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1 | | -author: Paul Kalhorn |
| 1 | +author: Paul Kalhorn |
2 | 2 | description: Compute Block that offers topic modeling algorithms |
3 | 3 | docker_image: ghcr.io/rwth-time/topic-modeling/topic-modeling |
4 | 4 | entrypoints: |
5 | 5 | lda_topic_modeling: |
6 | | - description: Sklearn LDA Topic Modeling |
| 6 | + description: Sklearn LDA Topic Modeling |
7 | 7 | envs: |
8 | 8 | LEARNING_METHOD: batch |
9 | 9 | MAX_ITER: 10 |
@@ -38,4 +38,38 @@ entrypoints: |
38 | 38 | top_terms_per_topic_PG_USER: null |
39 | 39 | description: A table that lists most likely terms for a topic |
40 | 40 | type: pg_table |
| 41 | + topic_explaination: |
| 42 | + description: <tbd> |
| 43 | + envs: |
| 44 | + MODEL_NAME: gpt-oss:120b |
| 45 | + OLLAMA_API_KEY: '' |
| 46 | + inputs: |
| 47 | + query_information: |
| 48 | + config: |
| 49 | + query_information_input_DB_TABLE: null |
| 50 | + query_information_input_PG_HOST: null |
| 51 | + query_information_input_PG_PASS: null |
| 52 | + query_information_input_PG_PORT: null |
| 53 | + query_information_input_PG_USER: null |
| 54 | + description: Information of the query used, must contain query, source, created_at |
| 55 | + type: pg_table |
| 56 | + topic_terms: |
| 57 | + config: |
| 58 | + topic_terms_input_DB_TABLE: null |
| 59 | + topic_terms_input_PG_HOST: null |
| 60 | + topic_terms_input_PG_PASS: null |
| 61 | + topic_terms_input_PG_PORT: null |
| 62 | + topic_terms_input_PG_USER: null |
| 63 | + description: A table that lists most likely terms for a topic |
| 64 | + type: pg_table |
| 65 | + outputs: |
| 66 | + explanations_output: |
| 67 | + config: |
| 68 | + explanations_output_DB_TABLE: null |
| 69 | + explanations_output_PG_HOST: null |
| 70 | + explanations_output_PG_PASS: null |
| 71 | + explanations_output_PG_PORT: null |
| 72 | + explanations_output_PG_USER: null |
| 73 | + description: Output of the generated explanations, contains topic_id and description |
| 74 | + type: pg_table |
41 | 75 | name: Topic-Modeling |
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