Support customization of the OpenAI base url in admin settings (#725)

- Allow self-hosted users to customize their open ai base url. This allows you to easily use a proxy service and extend support for other models.
- This also includes a migration that associates any existing openai chat model configuration with an openai processor configuration
- Make changing model a paid/subscriber feature
- Removes usage of langchain's OpenAI wrapper for better control over parsing input/output

src/khoj/database/adapters/__init__.py

@@ -623,10 +623,6 @@ class ConversationAdapters:
     def get_openai_conversation_config():
         return OpenAIProcessorConversationConfig.objects.filter().first()
 
-    @staticmethod
-    async def aget_openai_conversation_config():
-        return await OpenAIProcessorConversationConfig.objects.filter().afirst()
-
     @staticmethod
     def has_valid_openai_conversation_config():
         return OpenAIProcessorConversationConfig.objects.filter().exists()
@@ -659,7 +655,7 @@ class ConversationAdapters:
 
     @staticmethod
     async def aget_default_conversation_config():
-        return await ChatModelOptions.objects.filter().afirst()
+        return await ChatModelOptions.objects.filter().prefetch_related("openai_config").afirst()
 
     @staticmethod
     def save_conversation(
@@ -697,29 +693,15 @@ class ConversationAdapters:
         user_conversation_config.setting = new_config
         user_conversation_config.save()
 
-    @staticmethod
-    async def get_default_offline_llm():
-        return await ChatModelOptions.objects.filter(model_type="offline").afirst()
-
     @staticmethod
     async def aget_user_conversation_config(user: KhojUser):
-        config = await UserConversationConfig.objects.filter(user=user).prefetch_related("setting").afirst()
+        config = (
+            await UserConversationConfig.objects.filter(user=user).prefetch_related("setting__openai_config").afirst()
+        )
         if not config:
             return None
         return config.setting
 
-    @staticmethod
-    async def has_openai_chat():
-        return await OpenAIProcessorConversationConfig.objects.filter().aexists()
-
-    @staticmethod
-    async def aget_default_openai_llm():
-        return await ChatModelOptions.objects.filter(model_type="openai").afirst()
-
-    @staticmethod
-    async def get_openai_chat_config():
-        return await OpenAIProcessorConversationConfig.objects.filter().afirst()
-
     @staticmethod
     async def get_speech_to_text_config():
         return await SpeechToTextModelOptions.objects.filter().afirst()
@@ -744,7 +726,8 @@ class ConversationAdapters:
 
     @staticmethod
     def get_valid_conversation_config(user: KhojUser, conversation: Conversation):
-        if conversation.agent and conversation.agent.chat_model:
+        agent: Agent = conversation.agent if AgentAdapters.get_default_agent() != conversation.agent else None
+        if agent and agent.chat_model:
             conversation_config = conversation.agent.chat_model
         else:
             conversation_config = ConversationAdapters.get_conversation_config(user)
@@ -760,8 +743,7 @@ class ConversationAdapters:
 
             return conversation_config
 
-        openai_chat_config = ConversationAdapters.get_openai_conversation_config()
+        if conversation_config.model_type == "openai" and conversation_config.openai_config:
-        if openai_chat_config and conversation_config.model_type == "openai":
             return conversation_config
 
         else:

src/khoj/database/migrations/0037_chatmodeloptions_openai_config_and_more.py

@@ -0,0 +1,51 @@
+# Generated by Django 4.2.10 on 2024-04-24 05:46
+
+import django.db.models.deletion
+from django.db import migrations, models
+
+
+def attach_openai_config(apps, schema_editor):
+    OpenAIProcessorConversationConfig = apps.get_model("database", "OpenAIProcessorConversationConfig")
+    openai_processor_conversation_config = OpenAIProcessorConversationConfig.objects.first()
+    if openai_processor_conversation_config:
+        ChatModelOptions = apps.get_model("database", "ChatModelOptions")
+        for chat_model_option in ChatModelOptions.objects.all():
+            if chat_model_option.model_type == "openai":
+                chat_model_option.openai_config = openai_processor_conversation_config
+                chat_model_option.save()
+
+
+def separate_openai_config(apps, schema_editor):
+    pass
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("database", "0036_delete_offlinechatprocessorconversationconfig"),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name="chatmodeloptions",
+            name="openai_config",
+            field=models.ForeignKey(
+                blank=True,
+                default=None,
+                null=True,
+                on_delete=django.db.models.deletion.CASCADE,
+                to="database.openaiprocessorconversationconfig",
+            ),
+        ),
+        migrations.AddField(
+            model_name="openaiprocessorconversationconfig",
+            name="api_base_url",
+            field=models.URLField(blank=True, default=None, null=True),
+        ),
+        migrations.AddField(
+            model_name="openaiprocessorconversationconfig",
+            name="name",
+            field=models.CharField(default="default", max_length=200),
+            preserve_default=False,
+        ),
+        migrations.RunPython(attach_openai_config, reverse_code=separate_openai_config),
+    ]

src/khoj/database/migrations/0038_merge_20240425_0857.py

@@ -0,0 +1,14 @@
+# Generated by Django 4.2.10 on 2024-04-25 08:57
+
+from typing import List
+
+from django.db import migrations
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("database", "0037_chatmodeloptions_openai_config_and_more"),
+        ("database", "0037_searchmodelconfig_bi_encoder_docs_encode_config_and_more"),
+    ]
+
+    operations: List[str] = []

src/khoj/database/models/__init__.py

@@ -73,6 +73,12 @@ class Subscription(BaseModel):
     renewal_date = models.DateTimeField(null=True, default=None, blank=True)
 
 
+class OpenAIProcessorConversationConfig(BaseModel):
+    name = models.CharField(max_length=200)
+    api_key = models.CharField(max_length=200)
+    api_base_url = models.URLField(max_length=200, default=None, blank=True, null=True)
+
+
 class ChatModelOptions(BaseModel):
     class ModelType(models.TextChoices):
         OPENAI = "openai"
@@ -82,6 +88,9 @@ class ChatModelOptions(BaseModel):
     tokenizer = models.CharField(max_length=200, default=None, null=True, blank=True)
     chat_model = models.CharField(max_length=200, default="NousResearch/Hermes-2-Pro-Mistral-7B-GGUF")
     model_type = models.CharField(max_length=200, choices=ModelType.choices, default=ModelType.OFFLINE)
+    openai_config = models.ForeignKey(
+        OpenAIProcessorConversationConfig, on_delete=models.CASCADE, default=None, null=True, blank=True
+    )
 
 
 class Agent(BaseModel):
@@ -211,10 +220,6 @@ class TextToImageModelConfig(BaseModel):
     model_type = models.CharField(max_length=200, choices=ModelType.choices, default=ModelType.OPENAI)
 
 
-class OpenAIProcessorConversationConfig(BaseModel):
-    api_key = models.CharField(max_length=200)
-
-
 class SpeechToTextModelOptions(BaseModel):
     class ModelType(models.TextChoices):
         OPENAI = "openai"

src/khoj/interface/web/config.html

@@ -191,9 +191,15 @@
                     </select>
                 </div>
                 <div class="card-action-row">
+                    {% if (not billing_enabled) or (subscription_state != 'unsubscribed' and subscription_state != 'expired') %}
                     <button id="save-model" class="card-button happy" onclick="updateChatModel()">
                         Save
                     </button>
+                    {% else %}
+                    <button id="save-model" class="card-button" disabled>
+                        Subscribe to use different models
+                    </button>
+                    {% endif %}
                 </div>
             </div>
         </div>

src/khoj/migrations/migrate_server_pg.py

@@ -121,14 +121,16 @@ def migrate_server_pg(args):
                     if openai.get("chat-model") is None:
                         openai["chat-model"] = "gpt-3.5-turbo"
 
-                    OpenAIProcessorConversationConfig.objects.create(
+                    openai_config = OpenAIProcessorConversationConfig.objects.create(
-                        api_key=openai.get("api-key"),
+                        api_key=openai.get("api-key"), name="default"
                     )
+
                     ChatModelOptions.objects.create(
                         chat_model=openai.get("chat-model"),
                         tokenizer=processor_conversation.get("tokenizer"),
                         max_prompt_size=processor_conversation.get("max-prompt-size"),
                         model_type=ChatModelOptions.ModelType.OPENAI,
+                        openai_config=openai_config,
                     )
 
         save_config_to_file(raw_config, args.config_file)

src/khoj/processor/conversation/openai/gpt.py

@@ -23,6 +23,7 @@ def extract_questions(
     model: Optional[str] = "gpt-4-turbo-preview",
     conversation_log={},
     api_key=None,
+    api_base_url=None,
     temperature=0,
     max_tokens=100,
     location_data: LocationData = None,
@@ -64,12 +65,12 @@ def extract_questions(
     # Get Response from GPT
     response = completion_with_backoff(
         messages=messages,
-        completion_kwargs={"temperature": temperature, "max_tokens": max_tokens},
+        model=model,
-        model_kwargs={
+        temperature=temperature,
-            "model_name": model,
+        max_tokens=max_tokens,
-            "openai_api_key": api_key,
+        api_base_url=api_base_url,
-            "model_kwargs": {"response_format": {"type": "json_object"}},
+        model_kwargs={"response_format": {"type": "json_object"}},
-        },
+        openai_api_key=api_key,
     )
 
     # Extract, Clean Message from GPT's Response
@@ -89,7 +90,7 @@ def extract_questions(
     return questions
 
 
-def send_message_to_model(messages, api_key, model, response_type="text"):
+def send_message_to_model(messages, api_key, model, response_type="text", api_base_url=None):
     """
     Send message to model
     """
@@ -97,11 +98,10 @@ def send_message_to_model(messages, api_key, model, response_type="text"):
     # Get Response from GPT
     return completion_with_backoff(
         messages=messages,
-        model_kwargs={
+        model=model,
-            "model_name": model,
+        openai_api_key=api_key,
-            "openai_api_key": api_key,
+        api_base_url=api_base_url,
-            "model_kwargs": {"response_format": {"type": response_type}},
+        model_kwargs={"response_format": {"type": response_type}},
-        },
     )
 
 
@@ -112,6 +112,7 @@ def converse(
     conversation_log={},
     model: str = "gpt-3.5-turbo",
     api_key: Optional[str] = None,
+    api_base_url: Optional[str] = None,
     temperature: float = 0.2,
     completion_func=None,
     conversation_commands=[ConversationCommand.Default],
@@ -181,6 +182,7 @@ def converse(
         model_name=model,
         temperature=temperature,
         openai_api_key=api_key,
+        api_base_url=api_base_url,
         completion_func=completion_func,
         model_kwargs={"stop": ["Notes:\n["]},
     )

src/khoj/processor/conversation/openai/utils.py

@@ -1,12 +1,9 @@
 import logging
 import os
 from threading import Thread
-from typing import Any
+from typing import Dict
 
 import openai
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
-from langchain_openai import ChatOpenAI
 from tenacity import (
     before_sleep_log,
     retry,
@@ -20,14 +17,7 @@ from khoj.processor.conversation.utils import ThreadedGenerator
 
 logger = logging.getLogger(__name__)
 
-
+openai_clients: Dict[str, openai.OpenAI] = {}
-class StreamingChatCallbackHandler(StreamingStdOutCallbackHandler):
-    def __init__(self, gen: ThreadedGenerator):
-        super().__init__()
-        self.gen = gen
-
-    def on_llm_new_token(self, token: str, **kwargs) -> Any:
-        self.gen.send(token)
 
 
 @retry(
@@ -43,13 +33,37 @@ class StreamingChatCallbackHandler(StreamingStdOutCallbackHandler):
     before_sleep=before_sleep_log(logger, logging.DEBUG),
     reraise=True,
 )
-def completion_with_backoff(messages, model_kwargs={}, completion_kwargs={}) -> str:
+def completion_with_backoff(
-    if not "openai_api_key" in model_kwargs:
+    messages, model, temperature=0, openai_api_key=None, api_base_url=None, model_kwargs=None, max_tokens=None
-        model_kwargs["openai_api_key"] = os.getenv("OPENAI_API_KEY")
+) -> str:
-    llm = ChatOpenAI(**model_kwargs, request_timeout=20, max_retries=1)
+    client_key = f"{openai_api_key}--{api_base_url}"
+    client: openai.OpenAI = openai_clients.get(client_key)
+    if not client:
+        client = openai.OpenAI(
+            api_key=openai_api_key or os.getenv("OPENAI_API_KEY"),
+            base_url=api_base_url,
+        )
+        openai_clients[client_key] = client
+
+    formatted_messages = [{"role": message.role, "content": message.content} for message in messages]
+
+    chat = client.chat.completions.create(
+        stream=True,
+        messages=formatted_messages,  # type: ignore
+        model=model,  # type: ignore
+        temperature=temperature,
+        timeout=20,
+        max_tokens=max_tokens,
+        **(model_kwargs or dict()),
+    )
     aggregated_response = ""
-    for chunk in llm.stream(messages, **completion_kwargs):
+    for chunk in chat:
-        aggregated_response += chunk.content
+        delta_chunk = chunk.choices[0].delta  # type: ignore
+        if isinstance(delta_chunk, str):
+            aggregated_response += delta_chunk
+        elif delta_chunk.content:
+            aggregated_response += delta_chunk.content
+
     return aggregated_response
 
 
@@ -73,30 +87,45 @@ def chat_completion_with_backoff(
     model_name,
     temperature,
     openai_api_key=None,
+    api_base_url=None,
     completion_func=None,
     model_kwargs=None,
 ):
     g = ThreadedGenerator(compiled_references, online_results, completion_func=completion_func)
-    t = Thread(target=llm_thread, args=(g, messages, model_name, temperature, openai_api_key, model_kwargs))
+    t = Thread(
+        target=llm_thread, args=(g, messages, model_name, temperature, openai_api_key, api_base_url, model_kwargs)
+    )
     t.start()
     return g
 
 
-def llm_thread(g, messages, model_name, temperature, openai_api_key=None, model_kwargs=None):
+def llm_thread(g, messages, model_name, temperature, openai_api_key=None, api_base_url=None, model_kwargs=None):
-    callback_handler = StreamingChatCallbackHandler(g)
+    client_key = f"{openai_api_key}--{api_base_url}"
-    chat = ChatOpenAI(
+    if client_key not in openai_clients:
-        streaming=True,
+        client: openai.OpenAI = openai.OpenAI(
-        verbose=True,
+            api_key=openai_api_key or os.getenv("OPENAI_API_KEY"),
-        callback_manager=BaseCallbackManager([callback_handler]),
+            base_url=api_base_url,
-        model_name=model_name,  # type: ignore
+        )
+        openai_clients[client_key] = client
+    else:
+        client: openai.OpenAI = openai_clients[client_key]
+
+    formatted_messages = [{"role": message.role, "content": message.content} for message in messages]
+
+    chat = client.chat.completions.create(
+        stream=True,
+        messages=formatted_messages,
+        model=model_name,  # type: ignore
         temperature=temperature,
-        openai_api_key=openai_api_key or os.getenv("OPENAI_API_KEY"),
+        timeout=20,
-        model_kwargs=model_kwargs,
+        **(model_kwargs or dict()),
-        request_timeout=20,
-        max_retries=1,
-        client=None,
     )
 
-    chat(messages=messages)
+    for chunk in chat:
+        delta_chunk = chunk.choices[0].delta
+        if isinstance(delta_chunk, str):
+            g.send(delta_chunk)
+        elif delta_chunk.content:
+            g.send(delta_chunk.content)
 
     g.close()

src/khoj/processor/conversation/utils.py

@@ -14,6 +14,7 @@ from transformers import AutoTokenizer
 from khoj.database.adapters import ConversationAdapters
 from khoj.database.models import ClientApplication, KhojUser
 from khoj.processor.conversation.offline.utils import download_model, infer_max_tokens
+from khoj.utils import state
 from khoj.utils.helpers import is_none_or_empty, merge_dicts
 
 logger = logging.getLogger(__name__)
@@ -186,19 +187,31 @@ def truncate_messages(
     max_prompt_size,
     model_name: str,
     loaded_model: Optional[Llama] = None,
-    tokenizer_name="hf-internal-testing/llama-tokenizer",
+    tokenizer_name=None,
 ) -> list[ChatMessage]:
     """Truncate messages to fit within max prompt size supported by model"""
 
+    default_tokenizer = "hf-internal-testing/llama-tokenizer"
+
     try:
         if loaded_model:
             encoder = loaded_model.tokenizer()
         elif model_name.startswith("gpt-"):
             encoder = tiktoken.encoding_for_model(model_name)
+        elif tokenizer_name:
+            if tokenizer_name in state.pretrained_tokenizers:
+                encoder = state.pretrained_tokenizers[tokenizer_name]
+            else:
+                encoder = AutoTokenizer.from_pretrained(tokenizer_name)
+                state.pretrained_tokenizers[tokenizer_name] = encoder
         else:
             encoder = download_model(model_name).tokenizer()
     except:
-        encoder = AutoTokenizer.from_pretrained(tokenizer_name)
+        if default_tokenizer in state.pretrained_tokenizers:
+            encoder = state.pretrained_tokenizers[default_tokenizer]
+        else:
+            encoder = AutoTokenizer.from_pretrained(default_tokenizer)
+            state.pretrained_tokenizers[default_tokenizer] = encoder
         logger.warning(
             f"Fallback to default chat model tokenizer: {tokenizer_name}.\nConfigure tokenizer for unsupported model: {model_name} in Khoj settings to improve context stuffing."
         )

src/khoj/routers/api.py

@@ -267,7 +267,6 @@ async def transcribe(
 
 async def extract_references_and_questions(
     request: Request,
-    common: CommonQueryParams,
     meta_log: dict,
     q: str,
     n: int,
@@ -303,14 +302,12 @@ async def extract_references_and_questions(
     # Infer search queries from user message
     with timer("Extracting search queries took", logger):
         # If we've reached here, either the user has enabled offline chat or the openai model is enabled.
-        conversation_config = await ConversationAdapters.aget_conversation_config(user)
-        if conversation_config is None:
         conversation_config = await ConversationAdapters.aget_default_conversation_config()
+
         if conversation_config.model_type == ChatModelOptions.ModelType.OFFLINE:
             using_offline_chat = True
-            default_offline_llm = await ConversationAdapters.get_default_offline_llm()
+            chat_model = conversation_config.chat_model
-            chat_model = default_offline_llm.chat_model
+            max_tokens = conversation_config.max_prompt_size
-            max_tokens = default_offline_llm.max_prompt_size
             if state.offline_chat_processor_config is None:
                 state.offline_chat_processor_config = OfflineChatProcessorModel(chat_model, max_tokens)
 
@@ -324,11 +321,10 @@ async def extract_references_and_questions(
                 location_data=location_data,
                 max_prompt_size=conversation_config.max_prompt_size,
             )
-        elif conversation_config and conversation_config.model_type == ChatModelOptions.ModelType.OPENAI:
+        elif conversation_config.model_type == ChatModelOptions.ModelType.OPENAI:
-            openai_chat_config = await ConversationAdapters.get_openai_chat_config()
+            openai_chat_config = conversation_config.openai_config
-            default_openai_llm = await ConversationAdapters.aget_default_openai_llm()
             api_key = openai_chat_config.api_key
-            chat_model = default_openai_llm.chat_model
+            chat_model = conversation_config.chat_model
             inferred_queries = extract_questions(
                 defiltered_query,
                 model=chat_model,

src/khoj/routers/api_chat.py

@@ -380,7 +380,7 @@ async def websocket_endpoint(
             q = q.replace(f"/{cmd.value}", "").strip()
 
         compiled_references, inferred_queries, defiltered_query = await extract_references_and_questions(
-            websocket, None, meta_log, q, 7, 0.18, conversation_commands, location, send_status_update
+            websocket, meta_log, q, 7, 0.18, conversation_commands, location, send_status_update
         )
 
         if compiled_references:
@@ -575,7 +575,7 @@ async def chat(
     user_name = await aget_user_name(user)
 
     compiled_references, inferred_queries, defiltered_query = await extract_references_and_questions(
-        request, common, meta_log, q, (n or 5), (d or math.inf), conversation_commands, location
+        request, meta_log, q, (n or 5), (d or math.inf), conversation_commands, location
     )
     online_results: Dict[str, Dict] = {}
 

src/khoj/routers/api_config.py

@@ -7,7 +7,7 @@ from asgiref.sync import sync_to_async
 from fastapi import APIRouter, HTTPException, Request
 from fastapi.requests import Request
 from fastapi.responses import Response
-from starlette.authentication import requires
+from starlette.authentication import has_required_scope, requires
 
 from khoj.database import adapters
 from khoj.database.adapters import ConversationAdapters, EntryAdapters
@@ -20,6 +20,7 @@ from khoj.database.models import (
     LocalPdfConfig,
     LocalPlaintextConfig,
     NotionConfig,
+    Subscription,
 )
 from khoj.routers.helpers import CommonQueryParams, update_telemetry_state
 from khoj.utils import constants, state
@@ -236,6 +237,10 @@ async def update_chat_model(
     client: Optional[str] = None,
 ):
     user = request.user.object
+    subscribed = has_required_scope(request, ["premium"])
+
+    if not subscribed:
+        raise HTTPException(status_code=403, detail="User is not subscribed to premium")
 
     new_config = await ConversationAdapters.aset_user_conversation_processor(user, int(id))
 

src/khoj/routers/helpers.py

@@ -70,13 +70,14 @@ def validate_conversation_config():
     if default_config is None:
         raise HTTPException(status_code=500, detail="Contact the server administrator to set a default chat model.")
 
-    if default_config.model_type == "openai" and not ConversationAdapters.has_valid_openai_conversation_config():
+    if default_config.model_type == "openai" and not default_config.openai_config:
         raise HTTPException(status_code=500, detail="Contact the server administrator to set a default chat model.")
 
 
 async def is_ready_to_chat(user: KhojUser):
-    has_openai_config = await ConversationAdapters.has_openai_chat()
+    user_conversation_config = (await ConversationAdapters.aget_user_conversation_config(user)) or (
-    user_conversation_config = await ConversationAdapters.aget_user_conversation_config(user)
+        await ConversationAdapters.aget_default_conversation_config()
+    )
 
     if user_conversation_config and user_conversation_config.model_type == "offline":
         chat_model = user_conversation_config.chat_model
@@ -86,7 +87,13 @@ async def is_ready_to_chat(user: KhojUser):
             state.offline_chat_processor_config = OfflineChatProcessorModel(chat_model, max_tokens)
         return True
 
-    if not has_openai_config:
+    if (
+        user_conversation_config
+        and user_conversation_config.model_type == "openai"
+        and user_conversation_config.openai_config
+    ):
+        return True
+
     raise HTTPException(status_code=500, detail="Set your OpenAI API key or enable Local LLM via Khoj settings.")
 
 
@@ -407,8 +414,9 @@ async def send_message_to_model_wrapper(
         )
 
     elif conversation_config.model_type == "openai":
-        openai_chat_config = await ConversationAdapters.aget_openai_conversation_config()
+        openai_chat_config = conversation_config.openai_config
         api_key = openai_chat_config.api_key
+        api_base_url = openai_chat_config.api_base_url
         truncated_messages = generate_chatml_messages_with_context(
             user_message=message,
             system_message=system_message,
@@ -418,7 +426,11 @@ async def send_message_to_model_wrapper(
         )
 
         openai_response = send_message_to_model(
-            messages=truncated_messages, api_key=api_key, model=chat_model, response_type=response_type
+            messages=truncated_messages,
+            api_key=api_key,
+            model=chat_model,
+            response_type=response_type,
+            api_base_url=api_base_url,
         )
 
         return openai_response
@@ -480,7 +492,7 @@ def generate_chat_response(
             )
 
         elif conversation_config.model_type == "openai":
-            openai_chat_config = ConversationAdapters.get_openai_conversation_config()
+            openai_chat_config = conversation_config.openai_config
             api_key = openai_chat_config.api_key
             chat_model = conversation_config.chat_model
             chat_response = converse(
@@ -490,6 +502,7 @@ def generate_chat_response(
                 conversation_log=meta_log,
                 model=chat_model,
                 api_key=api_key,
+                api_base_url=openai_chat_config.api_base_url,
                 completion_func=partial_completion,
                 conversation_commands=conversation_commands,
                 max_prompt_size=conversation_config.max_prompt_size,

src/khoj/utils/state.py

@@ -2,7 +2,7 @@ import os
 import threading
 from collections import defaultdict
 from pathlib import Path
-from typing import Dict, List
+from typing import Any, Dict, List
 
 from openai import OpenAI
 from whisper import Whisper
@@ -34,6 +34,7 @@ khoj_version: str = None
 device = get_device()
 chat_on_gpu: bool = True
 anonymous_mode: bool = False
+pretrained_tokenizers: Dict[str, Any] = dict()
 billing_enabled: bool = (
     os.getenv("STRIPE_API_KEY") is not None
     and os.getenv("STRIPE_SIGNING_SECRET") is not None