg-dark-secondary'
|
||||
: 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
|
||||
mode.key === 'quality' && 'opacity-50 cursor-not-allowed',
|
||||
)}
|
||||
>
|
||||
<div className="flex flex-row items-center space-x-1 text-black dark:text-white">
|
||||
{mode.icon}
|
||||
<p className="text-sm font-medium">{mode.title}</p>
|
||||
</div>
|
||||
<p className="text-black/70 dark:text-white/70 text-xs">
|
||||
{mode.description}
|
||||
</p>
|
||||
</PopoverButton>
|
||||
))}
|
||||
</div>
|
||||
</PopoverPanel>
|
||||
</Transition>
|
||||
</Popover>
|
||||
);
|
||||
};
|
||||
|
||||
export default Optimization;
|
||||
|
|
@ -1,5 +1,11 @@
|
|||
/* eslint-disable @next/next/no-img-element */
|
||||
import { Dialog, Transition } from '@headlessui/react';
|
||||
import {
|
||||
Dialog,
|
||||
DialogPanel,
|
||||
DialogTitle,
|
||||
Transition,
|
||||
TransitionChild,
|
||||
} from '@headlessui/react';
|
||||
import { Document } from '@langchain/core/documents';
|
||||
import { Fragment, useState } from 'react';
|
||||
|
||||
|
|
@ -74,7 +80,7 @@ const MessageSources = ({ sources }: { sources: Document[] }) => {
|
|||
<Dialog as="div" className="relative z-50" onClose={closeModal}>
|
||||
<div className="fixed inset-0 overflow-y-auto">
|
||||
<div className="flex min-h-full items-center justify-center p-4 text-center">
|
||||
<Transition.Child
|
||||
<TransitionChild
|
||||
as={Fragment}
|
||||
enter="ease-out duration-200"
|
||||
enterFrom="opacity-0 scale-95"
|
||||
|
|
@ -83,10 +89,10 @@ const MessageSources = ({ sources }: { sources: Document[] }) => {
|
|||
leaveFrom="opacity-100 scale-200"
|
||||
leaveTo="opacity-0 scale-95"
|
||||
>
|
||||
<Dialog.Panel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
|
||||
<Dialog.Title className="text-lg font-medium leading-6 dark:text-white">
|
||||
<DialogPanel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
|
||||
<DialogTitle className="text-lg font-medium leading-6 dark:text-white">
|
||||
Sources
|
||||
</Dialog.Title>
|
||||
</DialogTitle>
|
||||
<div className="grid grid-cols-2 gap-2 overflow-auto max-h-[300px] mt-2 pr-2">
|
||||
{sources.map((source, i) => (
|
||||
<a
|
||||
|
|
@ -122,8 +128,8 @@ const MessageSources = ({ sources }: { sources: Document[] }) => {
|
|||
</a>
|
||||
))}
|
||||
</div>
|
||||
</Dialog.Panel>
|
||||
</Transition.Child>
|
||||
</DialogPanel>
|
||||
</TransitionChild>
|
||||
</div>
|
||||
</div>
|
||||
</Dialog>
|
||||
|
|
|
|||
|
|
@ -51,7 +51,7 @@ const SearchImages = ({
|
|||
|
||||
const data = await res.json();
|
||||
|
||||
const images = data.images;
|
||||
const images = data.images ?? [];
|
||||
setImages(images);
|
||||
setSlides(
|
||||
images.map((image: Image) => {
|
||||
|
|
|
|||
|
|
@ -64,7 +64,7 @@ const Searchvideos = ({
|
|||
|
||||
const data = await res.json();
|
||||
|
||||
const videos = data.videos;
|
||||
const videos = data.videos ?? [];
|
||||
setVideos(videos);
|
||||
setSlides(
|
||||
videos.map((video: Video) => {
|
||||
|
|
|
|||
|
|
@ -1,5 +1,11 @@
|
|||
import { cn } from '@/lib/utils';
|
||||
import { Dialog, Transition } from '@headlessui/react';
|
||||
import {
|
||||
Dialog,
|
||||
DialogPanel,
|
||||
DialogTitle,
|
||||
Transition,
|
||||
TransitionChild,
|
||||
} from '@headlessui/react';
|
||||
import { CloudUpload, RefreshCcw, RefreshCw } from 'lucide-react';
|
||||
import React, {
|
||||
Fragment,
|
||||
|
|
@ -49,10 +55,10 @@ export const Select = ({ className, options, ...restProps }: SelectProps) => {
|
|||
|
||||
interface SettingsType {
|
||||
chatModelProviders: {
|
||||
[key: string]: string[];
|
||||
[key: string]: [Record<string, any>];
|
||||
};
|
||||
embeddingModelProviders: {
|
||||
[key: string]: string[];
|
||||
[key: string]: [Record<string, any>];
|
||||
};
|
||||
openaiApiKey: string;
|
||||
groqApiKey: string;
|
||||
|
|
@ -68,6 +74,10 @@ const SettingsDialog = ({
|
|||
setIsOpen: (isOpen: boolean) => void;
|
||||
}) => {
|
||||
const [config, setConfig] = useState<SettingsType | null>(null);
|
||||
const [chatModels, setChatModels] = useState<Record<string, any>>({});
|
||||
const [embeddingModels, setEmbeddingModels] = useState<Record<string, any>>(
|
||||
{},
|
||||
);
|
||||
const [selectedChatModelProvider, setSelectedChatModelProvider] = useState<
|
||||
string | null
|
||||
>(null);
|
||||
|
|
@ -118,7 +128,9 @@ const SettingsDialog = ({
|
|||
const chatModel =
|
||||
localStorage.getItem('chatModel') ||
|
||||
(data.chatModelProviders &&
|
||||
data.chatModelProviders[chatModelProvider]?.[0]) ||
|
||||
data.chatModelProviders[chatModelProvider]?.length > 0
|
||||
? data.chatModelProviders[chatModelProvider][0].name
|
||||
: undefined) ||
|
||||
'';
|
||||
const embeddingModelProvider =
|
||||
localStorage.getItem('embeddingModelProvider') ||
|
||||
|
|
@ -127,7 +139,7 @@ const SettingsDialog = ({
|
|||
const embeddingModel =
|
||||
localStorage.getItem('embeddingModel') ||
|
||||
(data.embeddingModelProviders &&
|
||||
data.embeddingModelProviders[embeddingModelProvider]?.[0]) ||
|
||||
data.embeddingModelProviders[embeddingModelProvider]?.[0].name) ||
|
||||
'';
|
||||
|
||||
setSelectedChatModelProvider(chatModelProvider);
|
||||
|
|
@ -136,6 +148,8 @@ const SettingsDialog = ({
|
|||
setSelectedEmbeddingModel(embeddingModel);
|
||||
setCustomOpenAIApiKey(localStorage.getItem('openAIApiKey') || '');
|
||||
setCustomOpenAIBaseURL(localStorage.getItem('openAIBaseURL') || '');
|
||||
setChatModels(data.chatModelProviders || {});
|
||||
setEmbeddingModels(data.embeddingModelProviders || {});
|
||||
setIsLoading(false);
|
||||
};
|
||||
|
||||
|
|
@ -182,7 +196,7 @@ const SettingsDialog = ({
|
|||
className="relative z-50"
|
||||
onClose={() => setIsOpen(false)}
|
||||
>
|
||||
<Transition.Child
|
||||
<TransitionChild
|
||||
as={Fragment}
|
||||
enter="ease-out duration-300"
|
||||
enterFrom="opacity-0"
|
||||
|
|
@ -192,10 +206,10 @@ const SettingsDialog = ({
|
|||
leaveTo="opacity-0"
|
||||
>
|
||||
<div className="fixed inset-0 bg-white/50 dark:bg-black/50" />
|
||||
</Transition.Child>
|
||||
</TransitionChild>
|
||||
<div className="fixed inset-0 overflow-y-auto">
|
||||
<div className="flex min-h-full items-center justify-center p-4 text-center">
|
||||
<Transition.Child
|
||||
<TransitionChild
|
||||
as={Fragment}
|
||||
enter="ease-out duration-200"
|
||||
enterFrom="opacity-0 scale-95"
|
||||
|
|
@ -204,10 +218,10 @@ const SettingsDialog = ({
|
|||
leaveFrom="opacity-100 scale-200"
|
||||
leaveTo="opacity-0 scale-95"
|
||||
>
|
||||
<Dialog.Panel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
|
||||
<Dialog.Title className="text-xl font-medium leading-6 dark:text-white">
|
||||
<DialogPanel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
|
||||
<DialogTitle className="text-xl font-medium leading-6 dark:text-white">
|
||||
Settings
|
||||
</Dialog.Title>
|
||||
</DialogTitle>
|
||||
{config && !isLoading && (
|
||||
<div className="flex flex-col space-y-4 mt-6">
|
||||
<div className="flex flex-col space-y-1">
|
||||
|
|
@ -225,9 +239,14 @@ const SettingsDialog = ({
|
|||
value={selectedChatModelProvider ?? undefined}
|
||||
onChange={(e) => {
|
||||
setSelectedChatModelProvider(e.target.value);
|
||||
setSelectedChatModel(
|
||||
config.chatModelProviders[e.target.value][0],
|
||||
);
|
||||
if (e.target.value === 'custom_openai') {
|
||||
setSelectedChatModel('');
|
||||
} else {
|
||||
setSelectedChatModel(
|
||||
config.chatModelProviders[e.target.value][0]
|
||||
.name,
|
||||
);
|
||||
}
|
||||
}}
|
||||
options={Object.keys(config.chatModelProviders).map(
|
||||
(provider) => ({
|
||||
|
|
@ -260,8 +279,8 @@ const SettingsDialog = ({
|
|||
return chatModelProvider
|
||||
? chatModelProvider.length > 0
|
||||
? chatModelProvider.map((model) => ({
|
||||
value: model,
|
||||
label: model,
|
||||
value: model.name,
|
||||
label: model.displayName,
|
||||
}))
|
||||
: [
|
||||
{
|
||||
|
|
@ -337,7 +356,8 @@ const SettingsDialog = ({
|
|||
onChange={(e) => {
|
||||
setSelectedEmbeddingModelProvider(e.target.value);
|
||||
setSelectedEmbeddingModel(
|
||||
config.embeddingModelProviders[e.target.value][0],
|
||||
config.embeddingModelProviders[e.target.value][0]
|
||||
.name,
|
||||
);
|
||||
}}
|
||||
options={Object.keys(
|
||||
|
|
@ -370,8 +390,8 @@ const SettingsDialog = ({
|
|||
return embeddingModelProvider
|
||||
? embeddingModelProvider.length > 0
|
||||
? embeddingModelProvider.map((model) => ({
|
||||
label: model,
|
||||
value: model,
|
||||
label: model.displayName,
|
||||
value: model.name,
|
||||
}))
|
||||
: [
|
||||
{
|
||||
|
|
@ -479,8 +499,8 @@ const SettingsDialog = ({
|
|||
)}
|
||||
</button>
|
||||
</div>
|
||||
</Dialog.Panel>
|
||||
</Transition.Child>
|
||||
</DialogPanel>
|
||||
</TransitionChild>
|
||||
</div>
|
||||
</div>
|
||||
</Dialog>
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "perplexica-frontend",
|
||||
"version": "1.8.0",
|
||||
"version": "1.9.1",
|
||||
"license": "MIT",
|
||||
"author": "ItzCrazyKns",
|
||||
"scripts": {
|
||||
|
|
@ -11,7 +11,7 @@
|
|||
"format:write": "prettier . --write"
|
||||
},
|
||||
"dependencies": {
|
||||
"@headlessui/react": "^1.7.18",
|
||||
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|
||||
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|
||||
"@langchain/openai": "^0.0.25",
|
||||
"@tailwindcss/typography": "^0.5.12",
|
||||
|
|
|
|||
138
ui/yarn.lock
138
ui/yarn.lock
|
|
@ -66,13 +66,51 @@
|
|||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
dependencies:
|
||||
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|
||||
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|
||||
"@react-aria/interactions" "^3.21.3"
|
||||
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|
||||
|
||||
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|
||||
version "0.11.14"
|
||||
|
|
@ -278,6 +316,57 @@
|
|||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"@react-types/shared" "^3.25.0"
|
||||
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|
||||
clsx "^2.0.0"
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
dependencies:
|
||||
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|
||||
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|
||||
"@react-types/shared" "^3.25.0"
|
||||
"@swc/helpers" "^0.5.0"
|
||||
clsx "^2.0.0"
|
||||
|
||||
"@react-stately/utils@^3.10.4":
|
||||
version "3.10.4"
|
||||
resolved "https://registry.yarnpkg.com/@react-stately/utils/-/utils-3.10.4.tgz#310663a834b67048d305e1680ed258130092fe51"
|
||||
integrity sha512-gBEQEIMRh5f60KCm7QKQ2WfvhB2gLUr9b72sqUdIZ2EG+xuPgaIlCBeSicvjmjBvYZwOjoOEnmIkcx2GHp/HWw==
|
||||
dependencies:
|
||||
"@swc/helpers" "^0.5.0"
|
||||
|
||||
"@react-types/shared@^3.25.0":
|
||||
version "3.25.0"
|
||||
resolved "https://registry.yarnpkg.com/@react-types/shared/-/shared-3.25.0.tgz#7223baf72256e918a3c29081bb1ecc6fad4fbf58"
|
||||
integrity sha512-OZSyhzU6vTdW3eV/mz5i6hQwQUhkRs7xwY2d1aqPvTdMe0+2cY7Fwp45PAiwYLEj73i9ro2FxF9qC4DvHGSCgQ==
|
||||
|
||||
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|
||||
version "1.10.1"
|
||||
resolved "https://registry.yarnpkg.com/@rushstack/eslint-patch/-/eslint-patch-1.10.1.tgz#7ca168b6937818e9a74b47ac4e2112b2e1a024cf"
|
||||
|
|
@ -290,6 +379,13 @@
|
|||
dependencies:
|
||||
tslib "^2.4.0"
|
||||
|
||||
"@swc/helpers@^0.5.0":
|
||||
version "0.5.13"
|
||||
resolved "https://registry.yarnpkg.com/@swc/helpers/-/helpers-0.5.13.tgz#33e63ff3cd0cade557672bd7888a39ce7d115a8c"
|
||||
integrity sha512-UoKGxQ3r5kYI9dALKJapMmuK+1zWM/H17Z1+iwnNmzcJRnfFuevZs375TA5rW31pu4BS4NoSy1fRsexDXfWn5w==
|
||||
dependencies:
|
||||
tslib "^2.4.0"
|
||||
|
||||
"@tailwindcss/typography@^0.5.12":
|
||||
version "0.5.12"
|
||||
resolved "https://registry.yarnpkg.com/@tailwindcss/typography/-/typography-0.5.12.tgz#c0532fd594427b7f4e8e38eff7bf272c63a1dca4"
|
||||
|
|
@ -300,17 +396,17 @@
|
|||
lodash.merge "^4.6.2"
|
||||
postcss-selector-parser "6.0.10"
|
||||
|
||||
"@tanstack/react-virtual@^3.0.0-beta.60":
|
||||
version "3.2.0"
|
||||
resolved "https://registry.yarnpkg.com/@tanstack/react-virtual/-/react-virtual-3.2.0.tgz#fb70f9c6baee753a5a0f7618ac886205d5a02af9"
|
||||
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||||
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|
||||
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|
||||
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|
||||
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||||
dependencies:
|
||||
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|
||||
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|
||||
|
||||
"@tanstack/virtual-core@3.2.0":
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
"@types/json5@^0.0.29":
|
||||
version "0.0.29"
|
||||
|
|
@ -779,11 +875,16 @@ chokidar@^3.5.3:
|
|||
optionalDependencies:
|
||||
fsevents "~2.3.2"
|
||||
|
||||
client-only@0.0.1, client-only@^0.0.1:
|
||||
client-only@0.0.1:
|
||||
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|
||||
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|
||||
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|
||||
|
||||
clsx@^2.0.0:
|
||||
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|
||||
resolved "https://registry.yarnpkg.com/clsx/-/clsx-2.1.1.tgz#eed397c9fd8bd882bfb18deab7102049a2f32999"
|
||||
integrity sha512-eYm0QWBtUrBWZWG0d386OGAw16Z995PiOVo2B7bjWSbHedGl5e0ZWaq65kOGgUSNesEIDkB9ISbTg/JK9dhCZA==
|
||||
|
||||
clsx@^2.1.0:
|
||||
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|
||||
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|
||||
|
|
@ -2995,6 +3096,11 @@ supports-preserve-symlinks-flag@^1.0.0:
|
|||
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|
||||
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||||
|
||||
tabbable@^6.0.0:
|
||||
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|
||||
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|
||||
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||||
|
||||
tailwind-merge@^2.2.2:
|
||||
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|
||||
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|
||||
|
|
|
|||
131
yarn.lock
131
yarn.lock
|
|
@ -509,6 +509,14 @@
|
|||
resolved "https://registry.yarnpkg.com/@protobufjs/utf8/-/utf8-1.1.0.tgz#a777360b5b39a1a2e5106f8e858f2fd2d060c570"
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
dependencies:
|
||||
domhandler "^5.0.3"
|
||||
selderee "^0.11.0"
|
||||
|
||||
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|
||||
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|
||||
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|
||||
|
|
@ -578,6 +586,11 @@
|
|||
"@types/qs" "*"
|
||||
"@types/serve-static" "*"
|
||||
|
||||
"@types/html-to-text@^9.0.4":
|
||||
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|
||||
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|
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||||
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|
||||
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|
||||
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|
||||
|
|
@ -622,6 +635,11 @@
|
|||
dependencies:
|
||||
undici-types "~5.26.4"
|
||||
|
||||
"@types/pdf-parse@^1.1.4":
|
||||
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|
||||
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|
||||
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||||
|
||||
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|
||||
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|
||||
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|
||||
|
|
@ -672,6 +690,13 @@
|
|||
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|
||||
integrity sha512-jg+97EGIcY9AGHJJRaaPVgetKDsrTgbRjQ5Msgjh/DQKEFl0DtyRr/VCOyD1T2R1MNeWPK/u7JoGhlDZnKBAfA==
|
||||
|
||||
"@types/ws@^8.5.12":
|
||||
version "8.5.12"
|
||||
resolved "https://registry.yarnpkg.com/@types/ws/-/ws-8.5.12.tgz#619475fe98f35ccca2a2f6c137702d85ec247b7e"
|
||||
integrity sha512-3tPRkv1EtkDpzlgyKyI8pGsGZAGPEaXeu0DOj5DI25Ja91bdAYddYHbADRYVrZMRbfW+1l5YwXVDKohDJNQxkQ==
|
||||
dependencies:
|
||||
"@types/node" "*"
|
||||
|
||||
"@xenova/transformers@^2.17.1":
|
||||
version "2.17.1"
|
||||
resolved "https://registry.yarnpkg.com/@xenova/transformers/-/transformers-2.17.1.tgz#712f7a72c76c8aa2075749382f83dc7dd4e5a9a5"
|
||||
|
|
@ -1092,6 +1117,13 @@ debug@2.6.9:
|
|||
dependencies:
|
||||
ms "2.0.0"
|
||||
|
||||
debug@^3.1.0:
|
||||
version "3.2.7"
|
||||
resolved "https://registry.yarnpkg.com/debug/-/debug-3.2.7.tgz#72580b7e9145fb39b6676f9c5e5fb100b934179a"
|
||||
integrity sha512-CFjzYYAi4ThfiQvizrFQevTTXHtnCqWfe7x1AhgEscTz6ZbLbfoLRLPugTQyBth6f8ZERVUSyWHFD/7Wu4t1XQ==
|
||||
dependencies:
|
||||
ms "^2.1.1"
|
||||
|
||||
debug@^4:
|
||||
version "4.3.4"
|
||||
resolved "https://registry.yarnpkg.com/debug/-/debug-4.3.4.tgz#1319f6579357f2338d3337d2cdd4914bb5dcc865"
|
||||
|
|
@ -1123,6 +1155,11 @@ deep-extend@^0.6.0:
|
|||
resolved "https://registry.yarnpkg.com/deep-extend/-/deep-extend-0.6.0.tgz#c4fa7c95404a17a9c3e8ca7e1537312b736330ac"
|
||||
integrity sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA==
|
||||
|
||||
deepmerge@^4.3.1:
|
||||
version "4.3.1"
|
||||
resolved "https://registry.yarnpkg.com/deepmerge/-/deepmerge-4.3.1.tgz#44b5f2147cd3b00d4b56137685966f26fd25dd4a"
|
||||
integrity sha512-3sUqbMEc77XqpdNO7FRyRog+eW3ph+GYCbj+rK+uYyRMuwsVy0rMiVtPn+QJlKFvWP/1PYpapqYn0Me2knFn+A==
|
||||
|
||||
define-data-property@^1.1.4:
|
||||
version "1.1.4"
|
||||
resolved "https://registry.yarnpkg.com/define-data-property/-/define-data-property-1.1.4.tgz#894dc141bb7d3060ae4366f6a0107e68fbe48c5e"
|
||||
|
|
@ -1165,6 +1202,36 @@ digest-fetch@^1.3.0:
|
|||
base-64 "^0.1.0"
|
||||
md5 "^2.3.0"
|
||||
|
||||
dom-serializer@^2.0.0:
|
||||
version "2.0.0"
|
||||
resolved "https://registry.yarnpkg.com/dom-serializer/-/dom-serializer-2.0.0.tgz#e41b802e1eedf9f6cae183ce5e622d789d7d8e53"
|
||||
integrity sha512-wIkAryiqt/nV5EQKqQpo3SToSOV9J0DnbJqwK7Wv/Trc92zIAYZ4FlMu+JPFW1DfGFt81ZTCGgDEabffXeLyJg==
|
||||
dependencies:
|
||||
domelementtype "^2.3.0"
|
||||
domhandler "^5.0.2"
|
||||
entities "^4.2.0"
|
||||
|
||||
domelementtype@^2.3.0:
|
||||
version "2.3.0"
|
||||
resolved "https://registry.yarnpkg.com/domelementtype/-/domelementtype-2.3.0.tgz#5c45e8e869952626331d7aab326d01daf65d589d"
|
||||
integrity sha512-OLETBj6w0OsagBwdXnPdN0cnMfF9opN69co+7ZrbfPGrdpPVNBUj02spi6B1N7wChLQiPn4CSH/zJvXw56gmHw==
|
||||
|
||||
domhandler@^5.0.2, domhandler@^5.0.3:
|
||||
version "5.0.3"
|
||||
resolved "https://registry.yarnpkg.com/domhandler/-/domhandler-5.0.3.tgz#cc385f7f751f1d1fc650c21374804254538c7d31"
|
||||
integrity sha512-cgwlv/1iFQiFnU96XXgROh8xTeetsnJiDsTc7TYCLFd9+/WNkIqPTxiM/8pSd8VIrhXGTf1Ny1q1hquVqDJB5w==
|
||||
dependencies:
|
||||
domelementtype "^2.3.0"
|
||||
|
||||
domutils@^3.0.1:
|
||||
version "3.1.0"
|
||||
resolved "https://registry.yarnpkg.com/domutils/-/domutils-3.1.0.tgz#c47f551278d3dc4b0b1ab8cbb42d751a6f0d824e"
|
||||
integrity sha512-H78uMmQtI2AhgDJjWeQmHwJJ2bLPD3GMmO7Zja/ZZh84wkm+4ut+IUnUdRa8uCGX88DiVx1j6FRe1XfxEgjEZA==
|
||||
dependencies:
|
||||
dom-serializer "^2.0.0"
|
||||
domelementtype "^2.3.0"
|
||||
domhandler "^5.0.3"
|
||||
|
||||
dotenv@^16.4.5:
|
||||
version "16.4.5"
|
||||
resolved "https://registry.yarnpkg.com/dotenv/-/dotenv-16.4.5.tgz#cdd3b3b604cb327e286b4762e13502f717cb099f"
|
||||
|
|
@ -1206,6 +1273,11 @@ end-of-stream@^1.1.0, end-of-stream@^1.4.1:
|
|||
dependencies:
|
||||
once "^1.4.0"
|
||||
|
||||
entities@^4.2.0, entities@^4.4.0:
|
||||
version "4.5.0"
|
||||
resolved "https://registry.yarnpkg.com/entities/-/entities-4.5.0.tgz#5d268ea5e7113ec74c4d033b79ea5a35a488fb48"
|
||||
integrity sha512-V0hjH4dGPh9Ao5p0MoRY6BVqtwCjhz6vI5LT8AJ55H+4g9/4vbHx1I54fS0XuclLhDHArPQCiMjDxjaL8fPxhw==
|
||||
|
||||
es-define-property@^1.0.0:
|
||||
version "1.0.0"
|
||||
resolved "https://registry.yarnpkg.com/es-define-property/-/es-define-property-1.0.0.tgz#c7faefbdff8b2696cf5f46921edfb77cc4ba3845"
|
||||
|
|
@ -1529,6 +1601,27 @@ hasown@^2.0.0:
|
|||
dependencies:
|
||||
function-bind "^1.1.2"
|
||||
|
||||
html-to-text@^9.0.5:
|
||||
version "9.0.5"
|
||||
resolved "https://registry.yarnpkg.com/html-to-text/-/html-to-text-9.0.5.tgz#6149a0f618ae7a0db8085dca9bbf96d32bb8368d"
|
||||
integrity sha512-qY60FjREgVZL03vJU6IfMV4GDjGBIoOyvuFdpBDIX9yTlDw0TjxVBQp+P8NvpdIXNJvfWBTNul7fsAQJq2FNpg==
|
||||
dependencies:
|
||||
"@selderee/plugin-htmlparser2" "^0.11.0"
|
||||
deepmerge "^4.3.1"
|
||||
dom-serializer "^2.0.0"
|
||||
htmlparser2 "^8.0.2"
|
||||
selderee "^0.11.0"
|
||||
|
||||
htmlparser2@^8.0.2:
|
||||
version "8.0.2"
|
||||
resolved "https://registry.yarnpkg.com/htmlparser2/-/htmlparser2-8.0.2.tgz#f002151705b383e62433b5cf466f5b716edaec21"
|
||||
integrity sha512-GYdjWKDkbRLkZ5geuHs5NY1puJ+PXwP7+fHPRz06Eirsb9ugf6d8kkXav6ADhcODhFFPMIXyxkxSuMf3D6NCFA==
|
||||
dependencies:
|
||||
domelementtype "^2.3.0"
|
||||
domhandler "^5.0.3"
|
||||
domutils "^3.0.1"
|
||||
entities "^4.4.0"
|
||||
|
||||
http-errors@2.0.0:
|
||||
version "2.0.0"
|
||||
resolved "https://registry.yarnpkg.com/http-errors/-/http-errors-2.0.0.tgz#b7774a1486ef73cf7667ac9ae0858c012c57b9d3"
|
||||
|
|
@ -1727,6 +1820,11 @@ langsmith@~0.1.30:
|
|||
p-retry "4"
|
||||
uuid "^9.0.0"
|
||||
|
||||
leac@^0.6.0:
|
||||
version "0.6.0"
|
||||
resolved "https://registry.yarnpkg.com/leac/-/leac-0.6.0.tgz#dcf136e382e666bd2475f44a1096061b70dc0912"
|
||||
integrity sha512-y+SqErxb8h7nE/fiEX07jsbuhrpO9lL8eca7/Y1nuWV2moNlXhyd59iDGcRf6moVyDMbmTNzL40SUyrFU/yDpg==
|
||||
|
||||
lodash.set@^4.3.2:
|
||||
version "4.3.2"
|
||||
resolved "https://registry.yarnpkg.com/lodash.set/-/lodash.set-4.3.2.tgz#d8757b1da807dde24816b0d6a84bea1a76230b23"
|
||||
|
|
@ -1907,6 +2005,11 @@ node-domexception@1.0.0:
|
|||
resolved "https://registry.yarnpkg.com/node-domexception/-/node-domexception-1.0.0.tgz#6888db46a1f71c0b76b3f7555016b63fe64766e5"
|
||||
integrity sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ==
|
||||
|
||||
node-ensure@^0.0.0:
|
||||
version "0.0.0"
|
||||
resolved "https://registry.yarnpkg.com/node-ensure/-/node-ensure-0.0.0.tgz#ecae764150de99861ec5c810fd5d096b183932a7"
|
||||
integrity sha512-DRI60hzo2oKN1ma0ckc6nQWlHU69RH6xN0sjQTjMpChPfTYvKZdcQFfdYK2RWbJcKyUizSIy/l8OTGxMAM1QDw==
|
||||
|
||||
node-fetch@^2.6.7:
|
||||
version "2.7.0"
|
||||
resolved "https://registry.yarnpkg.com/node-fetch/-/node-fetch-2.7.0.tgz#d0f0fa6e3e2dc1d27efcd8ad99d550bda94d187d"
|
||||
|
|
@ -2071,6 +2174,14 @@ p-timeout@^3.2.0:
|
|||
dependencies:
|
||||
p-finally "^1.0.0"
|
||||
|
||||
parseley@^0.12.0:
|
||||
version "0.12.1"
|
||||
resolved "https://registry.yarnpkg.com/parseley/-/parseley-0.12.1.tgz#4afd561d50215ebe259e3e7a853e62f600683aef"
|
||||
integrity sha512-e6qHKe3a9HWr0oMRVDTRhKce+bRO8VGQR3NyVwcjwrbhMmFCX9KszEV35+rn4AdilFAq9VPxP/Fe1wC9Qjd2lw==
|
||||
dependencies:
|
||||
leac "^0.6.0"
|
||||
peberminta "^0.9.0"
|
||||
|
||||
parseurl@~1.3.3:
|
||||
version "1.3.3"
|
||||
resolved "https://registry.yarnpkg.com/parseurl/-/parseurl-1.3.3.tgz#9da19e7bee8d12dff0513ed5b76957793bc2e8d4"
|
||||
|
|
@ -2081,6 +2192,19 @@ path-to-regexp@0.1.7:
|
|||
resolved "https://registry.yarnpkg.com/path-to-regexp/-/path-to-regexp-0.1.7.tgz#df604178005f522f15eb4490e7247a1bfaa67f8c"
|
||||
integrity sha512-5DFkuoqlv1uYQKxy8omFBeJPQcdoE07Kv2sferDCrAq1ohOU+MSDswDIbnx3YAM60qIOnYa53wBhXW0EbMonrQ==
|
||||
|
||||
pdf-parse@^1.1.1:
|
||||
version "1.1.1"
|
||||
resolved "https://registry.yarnpkg.com/pdf-parse/-/pdf-parse-1.1.1.tgz#745e07408679548b3995ff896fd38e96e19d14a7"
|
||||
integrity sha512-v6ZJ/efsBpGrGGknjtq9J/oC8tZWq0KWL5vQrk2GlzLEQPUDB1ex+13Rmidl1neNN358Jn9EHZw5y07FFtaC7A==
|
||||
dependencies:
|
||||
debug "^3.1.0"
|
||||
node-ensure "^0.0.0"
|
||||
|
||||
peberminta@^0.9.0:
|
||||
version "0.9.0"
|
||||
resolved "https://registry.yarnpkg.com/peberminta/-/peberminta-0.9.0.tgz#8ec9bc0eb84b7d368126e71ce9033501dca2a352"
|
||||
integrity sha512-XIxfHpEuSJbITd1H3EeQwpcZbTLHc+VVr8ANI9t5sit565tsI4/xK3KWTUFE2e6QiangUkh3B0jihzmGnNrRsQ==
|
||||
|
||||
picomatch@^2.0.4, picomatch@^2.2.1:
|
||||
version "2.3.1"
|
||||
resolved "https://registry.yarnpkg.com/picomatch/-/picomatch-2.3.1.tgz#3ba3833733646d9d3e4995946c1365a67fb07a42"
|
||||
|
|
@ -2242,6 +2366,13 @@ safe-stable-stringify@^2.3.1:
|
|||
resolved "https://registry.yarnpkg.com/safer-buffer/-/safer-buffer-2.1.2.tgz#44fa161b0187b9549dd84bb91802f9bd8385cd6a"
|
||||
integrity sha512-YZo3K82SD7Riyi0E1EQPojLz7kpepnSQI9IyPbHHg1XXXevb5dJI7tpyN2ADxGcQbHG7vcyRHk0cbwqcQriUtg==
|
||||
|
||||
selderee@^0.11.0:
|
||||
version "0.11.0"
|
||||
resolved "https://registry.yarnpkg.com/selderee/-/selderee-0.11.0.tgz#6af0c7983e073ad3e35787ffe20cefd9daf0ec8a"
|
||||
integrity sha512-5TF+l7p4+OsnP8BCCvSyZiSPc4x4//p5uPwK8TCnVPJYRmU2aYKMpOXvw8zM5a5JvuuCGN1jmsMwuU2W02ukfA==
|
||||
dependencies:
|
||||
parseley "^0.12.0"
|
||||
|
||||
semver@^7.3.5, semver@^7.5.3, semver@^7.5.4:
|
||||
version "7.6.0"
|
||||
resolved "https://registry.yarnpkg.com/semver/-/semver-7.6.0.tgz#1a46a4db4bffcccd97b743b5005c8325f23d4e2d"
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue