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handsome_feng 2022-11-29 11:38:06 +08:00
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@ -12,7 +12,7 @@ dateCreated: 2022-03-11T03:18:01.489Z
CCAI provides many FCGI APIs. They are named `fcgi_xxxx`. Each fcgi API is a fcgi server, running in the background. Client APPs communicate with the fcgi server by using http post protocol.
![image7.png](/temp/image7.png)
![image7.png](./assets/image7.png)
These fcgi APIs will do AI for different cases, such as classification, face detection, OCR, TTS, or ASR. Please refer to the following API list to understand the specific API.
@ -20,7 +20,7 @@ Some fcgi APIs have two working modes. One mode is doing inference locally in th
The following picture shows two working modes.
![image5.png](/temp/image5.png)
![image5.png](./assets/image5.png)
Some FCGI APIs are implemented by two languages, C++ and python. So some APIs have two types of API: python API and C++ API. Both python API and C++ API provide the same functionality and parameters. The only difference is they have different http addresses. So clients' apps can get the same inference result from either FCGI C++ API or python API by using different addresses.
@ -984,7 +984,7 @@ This service is used to monitor the CCAI container.
CCAI framework not only provides FGCI APIs, but also provides many gRPC APIs. Client APPs can do inference by calling gRPC APIs.
![image14.png](/temp/image14.png)
![image14.png](./assets/image14.png)
The following are detailed gRPC APIs.
@ -1158,7 +1158,7 @@ Runtime APIs are *“simple” *APIs. *“simple”* means the number of APIs is
The runtime service library APIs are implemented by two kinds of languages, C++ and python. So it provides two types of APIs. One type is C++ APIs, it can be called by C++ programs directly. Another is python APIs, it is prepared for python programs.
![image13.png](/temp/image13.png)
![image13.png](./assets/image13.png)
**Notice:**

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@ -15,7 +15,7 @@ dateCreated: 2022-03-11T03:18:05.283Z
The picture below is showing the basic working model of CCAI as a whole services provider to provide high level APIs to external users of the services container. Basically, there are 2 methods to use those services which are provided in REST/gRPC APIs form. One is calling those APIs directly, the other one is calling simulation lib APIs (we will talk simulation lib later).
![image2.png](/temp/image2.png)
![image2.png](./assets/image2.png)
# CCAI (1.1 release) stack architecture
@ -24,4 +24,4 @@ The picture below is showing the basic working model of CCAI as a whole services
The architecture picture below is showing those modules and stacks in a high level picture, it shows CCAIs components and their dependencies. It is up to date for CCAI 1.1 release.
![image1.png](/temp/image1.png)
![image1.png](./assets/image1.png)

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@ -10,7 +10,7 @@ dateCreated: 2022-03-11T03:18:07.757Z
# CCAI service work mode
![image4.png](/temp/image4.png)
![image4.png](./assets/image4.png)
AI services for CCAI include two parts, one is client-side, the other is server-side. Customer applications are running on client-side. The CCAI services are running on server-side. Client-side sends http post requests or gRPC requests to server-side, and server-side replies responses to client-side. So developing AI services means development of server-side programs.
@ -140,7 +140,7 @@ Now you can verify your services by your test application from the host.
- Create a directory */opt/intel/service_runtime/service/your-service/* and put your binary file in this directory. Create a directory */opt/intel/service_runtime/service/lighttpd/conf-enabled/* and put your configuration file to this directory. The directory hierarchy example:
![image9.png](/temp/image9.png)
![image9.png](./assets/image9.png)
- Give permission for the user www-data to access your files, example:

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@ -198,11 +198,11 @@ If you want change the default configuration, you can execute make menuconfig
```bash
$>make menuconfig
```
![image18.png](/temp/image18.png)
![image18.png](./assets/image18.png)
You can type Space/Enter to expand a branch, or enable/disable an option.
![image19.png](/temp/image19.png)
![image19.png](./assets/image19.png)
```bash
$> make base_image
@ -309,7 +309,7 @@ $ ./release_build.sh image
You will get 3 Docker images as shown below:
![image20.png](/temp/image20.png)
![image20.png](./assets/image20.png)
b) The image service_runtime needs to be installed to OS on the target device, and the image service_runtime_openvino and the image service_runtime_base need to be saved for future incremental OTA image creation.
@ -336,7 +336,7 @@ If there is no the image service_runtime_openvino found, you may need to pull it
$ docker pull REGISTRY_SERVER/service_runtime_openvino:ubuntu_20.04
$ docker tag REGISTRY_SERVER/service_runtime_openvino:ubuntu_20.04 service_runtime_openvino:ubuntu_20.04
```
![image21.png](/temp/image21.png)
![image21.png](./assets/image21.png)
b) Build the image service_runtime following those instructions in CCAI build document
@ -346,7 +346,7 @@ $ ./release_build.sh image
You will get the Docker image service_runtime which should be installed to the OS of the target device.
![image22.png](/temp/image22.png)
![image22.png](./assets/image22.png)
Example 3, There is a new CCAI release, where both the layer service_runtime_openvino and the layer service_runtime are changed.
@ -363,7 +363,7 @@ $ docker pull REGISTRY_SERVER/service_runtime_base:ubuntu_20.04
$ docker tag REGISTRY_SERVER/service_runtime_base:ubuntu_20.04 service_runtime_base:ubuntu_20.04
```
![image24.png](/temp/image23.png)
![image24.png](./assets/image23.png)
b) Build both the image service_runtime_openvino and the image service_runtime respectively.
@ -371,7 +371,7 @@ b) Build both the image service_runtime_openvino and the image service_runtime r
$ ./release_build.sh openvino_image
$ ./release_build.sh image
```
![image24.png](/temp/image24.png)
![image24.png](./assets/image24.png)
c) The newly generated image service_runtime needs to be installed to the OS of the target device, and the newly generated image service_runtime_openvino needs to be updated to your registry server.

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@ -10,7 +10,7 @@ dateCreated: 2022-03-11T03:18:15.834Z
As mentioned above in chapter 6, CCAI services work mode are:
![image7.png](/temp/image4.png)
![image7.png](./assets/image4.png)
AI services for CCAI include two parts, one is client-side, the other is server-side. Customer applications are so called client-side. The CCAI services are server-side. Client-side sends http post requests or gRPC requests to server-side, and server-side replies responses to client-side.

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@ -21,4 +21,4 @@ In brief, one AI services API framework with the same development mode like deve
* **Intel** - platform differentiating capability developed by Intel
{.grid-list}
![image8.png](/temp/image8.png)
![image8.png](./assets/image8.png)

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