.

Author: penguine-ip

docs/content/integrations/index.mdx

@@ -71,80 +71,66 @@ Evaluation model integrations configure the LLM provider DeepEval uses for LLM-a
   <Card
     title="OpenAI"
     href="/integrations/models/openai"
-    description="Use OpenAI models for metrics, synthesis, simulation, and optimization."
   />
   <Card
     title="Azure OpenAI"
     href="/integrations/models/azure-openai"
-    description="Use Azure-hosted OpenAI deployments as DeepEval judges."
   />
   <Card
     title="Ollama"
     href="/integrations/models/ollama"
-    description="Run local Ollama models for evaluation."
   />
   <Card
     title="OpenRouter"
     href="/integrations/models/openrouter"
-    description="Route DeepEval model calls through OpenRouter."
   />
   <Card
     title="Anthropic"
     href="/integrations/models/anthropic"
-    description="Use Claude models as evaluation judges."
   />
   <Card
     title="Amazon Bedrock"
     href="/integrations/models/amazon-bedrock"
-    description="Use Bedrock-hosted models for evaluation."
   />
   <Card
     title="Gemini"
     href="/integrations/models/gemini"
-    description="Use Google Gemini models for LLM-as-a-judge metrics."
   />
   <Card
     title="DeepSeek"
     href="/integrations/models/deepseek"
-    description="Configure DeepSeek as an evaluation model provider."
   />
   <Card
     title="Vertex AI"
     href="/integrations/models/vertex-ai"
-    description="Run Gemini through Google Cloud Vertex AI."
   />
   <Card
     title="Grok"
     href="/integrations/models/grok"
-    description="Use xAI Grok models for evaluation."
   />
   <Card
     title="Moonshot"
     href="/integrations/models/moonshot"
-    description="Use Moonshot/Kimi models as judges."
   />
   <Card
     title="Portkey"
     href="/integrations/models/portkey"
-    description="Route model calls through Portkey."
   />
   <Card
     title="vLLM"
     href="/integrations/models/vllm"
-    description="Connect DeepEval to vLLM-hosted models."
   />
   <Card
     title="LM Studio"
     href="/integrations/models/lmstudio"
-    description="Use local LM Studio models for evaluation."
   />
   <Card
     title="LiteLLM"
     href="/integrations/models/litellm"
-    description="Use LiteLLM to route evaluation calls across providers."
   />
 </Cards>
 
+
 ## Vector DBs
 
 Vector database integrations show how to connect retrieval systems to DeepEval so RAG metrics can evaluate the context your application actually retrieves. Use these examples to benchmark retrieval quality and end-to-end RAG behavior.
@@ -153,31 +139,25 @@ Vector database integrations show how to connect retrieval systems to DeepEval s
   <Card
     title="Cognee"
     href="/integrations/vector-databases/cognee"
-    description="Evaluate retrieval from Cognee semantic memory graphs."
   />
   <Card
     title="Elasticsearch"
     href="/integrations/vector-databases/elasticsearch"
-    description="Evaluate RAG systems backed by Elasticsearch retrieval."
   />
   <Card
     title="Chroma"
     href="/integrations/vector-databases/chroma"
-    description="Evaluate Chroma-based vector search and RAG pipelines."
   />
   <Card
     title="Weaviate"
     href="/integrations/vector-databases/weaviate"
-    description="Evaluate retrieval quality from Weaviate collections."
   />
   <Card
     title="Qdrant"
     href="/integrations/vector-databases/qdrant"
-    description="Evaluate Qdrant-backed retrieval systems."
   />
   <Card
     title="PGVector"
     href="/integrations/vector-databases/pgvector"
-    description="Evaluate Postgres/PGVector retrieval pipelines."
   />
 </Cards>