adding readme methos for create mappings and inference endpoint

Author: Delacrobix

supporting-blog-content/local-rag-with-lightweight-elasticsearch/README.md

@@ -0,0 +1,31 @@
+# Local RAG with Elasticsearch & Local AI
+
+Simple RAG (Retrieval-Augmented Generation) system using Elasticsearch for semantic search and Local AI as model provider.
+
+## Prerequisites
+
+- Docker
+- Python 3.11+
+
+## Quick Start
+
+### 1. Activate Virtual Environment
+
+```bash
+python -m venv venv
+source venv/bin/activate 
+```
+
+### 2. Install Python Dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+### 3. Run the Script
+
+```bash
+python script.py
+```
+
+

supporting-blog-content/local-rag-with-lightweight-elasticsearch/app-logs/why-elasticsearch-is-so-cool.md

@@ -0,0 +1,18 @@
+>>> Why Elastic is so cool?
+
+## Raw Response
+
+```json
+{"created":1763994585,"object":"chat.completion","id":"d96f7e7a-003f-4167-bb07-501aa41ef8e7","model":"dolphin3.0-qwen2.5-0.5b","choices":[{"index":0,"finish_reason":"stop","message":{"role":"assistant","content":"The sky being blue is primarily due to the scattering of sunlight by the Earth's atmosphere. Here are a few key factors contributing to the blue color of the sky:\n\n1. **Scattering of Light**: Blue light is scattered more than other colors by the Earth's atmosphere. This scattering occurs because blue light has a shorter wavelength, which is more likely to travel through the Earth's atmosphere than other wavelengths. The scattering occurs as the light bounces off particles in the atmosphere, such as dust and water vapor, which have a higher concentration in the upper atmosphere.\n\n2. **Atmospheric Composition**: The Earth's atmosphere is composed of gases like nitrogen, oxygen, and water vapor. These gases have different properties, and their interactions with sunlight can affect the colors they transmit. Nitrogen and oxygen gases have a scattering effect that is more intense at shorter wavelengths than water vapor, which results in the blue color observed in the sky.\n\n3. **Atmospheric Reflection**: The blue color of the sky also depends on the amount of light reflecting off the Earth's surface. Clouds, for instance, can reflect a lot of sunlight, particularly blue and green light, which creates a blue tint to the sky. Additionally, the reflection of sunlight from the Earth's surface can contribute to the blue color observed in the sky.\n\n4. **Clouds and Precipitation**: The presence of clouds and precipitation can also affect the color of the sky. Clouds can scatter blue light, but they can also trap it, making the sky appear a bit less blue. Precipitation, particularly heavy rain or snow, can also scatter light, making the sky appear a bit darker and more gray.\n\nIn summary, the blue color of the sky is a result of the scattering of sunlight by the Earth's atmosphere, with the primary contributor being the scattering of blue light and the absorption of other wavelengths by particles in the atmosphere."}}],"usage":{"prompt_tokens":14,"completion_tokens":384,"total_tokens":398}}
+```
+
+## Answer
+
+The sky being blue is primarily due to the scattering of sunlight by the Earth's atmosphere. Here are a few key factors contributing to the blue color of the sky:
+
+1. **Scattering of Light**: Blue light is scattered more than other colors by the Earth's atmosphere. This scattering occurs because blue light has a shorter wavelength, which is more likely to travel through the Earth's atmosphere than other wavelengths. The scattering occurs as the light bounces off particles in the atmosphere, such as dust and water vapor, which have a higher concentration in the upper atmosphere.
+2. **Atmospheric Composition**: The Earth's atmosphere is composed of gases like nitrogen, oxygen, and water vapor. These gases have different properties, and their interactions with sunlight can affect the colors they transmit. Nitrogen and oxygen gases have a scattering effect that is more intense at shorter wavelengths than water vapor, which results in the blue color observed in the sky.
+3. **Atmospheric Reflection**: The blue color of the sky also depends on the amount of light reflecting off the Earth's surface. Clouds, for instance, can reflect a lot of sunlight, particularly blue and green light, which creates a blue tint to the sky. Additionally, the reflection of sunlight from the Earth's surface can contribute to the blue color observed in the sky.
+4. **Clouds and Precipitation**: The presence of clouds and precipitation can also affect the color of the sky. Clouds can scatter blue light, but they can also trap it, making the sky appear a bit less blue. Precipitation, particularly heavy rain or snow, can also scatter light, making the sky appear a bit darker and more gray.
+
+In summary, the blue color of the sky is a result of the scattering of sunlight by the Earth's atmosphere, with the primary contributor being the scattering of blue light and the absorption of other wavelengths by particles in the atmosphere.

supporting-blog-content/local-rag-with-lightweight-elasticsearch/app-logs/why-is-the-sky-blue.md

@@ -5,7 +5,7 @@
 from openai import OpenAI
 
 ES_URL = "http://localhost:9200"
-ES_API_KEY = "your-api-key-here"
+ES_API_KEY = "NDdDQWM1b0JPSDBFTV9JQzA0WVo6eHFXcWFJQmFYNzBwS1RjUllpRUNHZw=="
 INDEX_NAME = "team-data"
 LOCAL_AI_URL = "http://localhost:8080/v1"  # Local AI server URL
 DATASET_FOLDER = "./Dataset"
@@ -15,6 +15,79 @@
 ai_client = OpenAI(base_url=LOCAL_AI_URL, api_key="sk-x")
 
 
+def setup_inference_endpoint():
+    inference_id = "e5-small-model"
+    try:
+        es_client.inference.put(
+            inference_id=inference_id,
+            task_type="text_embedding",
+            body={
+                "service": "elasticsearch",
+                "service_settings": {
+                    "num_allocations": 1,
+                    "num_threads": 1,
+                    "model_id": ".multilingual-e5-small",
+                },
+            },
+        )
+        print(f"✅ Inference endpoint '{inference_id}' created successfully")
+    except Exception as e:
+        print(f"❌ Error creating inference endpoint: {str(e)}")
+
+
+def setup_inference_endpoint():
+    inference_id = "e5-small-model"
+
+    try:
+        es_client.inference.get(inference_id=inference_id)
+        print(f"✅ Inference endpoint '{inference_id}' already exists")
+    except Exception:
+        print(f"📦 Creating inference endpoint '{inference_id}'...")
+
+        try:
+            es_client.inference.put(
+                inference_id=inference_id,
+                task_type="text_embedding",
+                body={
+                    "service": "elasticsearch",
+                    "service_settings": {
+                        "num_allocations": 1,
+                        "num_threads": 1,
+                        "model_id": ".multilingual-e5-small",
+                    },
+                },
+            )
+            print(f"✅ Inference endpoint '{inference_id}' created successfully")
+        except Exception as e:
+            print(f"❌ Error creating inference endpoint: {str(e)}")
+
+
+def setup_index():
+    try:
+        if es_client.indices.exists(index=INDEX_NAME):
+            print(f"✅ Index '{INDEX_NAME}' already exists")
+
+        print(f"📦 Creating index '{INDEX_NAME}'...")
+        es_client.indices.create(
+            index=INDEX_NAME,
+            body={
+                "mappings": {
+                    "properties": {
+                        "file_title": {"type": "text", "copy_to": "semantic_field"},
+                        "file_content": {"type": "text", "copy_to": "semantic_field"},
+                        "semantic_field": {
+                            "type": "semantic_text",
+                            "inference_id": "e5-small-model",
+                        },
+                    }
+                }
+            },
+        )
+        print(f"✅ Index '{INDEX_NAME}' created successfully")
+    except Exception as e:
+        print(f"❌ Error creating index: {str(e)}")
+
+
 def build_documents(dataset_folder, index_name):
     for filename in os.listdir(dataset_folder):
         if filename.endswith(".txt"):
@@ -88,7 +161,13 @@ def query_local_ai(prompt, model):
 
 
 if __name__ == "__main__":
-    print("📥 Indexing documents...")
+    print("🚀 Setting up infrastructure...")
+
+    # Setup inference endpoint and index
+    setup_inference_endpoint()
+    setup_index()
+
+    print("\n📥 Indexing documents...")
     success, bulk_latency = index_documents()
 
     time.sleep(2)  # Wait for indexing to complete
@@ -106,7 +185,10 @@ def query_local_ai(prompt, model):
 
     prompt = f"{context}\nQuestion: {query}\nAnswer:"
 
-    ai_model = "dolphin3.0-qwen2.5-0.5b"
+    # ai_model = "llama-smoltalk-3.2-1b-instruct"
+    # ai_model = "dolphin3.0-qwen2.5-0.5b"
+    # ai_model = "fastllama-3.2-1b-instruct"
+    ai_model = "smollm2-1.7b-instruct"
 
     print(f"🤖 Asking to model: {ai_model}")
     response, ai_latency, tokens_per_second = query_local_ai(prompt, ai_model)