GITBOOK-521: docs: deprecate old models and o1-mini

Author: techpro-aimlapi

docs/SUMMARY.md

@@ -101,7 +101,6 @@
     * [gpt-4o-search-preview](api-references/text-models-llm/openai/gpt-4o-search-preview.md)
     * [gpt-4o-mini-search-preview](api-references/text-models-llm/openai/gpt-4o-mini-search-preview.md)
     * [o1](api-references/text-models-llm/OpenAI/o1.md)
-    * [o1-mini](api-references/text-models-llm/OpenAI/o1-mini.md)
     * [o3](api-references/text-models-llm/openai/o3.md)
     * [o3-mini](api-references/text-models-llm/OpenAI/o3-mini.md)
     * [o3-pro](api-references/text-models-llm/openai/o3-pro.md)

docs/api-references/model-database.md

@@ -116,7 +116,6 @@ def get_video(gen_id):
     return response.json()
 
 
-
 def main():
      # Running video generation and getting a task id
     gen_response = generate_video()

docs/api-references/text-models-llm/OpenAI/o1-mini.md

@@ -310,4 +310,4 @@ Processing complete:/n {'id': 'cgt-20250704191750-n4qjp', 'status': 'completed',
 
 **Low-res GIF preview**:
 
-<div align="left"><figure><img src="../../../.gitbook/assets/seedance_t2v_preview.gif" alt=""><figcaption><p><code>"A menacing evil dragon appears in a distance above the tallest mountain, then rushes toward the camera with its jaws open, revealing massive fangs. We see it's coming."</code></p></figcaption></figure></div>
+<div align="left"><figure><img src="../../../.gitbook/assets/seedance_t2v_preview.gif" alt=""><figcaption><p><code>"A menacing evil dragon appears in a distance above the tallest mountain, then</code> <br><code>rushes toward the camera with its jaws open, revealing massive fangs. We see it's coming."</code></p></figcaption></figure></div>

docs/api-references/text-models-llm/README.md

@@ -26,15 +26,37 @@ If you don’t have an API key for the AI/ML API yet, feel free to use our [Quic
 
 <summary>Step-by-Step Instructions</summary>
 
-Generating a video using this model involves sequentially calling two endpoints:&#x20;
+Generating a video using this model involves sequentially calling two endpoints:
 
 * The first one is for creating and sending a video generation task to the server (returns a generation ID).
-* The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.&#x20;
+* The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.
 
 Below, you can find both corresponding API schemas.
 
 </details>
 
+## API Schemas
+
+### Create a video generation task and send it to the server
+
+You can generate a video using this API. In the basic setup, you only need a prompt.\
+This endpoint creates and sends a video generation task to the server — and returns a generation ID.
+
+Note that in this model, the video duration is defined by the number of frames, not seconds. You can calculate the duration in seconds based on the frame rate of 16 frames per second.
+
+{% openapi-operation spec="krea-wan-14b-text-to-video" path="/v2/video/generations" method="post" %}
+[OpenAPI krea-wan-14b-text-to-video](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Krea/krea-wan-14b-text-to-video.json)
+{% endopenapi-operation %}
+
+### Retrieve the generated video from the server
+
+After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its `generation_id`, obtained from the endpoint described above.\
+If the video generation task status is `complete`, the response will include the final result — with the generated video URL and additional metadata.
+
+{% openapi-operation spec="fetch-video-universal-endpoint" path="/v2/video/generations" method="get" %}
+[OpenAPI fetch-video-universal-endpoint](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Sber-AI/kandinsky5-t2v-pair.json)
+{% endopenapi-operation %}
+
 ## Full Example: Generating and Retrieving the Video From the Server
 
 The code below creates a video generation task, then automatically polls the server every **10** seconds until it finally receives the video URL.
@@ -273,32 +295,8 @@ Processing complete:/n {'id': '67b69e0c-922f-4eae-9b90-8c4605131d3b:krea/krea-wa
 
 </details>
 
-**Processing time**:  11.6 sec.
+**Processing time**: 11.6 sec.
 
 **Generated Video** (832x480, without sound):
 
 {% embed url="https://drive.google.com/file/d/1lgAtCN0R_QTHStjbU4jFmggeFRd0PK-A/view" %}
-
-## API Schemas
-
-### Create a video generation task and send it to the server
-
-You can generate a video using this API. In the basic setup, you only need a prompt. \
-This endpoint creates and sends a video generation task to the server — and returns a generation ID.
-
-Note that in this model, the video duration is defined by the number of frames, not seconds. You can calculate the duration in seconds based on the frame rate of 16 frames per second.
-
-
-
-{% openapi-operation spec="krea-wan-14b-text-to-video" path="/v2/video/generations" method="post" %}
-[OpenAPI krea-wan-14b-text-to-video](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Krea/krea-wan-14b-text-to-video.json)
-{% endopenapi-operation %}
-
-### Retrieve the generated video from the server
-
-After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its `generation_id`, obtained from the endpoint described above.\
-If the video generation task status is `complete`, the response will include the final result — with the generated video URL and additional metadata.
-
-{% openapi-operation spec="fetch-video-universal-endpoint" path="/v2/video/generations" method="get" %}
-[OpenAPI fetch-video-universal-endpoint](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Sber-AI/kandinsky5-t2v-pair.json)
-{% endopenapi-operation %}

docs/api-references/video-models/bytedance/seedance-1.0-lite-image-to-video.md

@@ -26,15 +26,35 @@ If you don’t have an API key for the AI/ML API yet, feel free to use our [Quic
 
 <summary>Step-by-Step Instructions</summary>
 
-Generating a video using this model involves sequentially calling two endpoints:&#x20;
+Generating a video using this model involves sequentially calling two endpoints:
 
 * The first one is for creating and sending a video generation task to the server (returns a generation ID).
-* The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.&#x20;
+* The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.
 
 Below, you can find both corresponding API schemas.
 
 </details>
 
+## API Schemas
+
+### Create a video generation task and send it to the server
+
+You can generate a video using this API. In the basic setup, you only need a prompt.\
+This endpoint creates and sends a video generation task to the server — and returns a generation ID.
+
+{% openapi-operation spec="krea-wan-14b-video-to-video" path="/v2/video/generations" method="post" %}
+[OpenAPI krea-wan-14b-video-to-video](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Krea/krea-wan-14b-video-to-video.json)
+{% endopenapi-operation %}
+
+### Retrieve the generated video from the server
+
+After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its `generation_id`, obtained from the endpoint described above.\
+If the video generation task status is `complete`, the response will include the final result — with the generated video URL and additional metadata.
+
+{% openapi-operation spec="fetch-video-universal-endpoint" path="/v2/video/generations" method="get" %}
+[OpenAPI fetch-video-universal-endpoint](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Sber-AI/kandinsky5-t2v-pair.json)
+{% endopenapi-operation %}
+
 ## Full Example: Generating and Retrieving the Video From the Server
 
 The code below creates a video generation task, then automatically polls the server every **10** seconds until it finally receives the video URL.
@@ -282,23 +302,3 @@ Processing complete:/n {'id': '3637be63-2db8-4ecc-bc0f-00afbdf10a55:krea/krea-wa
 **Generated Video** (832x480, without sound):
 
 {% embed url="https://drive.google.com/file/d/1Npu3ROPtLTf2CY07jRwZMCNGunxaBEAU/view?usp=sharing" %}
-
-## API Schemas
-
-### Create a video generation task and send it to the server
-
-You can generate a video using this API. In the basic setup, you only need a prompt. \
-This endpoint creates and sends a video generation task to the server — and returns a generation ID.
-
-{% openapi-operation spec="krea-wan-14b-video-to-video" path="/v2/video/generations" method="post" %}
-[OpenAPI krea-wan-14b-video-to-video](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Krea/krea-wan-14b-video-to-video.json)
-{% endopenapi-operation %}
-
-### Retrieve the generated video from the server
-
-After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its `generation_id`, obtained from the endpoint described above.\
-If the video generation task status is `complete`, the response will include the final result — with the generated video URL and additional metadata.
-
-{% openapi-operation spec="fetch-video-universal-endpoint" path="/v2/video/generations" method="get" %}
-[OpenAPI fetch-video-universal-endpoint](https://raw.githubusercontent.com/aimlapi/api-docs/refs/heads/main/docs/api-references/video-models/Sber-AI/kandinsky5-t2v-pair.json)
-{% endopenapi-operation %}