Added improved docs index and overview pages and quickstart (#3603)

docs/components/rerankers/models/cohere.mdx

@@ -1,8 +1,6 @@
 ---
 title: Cohere
-description: 'Reranking with Cohere'
-icon: "building"
-iconType: "solid"
+description: "Reranking with Cohere"
 ---
 
 Cohere provides enterprise-grade reranking models with excellent multilingual support and production-ready performance.
@@ -37,7 +35,7 @@ config = {
     "llm": {
         "provider": "openai",
         "config": {
-            "model": "gpt-4o-mini"
+            "model": "gpt-4.1-nano-2025-04-14"
         }
     },
     "reranker": {
@@ -124,13 +122,13 @@ config = {
 
 ## Configuration Parameters
 
-| Parameter | Description | Type | Default |
-|-----------|-------------|------|---------|
-| `model` | Cohere rerank model to use | `str` | `"rerank-english-v3.0"` |
-| `api_key` | Cohere API key | `str` | `None` |
-| `top_k` | Maximum documents to return | `int` | `None` |
-| `return_documents` | Whether to return document texts | `bool` | `False` |
-| `max_chunks_per_doc` | Maximum chunks per document | `int` | `None` |
+| Parameter            | Description                      | Type   | Default                 |
+| -------------------- | -------------------------------- | ------ | ----------------------- |
+| `model`              | Cohere rerank model to use       | `str`  | `"rerank-english-v3.0"` |
+| `api_key`            | Cohere API key                   | `str`  | `None`                  |
+| `top_k`              | Maximum documents to return      | `int`  | `None`                  |
+| `return_documents`   | Whether to return document texts | `bool` | `False`                 |
+| `max_chunks_per_doc` | Maximum chunks per document      | `int`  | `None`                  |
 
 ## Features
 
@@ -144,4 +142,4 @@ config = {
 1. **Model Selection**: Use `rerank-english-v3.0` for English, `rerank-multilingual-v3.0` for other languages
 2. **Batch Processing**: Process multiple queries efficiently
 3. **Error Handling**: Implement retry logic for production systems
-4. **Monitoring**: Track reranking performance and costs
+4. **Monitoring**: Track reranking performance and costs

docs/components/rerankers/models/huggingface.mdx

@@ -1,8 +1,6 @@
 ---
 title: Hugging Face Reranker
 description: 'Access thousands of reranking models from Hugging Face Hub'
-icon: "face-smile"
-iconType: "solid"
 ---
 
 ## Overview

docs/components/rerankers/models/llm.mdx

@@ -1,8 +1,6 @@
 ---
 title: LLM as Reranker
 description: 'Flexible reranking using LLMs'
-icon: "robot"
-iconType: "solid"
 ---
 
 LLM-based reranker provides maximum flexibility by using any Large Language Model to score document relevance. This approach allows for custom prompts and domain-specific scoring logic.

docs/components/rerankers/models/llm_reranker.mdx

@@ -1,8 +1,6 @@
 ---
 title: LLM Reranker
 description: 'Use any language model as a reranker with custom prompts'
-icon: "robot"
-iconType: "solid"
 ---
 
 ## Overview

docs/components/rerankers/models/sentence_transformer.mdx

@@ -1,8 +1,6 @@
 ---
 title: Sentence Transformer
 description: 'Local reranking with HuggingFace cross-encoder models'
-icon: "server"
-iconType: "solid"
 ---
 
 Sentence Transformer reranker provides local reranking using HuggingFace cross-encoder models, perfect for privacy-focused deployments where you want to keep data on-premises.

docs/components/rerankers/models/zero_entropy.mdx

@@ -1,8 +1,6 @@
 ---
 title: Zero Entropy
 description: 'Neural reranking with Zero Entropy'
-icon: "sparkles"
-iconType: "solid"
 ---
 
 [Zero Entropy](https://www.zeroentropy.dev) provides neural reranking models that significantly improve search relevance with fast performance.