Update config import to use settings module
Replaced imports from config_manager with settings in chat_service.py and langflow_file_service.py to use get_openrag_config from config.settings. This change ensures consistency with the updated configuration structure.
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2 changed files with 4 additions and 4 deletions
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@ -66,7 +66,7 @@ class ChatService:
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extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
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extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
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# Pass the selected embedding model as a global variable
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# Pass the selected embedding model as a global variable
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from config.config_manager import get_openrag_config
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from config.settings import get_openrag_config
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config = get_openrag_config()
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config = get_openrag_config()
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embedding_model = config.knowledge.embedding_model
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embedding_model = config.knowledge.embedding_model
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extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
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extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
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@ -181,7 +181,7 @@ class ChatService:
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extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
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extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
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# Pass the selected embedding model as a global variable
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# Pass the selected embedding model as a global variable
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from config.config_manager import get_openrag_config
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from config.settings import get_openrag_config
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config = get_openrag_config()
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config = get_openrag_config()
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embedding_model = config.knowledge.embedding_model
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embedding_model = config.knowledge.embedding_model
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extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
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extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
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@ -305,7 +305,7 @@ class ChatService:
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extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
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extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
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# Pass the selected embedding model as a global variable
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# Pass the selected embedding model as a global variable
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from config.config_manager import get_openrag_config
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from config.settings import get_openrag_config
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config = get_openrag_config()
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config = get_openrag_config()
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embedding_model = config.knowledge.embedding_model
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embedding_model = config.knowledge.embedding_model
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extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
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extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
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@ -141,7 +141,7 @@ class LangflowFileService:
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mimetype = str(file_tuples[0][2]) if file_tuples and len(file_tuples) > 0 and len(file_tuples[0]) > 2 else ""
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mimetype = str(file_tuples[0][2]) if file_tuples and len(file_tuples) > 0 and len(file_tuples[0]) > 2 else ""
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# Get the current embedding model from config
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# Get the current embedding model from config
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from config.config_manager import get_openrag_config
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from config.settings import get_openrag_config
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config = get_openrag_config()
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config = get_openrag_config()
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embedding_model = config.knowledge.embedding_model
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embedding_model = config.knowledge.embedding_model
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