Resolve merge conflicts in French translations

.dockerignore

@@ -10,7 +10,8 @@ node_modules
 vite.config.js.timestamp-*
 vite.config.ts.timestamp-*
 __pycache__
-.env
+.idea
+venv
 _old
 uploads
 .ipynb_checkpoints

.gitignore

@@ -306,3 +306,4 @@ dist
 # cypress artifacts
 cypress/videos
 cypress/screenshots
+.vscode/settings.json

backend/apps/audio/main.py

@@ -14,7 +14,6 @@ from fastapi import (
 from fastapi.responses import StreamingResponse, JSONResponse, FileResponse
 
 from fastapi.middleware.cors import CORSMiddleware
-from faster_whisper import WhisperModel
 from pydantic import BaseModel
 
 import uuid
@@ -277,6 +276,8 @@ def transcribe(
             f.close()
 
         if app.state.config.STT_ENGINE == "":
+            from faster_whisper import WhisperModel
+
             whisper_kwargs = {
                 "model_size_or_path": WHISPER_MODEL,
                 "device": whisper_device_type,

backend/apps/images/main.py

@@ -12,7 +12,6 @@ from fastapi import (
     Form,
 )
 from fastapi.middleware.cors import CORSMiddleware
-from faster_whisper import WhisperModel
 
 from constants import ERROR_MESSAGES
 from utils.utils import (

backend/apps/openai/main.py

@@ -25,6 +25,7 @@ from utils.task import prompt_template
 from config import (
     SRC_LOG_LEVELS,
     ENABLE_OPENAI_API,
+    AIOHTTP_CLIENT_TIMEOUT,
     OPENAI_API_BASE_URLS,
     OPENAI_API_KEYS,
     CACHE_DIR,
@@ -463,7 +464,9 @@ async def generate_chat_completion(
     streaming = False
 
     try:
-        session = aiohttp.ClientSession(trust_env=True)
+        session = aiohttp.ClientSession(
+            trust_env=True, timeout=aiohttp.ClientTimeout(total=AIOHTTP_CLIENT_TIMEOUT)
+        )
         r = await session.request(
             method="POST",
             url=f"{url}/chat/completions",

backend/apps/rag/main.py

@@ -48,8 +48,6 @@ import mimetypes
 import uuid
 import json
 
-import sentence_transformers
-
 from apps.webui.models.documents import (
     Documents,
     DocumentForm,
@@ -93,6 +91,8 @@ from config import (
     SRC_LOG_LEVELS,
     UPLOAD_DIR,
     DOCS_DIR,
+    CONTENT_EXTRACTION_ENGINE,
+    TIKA_SERVER_URL,
     RAG_TOP_K,
     RAG_RELEVANCE_THRESHOLD,
     RAG_EMBEDDING_ENGINE,
@@ -148,6 +148,9 @@ app.state.config.ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION = (
     ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION
 )
 
+app.state.config.CONTENT_EXTRACTION_ENGINE = CONTENT_EXTRACTION_ENGINE
+app.state.config.TIKA_SERVER_URL = TIKA_SERVER_URL
+
 app.state.config.CHUNK_SIZE = CHUNK_SIZE
 app.state.config.CHUNK_OVERLAP = CHUNK_OVERLAP
 
@@ -190,6 +193,8 @@ def update_embedding_model(
     update_model: bool = False,
 ):
     if embedding_model and app.state.config.RAG_EMBEDDING_ENGINE == "":
+        import sentence_transformers
+
         app.state.sentence_transformer_ef = sentence_transformers.SentenceTransformer(
             get_model_path(embedding_model, update_model),
             device=DEVICE_TYPE,
@@ -204,6 +209,8 @@ def update_reranking_model(
     update_model: bool = False,
 ):
     if reranking_model:
+        import sentence_transformers
+
         app.state.sentence_transformer_rf = sentence_transformers.CrossEncoder(
             get_model_path(reranking_model, update_model),
             device=DEVICE_TYPE,
@@ -388,6 +395,10 @@ async def get_rag_config(user=Depends(get_admin_user)):
     return {
         "status": True,
         "pdf_extract_images": app.state.config.PDF_EXTRACT_IMAGES,
+        "content_extraction": {
+            "engine": app.state.config.CONTENT_EXTRACTION_ENGINE,
+            "tika_server_url": app.state.config.TIKA_SERVER_URL,
+        },
         "chunk": {
             "chunk_size": app.state.config.CHUNK_SIZE,
             "chunk_overlap": app.state.config.CHUNK_OVERLAP,
@@ -417,6 +428,11 @@ async def get_rag_config(user=Depends(get_admin_user)):
     }
 
 
+class ContentExtractionConfig(BaseModel):
+    engine: str = ""
+    tika_server_url: Optional[str] = None
+
+
 class ChunkParamUpdateForm(BaseModel):
     chunk_size: int
     chunk_overlap: int
@@ -450,6 +466,7 @@ class WebConfig(BaseModel):
 
 class ConfigUpdateForm(BaseModel):
     pdf_extract_images: Optional[bool] = None
+    content_extraction: Optional[ContentExtractionConfig] = None
     chunk: Optional[ChunkParamUpdateForm] = None
     youtube: Optional[YoutubeLoaderConfig] = None
     web: Optional[WebConfig] = None
@@ -463,6 +480,11 @@ async def update_rag_config(form_data: ConfigUpdateForm, user=Depends(get_admin_
         else app.state.config.PDF_EXTRACT_IMAGES
     )
 
+    if form_data.content_extraction is not None:
+        log.info(f"Updating text settings: {form_data.content_extraction}")
+        app.state.config.CONTENT_EXTRACTION_ENGINE = form_data.content_extraction.engine
+        app.state.config.TIKA_SERVER_URL = form_data.content_extraction.tika_server_url
+
     if form_data.chunk is not None:
         app.state.config.CHUNK_SIZE = form_data.chunk.chunk_size
         app.state.config.CHUNK_OVERLAP = form_data.chunk.chunk_overlap
@@ -499,6 +521,10 @@ async def update_rag_config(form_data: ConfigUpdateForm, user=Depends(get_admin_
     return {
         "status": True,
         "pdf_extract_images": app.state.config.PDF_EXTRACT_IMAGES,
+        "content_extraction": {
+            "engine": app.state.config.CONTENT_EXTRACTION_ENGINE,
+            "tika_server_url": app.state.config.TIKA_SERVER_URL,
+        },
         "chunk": {
             "chunk_size": app.state.config.CHUNK_SIZE,
             "chunk_overlap": app.state.config.CHUNK_OVERLAP,
@@ -985,6 +1011,41 @@ def store_docs_in_vector_db(docs, collection_name, overwrite: bool = False) -> b
         return False
 
 
+class TikaLoader:
+    def __init__(self, file_path, mime_type=None):
+        self.file_path = file_path
+        self.mime_type = mime_type
+
+    def load(self) -> List[Document]:
+        with open(self.file_path, "rb") as f:
+            data = f.read()
+
+        if self.mime_type is not None:
+            headers = {"Content-Type": self.mime_type}
+        else:
+            headers = {}
+
+        endpoint = app.state.config.TIKA_SERVER_URL
+        if not endpoint.endswith("/"):
+            endpoint += "/"
+        endpoint += "tika/text"
+
+        r = requests.put(endpoint, data=data, headers=headers)
+
+        if r.ok:
+            raw_metadata = r.json()
+            text = raw_metadata.get("X-TIKA:content", "<No text content found>")
+
+            if "Content-Type" in raw_metadata:
+                headers["Content-Type"] = raw_metadata["Content-Type"]
+
+            log.info("Tika extracted text: %s", text)
+
+            return [Document(page_content=text, metadata=headers)]
+        else:
+            raise Exception(f"Error calling Tika: {r.reason}")
+
+
 def get_loader(filename: str, file_content_type: str, file_path: str):
     file_ext = filename.split(".")[-1].lower()
     known_type = True
@@ -1035,47 +1096,58 @@ def get_loader(filename: str, file_content_type: str, file_path: str):
         "msg",
     ]
 
-    if file_ext == "pdf":
-        loader = PyPDFLoader(
-            file_path, extract_images=app.state.config.PDF_EXTRACT_IMAGES
-        )
-    elif file_ext == "csv":
-        loader = CSVLoader(file_path)
-    elif file_ext == "rst":
-        loader = UnstructuredRSTLoader(file_path, mode="elements")
-    elif file_ext == "xml":
-        loader = UnstructuredXMLLoader(file_path)
-    elif file_ext in ["htm", "html"]:
-        loader = BSHTMLLoader(file_path, open_encoding="unicode_escape")
-    elif file_ext == "md":
-        loader = UnstructuredMarkdownLoader(file_path)
-    elif file_content_type == "application/epub+zip":
-        loader = UnstructuredEPubLoader(file_path)
-    elif (
-        file_content_type
-        == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
-        or file_ext in ["doc", "docx"]
+    if (
+        app.state.config.CONTENT_EXTRACTION_ENGINE == "tika"
+        and app.state.config.TIKA_SERVER_URL
     ):
-        loader = Docx2txtLoader(file_path)
-    elif file_content_type in [
-        "application/vnd.ms-excel",
-        "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
-    ] or file_ext in ["xls", "xlsx"]:
-        loader = UnstructuredExcelLoader(file_path)
-    elif file_content_type in [
-        "application/vnd.ms-powerpoint",
-        "application/vnd.openxmlformats-officedocument.presentationml.presentation",
-    ] or file_ext in ["ppt", "pptx"]:
-        loader = UnstructuredPowerPointLoader(file_path)
-    elif file_ext == "msg":
-        loader = OutlookMessageLoader(file_path)
-    elif file_ext in known_source_ext or (
-        file_content_type and file_content_type.find("text/") >= 0
-    ):
-        loader = TextLoader(file_path, autodetect_encoding=True)
+        if file_ext in known_source_ext or (
+            file_content_type and file_content_type.find("text/") >= 0
+        ):
+            loader = TextLoader(file_path, autodetect_encoding=True)
+        else:
+            loader = TikaLoader(file_path, file_content_type)
     else:
-        loader = TextLoader(file_path, autodetect_encoding=True)
-        known_type = False
+        if file_ext == "pdf":
+            loader = PyPDFLoader(
+                file_path, extract_images=app.state.config.PDF_EXTRACT_IMAGES
+            )
+        elif file_ext == "csv":
+            loader = CSVLoader(file_path)
+        elif file_ext == "rst":
+            loader = UnstructuredRSTLoader(file_path, mode="elements")
+        elif file_ext == "xml":
+            loader = UnstructuredXMLLoader(file_path)
+        elif file_ext in ["htm", "html"]:
+            loader = BSHTMLLoader(file_path, open_encoding="unicode_escape")
+        elif file_ext == "md":
+            loader = UnstructuredMarkdownLoader(file_path)
+        elif file_content_type == "application/epub+zip":
+            loader = UnstructuredEPubLoader(file_path)
+        elif (
+            file_content_type
+            == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+            or file_ext in ["doc", "docx"]
+        ):
+            loader = Docx2txtLoader(file_path)
+        elif file_content_type in [
+            "application/vnd.ms-excel",
+            "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+        ] or file_ext in ["xls", "xlsx"]:
+            loader = UnstructuredExcelLoader(file_path)
+        elif file_content_type in [
+            "application/vnd.ms-powerpoint",
+            "application/vnd.openxmlformats-officedocument.presentationml.presentation",
+        ] or file_ext in ["ppt", "pptx"]:
+            loader = UnstructuredPowerPointLoader(file_path)
+        elif file_ext == "msg":
+            loader = OutlookMessageLoader(file_path)
+        elif file_ext in known_source_ext or (
+            file_content_type and file_content_type.find("text/") >= 0
+        ):
+            loader = TextLoader(file_path, autodetect_encoding=True)
+        else:
+            loader = TextLoader(file_path, autodetect_encoding=True)
+            known_type = False
 
     return loader, known_type
 

backend/apps/rag/utils.py

@@ -294,14 +294,16 @@ def get_rag_context(
 
         extracted_collections.extend(collection_names)
 
-    context_string = ""
-
+    contexts = []
     citations = []
+
     for context in relevant_contexts:
         try:
             if "documents" in context:
-                context_string += "\n\n".join(
-                    [text for text in context["documents"][0] if text is not None]
+                contexts.append(
+                    "\n\n".join(
+                        [text for text in context["documents"][0] if text is not None]
+                    )
                 )
 
                 if "metadatas" in context:
@@ -315,9 +317,7 @@ def get_rag_context(
         except Exception as e:
             log.exception(e)
 
-    context_string = context_string.strip()
-
-    return context_string, citations
+    return contexts, citations
 
 
 def get_model_path(model: str, update_model: bool = False):
@@ -442,8 +442,6 @@ from langchain_core.documents import BaseDocumentCompressor, Document
 from langchain_core.callbacks import Callbacks
 from langchain_core.pydantic_v1 import Extra
 
-from sentence_transformers import util
-
 
 class RerankCompressor(BaseDocumentCompressor):
     embedding_function: Any
@@ -468,6 +466,8 @@ class RerankCompressor(BaseDocumentCompressor):
                 [(query, doc.page_content) for doc in documents]
             )
         else:
+            from sentence_transformers import util
+
             query_embedding = self.embedding_function(query)
             document_embedding = self.embedding_function(
                 [doc.page_content for doc in documents]

backend/apps/webui/main.py

@@ -259,6 +259,9 @@ async def generate_function_chat_completion(form_data, user):
                         if isinstance(line, BaseModel):
                             line = line.model_dump_json()
                             line = f"data: {line}"
+                        if isinstance(line, dict):
+                            line = f"data: {json.dumps(line)}"
+
                         try:
                             line = line.decode("utf-8")
                         except:

backend/apps/webui/models/functions.py

@@ -214,8 +214,7 @@ class FunctionsTable:
             user_settings["functions"]["valves"][id] = valves
 
             # Update the user settings in the database
-            query = Users.update_user_by_id(user_id, {"settings": user_settings})
-            query.execute()
+            Users.update_user_by_id(user_id, {"settings": user_settings})
 
             return user_settings["functions"]["valves"][id]
         except Exception as e:

backend/apps/webui/models/tools.py

@@ -170,8 +170,7 @@ class ToolsTable:
             user_settings["tools"]["valves"][id] = valves
 
             # Update the user settings in the database
-            query = Users.update_user_by_id(user_id, {"settings": user_settings})
-            query.execute()
+            Users.update_user_by_id(user_id, {"settings": user_settings})
 
             return user_settings["tools"]["valves"][id]
         except Exception as e:

backend/config.py

@@ -5,9 +5,8 @@ import importlib.metadata
 import pkgutil
 import chromadb
 from chromadb import Settings
-from base64 import b64encode
 from bs4 import BeautifulSoup
-from typing import TypeVar, Generic, Union
+from typing import TypeVar, Generic
 from pydantic import BaseModel
 from typing import Optional
 
@@ -19,7 +18,6 @@ import markdown
 import requests
 import shutil
 
-from secrets import token_bytes
 from constants import ERROR_MESSAGES
 
 ####################################
@@ -768,12 +766,14 @@ class BannerModel(BaseModel):
     dismissible: bool
     timestamp: int
 
+try:
+    banners = json.loads(os.environ.get("WEBUI_BANNERS", "[]"))
+    banners = [BannerModel(**banner) for banner in banners]
+except Exception as e:
+    print(f"Error loading WEBUI_BANNERS: {e}")
+    banners = []
 
-WEBUI_BANNERS = PersistentConfig(
-    "WEBUI_BANNERS",
-    "ui.banners",
-    [BannerModel(**banner) for banner in json.loads("[]")],
-)
+WEBUI_BANNERS = PersistentConfig("WEBUI_BANNERS", "ui.banners", banners)
 
 
 SHOW_ADMIN_DETAILS = PersistentConfig(
@@ -885,6 +885,22 @@ WEBUI_SESSION_COOKIE_SECURE = os.environ.get(
 if WEBUI_AUTH and WEBUI_SECRET_KEY == "":
     raise ValueError(ERROR_MESSAGES.ENV_VAR_NOT_FOUND)
 
+####################################
+# RAG document content extraction
+####################################
+
+CONTENT_EXTRACTION_ENGINE = PersistentConfig(
+    "CONTENT_EXTRACTION_ENGINE",
+    "rag.CONTENT_EXTRACTION_ENGINE",
+    os.environ.get("CONTENT_EXTRACTION_ENGINE", "").lower(),
+)
+
+TIKA_SERVER_URL = PersistentConfig(
+    "TIKA_SERVER_URL",
+    "rag.tika_server_url",
+    os.getenv("TIKA_SERVER_URL", "http://tika:9998"),  # Default for sidecar deployment
+)
+
 ####################################
 # RAG
 ####################################

backend/requirements.txt

@@ -10,7 +10,7 @@ python-socketio==5.11.3
 python-jose==3.3.0
 passlib[bcrypt]==1.7.4
 
-requests==2.32.2
+requests==2.32.3
 aiohttp==3.9.5
 peewee==3.17.5
 peewee-migrate==1.12.2
@@ -30,21 +30,21 @@ openai
 anthropic
 google-generativeai==0.5.4
 
-langchain==0.2.0
-langchain-community==0.2.0
+langchain==0.2.6
+langchain-community==0.2.6
 langchain-chroma==0.1.2
 
 fake-useragent==1.5.1
 chromadb==0.5.3
-sentence-transformers==2.7.0
+sentence-transformers==3.0.1
 pypdf==4.2.0
 docx2txt==0.8
 python-pptx==0.6.23
-unstructured==0.14.0
+unstructured==0.14.9
 Markdown==3.6
 pypandoc==1.13
 pandas==2.2.2
-openpyxl==3.1.2
+openpyxl==3.1.5
 pyxlsb==1.0.10
 xlrd==2.0.1
 validators==0.28.1
@@ -61,7 +61,7 @@ PyJWT[crypto]==2.8.0
 authlib==1.3.1
 
 black==24.4.2
-langfuse==2.33.0
+langfuse==2.36.2
 youtube-transcript-api==0.6.2
 pytube==15.0.0
 

backend/utils/misc.py

@@ -8,14 +8,22 @@ import uuid
 import time
 
 
-def get_last_user_message(messages: List[dict]) -> str:
+def get_last_user_message_item(messages: List[dict]) -> str:
     for message in reversed(messages):
         if message["role"] == "user":
-            if isinstance(message["content"], list):
-                for item in message["content"]:
-                    if item["type"] == "text":
-                        return item["text"]
-            return message["content"]
+            return message
+    return None
+
+
+def get_last_user_message(messages: List[dict]) -> str:
+    message = get_last_user_message_item(messages)
+
+    if message is not None:
+        if isinstance(message["content"], list):
+            for item in message["content"]:
+                if item["type"] == "text":
+                    return item["text"]
+        return message["content"]
     return None
 
 

package-lock.json

 {
 	"name": "open-webui",
-	"version": "0.3.7",
+	"version": "0.3.8",
 	"lockfileVersion": 3,
 	"requires": true,
 	"packages": {
 		"": {
 			"name": "open-webui",
-			"version": "0.3.7",
+			"version": "0.3.8",
 			"dependencies": {
 				"@codemirror/lang-javascript": "^6.2.2",
 				"@codemirror/lang-python": "^6.1.6",

package.json

 {
 	"name": "open-webui",
-	"version": "0.3.7",
+	"version": "0.3.8",
 	"private": true,
 	"scripts": {
 		"dev": "npm run pyodide:fetch && vite dev --host",

src/lib/apis/rag/index.ts

@@ -32,6 +32,11 @@ type ChunkConfigForm = {
 	chunk_overlap: number;
 };
 
+type ContentExtractConfigForm = {
+	engine: string;
+	tika_server_url: string | null;
+};
+
 type YoutubeConfigForm = {
 	language: string[];
 	translation?: string | null;
@@ -40,6 +45,7 @@ type YoutubeConfigForm = {
 type RAGConfigForm = {
 	pdf_extract_images?: boolean;
 	chunk?: ChunkConfigForm;
+	content_extraction?: ContentExtractConfigForm;
 	web_loader_ssl_verification?: boolean;
 	youtube?: YoutubeConfigForm;
 };

src/lib/components/admin/Settings/Documents.svelte

@@ -37,6 +37,10 @@
 	let embeddingModel = '';
 	let rerankingModel = '';
 
+	let contentExtractionEngine = 'default';
+	let tikaServerUrl = '';
+	let showTikaServerUrl = false;
+
 	let chunkSize = 0;
 	let chunkOverlap = 0;
 	let pdfExtractImages = true;
@@ -163,11 +167,20 @@
 			rerankingModelUpdateHandler();
 		}
 
+		if (contentExtractionEngine === 'tika' && tikaServerUrl === '') {
+			toast.error($i18n.t('Tika Server URL required.'));
+			return;
+		}
+
 		const res = await updateRAGConfig(localStorage.token, {
 			pdf_extract_images: pdfExtractImages,
 			chunk: {
 				chunk_overlap: chunkOverlap,
 				chunk_size: chunkSize
+			},
+			content_extraction: {
+				engine: contentExtractionEngine,
+				tika_server_url: tikaServerUrl
 			}
 		});
 
@@ -213,6 +226,10 @@
 
 			chunkSize = res.chunk.chunk_size;
 			chunkOverlap = res.chunk.chunk_overlap;
+
+			contentExtractionEngine = res.content_extraction.engine;
+			tikaServerUrl = res.content_extraction.tika_server_url;
+			showTikaServerUrl = contentExtractionEngine === 'tika';
 		}
 	});
 </script>
@@ -388,7 +405,7 @@
 			</div>
 		</div>
 
-		<hr class=" dark:border-gray-850 my-1" />
+		<hr class="dark:border-gray-850" />
 
 		<div class="space-y-2" />
 		<div>
@@ -562,6 +579,39 @@
 
 		<hr class=" dark:border-gray-850" />
 
+		<div class="">
+			<div class="text-sm font-medium">{$i18n.t('Content Extraction')}</div>
+
+			<div class="flex w-full justify-between mt-2">
+				<div class="self-center text-xs font-medium">{$i18n.t('Engine')}</div>
+				<div class="flex items-center relative">
+					<select
+						class="dark:bg-gray-900 w-fit pr-8 rounded px-2 p-1 text-xs bg-transparent outline-none text-right"
+						bind:value={contentExtractionEngine}
+						on:change={(e) => {
+							showTikaServerUrl = e.target.value === 'tika';
+						}}
+					>
+						<option value="">{$i18n.t('Default')} </option>
+						<option value="tika">{$i18n.t('Tika')}</option>
+					</select>
+				</div>
+			</div>
+
+			{#if showTikaServerUrl}
+				<div class="flex w-full mt-2">
+					<div class="flex-1 mr-2">
+						<input
+							class="w-full rounded-lg py-2 px-4 text-sm dark:text-gray-300 dark:bg-gray-850 outline-none"
+							placeholder={$i18n.t('Enter Tika Server URL')}
+							bind:value={tikaServerUrl}
+						/>
+					</div>
+				</div>
+			{/if}
+		</div>
+		<hr class=" dark:border-gray-850" />
+
 		<div class=" ">
 			<div class=" text-sm font-medium">{$i18n.t('Query Params')}</div>
 

src/lib/components/admin/Settings/Pipelines.svelte

@@ -19,6 +19,7 @@
 	} from '$lib/apis';
 
 	import Spinner from '$lib/components/common/Spinner.svelte';
+	import Switch from '$lib/components/common/Switch.svelte';
 
 	const i18n: Writable<i18nType> = getContext('i18n');
 
@@ -476,15 +477,40 @@
 												</div>
 
 												{#if (valves[property] ?? null) !== null}
-													<div class="flex mt-0.5 space-x-2">
+													<!-- {valves[property]} -->
+													<div class="flex mt-0.5 mb-1.5 space-x-2">
 														<div class=" flex-1">
-															<input
-																class="w-full rounded-lg py-2 px-4 text-sm dark:text-gray-300 dark:bg-gray-850 outline-none"
-																type="text"
-																placeholder={valves_spec.properties[property].title}
-																bind:value={valves[property]}
-																autocomplete="off"
-															/>
+															{#if valves_spec.properties[property]?.enum ?? null}
+																<select
+																	class="w-full rounded-lg py-2 px-4 text-sm dark:text-gray-300 dark:bg-gray-850 outline-none"
+																	bind:value={valves[property]}
+																>
+																	{#each valves_spec.properties[property].enum as option}
+																		<option value={option} selected={option === valves[property]}>
+																			{option}
+																		</option>
+																	{/each}
+																</select>
+															{:else if (valves_spec.properties[property]?.type ?? null) === 'boolean'}
+																<div class="flex justify-between items-center">
+																	<div class="text-xs text-gray-500">
+																		{valves[property] ? 'Enabled' : 'Disabled'}
+																	</div>
+
+																	<div class=" pr-2">
+																		<Switch bind:state={valves[property]} />
+																	</div>
+																</div>
+															{:else}
+																<input
+																	class="w-full rounded-lg py-2 px-4 text-sm dark:text-gray-300 dark:bg-gray-850 outline-none"
+																	type="text"
+																	placeholder={valves_spec.properties[property].title}
+																	bind:value={valves[property]}
+																	autocomplete="off"
+																	required
+																/>
+															{/if}
 														</div>
 													</div>
 												{/if}

src/lib/components/chat/Chat.svelte

@@ -126,6 +126,27 @@
 		})();
 	}
 
+	const chatEventHandler = async (data) => {
+		if (data.chat_id === $chatId) {
+			await tick();
+			console.log(data);
+			let message = history.messages[data.message_id];
+
+			const status = {
+				done: data?.data?.done ?? null,
+				description: data?.data?.status ?? null
+			};
+
+			if (message.statusHistory) {
+				message.statusHistory.push(status);
+			} else {
+				message.statusHistory = [status];
+			}
+
+			messages = messages;
+		}
+	};
+
 	onMount(async () => {
 		const onMessageHandler = async (event) => {
 			if (event.origin === window.origin) {
@@ -163,6 +184,8 @@
 		};
 		window.addEventListener('message', onMessageHandler);
 
+		$socket.on('chat-events', chatEventHandler);
+
 		if (!$chatId) {
 			chatId.subscribe(async (value) => {
 				if (!value) {
@@ -177,6 +200,8 @@
 
 		return () => {
 			window.removeEventListener('message', onMessageHandler);
+
+			$socket.off('chat-events');
 		};
 	});
 
@@ -302,7 +327,7 @@
 		}
 	};
 
-	const chatCompletedHandler = async (modelId, messages) => {
+	const chatCompletedHandler = async (modelId, responseMessageId, messages) => {
 		await mermaid.run({
 			querySelector: '.mermaid'
 		});
@@ -316,7 +341,9 @@
 				info: m.info ? m.info : undefined,
 				timestamp: m.timestamp
 			})),
-			chat_id: $chatId
+			chat_id: $chatId,
+			session_id: $socket?.id,
+			id: responseMessageId
 		}).catch((error) => {
 			toast.error(error);
 			messages.at(-1).error = { content: error };
@@ -665,6 +692,7 @@
 		await tick();
 
 		const [res, controller] = await generateChatCompletion(localStorage.token, {
+			stream: true,
 			model: model.id,
 			messages: messagesBody,
 			options: {
@@ -682,8 +710,9 @@
 			keep_alive: $settings.keepAlive ?? undefined,
 			tool_ids: selectedToolIds.length > 0 ? selectedToolIds : undefined,
 			files: files.length > 0 ? files : undefined,
-			citations: files.length > 0 ? true : undefined,
-			chat_id: $chatId
+			session_id: $socket?.id,
+			chat_id: $chatId,
+			id: responseMessageId
 		});
 
 		if (res && res.ok) {
@@ -704,7 +733,7 @@
 						controller.abort('User: Stop Response');
 					} else {
 						const messages = createMessagesList(responseMessageId);
-						await chatCompletedHandler(model.id, messages);
+						await chatCompletedHandler(model.id, responseMessageId, messages);
 					}
 
 					_response = responseMessage.content;
@@ -912,8 +941,8 @@
 			const [res, controller] = await generateOpenAIChatCompletion(
 				localStorage.token,
 				{
-					model: model.id,
 					stream: true,
+					model: model.id,
 					stream_options:
 						model.info?.meta?.capabilities?.usage ?? false
 							? {
@@ -983,9 +1012,9 @@
 					max_tokens: $settings?.params?.max_tokens ?? undefined,
 					tool_ids: selectedToolIds.length > 0 ? selectedToolIds : undefined,
 					files: files.length > 0 ? files : undefined,
-					citations: files.length > 0 ? true : undefined,
-
-					chat_id: $chatId
+					session_id: $socket?.id,
+					chat_id: $chatId,
+					id: responseMessageId
 				},
 				`${WEBUI_BASE_URL}/api`
 			);
@@ -1014,7 +1043,7 @@
 						} else {
 							const messages = createMessagesList(responseMessageId);
 
-							await chatCompletedHandler(model.id, messages);
+							await chatCompletedHandler(model.id, responseMessageId, messages);
 						}
 
 						_response = responseMessage.content;