File size: 3,179 Bytes
824c85b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | import pandas as pd
from datetime import datetime
import hashlib
import uuid
# Load core memory layers
memory_path = "SegmentMemory.csv"
conflict_path = "SegmentConflictMap.csv"
memory_df = pd.read_csv(memory_path)
conflict_df = pd.read_csv(conflict_path)
def generate_segment_id():
# Simulate infinite room logic by adding new numeric ID
existing_ids = memory_df['SegmentID'].astype(int)
return str(existing_ids.max() + 1 if not existing_ids.empty else 1).zfill(4)
def hash_segment(segment):
return hashlib.sha256(segment.encode()).hexdigest()[:12]
def insert_segment(raw_text, concepts, terms, structure, datapoints, comparisons, applications):
new_hash = hash_segment(raw_text)
# Check for duplicates by hash
if new_hash in memory_df['HashChecksum'].values:
print("Duplicate segment detected. Skipping insertion.")
return
# Basic simulated trust/conflict logic
trust_score = 0.75 if "error" not in raw_text.lower() else -0.4
relevance_score = 0.6
entropy = 0.5
# Check conflicts by comparing against concepts or raw text
conflicting_rows = memory_df[memory_df['RawText'].str.contains(raw_text.split(" ")[0], case=False, na=False)]
if not conflicting_rows.empty:
for _, row in conflicting_rows.iterrows():
conflict_entry = {
"SegmentA": row["SegmentID"],
"SegmentB": generate_segment_id(),
"ConflictType": "Concept Overlap",
"ConflictScore": 0.8,
"ResolutionStrategy": "Manual Review",
"WinningSegment": "",
"LastChecked": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
"ResolutionStatus": "Pending Review",
"AgentTrigger": "System",
"Notes": "Auto-detected via insertion engine"
}
conflict_df.loc[len(conflict_df)] = conflict_entry
conflict_df.to_csv(conflict_path, index=False)
print("Conflict detected. Segment routed to ConflictMap.")
return
# Accept segment
new_row = {
"SegmentID": generate_segment_id(),
"RawText": raw_text,
"Concepts": concepts,
"Terms": terms,
"Structure": structure,
"DataPoints": datapoints,
"Comparisons": comparisons,
"Applications": applications,
"Links": "",
"Entropy": entropy,
"TrustScore": trust_score,
"RelevanceScore": relevance_score,
"RecallCount": 0,
"LastUsed": "",
"ConflictsWith": "",
"Verified": trust_score > 0.5,
"HashChecksum": new_hash
}
memory_df.loc[len(memory_df)] = new_row
memory_df.to_csv(memory_path, index=False)
print(f"Segment added successfully with ID {new_row['SegmentID']}")
# Example Usage
if __name__ == "__main__":
insert_segment(
"Hydrogen is the lightest element in the periodic table.",
"lightest element, hydrogen",
"hydrogen, element, periodic",
"Chemistry > Elements",
"Atomic number: 1, Mass: 1.008",
"Compared to helium and lithium",
"Used in hydrogen fuel cells"
)
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