This quickstart demonstrates how to create a simple LLM application. It shows you how to connect to the LLM and perform a basic chat interaction.
Requirements:
-
You have a valid Google Gemini API Key.
-
Import Google Gemini server certificates into SAP trust manager. The abapGit documentation explains in detail how to do it.
Note: To run the application on SAP NetWeaver AS ABAP Developer Edition, we recommend using NGINX as a reverse proxy to expose a local HTTP endpoint—it’s much simpler than manually configuring SSL on the SAP system.
Steps:
- Create an ABAP AI Connection instance;
- Set the Base URL;
- Set the API Key;
- Create an ABAP AI Google Gemini instance;
- Call the CHAT method.
Example:
REPORT yaai_r_simple_llm_app_google LINE-SIZE 500.
DATA(o_aai_conn) = NEW ycl_aai_conn( i_api = 'GOOGLE' ).
o_aai_conn->set_base_url( i_base_url = 'https://generativelanguage.googleapis.com' ).
" The hardcoded API key in this example is intended for testing and development only.
" Hardcoding API keys directly into your ABAP code is highly discouraged.
o_aai_conn->set_api_key( i_api_key = 'REPLACE_THIS_TEXT_WITH_YOUR_GOOGLE_GEMINI_API_KEY' ).
o_aai_conn->yif_aai_conn~suppress_content_type( ).
DATA(o_aai_google) = NEW ycl_aai_google( i_model = 'gemini-2.5-flash'
i_o_connection = o_aai_conn ).
o_aai_google->chat(
EXPORTING
i_message = 'What is the capital of Italy?'
IMPORTING
e_t_response = DATA(t_response)
).
LOOP AT t_response INTO DATA(l_response_line).
WRITE: / l_response_line.
ENDLOOP.Result:
The following screenshot shows the output you can expect after running the example ABAP AI report. The response from the LLM will be displayed line by line in the SAP GUI output window.
The ABAP AI Chat stores all conversation exchanges in memory. At any time, you can retrieve the full conversation history, allowing you to review previous messages or continue the dialogue seamlessly.
REPORT yaai_r_simple_llm_chat_google.
SELECTION-SCREEN BEGIN OF BLOCK b1 WITH FRAME.
PARAMETERS: p_model TYPE string DEFAULT 'gemini-2.5-flash' LOWER CASE VISIBLE LENGTH 20,
p_prompt TYPE string DEFAULT 'What is the capital of Italy?' LOWER CASE VISIBLE LENGTH 50.
SELECTION-SCREEN: SKIP 1,
BEGIN OF LINE,
PUSHBUTTON 68(10) button USER-COMMAND cli1,
END OF LINE.
SELECTION-SCREEN END OF BLOCK b1.
INITIALIZATION.
"Set text for the selection screen fields and button
%_p_model_%_app_%-text = 'Model'.
%_p_prompt_%_app_%-text = 'Prompt'.
button = 'Send'.
DATA(o_aai_conn) = NEW ycl_aai_conn( i_api = 'GOOGLE' ).
o_aai_conn->set_base_url( i_base_url = 'https://generativelanguage.googleapis.com' ).
o_aai_conn->set_api_key( i_api_key = 'REPLACE_THIS_TEXT_WITH_YOUR_GOOGLE_GEMINI_API_KEY' ).
o_aai_conn->yif_aai_conn~suppress_content_type( ).
DATA(o_aai_google) = NEW ycl_aai_google( i_model = 'gemini-2.5-flash'
i_o_connection = o_aai_conn ).
AT SELECTION-SCREEN.
o_aai_google->chat(
EXPORTING
i_message = p_prompt
IMPORTING
e_response = DATA(l_response)
).
cl_demo_output=>display_json( o_aai_google->get_conversation( ) ).Result:
The following screenshots show the output you can expect after running the example ABAP AI Chat report.
Now that you've run your first Google Gemini ABAP AI applications, consider exploring additional features.😊
- Prompt Templates: Learn how to define and use prompt templates for more dynamic and reusable prompts.
- LLM System Instructions: Pass system instructions to guide the behavior of the language model for specific tasks.
- Tool/Function Calling: Enable LLM applications to trigger ABAP logic using tools.
- Retrieval-Augmented Generation (RAG): Enhance your LLM applications by incorporating external knowledge sources and retrieval mechanisms.