Merge branch 'main' into evaluating-search-engines

Author: freddiev4

notebooks/en/_toctree.yml

@@ -5,6 +5,12 @@
     - local: index
       title: Overview
 
+    - title: MLOps Recipes
+      isExpanded: false
+      sections:
+        - local: mlflow_ray_serve
+          title: Signature-Aware Model Serving from MLflow with Ray Serve
+
     - title: LLM Recipes
       isExpanded: false
       sections:
@@ -66,7 +72,9 @@
           title: Enhancing RAG Reasoning with Knowledge Graphs
         - local: phoenix_observability_on_hf_spaces
           title: Phoenix Observability Dashboard on HF Spaces
-          
+        - local: search_and_learn
+          title: Scaling Test-Time Compute for Longer Thinking in LLMs
+
     - title: Computer Vision Recipes
       isExpanded: false
       sections:
@@ -100,23 +108,26 @@
           title: Fine-tuning SmolVLM with TRL on a consumer GPU
         - local: multimodal_rag_using_document_retrieval_and_smol_vlm
           title: Smol Multimodal RAG, Building with ColSmolVLM and SmolVLM on Colab's Free-Tier GPU
-
+        - local: fine_tuning_vlm_dpo_smolvlm_instruct
+          title: Fine-tuning SmolVLM using direct preference optimization (DPO) with TRL on a consumer GPU
+        - local: structured_generation_vision_language_models
+          title: Structured Generation from Images or Documents Using Vision Language Models
 
     - title: Search Recipes
       isExpanded: false
       sections:
       - local: semantic_reranking_elasticsearch
         title: Semantic Reranking with Elasticsearch
+      - local: vector_search_with_hub_as_backend
+        title: Vector Search on Hugging Face with the Hub as Backend
 
     - title: Agents Recipes
       isExpanded: false
       sections:
         - local: agents
-          title: Build an agent with tool-calling superpowers using Transformers Agents
+          title: Build an agent with tool-calling superpowers using smolagents
         - local: agent_rag
           title: Agentic RAG - turbocharge your RAG with query reformulation and self-query
-        - local: agent_change_llm
-          title: Create a Transformers Agent from any LLM inference provider
         - local: agent_text_to_sql
           title: Agent for Text-to-SQL with automatic error correction
         - local: agent_data_analyst
@@ -125,6 +136,8 @@
           title: Have several agents collaborate in a multi-agent hierarchy
         - local: multiagent_rag_system
           title: Multi-agent RAG System 🤖🤝🤖
+        - local: mongodb_smolagents_multi_micro_agents
+          title: MongoDB + SmolAgents Multi-Micro Agents to facilitate a data driven order-delivery AI agent
 
 - title: Enterprise Hub Cookbook
   isExpanded: True

notebooks/en/advanced_rag.ipynb

@@ -28,7 +28,7 @@
     "\n",
     "In this notebook, we will take a look into many of these blue notes to see how to tune your RAG system and get the best performance.\n",
     "\n",
-    "__Let's dig into the model building!__ First, we install the required model dependancies."
+    "__Let's dig into the model building!__ First, we install the required model dependencies."
    ]
   },
   {
@@ -39,7 +39,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install -q torch transformers transformers accelerate bitsandbytes langchain sentence-transformers faiss-cpu openpyxl pacmap datasets langchain-community ragatouille"
+    "!pip install -q torch transformers accelerate bitsandbytes langchain sentence-transformers faiss-cpu openpyxl pacmap datasets langchain-community ragatouille"
    ]
   },
   {
@@ -272,7 +272,7 @@
     "👀 As you can see, __the chunk lengths are not aligned with our limit of 512 tokens__, and some documents are above the limit, thus some part of them will be lost in truncation!\n",
     " - So we should change the `RecursiveCharacterTextSplitter` class to count length in number of tokens instead of number of characters.\n",
     " - Then we can choose a specific chunk size, here we would choose a lower threshold than 512:\n",
-    "    - smaller documents could allow the split to focus more on specific ideas.\n",
+    "    - Smaller documents could allow the split to focus more on specific ideas.\n",
     "    - But too small chunks would split sentences in half, thus losing meaning again: the proper tuning is a matter of balance."
    ]
   },