Architectures and Middleware @IAAS

Dataverse for all research projects related to software architecture or cloud computing of the Institute of Architecture of Application Systems (IAAS)

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2,281 to 2,290 of 2,331 Results

prompt_8_set_2.py Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing Python Source Code - 3.4 KB - MD5: ce5c68151f6ea332fe1a07f2cd1c42ce
prompt_generation.py Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing Python Source Code - 22.8 KB - MD5: 115fabeb0f2fe767cac106532de0fa52
prompt_template.txt Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing Plain Text - 1.7 KB - MD5: 6f715e5fe465b98fbde1c47eaf604017 Pseudo code for the prompt template.
pyproject.toml Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing Unknown - 674 B - MD5: 22fa20f5b009a77411d9638dfdbdc973 Project description and dependencies
README.md Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing Markdown Text - 1.0 KB - MD5: 9121406222628427c9ab3cd2af366119
rest.py Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing Python Source Code - 1.6 KB - MD5: e4b50a7409dd7b0c22d11b4c8489ad89
Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities Nov 27, 2023 Pesl, Robin D.; Stötzner, Miles; Georgievski, Ilche; Aiello, Marco, 2023, "Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities", https://doi.org/10.18419/DARUS-3767, DaRUS, V1, UNF:6:GV+GzTPs7xXW9ITeS6uC7Q== [fileUNF] Experimental results for the ICSOC 2023 AI-PA position paper "Uncovering LLMs for Service-Composition: Challenges and Opportunities." Exemplars: List of scenarios found in the Google Scholar literature search. Experiment 1 Service Discovery: Chat history for experiment 1 asking ChatGPT for existing real services. Experiment 2 Service Composition: C...
ChatGPT_1_21.png Nov 27, 2023 - Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities PNG Image - 6.5 MB - MD5: 8b133aab3938b353cdcf0f0f77d8f319
ChatGPT_1_25.png Nov 27, 2023 - Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities PNG Image - 5.9 MB - MD5: f0f01ecd67f160810c5a0cb60d0368e2
ChatGPT_1_32.png Nov 27, 2023 - Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities PNG Image - 3.4 MB - MD5: 09d212cfd434a4d4f09bae18057a7aec

prompt_8_set_2.py

Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing

Python Source Code - 3.4 KB -

prompt_generation.py

Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing

Python Source Code - 22.8 KB -

prompt_template.txt

Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing

Plain Text - 1.7 KB -

Pseudo code for the prompt template.

pyproject.toml

Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing

Unknown - 674 B -

Project description and dependencies

README.md

Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing

Markdown Text - 1.0 KB -

rest.py

Oct 7, 2024 - Replication Data for: Compositio Prompto: An Architecture to Employ Large Language Models in Automated Service Computing

Python Source Code - 1.6 KB -

Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities

Nov 27, 2023

Pesl, Robin D.; Stötzner, Miles; Georgievski, Ilche; Aiello, Marco, 2023, "Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities", https://doi.org/10.18419/DARUS-3767, DaRUS, V1, UNF:6:GV+GzTPs7xXW9ITeS6uC7Q== [fileUNF]

Experimental results for the ICSOC 2023 AI-PA position paper "Uncovering LLMs for Service-Composition: Challenges and Opportunities." Exemplars: List of scenarios found in the Google Scholar literature search. Experiment 1 Service Discovery: Chat history for experiment 1 asking ChatGPT for existing real services. Experiment 2 Service Composition: C...

ChatGPT_1_21.png

Nov 27, 2023 - Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities

PNG Image - 6.5 MB -

ChatGPT_1_25.png

Nov 27, 2023 - Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities

PNG Image - 5.9 MB -

ChatGPT_1_32.png

Nov 27, 2023 - Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities

PNG Image - 3.4 MB -

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