feat: Add credential and vector store resources with data sources

- Add new litellm_credential resource for managing secure authentication
  - Support for storing sensitive credential values (API keys, tokens, etc.)
  - Non-sensitive credential information storage
  - Model ID association for credentials
  - Secure handling of sensitive data with Terraform's sensitive attribute

- Add new litellm_vector_store resource for managing vector stores
  - Support for multiple vector store providers (Pinecone, Weaviate, Chroma, Qdrant, etc.)
  - Integration with credential management for secure authentication
  - Configurable metadata and provider-specific parameters
  - Full CRUD operations for vector store lifecycle management

- Add corresponding data sources for both resources
  - litellm_credential data source for cross-stack referencing
  - litellm_vector_store data source for monitoring and validation
  - Security-conscious design excluding sensitive values from data sources

- Enhanced API response handling and error management
- Comprehensive documentation and examples for all new resources
- Updated provider configuration and version to 0.3.11

Author: Nicholas Cecere

CHANGELOG.md

@@ -7,6 +7,36 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.3.11] - 2025-08-10
+
+### Added
+- **New Resource**: `litellm_credential` - Manage credentials for secure authentication
+  - Support for storing sensitive credential values (API keys, tokens, etc.)
+  - Non-sensitive credential information storage
+  - Model ID association for credentials
+  - Secure handling of sensitive data with Terraform's sensitive attribute
+- **New Resource**: `litellm_vector_store` - Manage vector stores for embeddings and RAG
+  - Support for multiple vector store providers (Pinecone, Weaviate, Chroma, Qdrant, etc.)
+  - Integration with credential management for secure authentication
+  - Configurable metadata and provider-specific parameters
+  - Full CRUD operations for vector store lifecycle management
+- **New Data Source**: `litellm_credential` - Retrieve information about existing credentials
+  - Read-only access to credential metadata (sensitive values excluded for security)
+  - Support for model ID filtering
+  - Cross-stack and cross-configuration referencing capabilities
+- **New Data Source**: `litellm_vector_store` - Retrieve information about existing vector stores
+  - Complete vector store information retrieval
+  - Support for monitoring, validation, and cross-referencing use cases
+  - Metadata-based conditional logic support
+- Enhanced API response handling for credential and vector store operations
+- Comprehensive documentation and examples for new resources and data sources
+- Example Terraform configurations for common use cases
+
+### Changed
+- Extended `utils.go` with specialized API response handlers for credentials and vector stores
+- Updated provider configuration to include new resources and data sources
+- Enhanced error handling for credential and vector store not found scenarios
+
 ## [0.3.10] - 2025-08-10
 
 ### Added

README.md

@@ -28,7 +28,7 @@ terraform {
   required_providers {
     litellm = {
       source  = "ncecere/litellm"
-      version = "~> 0.3.10"
+      version = "~> 0.3.11"
     }
   }
 }
@@ -132,6 +132,13 @@ For full details on the <code>litellm_key</code> resource, see the [key resource
 - <code>litellm_team_member</code>: Manage team members. [Documentation](docs/resources/team_member.md)
 - <code>litellm_key</code>: Manage API keys. [Documentation](docs/resources/key.md)
 - <code>litellm_mcp_server</code>: Manage MCP (Model Context Protocol) servers. [Documentation](docs/resources/mcp_server.md)
+- <code>litellm_credential</code>: Manage credentials for secure authentication. [Documentation](docs/resources/credential.md)
+- <code>litellm_vector_store</code>: Manage vector stores for embeddings and RAG. [Documentation](docs/resources/vector_store.md)
+
+### Available Data Sources
+
+- <code>litellm_credential</code>: Retrieve information about existing credentials. [Documentation](docs/data-sources/credential.md)
+- <code>litellm_vector_store</code>: Retrieve information about existing vector stores. [Documentation](docs/data-sources/vector_store.md)
 
 ## Development
 

docs/data-sources/credential.md

@@ -0,0 +1,153 @@
+---
+# generated by https://github.com/hashicorp/terraform-plugin-docs
+page_title: "litellm_credential Data Source - terraform-provider-litellm"
+subcategory: ""
+description: |-
+  Retrieves information about an existing LiteLLM credential.
+---
+
+# litellm_credential (Data Source)
+
+Retrieves information about an existing LiteLLM credential. This data source allows you to reference credentials that were created outside of Terraform or in other Terraform configurations.
+
+## Example Usage
+
+```terraform
+# Retrieve an existing credential by name
+data "litellm_credential" "existing_openai" {
+  credential_name = "openai-production-key"
+}
+
+# Use the credential in a model resource
+resource "litellm_model" "gpt4_with_existing_cred" {
+  model_name          = "gpt-4-with-existing-cred"
+  custom_llm_provider = "openai"
+  base_model          = "gpt-4"
+  tier                = "paid"
+  mode                = "chat"
+  
+  # Reference the existing credential's info
+  additional_litellm_params = {
+    credential_name = data.litellm_credential.existing_openai.credential_name
+  }
+}
+```
+
+## Example Usage with Model ID
+
+```terraform
+# Retrieve a credential associated with a specific model
+data "litellm_credential" "model_specific_cred" {
+  credential_name = "claude-api-key"
+  model_id        = "claude-3-sonnet"
+}
+
+# Use in a vector store
+resource "litellm_vector_store" "knowledge_base" {
+  vector_store_name       = "claude-knowledge-base"
+  custom_llm_provider     = "anthropic"
+  litellm_credential_name = data.litellm_credential.model_specific_cred.credential_name
+  
+  vector_store_description = "Knowledge base using Claude credentials"
+}
+```
+
+## Example Usage for Cross-Reference
+
+```terraform
+# Get credential info to use in other resources
+data "litellm_credential" "shared_cred" {
+  credential_name = "shared-api-key"
+}
+
+# Create multiple resources using the same credential
+resource "litellm_vector_store" "store_1" {
+  vector_store_name       = "store-1"
+  custom_llm_provider     = "pinecone"
+  litellm_credential_name = data.litellm_credential.shared_cred.credential_name
+  
+  vector_store_description = "First store using shared credential"
+}
+
+resource "litellm_vector_store" "store_2" {
+  vector_store_name       = "store-2"
+  custom_llm_provider     = "pinecone"
+  litellm_credential_name = data.litellm_credential.shared_cred.credential_name
+  
+  vector_store_description = "Second store using shared credential"
+}
+```
+
+## Argument Reference
+
+The following arguments are supported:
+
+* `credential_name` - (Required) Name of the credential to retrieve.
+* `model_id` - (Optional) Model ID associated with this credential. Use this when the same credential name is used for different models.
+
+## Attributes Reference
+
+In addition to all arguments above, the following attributes are exported:
+
+* `credential_info` - Map of additional non-sensitive information about the credential.
+
+## Security Note
+
+For security reasons, the `credential_values` (sensitive data like API keys) are not exposed through data sources. This prevents accidental exposure of sensitive information in Terraform plans and logs. If you need to access credential values, you should manage them through the resource directly or use external secret management systems.
+
+## Common Use Cases
+
+### 1. Cross-Stack References
+Use data sources to reference credentials created in other Terraform configurations or stacks:
+
+```terraform
+data "litellm_credential" "shared_openai" {
+  credential_name = "openai-shared-key"
+}
+
+resource "litellm_model" "gpt4" {
+  model_name          = "gpt-4-cross-stack"
+  custom_llm_provider = "openai"
+  base_model          = "gpt-4"
+  
+  additional_litellm_params = {
+    credential_reference = data.litellm_credential.shared_openai.credential_name
+  }
+}
+```
+
+### 2. Conditional Logic
+Use credential information for conditional resource creation:
+
+```terraform
+data "litellm_credential" "optional_cred" {
+  credential_name = var.credential_name
+}
+
+resource "litellm_vector_store" "conditional_store" {
+  count = length(data.litellm_credential.optional_cred.credential_info) > 0 ? 1 : 0
+  
+  vector_store_name       = "conditional-store"
+  custom_llm_provider     = "weaviate"
+  litellm_credential_name = data.litellm_credential.optional_cred.credential_name
+}
+```
+
+### 3. Validation and Verification
+Verify that required credentials exist before creating dependent resources:
+
+```terraform
+data "litellm_credential" "required_cred" {
+  credential_name = "production-api-key"
+}
+
+# This will fail if the credential doesn't exist
+resource "litellm_model" "production_model" {
+  model_name          = "production-gpt-4"
+  custom_llm_provider = "openai"
+  base_model          = "gpt-4"
+  
+  additional_litellm_params = {
+    credential_name = data.litellm_credential.required_cred.credential_name
+  }
+}