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Merge pull request #1 from Cinnamon/misc/config-model-from-file

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Misc/config model from file
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ian_Cin 2024-03-28 16:29:26 +07:00 committed by GitHub
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18 changed files with 146 additions and 74 deletions
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18
.env Normal file
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@ -0,0 +1,18 @@
# settings for OpenAI
OPENAI_API_BASE=https://api.openai.com/v1
OPENAI_API_KEY=
OPENAI_CHAT_MODEL=gpt-3.5-turbo
OPENAI_EMBEDDINGS_MODEL=text-embedding-ada-002
# settings for Azure OpenAI
AZURE_OPENAI_ENDPOINT=
AZURE_OPENAI_API_KEY=
OPENAI_API_VERSION=2024-02-15-preview
AZURE_OPENAI_CHAT_DEPLOYMENT=gpt-35-turbo
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT=text-embedding-ada-002
# settings for Cohere
COHERE_API_KEY=
# settings for local models
LOCAL_MODEL=

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4
.gitignore vendored
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@ -332,7 +332,6 @@ celerybeat.pid
*.sage.py
# Environments
.env
.venv
env/
venv/
@ -457,7 +456,6 @@ $RECYCLE.BIN/
logs/
.gitsecret/keys/random_seed
!*.secret
.env
.envrc
S.gpg-agent*
@ -467,4 +465,4 @@ storage/*
# Conda and env storages
*install_dir/
doc_env
doc_env/

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1
.gitsecret/paths/mapping.cfg
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@ -1 +0,0 @@
.env:555d804179d7207ad6784a84afb88d2ec44f90ea3b7a061d0e38f9dd53fe7211

4
libs/kotaemon/kotaemon/embeddings/langchain_based.py
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@ -137,14 +137,14 @@ class AzureOpenAIEmbeddings(LCEmbeddingMixin, BaseEmbeddings):
azure_endpoint: Optional[str] = None,
deployment: Optional[str] = None,
openai_api_key: Optional[str] = None,
openai_api_version: Optional[str] = None,
api_version: Optional[str] = None,
request_timeout: Optional[float] = None,
**params,
):
super().__init__(
azure_endpoint=azure_endpoint,
deployment=deployment,
openai_api_version=openai_api_version,
api_version=api_version,
openai_api_key=openai_api_key,
request_timeout=request_timeout,
**params,

3
libs/kotaemon/kotaemon/llms/__init__.py
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@ -2,7 +2,7 @@ from kotaemon.base.schema import AIMessage, BaseMessage, HumanMessage, SystemMes
from .base import BaseLLM
from .branching import GatedBranchingPipeline, SimpleBranchingPipeline
from .chats import AzureChatOpenAI, ChatLLM, EndpointChatLLM, LlamaCppChat
from .chats import AzureChatOpenAI, ChatLLM, ChatOpenAI, EndpointChatLLM, LlamaCppChat
from .completions import LLM, AzureOpenAI, LlamaCpp, OpenAI
from .cot import ManualSequentialChainOfThought, Thought
from .linear import GatedLinearPipeline, SimpleLinearPipeline
@ -17,6 +17,7 @@ __all__ = [
"HumanMessage",
"AIMessage",
"SystemMessage",
"ChatOpenAI",
"AzureChatOpenAI",
"LlamaCppChat",
# completion-specific components

3
libs/kotaemon/kotaemon/llms/chats/__init__.py
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@ -1,11 +1,12 @@
from .base import ChatLLM
from .endpoint_based import EndpointChatLLM
from .langchain_based import AzureChatOpenAI, LCChatMixin
from .langchain_based import AzureChatOpenAI, ChatOpenAI, LCChatMixin
from .llamacpp import LlamaCppChat
__all__ = [
"ChatLLM",
"EndpointChatLLM",
"ChatOpenAI",
"AzureChatOpenAI",
"LCChatMixin",
"LlamaCppChat",

29
libs/kotaemon/kotaemon/llms/chats/langchain_based.py
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@ -165,7 +165,36 @@ class LCChatMixin:
raise ValueError(f"Invalid param {path}")
class ChatOpenAI(LCChatMixin, ChatLLM): # type: ignore
def __init__(
self,
openai_api_base: str | None = None,
openai_api_key: str | None = None,
model: str | None = None,
temperature: float = 0.7,
request_timeout: float | None = None,
**params,
):
super().__init__(
openai_api_base=openai_api_base,
openai_api_key=openai_api_key,
model=model,
temperature=temperature,
request_timeout=request_timeout,
**params,
)
def _get_lc_class(self):
try:
from langchain_openai import ChatOpenAI
except ImportError:
from langchain.chat_models import ChatOpenAI
return ChatOpenAI
class AzureChatOpenAI(LCChatMixin, ChatLLM): # type: ignore
def __init__(
self,
azure_endpoint: str | None = None,

146
libs/ktem/flowsettings.py
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@ -31,70 +31,98 @@ KH_VECTORSTORE = {
"__type__": "kotaemon.storages.ChromaVectorStore",
"path": str(user_cache_dir / "vectorstore"),
}
KH_LLMS = {
# example for using Azure OpenAI, the config variables can set as environment
# variables or in the .env file
# "gpt4": {
# "def": {
# "__type__": "kotaemon.llms.AzureChatOpenAI",
# "temperature": 0,
# "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
# "openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
# "openai_api_version": config("OPENAI_API_VERSION", default=""),
# "deployment_name": "<your deployment name>",
# "stream": True,
# },
# "accuracy": 10,
# "cost": 10,
# "default": False,
# },
# "gpt35": {
# "def": {
# "__type__": "kotaemon.llms.AzureChatOpenAI",
# "temperature": 0,
# "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
# "openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
# "openai_api_version": config("OPENAI_API_VERSION", default=""),
# "deployment_name": "<your deployment name>",
# "request_timeout": 10,
# "stream": False,
# },
# "accuracy": 5,
# "cost": 5,
# "default": False,
# },
"local": {
KH_LLMS = {}
KH_EMBEDDINGS = {}
# populate options from config
if config("AZURE_OPENAI_API_KEY", default="") and config(
"AZURE_OPENAI_ENDPOINT", default=""
):
if config("AZURE_OPENAI_CHAT_DEPLOYMENT", default=""):
KH_LLMS["azure"] = {
"def": {
"__type__": "kotaemon.llms.AzureChatOpenAI",
"temperature": 0,
"azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
"openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
"api_version": config("OPENAI_API_VERSION", default="")
or "2024-02-15-preview",
"deployment_name": config("AZURE_OPENAI_CHAT_DEPLOYMENT", default=""),
"request_timeout": 10,
"stream": False,
},
"default": False,
"accuracy": 5,
"cost": 5,
}
if config("AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT", default=""):
KH_EMBEDDINGS["azure"] = {
"def": {
"__type__": "kotaemon.embeddings.AzureOpenAIEmbeddings",
"azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
"openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
"api_version": config("OPENAI_API_VERSION", default="")
or "2024-02-15-preview",
"deployment": config("AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT", default=""),
"request_timeout": 10,
"chunk_size": 16,
},
"default": False,
"accuracy": 5,
"cost": 5,
}
if config("OPENAI_API_KEY", default=""):
KH_LLMS["openai"] = {
"def": {
"__type__": "kotaemon.llms.ChatOpenAI",
"temperature": 0,
"openai_api_base": config("OPENAI_API_BASE", default="")
or "https://api.openai.com/v1",
"openai_api_key": config("OPENAI_API_KEY", default=""),
"model": config("OPENAI_CHAT_MODEL", default="") or "gpt-3.5-turbo",
"request_timeout": 10,
"stream": False,
},
"default": False,
}
if len(KH_EMBEDDINGS) < 1:
KH_EMBEDDINGS["openai"] = {
"def": {
"__type__": "kotaemon.embeddings.OpenAIEmbeddings",
"openai_api_base": config("OPENAI_API_BASE", default="")
or "https://api.openai.com/v1",
"openai_api_key": config("OPENAI_API_KEY", default=""),
"model": config(
"OPENAI_EMBEDDINGS_MODEL", default="text-embedding-ada-002"
)
or "text-embedding-ada-002",
"request_timeout": 10,
"chunk_size": 16,
},
"default": False,
}
if config("LOCAL_MODEL", default=""):
KH_LLMS["local"] = {
"def": {
"__type__": "kotaemon.llms.EndpointChatLLM",
"endpoint_url": "http://localhost:31415/v1/chat/completions",
},
"default": False,
},
}
KH_EMBEDDINGS = {
# example for using Azure OpenAI, the config variables can set as environment
# variables or in the .env file
# "ada": {
# "def": {
# "__type__": "kotaemon.embeddings.AzureOpenAIEmbeddings",
# "model": "text-embedding-ada-002",
# "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
# "openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
# "deployment": "<your deployment name>",
# "chunk_size": 16,
# },
# "accuracy": 5,
# "cost": 5,
# "default": True,
# },
"local": {
"def": {
"__type__": "kotaemon.embeddings.EndpointEmbeddings",
"endpoint_url": "http://localhost:31415/v1/embeddings",
},
"default": False,
},
}
"cost": 0,
}
if len(KH_EMBEDDINGS) < 1:
KH_EMBEDDINGS["local"] = {
"def": {
"__type__": "kotaemon.embeddings.EndpointEmbeddings",
"endpoint_url": "http://localhost:31415/v1/embeddings",
},
"default": False,
"cost": 0,
}
KH_REASONINGS = ["ktem.reasoning.simple.FullQAPipeline"]

0
libs/ktem/khapptests/__init__.py → libs/ktem/ktem_tests/__init__.py
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0
libs/ktem/khapptests/resources/embedding_openai.json → libs/ktem/ktem_tests/resources/embedding_openai.json
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0
libs/ktem/khapptests/test_qa.py → libs/ktem/ktem_tests/test_qa.py
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6
scripts/serve_local.py
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@ -3,9 +3,7 @@ import subprocess
from inspect import currentframe, getframeinfo
from pathlib import Path
import dotenv
configs = dotenv.dotenv_values(".env")
from decouple import config
system_name = platform.system()
@ -53,7 +51,7 @@ def serve_llamacpp_python(local_model_file: Path, **kwargs):
def main():
local_model_file = configs.get("LOCAL_MODEL", "")
local_model_file = config("LOCAL_MODEL", default="")
if not local_model_file:
print("LOCAL_MODEL not set in the `.env` file.")

2
scripts/server_llamacpp_linux.sh
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@ -87,7 +87,7 @@ activate_environment
# install dependencies
# ver 0.2.56 produces segment error for /embeddings on MacOS
python -m pip install llama-cpp-python[server]!=0.2.56
python -m pip install llama-cpp-python[server]==0.2.55
# start the server with passed params
python -m llama_cpp.server $@

2
scripts/server_llamacpp_macos.sh
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@ -88,7 +88,7 @@ activate_environment
# install dependencies
# ver 0.2.56 produces segment error for /embeddings on MacOS
python -m pip install llama-cpp-python[server]!=0.2.56
python -m pip install llama-cpp-python[server]==0.2.55
# start the server with passed params
python -m llama_cpp.server $@

2
scripts/server_llamacpp_windows.bat
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@ -28,7 +28,7 @@ call :activate_environment
@rem install dependencies
@rem ver 0.2.56 produces segment error for /embeddings on MacOS
call python -m pip install llama-cpp-python[server]!=0.2.56
call python -m pip install llama-cpp-python[server]==0.2.55
@REM @rem start the server with passed params
call python -m llama_cpp.server %*