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refactor: formatting + token limit for gemini-2.0-flash-exp

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Siddhant Rai
2025-02-14 00:27:27 +05:30
parent 5cf5bed6a8
commit 7b05afab74
1 changed files with 30 additions and 11 deletions
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41
application/core/settings.py
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@@ -1,26 +1,37 @@
import os
from pathlib import Path
from typing import Optional
import os
from pydantic_settings import BaseSettings
current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
current_dir = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
)
class Settings(BaseSettings):
LLM_NAME: str = "docsgpt"
MODEL_NAME: Optional[str] = None # if LLM_NAME is openai, MODEL_NAME can be gpt-4 or gpt-3.5-turbo
MODEL_NAME: Optional[str] = (
None # if LLM_NAME is openai, MODEL_NAME can be gpt-4 or gpt-3.5-turbo
)
EMBEDDINGS_NAME: str = "huggingface_sentence-transformers/all-mpnet-base-v2"
CELERY_BROKER_URL: str = "redis://localhost:6379/0"
CELERY_RESULT_BACKEND: str = "redis://localhost:6379/1"
MONGO_URI: str = "mongodb://localhost:27017/docsgpt"
MODEL_PATH: str = os.path.join(current_dir, "models/docsgpt-7b-f16.gguf")
DEFAULT_MAX_HISTORY: int = 150
MODEL_TOKEN_LIMITS: dict = {"gpt-4o-mini": 128000, "gpt-3.5-turbo": 4096, "claude-2": 1e5}
MODEL_TOKEN_LIMITS: dict = {
"gpt-4o-mini": 128000,
"gpt-3.5-turbo": 4096,
"claude-2": 1e5,
"gemini-2.0-flash-exp": 1e6,
}
UPLOAD_FOLDER: str = "inputs"
PARSE_PDF_AS_IMAGE: bool = False
VECTOR_STORE: str = "faiss" # "faiss" or "elasticsearch" or "qdrant" or "milvus" or "lancedb"
RETRIEVERS_ENABLED: list = ["classic_rag", "duckduck_search"] # also brave_search
VECTOR_STORE: str = (
"faiss" # "faiss" or "elasticsearch" or "qdrant" or "milvus" or "lancedb"
)
RETRIEVERS_ENABLED: list = ["classic_rag", "duckduck_search"] # also brave_search
# LLM Cache
CACHE_REDIS_URL: str = "redis://localhost:6379/2"
@@ -28,12 +39,18 @@ class Settings(BaseSettings):
API_URL: str = "http://localhost:7091" # backend url for celery worker
API_KEY: Optional[str] = None # LLM api key
EMBEDDINGS_KEY: Optional[str] = None # api key for embeddings (if using openai, just copy API_KEY)
EMBEDDINGS_KEY: Optional[str] = (
None # api key for embeddings (if using openai, just copy API_KEY)
)
OPENAI_API_BASE: Optional[str] = None # azure openai api base url
OPENAI_API_VERSION: Optional[str] = None # azure openai api version
AZURE_DEPLOYMENT_NAME: Optional[str] = None # azure deployment name for answering
AZURE_EMBEDDINGS_DEPLOYMENT_NAME: Optional[str] = None # azure deployment name for embeddings
OPENAI_BASE_URL: Optional[str] = None # openai base url for open ai compatable models
AZURE_EMBEDDINGS_DEPLOYMENT_NAME: Optional[str] = (
None # azure deployment name for embeddings
)
OPENAI_BASE_URL: Optional[str] = (
None # openai base url for open ai compatable models
)
# elasticsearch
ELASTIC_CLOUD_ID: Optional[str] = None # cloud id for elasticsearch
@@ -68,12 +85,14 @@ class Settings(BaseSettings):
# Milvus vectorstore config
MILVUS_COLLECTION_NAME: Optional[str] = "docsgpt"
MILVUS_URI: Optional[str] = "./milvus_local.db" # milvus lite version as default
MILVUS_URI: Optional[str] = "./milvus_local.db" # milvus lite version as default
MILVUS_TOKEN: Optional[str] = ""
# LanceDB vectorstore config
LANCEDB_PATH: str = "/tmp/lancedb" # Path where LanceDB stores its local data
LANCEDB_TABLE_NAME: Optional[str] = "docsgpts" # Name of the table to use for storing vectors
LANCEDB_TABLE_NAME: Optional[str] = (
"docsgpts" # Name of the table to use for storing vectors
)
BRAVE_SEARCH_API_KEY: Optional[str] = None
FLASK_DEBUG_MODE: bool = False