feat: improved compatability layer and responses api handing

docs/content/Models/cloud-providers.mdx

@@ -67,10 +67,11 @@ This is the mechanism behind catalog entries like DeepSeek, which declare their
 For OpenAI models that support it, DocsGPT can call the newer **Responses API** (`/v1/responses`) instead of Chat Completions. This is selected per model in the catalog via an `api_flavor: responses` capability and enables features like server-side reasoning. Related settings:
 
 - `reasoning_effort` — per-model reasoning effort hint (for example `medium`) declared in the model catalog.
-- `OPENAI_RESPONSES_STORE` (default `false`) — when `true`, lets OpenAI persist Responses API state server-side.
+- `OPENAI_RESPONSES_STORE` (default `false`) — when `true`, lets OpenAI persist Responses API state server-side and chains calls with `previous_response_id`. When `false`, DocsGPT requests encrypted reasoning items and persists those ciphertext items itself so reasoning survives tool calls and later conversation turns without OpenAI retaining the response.
+- `V1_SESSION_TTL_SECONDS` (default `86400`) — lifetime of the hashed Redis mapping used to associate OpenAI-compatible client session headers with hidden DocsGPT conversations. Explicit DocsGPT conversation IDs always take precedence.
 
 See [App Configuration](/Deploying/DocsGPT-Settings) for the full settings reference.
 
 ## Adding Support for Other Cloud Providers
 
-If you wish to connect to a cloud provider that is not explicitly listed above or doesn't offer OpenAI API compatibility, you can extend DocsGPT to support it. Within the DocsGPT repository, navigate to the `application/llm` directory. Here, you will find Python files defining the existing LLM integrations.  You can use these files as examples to create a new module for your desired cloud provider.  After creating your new LLM module, you will need to register it within the `llm_creator.py` file. This process involves some coding, but it allows for virtually unlimited extensibility to connect to any cloud-based LLM service with an accessible API.
+If you wish to connect to a cloud provider that is not explicitly listed above or doesn't offer OpenAI API compatibility, you can extend DocsGPT to support it. Within the DocsGPT repository, navigate to the `application/llm` directory. Here, you will find Python files defining the existing LLM integrations.  You can use these files as examples to create a new module for your desired cloud provider.  After creating your new LLM module, you will need to register it within the `llm_creator.py` file. This process involves some coding, but it allows for virtually unlimited extensibility to connect to any cloud-based LLM service with an accessible API.