RafaelRuiz
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assistance-engine
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Remove deprecated configuration files and update Docker Compose for Ollama service

This commit is contained in:
acano 2026-03-03 10:29:52 +01:00
parent a7c40d4f2c
commit 45d124e017
6 changed files with 45 additions and 181 deletions
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81
Docker/config.py
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@ -1,81 +0,0 @@
from pathlib import Path
from pydantic_settings import BaseSettings, SettingsConfigDict
from dotenv import load_dotenv
from datetime import timedelta
import warnings
import os
load_dotenv()
MODEL_NAME=os.getenv("MODEL_NAME", "gpt-3.5-turbo")
OPENAI_API_KEY=os.getenv("OPENAI_API_KEY", "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")
OLLAMA_URL=os.getenv("OLLAMA_URL", "http://host.docker.internal:11434")
OLLAMA_LOCAL_URL=os.getenv("OLLAMA_LOCAL_URL", "http://localhost:11434")
OLLAMA_MODEL_NAME=os.getenv("OLLAMA_MODEL_NAME", "qwen3-0.6B:latest")
OLLAMA_EMB_MODEL_NAME=os.getenv("OLLAMA_EMB_MODEL_NAME", "qwen3-0.6B-emb:latest")
LANGFUSE_HOST=os.getenv("LANGFUSE_HOST", "http://45.77.119.180")
LANGFUSE_PUBLIC_KEY=os.getenv("LANGFUSE_PUBLIC_KEY", "pk-lf-0e6db694-3e95-4dd4-aedf-5a2694267058")
LANGFUSE_SECRET_KEY=os.getenv("LANGFUSE_SECRET_KEY", "sk-lf-dbf28bb9-15bb-4d03-a8c3-05caa3e3905f")
ELASTICSEARCH_URL=os.getenv("ELASTICSEARCH_URL", "http://host.docker.internal:9200")
ELASTICSEARCH_LOCAL_URL=os.getenv("ELASTICSEARCH_LOCAL_URL", "http://localhost:9200")
ELASTICSEARCH_INDEX=os.getenv("ELASTICSEARCH_INDEX", "avap-docs-test")
DATABASE_URL=os.getenv("DATABASE_URL", "postgresql://postgres:brunix_pass@host.docker.internal:5432/postgres")
KUBECONFIG_PATH=os.getenv("KUBECONFIG_PATH", "kubernetes/kubeconfig.yaml")
HF_TOKEN=os.getenv("HF_TOKEN", "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")
HF_EMB_MODEL_NAME=os.getenv("HF_EMB_MODEL_NAME", "Qwen/Qwen3-Embedding-0.6B")
MRH_AVAP_DATA_PATH_=os.getenv("MRH_AVAP_DATA_PATH_", "/home/pseco/VsCodeProjects/assistance-engine/data/")
MRH_AVAP_MODELS_PATH_=os.getenv("MRH_AVAP_MODELS_PATH_", "/home/pseco/VsCodeProjects/assistance-engine/data/models")
MRH_AVAP_RAW_PATH_=os.getenv("MRH_AVAP_RAW_PATH_", "/home/pseco/VsCodeProjects/assistance-engine/data/raw")
MRH_AVAP_PROCESSED_PATH_=os.getenv("MRH_AVAP_PROCESSED_PATH_", "/home/pseco/VsCodeProjects/assistance-engine/data/processed")
MRH_AVAP_INTERIM_PATH_=os.getenv("MRH_AVAP_INTERIM_PATH_", "/home/pseco/VsCodeProjects/assistance-engine/data/interim")
MRH_AVAP_EXTERNAL_PATH_=os.getenv("MRH_AVAP_EXTERNAL_PATH_", "/home/pseco/VsCodeProjects/assistance-engine/data/external")
class Settings(BaseSettings):
raw_path_: str
processed_path_: str
models_path_:str
interim_path_:str
external_path_:str
model_config = SettingsConfigDict(
env_prefix="mrh_avap_",
env_file=".env",
env_file_encoding="utf-8",
case_sensitive=False,
extra="ignore",
)
@property
def raw_path(self) -> Path:
return Path(self.raw_path_)
@property
def processed_path(self) -> Path:
return Path(self.processed_path_)
@property
def proj_root(self) -> Path:
return Path(__file__).resolve().parents[1]
@property
def interim_path(self) -> Path:
return Path(self.interim_path_)
@property
def external_path(self) -> Path:
return Path(self.external_path_)
@property
def models_path(self) -> Path:
return Path(self.models_path_)
settings = Settings()

2
Docker/docker-compose.yaml
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@ -13,7 +13,7 @@ services:
LANGFUSE_HOST: ${LANGFUSE_HOST}
LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY}
LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY}
OLLAMA_URL: ${OLLAMA_LOCAL_URL}
OLLAMA_URL: ${OLLAMA_URL}
OLLAMA_MODEL_NAME: ${OLLAMA_MODEL_NAME}
OLLAMA_EMB_MODEL_NAME: ${OLLAMA_EMB_MODEL_NAME}

24
Docker/src/instances.py
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@ -1,24 +0,0 @@
import os
from langchain_elasticsearch import ElasticsearchStore
from utils.llm_factory import create_chat_model
from utils.emb_factory import create_embedding_model
llm = create_chat_model(
provider="ollama",
model=os.getenv("OLLAMA_MODEL_NAME"),
temperature=0,
validate_model_on_init=True,
)
embeddings = create_embedding_model(
provider="ollama",
model=os.getenv("OLLAMA_EMB_MODEL_NAME"),
)
vector_store = ElasticsearchStore(
es_url=os.getenv("ELASTICSEARCH_URL"),
index_name=os.getenv("ELASTICSEARCH_INDEX"),
embedding=embeddings,
query_field="text",
vector_query_field="vector",
)

5
Docker/src/server.py
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@ -1,15 +1,12 @@
import logging
import os
import sys
from concurrent import futures
from pathlib import Path
from typing import Any
import brunix_pb2
import brunix_pb2_grpc
import grpc
from grpc_reflection.v1alpha import reflection
from langchain_core.prompts import ChatPromptTemplate
from langchain_elasticsearch import ElasticsearchStore
from utils.llm_factory import create_chat_model
@ -35,12 +32,14 @@ class BrunixEngine(brunix_pb2_grpc.AssistanceEngineServicer):
self.llm = create_chat_model(
provider="ollama",
model=os.getenv("OLLAMA_MODEL_NAME"),
base_url=os.getenv("OLLAMA_URL"),
temperature=0,
validate_model_on_init=True,
)
self.embeddings = create_embedding_model(
provider="ollama",
model=os.getenv("OLLAMA_EMB_MODEL_NAME"),
base_url=os.getenv("OLLAMA_URL"),
)
self.vector_store = ElasticsearchStore(
es_url=os.getenv("ELASTICSEARCH_URL"),

108
notebooks/langgraph_agent_simple.ipynb
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6
scripts/start-tunnels.sh
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@ -22,9 +22,9 @@ if [ ! -f "$KUBECONFIG_PATH" ]; then
fi
# 1. AI Model Tunnel (Ollama)
# echo -e "${YELLOW}[1/3]${NC} Starting Ollama Light Service tunnel (localhost:11434)..."
# kubectl port-forward --address 0.0.0.0 svc/ollama-light-service 11434:11434 -n brunix --kubeconfig "$KUBECONFIG_PATH" &
# OLLAMA_PID=$!
echo -e "${YELLOW}[1/3]${NC} Starting Ollama Light Service tunnel (localhost:11434)..."
kubectl port-forward --address 0.0.0.0 svc/ollama-light-service 11434:11434 -n brunix --kubeconfig "$KUBECONFIG_PATH" &
OLLAMA_PID=$!
# 2. Knowledge Base Tunnel (Elasticsearch)
echo -e "${YELLOW}[2/3]${NC} Starting Elasticsearch Vector DB tunnel (localhost:9200)..."