fix wechat
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@@ -192,7 +192,7 @@ All RAG examples share these common parameters. **Interactive mode** is availabl
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# Search Parameters
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--top-k N # Number of results to retrieve (default: 20)
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--search-complexity N # Search complexity for graph traversal (default: 64)
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--search-complexity N # Search complexity for graph traversal (default: 32)
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# Chunking Parameters
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--chunk-size N # Size of text chunks (default varies by source: 256 for most, 192 for WeChat)
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@@ -18,6 +18,7 @@ class EmailRAG(BaseRAGExample):
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def __init__(self):
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# Set default values BEFORE calling super().__init__
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self.max_items_default = -1 # Process all emails by default
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self.embedding_model_default = (
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"sentence-transformers/all-MiniLM-L6-v2" # Fast 384-dim model
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)
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@@ -19,7 +19,7 @@ class WeChatRAG(BaseRAGExample):
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def __init__(self):
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# Set default values BEFORE calling super().__init__
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self.max_items_default = 50 # Match original default
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self.max_items_default = -1 # Match original default
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self.embedding_model_default = (
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"sentence-transformers/all-MiniLM-L6-v2" # Fast 384-dim model
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)
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@@ -143,6 +143,7 @@ class WeChatRAG(BaseRAGExample):
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return []
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print(f"\nTotal loaded {len(all_documents)} chat documents from {len(export_dirs)} exports")
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print("now starting to split into text chunks ... take some time")
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# Convert to text chunks with contact information
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all_texts = []
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@@ -463,8 +463,9 @@ class LeannSearcher:
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print(
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f"Leann metadata file not found at {self.meta_path_str}, and you may need to rm -rf {parent_dir}"
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)
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# highlight in red the filenotfound error
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raise FileNotFoundError(
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f"Leann metadata file not found at {self.meta_path_str}, you may need to rm -rf {parent_dir}"
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f"Leann metadata file not found at {self.meta_path_str}, \033[91m you may need to rm -rf {parent_dir}\033[0m"
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)
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with open(self.meta_path_str, encoding="utf-8") as f:
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self.meta_data = json.load(f)
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