feat: allow agents to use advanced input and search for information
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feat: save user messages to improve agent responses refactor: pass database connection to knowledge store maintenance: bump version to 1.30.0
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@ -25,6 +25,14 @@
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## Version 1.29.0 - 2025-11-08
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Agents can now use more advanced input and automatically search for relevant information. User messages are saved and used to improve agent responses.
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**Changes:** 5 files, 58 lines
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**Languages:** Markdown (9 lines), Python (47 lines), TOML (2 lines)
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## Version 1.28.0 - 2025-11-08
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@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
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[project]
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name = "rp"
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version = "1.28.0"
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version = "1.29.0"
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description = "R python edition. The ultimate autonomous AI CLI."
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readme = "README.md"
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requires-python = ">=3.10"
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@ -109,7 +109,7 @@ class Assistant:
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self.last_result = None
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self.init_database()
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from rp.memory import KnowledgeStore, FactExtractor
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self.knowledge_store = KnowledgeStore(DB_PATH)
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self.knowledge_store = KnowledgeStore(DB_PATH, db_conn=self.db_conn)
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self.fact_extractor = FactExtractor()
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self.messages.append(init_system_message(args))
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try:
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@ -34,9 +34,9 @@ class KnowledgeEntry:
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class KnowledgeStore:
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def __init__(self, db_path: str):
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def __init__(self, db_path: str, db_conn: Optional[sqlite3.Connection] = None):
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self.db_path = db_path
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self.conn = sqlite3.connect(self.db_path, check_same_thread=False)
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self.conn = db_conn if db_conn else sqlite3.connect(self.db_path, check_same_thread=False)
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self.lock = threading.Lock()
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self.semantic_index = SemanticIndex()
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self._initialize_store()
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