93 lines
2.9 KiB
YAML
Executable File
93 lines
2.9 KiB
YAML
Executable File
vectordb:
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- name: chroma_dragonkue2
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db_type: chroma
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client_type: persistent
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embedding_model: huggingface_drangonku-v2-ko
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collection_name: huggingface_drangonku-v2-ko
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path: ${PROJECT_DIR}/resources/chroma
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node_lines:
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- node_line_name: retrieve_node_line # Arbitrary node line name
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nodes:
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- node_type: retrieval
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strategy:
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metrics: [ retrieval_f1, retrieval_recall, retrieval_precision,
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retrieval_ndcg, retrieval_map, retrieval_mrr ]
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speed_threshold: 10
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top_k: 10
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modules:
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- module_type: bm25
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bm25_tokenizer: [ ko_kiwi, ko_okt ]
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- module_type: vectordb
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vectordb: chroma_dragonkue2 # chromadb
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- module_type: hybrid_cc
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normalize_method: [ mm, tmm, z, dbsf ]
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target_modules: ('bm25', 'vectordb')
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weight_range: (0.6, 0.4)
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test_weight_size: 101
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- node_type: passage_reranker # re-ranker
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strategy:
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metrics:
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- retrieval_recall
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- retrieval_precision
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- retrieval_map
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modules:
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- module_type: dragonkue2
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top_k: 5
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- node_line_name: post_retrieve_node_line # 생성노드
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nodes:
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- node_type: prompt_maker
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strategy:
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metrics:
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- metric_name: bleu
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- metric_name: meteor
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- metric_name: rouge
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- metric_name: sem_score
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embedding_model: huggingface_drangonku-v2-ko # raise ValueError("Only one embedding model is supported")
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lang: ko
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generator_modules:
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- module_type: llama_index_llm
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llm: ollama
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model: [ gemma3:12b, phi4, deepseek-r1:14b, aya-expanse:8b ]
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request_timeout: 3000.0
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modules:
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- module_type: fstring
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prompt:
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- |
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### Task:
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Respond to the user query using the provided context.
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### Guidelines:
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- If you don't know the answer, clearly state that.
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- If uncertain, ask the user for clarification.
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- Respond in the same language as the user's query.
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- If the context is unreadable or of poor quality, inform the user and provide the best possible answer.
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- If the answer isn't present in the context but you possess the knowledge, explain this to the user and provide the answer using your own understanding.
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- Do not use XML tags in your response.
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### Output:
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Provide a clear and direct response to the user's query.
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<context>
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{retrieved_contents}
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</context>
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<user_query>
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{query}
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</user_query>
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- node_type: generator # Gen-LLM
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strategy:
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metrics:
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- metric_name: bleu
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- metric_name: meteor
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- metric_name: rouge
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- metric_name: sem_score
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modules:
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- module_type: llama_index_llm
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llm: ollama
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model: gemma3:12b # phi4, deepseek-r1:14b, aya-expanse:8b
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temperature: 0.0
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request_timeout: 30000.0
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batch: 4
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