modified config.py

scratches/pseco/ingestion/Code Ingestion/n00 Proper Lark Chunking.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 5,
    "id": "0a8abbfa",
    "metadata": {},
    "outputs": [
@@ -12,7 +12,7 @@
        "True"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -24,7 +24,7 @@
     "from dataclasses import dataclass\n",
     "from pathlib import Path\n",
     "from typing import Any, Dict, List, Optional, Tuple\n",
-    "from bnf import grammar\n",
+    "# from bnf import grammar\n",
     "import nltk\n",
     "from elasticsearch import Elasticsearch\n",
     "from langchain_core.documents import Document\n",
@@ -33,26 +33,40 @@
     "from lark import Lark, Token, Transformer, Tree\n",
     "from transformers import AutoConfig\n",
     "\n",
-    "from src.config import (DATA_DIR, ELASTICSEARCH_CODE_INDEX,\n",
+    "from src.config import settings\n",
-    "                        ELASTICSEARCH_DOCS_INDEX, ELASTICSEARCH_INDEX,\n",
-    "                        ELASTICSEARCH_URL, HF_EMB_MODEL_NAME,\n",
-    "                        OLLAMA_EMB_MODEL_NAME, OLLAMA_LOCAL_URL,\n",
-    "                        OLLAMA_MODEL_NAME, OLLAMA_URL, PROJ_ROOT)\n",
     "\n",
     "nltk.download(\"punkt\", quiet=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 6,
    "id": "5c9d292b",
    "metadata": {},
    "outputs": [],
    "source": [
-    "config = AutoConfig.from_pretrained(HF_EMB_MODEL_NAME)\n",
+    "config = AutoConfig.from_pretrained(settings.hf_emb_model_name)\n",
     "embedding_dim = config.hidden_size"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "d2009c2b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "qwen3.5:2b\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(settings.ollama_model_name)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "baa779f3",

src/config.py

@@ -1,39 +1,150 @@
 from pathlib import Path
+from pydantic_settings import BaseSettings, SettingsConfigDict
+from pydantic import Field
 from dotenv import load_dotenv
-import os
+from datetime import timedelta
+import warnings
+
 
 load_dotenv()
 
-OPENAI_API_KEY=os.getenv("OPENAI_API_KEY", "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")
+class Settings(BaseSettings):
+    raw_path_: str 
+    data_path_: str
+    processed_path_: str 
+    models_path_: str 
+    external_path_: str 
+    kubeconfig_path: str 
+    interim_path_: str 
+    database_url: str 
+    openai_api_key: str 
+    elasticsearch_index: str 
+    elasticsearch_docs_index: str 
+    elasticsearch_code_index: str 
+    llm_base_url: str 
+    ollama_url: str 
+    ollama_local_url: str 
+    langfuse_host: str 
+    elasticsearch_url: str 
+    elasticsearch_local_url: str 
+    ollama_model_name: str 
+    ollama_emb_model_name: str 
+    model_name: str 
+    hf_emb_model_name: str 
+    langfuse_public_key: str 
+    langfuse_secret_key: str 
+    hf_token: str 
 
-OLLAMA_URL=os.getenv("OLLAMA_URL", "http://host.docker.internal:11434")
+    model_config = SettingsConfigDict(
-OLLAMA_LOCAL_URL=os.getenv("OLLAMA_LOCAL_URL", "http://localhost:11434")
+        env_file=".env",
-OLLAMA_MODEL_NAME=os.getenv("OLLAMA_MODEL_NAME", "qwen3-0.6B:latest")
+        env_file_encoding="utf-8",
-OLLAMA_EMB_MODEL_NAME=os.getenv("OLLAMA_EMB_MODEL_NAME", "qwen3-0.6B-emb:latest")
+        case_sensitive=False,
-ELASTICSEARCH_DOCS_INDEX = os.getenv("ELASTICSEARCH_DOCS_INDEX")
+        extra="ignore",
-ELASTICSEARCH_CODE_INDEX = os.getenv("ELASTICSEARCH_CODE_INDEX")
+    )
 
-LANGFUSE_HOST=os.getenv("LANGFUSE_HOST", "http://45.77.119.180")
+    @property
-LANGFUSE_PUBLIC_KEY=os.getenv("LANGFUSE_PUBLIC_KEY", "pk-lf-0e6db694-3e95-4dd4-aedf-5a2694267058")
+    def data_path(self) -> Path:
-LANGFUSE_SECRET_KEY=os.getenv("LANGFUSE_SECRET_KEY", "sk-lf-dbf28bb9-15bb-4d03-a8c3-05caa3e3905f")
+        return Path(self.data_path_)
     
-ELASTICSEARCH_URL=os.getenv("ELASTICSEARCH_URL", "http://host.docker.internal:9200")
+    @property
-ELASTICSEARCH_LOCAL_URL=os.getenv("ELASTICSEARCH_LOCAL_URL", "http://localhost:9200")
+    def models_path(self) -> Path:
-ELASTICSEARCH_INDEX=os.getenv("ELASTICSEARCH_INDEX", "avap-docs-test")
+        return Path(self.models_path_)
 
-DATABASE_URL=os.getenv("DATABASE_URL", "postgresql://postgres:brunix_pass@host.docker.internal:5432/postgres")
+    @property
+    def processed_path(self) -> Path:
+        return Path(self.processed_path_)
 
-KUBECONFIG_PATH=os.getenv("KUBECONFIG_PATH", "kubernetes/kubeconfig.yaml")
+    @property
+    def raw_path(self) -> Path:
+        return Path(self.raw_path_)
 
-HF_TOKEN=os.getenv("HF_TOKEN", "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")
+    @property
-HF_EMB_MODEL_NAME=os.getenv("HF_EMB_MODEL_NAME", "Qwen/Qwen3-Embedding-0.6B")
+    def interim_path(self) -> Path:
+        return Path(self.interim_path_)
 
-PROJ_ROOT = Path(__file__).resolve().parents[1]
+    @property
+    def external_path(self) -> Path:
+        return Path(self.external_path_)
 
-DATA_DIR=PROJ_ROOT / "data"
+    @property
-MODELS_DIR=DATA_DIR / "models"
+    def proj_root(self) -> Path:
-RAW_DIR=DATA_DIR / "raw"
+        return Path(__file__).resolve().parents[1]
-PROCESSED_DIR=DATA_DIR / "processed"
+
-INTERIM_DIR=DATA_DIR / "interim"
+    @property
-EXTERNAL_DIR=DATA_DIR / "external"
+    def database_url(self) -> str:
-DOCS_DIR=PROJ_ROOT / "docs"
+        return self.database_url
+
+    @property
+    def openai_api_key(self) -> str:
+        return self.openai_api_key
+
+    @property
+    def elasticsearch_index(self) -> str:
+        return self.elasticsearch_index
+
+    @property
+    def elasticsearch_docs_index(self) -> str:
+        return self.elasticsearch_docs_index
+
+    @property
+    def elasticsearch_code_index(self) -> str:
+        return self.elasticsearch_code_index
+
+    @property
+    def llm_base_url(self) -> str:
+        return self.llm_base_url
+
+    @property
+    def ollama_url(self) -> str:
+        return self.ollama_url
+
+    @property
+    def ollama_local_url(self) -> str:
+        return self.ollama_local_url
+
+    @property
+    def langfuse_host(self) -> str:
+        return self.langfuse_host
+
+    @property
+    def elasticsearch_url(self) -> str:
+        return self.elasticsearch_url
+
+    @property
+    def elasticsearch_local_url(self) -> str:
+        return self.elasticsearch_local_url
+
+    @property
+    def ollama_model_name(self) -> str:
+        return self.ollama_model_name
+
+    @property
+    def ollama_emb_model_name(self) -> str:
+        return self.ollama_emb_model_name
+
+    @property
+    def model_name(self) -> str:
+        return self.model_name
+
+    @property
+    def hf_emb_model_name(self) -> str:
+        return self.hf_emb_model_name
+
+    @property
+    def langfuse_public_key(self) -> str:
+        return self.langfuse_public_key
+
+    @property
+    def langfuse_secret_key(self) -> str:
+        return self.langfuse_secret_key
+
+    @property
+    def hf_token(self) -> str:
+        return self.hf_token
+
+    @property
+    def kubeconfig_path(self) -> Path:
+        return Path(self.kubeconfig_path)
+
+
+settings = Settings()