# LLM Configuration (Beta) Diffblue Cover supports remote AI/LLM integration to enhance features such as object creation, string generation, and automated test completion. Configuration options for LLMs are managed using `cover.properties`, environment variables, and system properties, with the same precedence and formatting rules as other Diffblue Cover properties. ### Configuring LLMs in `cover.properties` The initial use case for Cover using LLMs is to produce more interesting `String` inputs. Multiple named LLM connections can be defined in `~/.diffblue/cover.properties` so that experiments switching between various configurations can be performed with minimal fuss. The following example configuration defines a connection named "external" and configures `String` creation to make use of it: ``` cover.llm.strings=external cover.llm.api.external.provider=OpenAI cover.llm.api.external.model=gpt-4 cover.llm.api.external.key=sk-proj-ABCDEFGHIJKLM ``` This configuration tells cover to enable sourcing strings from the "external" LLM connection, which is then configured to use OpenAI's `gpt-4` model with a specific key. Some organisations have a custom LLM installation with embedded domain-specific knowledge, accessible at some internal URL. To begin comparisons with this you could define a new "internal" connection using these new settings: ``` cover.llm.api.internal.provider=Anthropic cover.llm.api.internal.model=claude-sonnet-4-5 cover.llm.api.internal.key=sk-ant-NOPQRSTUVWXYZ cover.llm.api.internal.url=https://claude.internal.example.com ``` Now all that remains is to switch to use this new connection for `String` inputs: ``` cover.llm.strings=internal ``` *** ### Environment Checks During the environment checks phase the detected configuration will be logged (and shown in the console if running `--verbose` mode) indicating which named configuration was picked up: ``` INFO Detected LLM 'internal' configuration ``` Some minimal validation is performed as part of the environment checks to ensure that Cover will have enough information in order to connect later on. If you've mistyped a provider so that it's not supported, provided a non-numeric token limit, or Cover has not been able to identify a default URL to use then the environment checks will fail with an error along the following lines: ``` ERROR E158: LLM misconfigured The provided configuration for calling out to an LLM is invalid. - Postprocessing should be true or false but found: yes special: - Unknown provider: anthropomorphic - Provider should be one of Anthropic, AzureML, Copilot, Llama, OpenAI - Missing url - Invalid prompt token limit: 6000x provider: anthropomorphic model: claude-sonnet-4-5 key: ******* url: deployment: preferred: - Invalid prompt token limit: 6000x provider: OpenAI model: gpt-5 key: ******* url: http://openai.internal.example.com/ deployment: internal Please refer to configuration documentation. ``` Note that currently these checks do not include any active communication and so invalid URLs, models, and keys may cause failures later in the process. *** ### Configuration Properties | Property | Description | | -------------------------------------- | ------------------------------------------------------------------------------- | | `cover.llm.strings` | Enables string creation mode; set to "preferred" or "special". | | `cover.llm.postprocessing` | Whether to post-process LLM results (default: true, set to `false` to disable). | | `cover.llm.api..provider` | Name of the preferred LLM provider (e.g., OpenAI, Anthropic). | | `cover.llm.api..model` | Name of the preferred LLM model to use. | | `cover.llm.api..key` | API key for the preferred provider. | | `cover.llm.api..url` | Custom API endpoint, if applicable. | | `cover.llm.api..deployment` | Optional deployment specifier. | | `cover.llm.api..tokens.prompt` | Token limit for LLM prompts (optional, default depends on provider/model). | | `cover.llm.api..tokens.response` | Token limit for LLM responses (optional, default depends on provider/model). | ### Applying Changes When adjusting `cover.properties`, ensure Cover is restarted (and Intellij, if using the Cover Plugin), so new settings are loaded by the JVM. In time it is expected that Cover will automatically identify when to use LLM inputs based on various heuristics. For now the `@InTestsUseLLM` annotation is needed to identify the package / class / method context where LLM inputs should be provided. Please refer to [LLM Input Annotations (Beta)](/features/cover-annotations/llm-input-annotations-beta.md) for guidance on using the annotation. ### OpenAI Example To enable string creation with the "default" OpenAI `gpt-4`, use the following in `.diffblue/cover.properties`: ``` cover.llm.strings=default cover.llm.api.default.provider=OpenAI cover.llm.api.default.model=gpt-4 cover.llm.api.default.key=sk-proj-ABCDEFGHIJKLM ``` ### Anthropic / Claude Example Alternatively to do the same but using Anthropic's `claude-sonnet-4-5` model, use the following: ``` cover.llm.strings=default cover.llm.api.default.provider=Anthropic cover.llm.api.default.model=claude-sonnet-4-5 cover.llm.api.default.key=sk-ant-NOPQRSTUVWXYZ ``` This structure ensures LLM configuration is managed consistently with all other Diffblue Cover properties and can be overridden at runtime as necessary for flexibility in various execution and CI environments. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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