Unverified Commit ddc8d22e authored by Timothy Jaeryang Baek's avatar Timothy Jaeryang Baek Committed by GitHub
Browse files

Merge pull request #2599 from open-webui/websearch

feat: websearch
parents b6b71c08 66734a70
......@@ -11,7 +11,7 @@ from fastapi.middleware.cors import CORSMiddleware
import os, shutil, logging, re
from pathlib import Path
from typing import List
from typing import List, Union, Sequence
from chromadb.utils.batch_utils import create_batches
......@@ -59,6 +59,7 @@ from apps.rag.utils import (
query_doc_with_hybrid_search,
query_collection,
query_collection_with_hybrid_search,
search_web,
)
from utils.misc import (
......@@ -95,6 +96,7 @@ from config import (
RAG_TEMPLATE,
ENABLE_RAG_LOCAL_WEB_FETCH,
YOUTUBE_LOADER_LANGUAGE,
RAG_WEB_SEARCH_CONCURRENT_REQUESTS,
AppConfig,
)
......@@ -201,6 +203,10 @@ class UrlForm(CollectionNameForm):
url: str
class SearchForm(CollectionNameForm):
query: str
@app.get("/")
async def get_status():
return {
......@@ -589,24 +595,40 @@ def store_web(form_data: UrlForm, user=Depends(get_current_user)):
)
def get_web_loader(url: str, verify_ssl: bool = True):
def get_web_loader(url: Union[str, Sequence[str]], verify_ssl: bool = True):
# Check if the URL is valid
if isinstance(validators.url(url), validators.ValidationError):
if not validate_url(url):
raise ValueError(ERROR_MESSAGES.INVALID_URL)
if not ENABLE_RAG_LOCAL_WEB_FETCH:
# Local web fetch is disabled, filter out any URLs that resolve to private IP addresses
parsed_url = urllib.parse.urlparse(url)
# Get IPv4 and IPv6 addresses
ipv4_addresses, ipv6_addresses = resolve_hostname(parsed_url.hostname)
# Check if any of the resolved addresses are private
# This is technically still vulnerable to DNS rebinding attacks, as we don't control WebBaseLoader
for ip in ipv4_addresses:
if validators.ipv4(ip, private=True):
raise ValueError(ERROR_MESSAGES.INVALID_URL)
for ip in ipv6_addresses:
if validators.ipv6(ip, private=True):
raise ValueError(ERROR_MESSAGES.INVALID_URL)
return WebBaseLoader(url, verify_ssl=verify_ssl)
return WebBaseLoader(
url,
verify_ssl=verify_ssl,
requests_per_second=RAG_WEB_SEARCH_CONCURRENT_REQUESTS,
continue_on_failure=True,
)
def validate_url(url: Union[str, Sequence[str]]):
if isinstance(url, str):
if isinstance(validators.url(url), validators.ValidationError):
raise ValueError(ERROR_MESSAGES.INVALID_URL)
if not ENABLE_RAG_LOCAL_WEB_FETCH:
# Local web fetch is disabled, filter out any URLs that resolve to private IP addresses
parsed_url = urllib.parse.urlparse(url)
# Get IPv4 and IPv6 addresses
ipv4_addresses, ipv6_addresses = resolve_hostname(parsed_url.hostname)
# Check if any of the resolved addresses are private
# This is technically still vulnerable to DNS rebinding attacks, as we don't control WebBaseLoader
for ip in ipv4_addresses:
if validators.ipv4(ip, private=True):
raise ValueError(ERROR_MESSAGES.INVALID_URL)
for ip in ipv6_addresses:
if validators.ipv6(ip, private=True):
raise ValueError(ERROR_MESSAGES.INVALID_URL)
return True
elif isinstance(url, Sequence):
return all(validate_url(u) for u in url)
else:
return False
def resolve_hostname(hostname):
......@@ -620,6 +642,39 @@ def resolve_hostname(hostname):
return ipv4_addresses, ipv6_addresses
@app.post("/web/search")
def store_web_search(form_data: SearchForm, user=Depends(get_current_user)):
try:
try:
web_results = search_web(form_data.query)
except Exception as e:
log.exception(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.WEB_SEARCH_ERROR,
)
urls = [result.link for result in web_results]
loader = get_web_loader(urls)
data = loader.load()
collection_name = form_data.collection_name
if collection_name == "":
collection_name = calculate_sha256_string(form_data.query)[:63]
store_data_in_vector_db(data, collection_name, overwrite=True)
return {
"status": True,
"collection_name": collection_name,
"filenames": urls,
}
except Exception as e:
log.exception(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e),
)
def store_data_in_vector_db(data, collection_name, overwrite: bool = False) -> bool:
text_splitter = RecursiveCharacterTextSplitter(
......
import logging
import requests
from apps.rag.search.main import SearchResult
from config import SRC_LOG_LEVELS, RAG_WEB_SEARCH_RESULT_COUNT
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["RAG"])
def search_brave(api_key: str, query: str) -> list[SearchResult]:
"""Search using Brave's Search API and return the results as a list of SearchResult objects.
Args:
api_key (str): A Brave Search API key
query (str): The query to search for
"""
url = "https://api.search.brave.com/res/v1/web/search"
headers = {
"Accept": "application/json",
"Accept-Encoding": "gzip",
"X-Subscription-Token": api_key,
}
params = {"q": query, "count": RAG_WEB_SEARCH_RESULT_COUNT}
response = requests.get(url, headers=headers, params=params)
response.raise_for_status()
json_response = response.json()
results = json_response.get("web", {}).get("results", [])
return [
SearchResult(
link=result["url"], title=result.get("title"), snippet=result.get("snippet")
)
for result in results[:RAG_WEB_SEARCH_RESULT_COUNT]
]
import json
import logging
import requests
from apps.rag.search.main import SearchResult
from config import SRC_LOG_LEVELS, RAG_WEB_SEARCH_RESULT_COUNT
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["RAG"])
def search_google_pse(
api_key: str, search_engine_id: str, query: str
) -> list[SearchResult]:
"""Search using Google's Programmable Search Engine API and return the results as a list of SearchResult objects.
Args:
api_key (str): A Programmable Search Engine API key
search_engine_id (str): A Programmable Search Engine ID
query (str): The query to search for
"""
url = "https://www.googleapis.com/customsearch/v1"
headers = {"Content-Type": "application/json"}
params = {
"cx": search_engine_id,
"q": query,
"key": api_key,
"num": RAG_WEB_SEARCH_RESULT_COUNT,
}
response = requests.request("GET", url, headers=headers, params=params)
response.raise_for_status()
json_response = response.json()
results = json_response.get("items", [])
return [
SearchResult(
link=result["link"],
title=result.get("title"),
snippet=result.get("snippet"),
)
for result in results
]
from typing import Optional
from pydantic import BaseModel
class SearchResult(BaseModel):
link: str
title: Optional[str]
snippet: Optional[str]
import logging
import requests
from apps.rag.search.main import SearchResult
from config import SRC_LOG_LEVELS, RAG_WEB_SEARCH_RESULT_COUNT
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["RAG"])
def search_searxng(query_url: str, query: str) -> list[SearchResult]:
"""Search a SearXNG instance for a query and return the results as a list of SearchResult objects.
Args:
query_url (str): The URL of the SearXNG instance to search. Must contain "<query>" as a placeholder
query (str): The query to search for
"""
url = query_url.replace("<query>", query)
if "&format=json" not in url:
url += "&format=json"
log.debug(f"searching {url}")
r = requests.get(
url,
headers={
"User-Agent": "Open WebUI (https://github.com/open-webui/open-webui) RAG Bot",
"Accept": "text/html",
"Accept-Encoding": "gzip, deflate",
"Accept-Language": "en-US,en;q=0.5",
"Connection": "keep-alive",
},
)
r.raise_for_status()
json_response = r.json()
results = json_response.get("results", [])
sorted_results = sorted(results, key=lambda x: x.get("score", 0), reverse=True)
return [
SearchResult(
link=result["url"], title=result.get("title"), snippet=result.get("content")
)
for result in sorted_results[:RAG_WEB_SEARCH_RESULT_COUNT]
]
import json
import logging
import requests
from apps.rag.search.main import SearchResult
from config import SRC_LOG_LEVELS, RAG_WEB_SEARCH_RESULT_COUNT
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["RAG"])
def search_serper(api_key: str, query: str) -> list[SearchResult]:
"""Search using serper.dev's API and return the results as a list of SearchResult objects.
Args:
api_key (str): A serper.dev API key
query (str): The query to search for
"""
url = "https://google.serper.dev/search"
payload = json.dumps({"q": query})
headers = {"X-API-KEY": api_key, "Content-Type": "application/json"}
response = requests.request("POST", url, headers=headers, data=payload)
response.raise_for_status()
json_response = response.json()
results = sorted(
json_response.get("organic", []), key=lambda x: x.get("position", 0)
)
return [
SearchResult(
link=result["link"],
title=result.get("title"),
snippet=result.get("description"),
)
for result in results[:RAG_WEB_SEARCH_RESULT_COUNT]
]
import json
import logging
import requests
from apps.rag.search.main import SearchResult
from config import SRC_LOG_LEVELS, RAG_WEB_SEARCH_RESULT_COUNT
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["RAG"])
def search_serpstack(
api_key: str, query: str, https_enabled: bool = True
) -> list[SearchResult]:
"""Search using serpstack.com's and return the results as a list of SearchResult objects.
Args:
api_key (str): A serpstack.com API key
query (str): The query to search for
https_enabled (bool): Whether to use HTTPS or HTTP for the API request
"""
url = f"{'https' if https_enabled else 'http'}://api.serpstack.com/search"
headers = {"Content-Type": "application/json"}
params = {
"access_key": api_key,
"query": query,
}
response = requests.request("POST", url, headers=headers, params=params)
response.raise_for_status()
json_response = response.json()
results = sorted(
json_response.get("organic_results", []), key=lambda x: x.get("position", 0)
)
return [
SearchResult(
link=result["url"], title=result.get("title"), snippet=result.get("snippet")
)
for result in results[:RAG_WEB_SEARCH_RESULT_COUNT]
]
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{
"query": "python",
"number_of_results": 116000000,
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"url": "https://www.python.org/",
"title": "Welcome to Python.org",
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"value": "Chicago, IL"
},
{
"attribute": "kc:/organization/organization:president",
"link": "http://www.google.com/search?safe=0\u0026sca_esv=c9c7fd42856085e2\u0026sca_upv=1\u0026gl=us\u0026hl=en\u0026q=Chris+Kempczinski\u0026si=ACC90nwLLwns5sISZcdzuISy7t-NHozt8Cbt6G3WNQfC9ekAgKFbjdEFCDgxLbt57EDZGosYDGiZuq1AcBhA6IhTOSZxfVSySuGQ3VDwmmTA7Z93n3K3596jAuZH9VVv5h8PyvKJSuGuSsQWviJTl3eKj2UL1ZIWuDgkjyVMnC47rN7j0G9PlHRCCLdQF7VDQ1gubTiC4onXqLRBTbwAj6a--PD6Jv_NoA%3D%3D\u0026sa=X\u0026ved=2ahUKEwjF55alk_iFAxXlamwGHbqgAs4QmxMoAHoECHEQAg",
"name": "President: ",
"value": "Chris Kempczinski"
}
],
"website": "https://www.mcdonalds.com/us/en-us.html",
"profiles": [
{
"name": "Instagram",
"url": "https://www.instagram.com/McDonalds"
},
{
"name": "X (Twitter)",
"url": "https://twitter.com/McDonalds"
},
{
"name": "Facebook",
"url": "https://www.facebook.com/McDonaldsUS"
},
{
"name": "YouTube",
"url": "https://www.youtube.com/user/McDonaldsUS"
},
{
"name": "Pinterest",
"url": "https://www.pinterest.com/mcdonalds"
}
],
"founded": "April 15, 1955, Des Plaines, IL",
"headquarters": "Chicago, IL",
"founders": [
{
"name": "Ray Kroc",
"link": "http://www.google.com/search?safe=0\u0026sca_esv=c9c7fd42856085e2\u0026sca_upv=1\u0026gl=us\u0026hl=en\u0026q=Ray+Kroc\u0026si=ACC90nzx_D3_zUKRnpAjmO0UBLNxnt7EyN4YYdru6U3bxLI-LxARWRdbk5SkoY2sDn5Qq7yOmqYGei6qZ7sfJhsjZXBPgjMlLbS7824rpJOm69GzqVWMdoNIZiFX2T4A2td14sZOn4a1BexZLtZXHU7NZdF6VsWbGMVuiSYtXdev7uaUjEJKumiwlqTAATTebOriYTEBuSzC\u0026sa=X\u0026ved=2ahUKEwjF55alk_iFAxXlamwGHbqgAs4QmxMoAHoECHgQAg"
}
]
}
}
......@@ -19,8 +19,24 @@ from langchain.retrievers import (
)
from typing import Optional
from config import SRC_LOG_LEVELS, CHROMA_CLIENT
from apps.rag.search.brave import search_brave
from apps.rag.search.google_pse import search_google_pse
from apps.rag.search.main import SearchResult
from apps.rag.search.searxng import search_searxng
from apps.rag.search.serper import search_serper
from apps.rag.search.serpstack import search_serpstack
from config import (
SRC_LOG_LEVELS,
CHROMA_CLIENT,
SEARXNG_QUERY_URL,
GOOGLE_PSE_API_KEY,
GOOGLE_PSE_ENGINE_ID,
BRAVE_SEARCH_API_KEY,
SERPSTACK_API_KEY,
SERPSTACK_HTTPS,
SERPER_API_KEY,
)
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["RAG"])
......@@ -520,3 +536,31 @@ class RerankCompressor(BaseDocumentCompressor):
)
final_results.append(doc)
return final_results
def search_web(query: str) -> list[SearchResult]:
"""Search the web using a search engine and return the results as a list of SearchResult objects.
Will look for a search engine API key in environment variables in the following order:
- SEARXNG_QUERY_URL
- GOOGLE_PSE_API_KEY + GOOGLE_PSE_ENGINE_ID
- BRAVE_SEARCH_API_KEY
- SERPSTACK_API_KEY
- SERPER_API_KEY
Args:
query (str): The query to search for
"""
# TODO: add playwright to search the web
if SEARXNG_QUERY_URL:
return search_searxng(SEARXNG_QUERY_URL, query)
elif GOOGLE_PSE_API_KEY and GOOGLE_PSE_ENGINE_ID:
return search_google_pse(GOOGLE_PSE_API_KEY, GOOGLE_PSE_ENGINE_ID, query)
elif BRAVE_SEARCH_API_KEY:
return search_brave(BRAVE_SEARCH_API_KEY, query)
elif SERPSTACK_API_KEY:
return search_serpstack(SERPSTACK_API_KEY, query, https_enabled=SERPSTACK_HTTPS)
elif SERPER_API_KEY:
return search_serper(SERPER_API_KEY, query)
else:
raise Exception("No search engine API key found in environment variables")
......@@ -574,6 +574,7 @@ ENABLE_COMMUNITY_SHARING = PersistentConfig(
os.environ.get("ENABLE_COMMUNITY_SHARING", "True").lower() == "true",
)
class BannerModel(BaseModel):
id: str
type: str
......@@ -765,6 +766,28 @@ YOUTUBE_LOADER_LANGUAGE = PersistentConfig(
os.getenv("YOUTUBE_LOADER_LANGUAGE", "en").split(","),
)
SEARXNG_QUERY_URL = os.getenv("SEARXNG_QUERY_URL", "")
GOOGLE_PSE_API_KEY = os.getenv("GOOGLE_PSE_API_KEY", "")
GOOGLE_PSE_ENGINE_ID = os.getenv("GOOGLE_PSE_ENGINE_ID", "")
BRAVE_SEARCH_API_KEY = os.getenv("BRAVE_SEARCH_API_KEY", "")
SERPSTACK_API_KEY = os.getenv("SERPSTACK_API_KEY", "")
SERPSTACK_HTTPS = os.getenv("SERPSTACK_HTTPS", "True").lower() == "true"
SERPER_API_KEY = os.getenv("SERPER_API_KEY", "")
RAG_WEB_SEARCH_ENABLED = (
SEARXNG_QUERY_URL != ""
or (GOOGLE_PSE_API_KEY != "" and GOOGLE_PSE_ENGINE_ID != "")
or BRAVE_SEARCH_API_KEY != ""
or SERPSTACK_API_KEY != ""
or SERPER_API_KEY != ""
)
RAG_WEB_SEARCH_RESULT_COUNT = int(os.getenv("RAG_WEB_SEARCH_RESULT_COUNT", "3"))
RAG_WEB_SEARCH_CONCURRENT_REQUESTS = int(
os.getenv("RAG_WEB_SEARCH_CONCURRENT_REQUESTS", "10")
)
####################################
# Transcribe
####################################
......
......@@ -80,3 +80,7 @@ class ERROR_MESSAGES(str, Enum):
INVALID_URL = (
"Oops! The URL you provided is invalid. Please double-check and try again."
)
WEB_SEARCH_ERROR = (
"Oops! Something went wrong while searching the web. Please try again later."
)
......@@ -54,6 +54,7 @@ from config import (
SRC_LOG_LEVELS,
WEBHOOK_URL,
ENABLE_ADMIN_EXPORT,
RAG_WEB_SEARCH_ENABLED,
AppConfig,
WEBUI_BUILD_HASH,
)
......@@ -117,6 +118,14 @@ app.state.MODELS = {}
origins = ["*"]
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Custom middleware to add security headers
# class SecurityHeadersMiddleware(BaseHTTPMiddleware):
......@@ -220,15 +229,6 @@ class RAGMiddleware(BaseHTTPMiddleware):
app.add_middleware(RAGMiddleware)
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.middleware("http")
async def check_url(request: Request, call_next):
if len(app.state.MODELS) == 0:
......@@ -365,9 +365,10 @@ async def get_app_config():
"auth": WEBUI_AUTH,
"auth_trusted_header": bool(webui_app.state.AUTH_TRUSTED_EMAIL_HEADER),
"enable_signup": webui_app.state.config.ENABLE_SIGNUP,
"enable_web_search": RAG_WEB_SEARCH_ENABLED,
"enable_image_generation": images_app.state.config.ENABLED,
"enable_admin_export": ENABLE_ADMIN_EXPORT,
"enable_community_sharing": webui_app.state.config.ENABLE_COMMUNITY_SHARING,
"enable_admin_export": ENABLE_ADMIN_EXPORT,
},
}
......
import { OPENAI_API_BASE_URL } from '$lib/constants';
import { promptTemplate } from '$lib/utils';
import { type Model, models, settings } from '$lib/stores';
export const getOpenAIConfig = async (token: string = '') => {
let error = null;
......@@ -391,3 +392,71 @@ export const generateTitle = async (
return res?.choices[0]?.message?.content.replace(/["']/g, '') ?? 'New Chat';
};
export const generateSearchQuery = async (
token: string = '',
model: string,
previousMessages: string[],
prompt: string,
url: string = OPENAI_API_BASE_URL
): Promise<string | undefined> => {
let error = null;
// TODO: Allow users to specify the prompt
// Get the current date in the format "January 20, 2024"
const currentDate = new Intl.DateTimeFormat('en-US', {
year: 'numeric',
month: 'long',
day: '2-digit'
}).format(new Date());
const res = await fetch(`${url}/chat/completions`, {
method: 'POST',
headers: {
Accept: 'application/json',
'Content-Type': 'application/json',
Authorization: `Bearer ${token}`
},
body: JSON.stringify({
model: model,
// Few shot prompting
messages: [
{
role: 'assistant',
content: `You are tasked with generating web search queries. Give me an appropriate query to answer my question for google search. Answer with only the query. Today is ${currentDate}.`
},
{
role: 'user',
content: prompt
}
// {
// role: 'user',
// content:
// (previousMessages.length > 0
// ? `Previous Questions:\n${previousMessages.join('\n')}\n\n`
// : '') + `Current Question: ${prompt}`
// }
],
stream: false,
// Restricting the max tokens to 30 to avoid long search queries
max_tokens: 30
})
})
.then(async (res) => {
if (!res.ok) throw await res.json();
return res.json();
})
.catch((err) => {
console.log(err);
if ('detail' in err) {
error = err.detail;
}
return undefined;
});
if (error) {
throw error;
}
return res?.choices[0]?.message?.content.replace(/["']/g, '') ?? undefined;
};
......@@ -513,3 +513,35 @@ export const updateRerankingConfig = async (token: string, payload: RerankingMod
return res;
};
export const runWebSearch = async (
token: string,
query: string,
collection_name?: string
): Promise<SearchDocument | undefined> => {
return await fetch(`${RAG_API_BASE_URL}/web/search`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${token}`
},
body: JSON.stringify({
query,
collection_name: collection_name ?? ''
})
})
.then(async (res) => {
if (!res.ok) throw await res.json();
return res.json();
})
.catch((err) => {
console.log(err);
return undefined;
});
};
export interface SearchDocument {
status: boolean;
collection_name: string;
filenames: string[];
}
......@@ -31,7 +31,11 @@
getTagsById,
updateChatById
} from '$lib/apis/chats';
import { generateOpenAIChatCompletion, generateTitle } from '$lib/apis/openai';
import {
generateOpenAIChatCompletion,
generateSearchQuery,
generateTitle
} from '$lib/apis/openai';
import MessageInput from '$lib/components/chat/MessageInput.svelte';
import Messages from '$lib/components/chat/Messages.svelte';
......@@ -41,6 +45,7 @@
import { queryMemory } from '$lib/apis/memories';
import type { Writable } from 'svelte/store';
import type { i18n as i18nType } from 'i18next';
import { runWebSearch } from '$lib/apis/rag';
import Banner from '../common/Banner.svelte';
import { getUserSettings } from '$lib/apis/users';
......@@ -60,6 +65,8 @@
let selectedModels = [''];
let atSelectedModel: Model | undefined;
let webSearchEnabled = false;
let chat = null;
let tags = [];
......@@ -399,6 +406,10 @@
}
responseMessage.userContext = userContext;
if (webSearchEnabled) {
await getWebSearchResults(model.id, parentId, responseMessageId);
}
if (model?.owned_by === 'openai') {
await sendPromptOpenAI(model, prompt, responseMessageId, _chatId);
} else if (model) {
......@@ -413,6 +424,73 @@
await chats.set(await getChatList(localStorage.token));
};
const getWebSearchResults = async (model: string, parentId: string, responseId: string) => {
const responseMessage = history.messages[responseId];
responseMessage.status = {
done: false,
action: 'web_search',
description: $i18n.t('Generating search query')
};
messages = messages;
const prompt = history.messages[parentId].content;
let searchQuery = prompt;
if (prompt.length > 100) {
searchQuery = await generateChatSearchQuery(model, prompt);
if (!searchQuery) {
toast.warning($i18n.t('No search query generated'));
responseMessage.status = {
...responseMessage.status,
done: true,
error: true,
description: 'No search query generated'
};
messages = messages;
return;
}
}
responseMessage.status = {
...responseMessage.status,
description: $i18n.t("Searching the web for '{{searchQuery}}'", { searchQuery })
};
messages = messages;
const results = await runWebSearch(localStorage.token, searchQuery);
if (results === undefined) {
toast.warning($i18n.t('No search results found'));
responseMessage.status = {
...responseMessage.status,
done: true,
error: true,
description: 'No search results found'
};
messages = messages;
return;
}
responseMessage.status = {
...responseMessage.status,
done: true,
description: $i18n.t('Searched {{count}} sites', { count: results.filenames.length }),
urls: results.filenames
};
if (responseMessage?.files ?? undefined === undefined) {
responseMessage.files = [];
}
responseMessage.files.push({
collection_name: results.collection_name,
name: searchQuery,
type: 'web_search_results',
urls: results.filenames
});
messages = messages;
};
const sendPromptOllama = async (model, userPrompt, responseMessageId, _chatId) => {
model = model.id;
const responseMessage = history.messages[responseMessageId];
......@@ -475,7 +553,9 @@
const docs = messages
.filter((message) => message?.files ?? null)
.map((message) =>
message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
message.files.filter((item) =>
['doc', 'collection', 'web_search_results'].includes(item.type)
)
)
.flat(1);
......@@ -671,7 +751,9 @@
const docs = messages
.filter((message) => message?.files ?? null)
.map((message) =>
message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
message.files.filter((item) =>
['doc', 'collection', 'web_search_results'].includes(item.type)
)
)
.flat(1);
......@@ -907,7 +989,7 @@
const model = $models.filter((m) => m.id === responseMessage.model).at(0);
if (model) {
if (model?.external) {
if (model?.owned_by === 'openai') {
await sendPromptOpenAI(
model,
history.messages[responseMessage.parentId].content,
......@@ -932,7 +1014,7 @@
const model = $models.find((model) => model.id === selectedModels[0]);
const titleModelId =
model?.external ?? false
model?.owned_by === 'openai' ?? false
? $settings?.title?.modelExternal ?? selectedModels[0]
: $settings?.title?.model ?? selectedModels[0];
const titleModel = $models.find((model) => model.id === titleModelId);
......@@ -957,6 +1039,29 @@
}
};
const generateChatSearchQuery = async (modelId: string, prompt: string) => {
const model = $models.find((model) => model.id === modelId);
const taskModelId =
model?.owned_by === 'openai' ?? false
? $settings?.title?.modelExternal ?? modelId
: $settings?.title?.model ?? modelId;
const taskModel = $models.find((model) => model.id === taskModelId);
const previousMessages = messages
.filter((message) => message.role === 'user')
.map((message) => message.content);
return await generateSearchQuery(
localStorage.token,
taskModelId,
previousMessages,
prompt,
taskModel?.owned_by === 'openai' ?? false
? `${OPENAI_API_BASE_URL}`
: `${OLLAMA_API_BASE_URL}/v1`
);
};
const setChatTitle = async (_chatId, _title) => {
if (_chatId === $chatId) {
title = _title;
......@@ -1081,6 +1186,7 @@
bind:files
bind:prompt
bind:autoScroll
bind:webSearchEnabled
bind:atSelectedModel
{selectedModels}
{messages}
......
<script lang="ts">
import { toast } from 'svelte-sonner';
import { onMount, tick, getContext } from 'svelte';
import { type Model, mobile, settings, showSidebar, models } from '$lib/stores';
import { type Model, mobile, settings, showSidebar, models, config } from '$lib/stores';
import { blobToFile, calculateSHA256, findWordIndices } from '$lib/utils';
import {
......@@ -20,6 +20,8 @@
import Models from './MessageInput/Models.svelte';
import Tooltip from '../common/Tooltip.svelte';
import XMark from '$lib/components/icons/XMark.svelte';
import InputMenu from './MessageInput/InputMenu.svelte';
import { t } from 'i18next';
const i18n = getContext('i18n');
......@@ -46,8 +48,8 @@
export let files = [];
export let fileUploadEnabled = true;
export let speechRecognitionEnabled = true;
export let webSearchEnabled = false;
export let prompt = '';
export let messages = [];
......@@ -776,37 +778,39 @@
{/if}
<div class=" flex">
{#if fileUploadEnabled}
<div class=" self-end mb-2 ml-1">
<Tooltip content={$i18n.t('Upload files')}>
<button
class="bg-gray-50 hover:bg-gray-100 text-gray-800 dark:bg-gray-850 dark:text-white dark:hover:bg-gray-800 transition rounded-full p-1.5"
type="button"
on:click={() => {
filesInputElement.click();
}}
<div class=" ml-1 flex items-center">
<InputMenu
bind:webSearchEnabled
uploadFilesHandler={() => {
filesInputElement.click();
}}
onClose={async () => {
await tick();
chatTextAreaElement?.focus();
}}
>
<button
class="bg-gray-50 hover:bg-gray-100 text-gray-800 dark:bg-gray-850 dark:text-white dark:hover:bg-gray-800 transition rounded-full p-1.5 outline-none focus:outline-none"
type="button"
>
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 16 16"
fill="currentColor"
class="size-5"
>
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 16 16"
fill="currentColor"
class="w-[1.2rem] h-[1.2rem]"
>
<path
d="M8.75 3.75a.75.75 0 0 0-1.5 0v3.5h-3.5a.75.75 0 0 0 0 1.5h3.5v3.5a.75.75 0 0 0 1.5 0v-3.5h3.5a.75.75 0 0 0 0-1.5h-3.5v-3.5Z"
/>
</svg>
</button>
</Tooltip>
</div>
{/if}
<path
d="M8.75 3.75a.75.75 0 0 0-1.5 0v3.5h-3.5a.75.75 0 0 0 0 1.5h3.5v3.5a.75.75 0 0 0 1.5 0v-3.5h3.5a.75.75 0 0 0 0-1.5h-3.5v-3.5Z"
/>
</svg>
</button>
</InputMenu>
</div>
<textarea
id="chat-textarea"
bind:this={chatTextAreaElement}
class="scrollbar-hidden bg-gray-50 dark:bg-gray-850 dark:text-gray-100 outline-none w-full py-3 px-3 {fileUploadEnabled
? ''
: ' pl-4'} rounded-xl resize-none h-[48px]"
class="scrollbar-hidden bg-gray-50 dark:bg-gray-850 dark:text-gray-100 outline-none w-full py-3 px-3 rounded-xl resize-none h-[48px]"
placeholder={chatInputPlaceholder !== ''
? chatInputPlaceholder
: isRecording
......
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