Fix, Improve chat config via CLI on first run by using defaults

- Fix setting prompt size for online chat
- generally improve chat config via cli by using default chat model,
  prompt size for online and offline chat
This commit is contained in:
Debanjum Singh Solanky 2023-11-20 16:43:48 -08:00
parent d61b0dd55c
commit c07401cf76
2 changed files with 33 additions and 12 deletions

View file

@ -7,6 +7,7 @@ app_env_filepath = "~/.khoj/env"
telemetry_server = "https://khoj.beta.haletic.com/v1/telemetry"
content_directory = "~/.khoj/content/"
default_offline_chat_model = "mistral-7b-instruct-v0.1.Q4_0.gguf"
default_online_chat_model = "gpt-4"
empty_config = {
"search-type": {

View file

@ -8,7 +8,8 @@ from database.models import (
ChatModelOptions,
)
from khoj.utils.constants import default_offline_chat_model
from khoj.utils.constants import default_offline_chat_model, default_online_chat_model
from khoj.processor.conversation.utils import model_to_prompt_size, model_to_tokenizer
from database.adapters import ConversationAdapters
@ -30,11 +31,6 @@ def initialization():
logger.info(
"🗣️ Configure chat models available to your server. You can always update these at /server/admin using the credentials of your admin account"
)
try:
# Some environments don't support interactive input. We catch the exception and return if that's the case. The admin can still configure their settings from the admin page.
input()
except EOFError:
return
try:
# Note: gpt4all package is not available on all devices.
@ -47,15 +43,27 @@ def initialization():
OfflineChatProcessorConversationConfig.objects.create(enabled=True)
offline_chat_model = input(
f"Enter the name of the offline chat model you want to use, based on the models in HuggingFace (press enter to use the default: {default_offline_chat_model}): "
f"Enter the offline chat model you want to use, See GPT4All for supported models (default: {default_offline_chat_model}): "
)
if offline_chat_model == "":
ChatModelOptions.objects.create(
chat_model=default_offline_chat_model, model_type=ChatModelOptions.ModelType.OFFLINE
)
else:
max_tokens = input("Enter the maximum number of tokens to use for the offline chat model:")
tokenizer = input("Enter the tokenizer to use for the offline chat model:")
default_max_tokens = model_to_prompt_size.get(offline_chat_model, 2000)
max_tokens = input(
f"Enter the maximum number of tokens to use for the offline chat model (default {default_max_tokens}):"
)
max_tokens = max_tokens or default_max_tokens
default_tokenizer = model_to_tokenizer.get(
offline_chat_model, "hf-internal-testing/llama-tokenizer"
)
tokenizer = input(
f"Enter the tokenizer to use for the offline chat model (default: {default_tokenizer}):"
)
tokenizer = tokenizer or default_tokenizer
ChatModelOptions.objects.create(
chat_model=offline_chat_model,
model_type=ChatModelOptions.ModelType.OFFLINE,
@ -71,10 +79,19 @@ def initialization():
logger.info("🗣️ Setting up OpenAI chat model")
api_key = input("Enter your OpenAI API key: ")
OpenAIProcessorConversationConfig.objects.create(api_key=api_key)
openai_chat_model = input("Enter the name of the OpenAI chat model you want to use: ")
max_tokens = input("Enter the maximum number of tokens to use for the OpenAI chat model:")
openai_chat_model = input(
f"Enter the OpenAI chat model you want to use (default: {default_online_chat_model}): "
)
openai_chat_model = openai_chat_model or default_online_chat_model
default_max_tokens = model_to_prompt_size.get(openai_chat_model, 2000)
max_tokens = input(
f"Enter the maximum number of tokens to use for the OpenAI chat model (default: {default_max_tokens}): "
)
max_tokens = max_tokens or default_max_tokens
ChatModelOptions.objects.create(
chat_model=openai_chat_model, model_type=ChatModelOptions.ModelType.OPENAI, max_tokens=max_tokens
chat_model=openai_chat_model, model_type=ChatModelOptions.ModelType.OPENAI, max_prompt_size=max_tokens
)
logger.info("🗣️ Chat model configuration complete")
@ -94,5 +111,8 @@ def initialization():
try:
_create_chat_configuration()
break
# Some environments don't support interactive input. We catch the exception and return if that's the case. The admin can still configure their settings from the admin page.
except EOFError:
return
except Exception as e:
logger.error(f"🚨 Failed to create chat configuration: {e}", exc_info=True)