Refactor EnhancedContextPlugin to store datetime in SQLite format, handle datetime strings properly, and extract/store entities for context

This commit is contained in:
2024-11-06 09:03:38 -05:00
parent 4c1d1fa873
commit 4b87a8b91c
+199 -40
View File
@@ -24,12 +24,16 @@ DB_PATH = "enhanced_context.db"
class EnhancedContextPlugin(sm.BasePlugin):
model_config = {"extra": "allow"}
def __init__(self):
def __init__(self, verbose: bool = False):
super().__init__()
# Set up logging
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
)
self.verbose = verbose
if verbose:
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
)
else:
logging.basicConfig(level=logging.WARNING)
self.logger = logging.getLogger(__name__)
# Initialize NLP model
@@ -91,6 +95,18 @@ class EnhancedContextPlugin(sm.BasePlugin):
"""
)
# Create essence markers table
conn.execute(
"""
CREATE TABLE IF NOT EXISTS essence_markers (
marker_type TEXT,
marker_text TEXT,
timestamp TIMESTAMP,
PRIMARY KEY (marker_type, marker_text)
)
"""
)
def store_entity(self, entity: str) -> None:
"""Store or update entity mention with error handling"""
try:
@@ -170,18 +186,20 @@ class EnhancedContextPlugin(sm.BasePlugin):
# Add identity context if available and requested
if include_identity and self.personal_identity:
context_parts.append(f"You are speaking with {self.personal_identity}")
context_parts.append(
f"The user's name is {self.personal_identity}. Remember to use their name naturally in conversation when appropriate."
)
# Add entity context if available
if entities:
# Format entities with their mention counts
entity_strings = [
f"{entity} ({'mentioned multiple times' if count > 1 else 'mentioned recently'})"
f"{entity} (mentioned {count} {'times' if count > 1 else 'time'})"
for entity, count in entities
]
context_parts.append(
f"Previously discussed topic{'s' if len(entity_strings) > 1 else ''}: "
"Recent conversation history includes: "
+ (
", ".join(entity_strings[:-1]) + f" and {entity_strings[-1]}"
if len(entity_strings) > 1
@@ -189,7 +207,13 @@ class EnhancedContextPlugin(sm.BasePlugin):
)
)
return ". ".join(context_parts) + ("." if context_parts else "")
# Add instructions for memory queries
context_parts.append(
"If the user asks about memories or what has been discussed, "
"naturally incorporate the above context into your response."
)
return " ".join(context_parts)
def extract_identity(self, text: str) -> str | None:
"""Extract identity statements like 'I am X'"""
@@ -280,6 +304,159 @@ class EnhancedContextPlugin(sm.BasePlugin):
self.logger.error(f"Database error while loading identity: {e}")
return None
def is_memory_question(self, text: str) -> bool:
"""Detect questions about memory and recall"""
text = text.lower().strip()
# Keywords related to memory and recall
memory_words = {
"remember",
"recall",
"memory",
"memories",
"mentioned",
"talked about",
"discussed",
"tell me about",
"what do you know",
}
return any(word in text for word in memory_words)
def extract_essence_markers(self, text: str) -> List[tuple[str, str]]:
"""Extract essence markers from text.
Returns list of tuples (marker_type, marker_text)"""
# Common patterns for essence markers
patterns = {
"value": [
r"I (?:really )?(?:believe|think) (?:that )?(.+)",
r"(?:It's|Its) important (?:to me )?that (.+)",
r"I value (.+)",
r"(?:The )?most important (?:thing|aspect) (?:to me )?is (.+)",
],
"identity": [
r"I am(?: a| an)? (.+)",
r"I consider myself(?: a| an)? (.+)",
r"I identify as(?: a| an)? (.+)",
],
"preference": [
r"I (?:really )?(?:like|love|enjoy|prefer) (.+)",
r"I can't stand (.+)",
r"I hate (.+)",
r"I always (.+)",
r"I never (.+)",
],
"emotion": [
r"I feel (.+)",
r"I'm feeling (.+)",
r"(?:It|That) makes me feel (.+)",
],
}
markers = []
# Process with spaCy for better sentence splitting
doc = self.nlp(text)
for sent in doc.sents:
sent_text = sent.text.strip().lower()
# Check each pattern type
for marker_type, pattern_list in patterns.items():
for pattern in pattern_list:
matches = re.finditer(pattern, sent_text, re.IGNORECASE)
for match in matches:
marker_text = match.group(1).strip()
# Filter out very short or common phrases
if len(marker_text) > 3 and not any(
w in marker_text for w in ["um", "uh", "like"]
):
markers.append((marker_type, marker_text))
return markers
def store_essence_marker(self, marker_type: str, marker_text: str) -> None:
"""Store essence marker in database"""
try:
with self.get_connection() as conn:
now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
conn.execute(
"""
INSERT OR REPLACE INTO essence_markers (marker_type, marker_text, timestamp)
VALUES (?, ?, ?)
""",
(marker_type, marker_text, now),
)
conn.commit()
self.logger.info(
f"Stored essence marker: {marker_type} - {marker_text}"
)
except sqlite3.Error as e:
self.logger.error(f"Database error storing essence marker: {e}")
def retrieve_essence_markers(self, days: int = 30) -> List[tuple[str, str]]:
"""Retrieve recent essence markers"""
try:
with self.get_connection() as conn:
cur = conn.cursor()
cur.execute(
"""
SELECT DISTINCT marker_type, marker_text
FROM essence_markers
WHERE timestamp >= datetime('now', ?, 'localtime')
ORDER BY timestamp DESC
""",
(f"-{days} days",),
)
markers = cur.fetchall()
self.logger.info(f"Retrieved essence markers: {markers}")
return markers
except sqlite3.Error as e:
self.logger.error(f"Database error retrieving essence markers: {e}")
return []
def format_context_message(
self, entities: List[tuple], include_identity: bool = True
) -> str:
"""Format context message with essence markers"""
context_parts = []
# Add identity context
if include_identity and self.personal_identity:
context_parts.append(f"The user's name is {self.personal_identity}.")
# Add essence markers
essence_markers = self.retrieve_essence_markers()
if essence_markers:
markers_by_type = {}
for marker_type, marker_text in essence_markers:
if marker_type not in markers_by_type:
markers_by_type[marker_type] = []
markers_by_type[marker_type].append(marker_text)
context_parts.append("User characteristics:")
for marker_type, markers in markers_by_type.items():
context_parts.append(f"- {marker_type.title()}: {', '.join(markers)}")
# Add entity context
if entities:
entity_strings = [
f"{entity} (mentioned {count} {'times' if count > 1 else 'time'})"
for entity, count in entities
]
context_parts.append(
"Recent conversation topics: "
+ (
", ".join(entity_strings[:-1]) + f" and {entity_strings[-1]}"
if len(entity_strings) > 1
else entity_strings[0]
)
)
return "\n".join(context_parts)
def pre_send_hook(self, conversation: sm.Conversation):
last_message = conversation.get_last_message(role="user")
if not last_message:
@@ -287,52 +464,34 @@ class EnhancedContextPlugin(sm.BasePlugin):
self.logger.info(f"Processing message: {last_message.text}")
# Check for identity statements FIRST
identity = self.extract_identity(last_message.text)
if identity:
self.logger.info(f"Extracted identity: {identity}")
self.personal_identity = identity
self.store_identity(identity)
conversation.add_message(
role="assistant", text=f"I'll remember that your name is {identity}."
)
return False
# Handle identity questions
if self.is_identity_question(last_message.text):
self.load_identity() # Reload identity from database
conversation.add_message(
role="assistant",
text=(
f"You are {self.personal_identity}."
if self.personal_identity
else "I don't know your name yet. You can tell me by saying 'I am [your name]' or 'My name is [your name]'."
),
)
return False
# Extract and store entities
entities = self.extract_entities(last_message.text)
for entity in entities:
self.store_entity(entity)
self.logger.info(f"Stored entity: {entity}")
if not entities:
self.logger.info("No entities found in message")
# Extract and store essence markers
essence_markers = self.extract_essence_markers(last_message.text)
for marker_type, marker_text in essence_markers:
self.store_essence_marker(marker_type, marker_text)
self.logger.info(f"Found essence marker: {marker_type} - {marker_text}")
# Add context message
recent_entities = self.retrieve_recent_entities()
recent_entities = self.retrieve_recent_entities(days=30)
context_message = self.format_context_message(recent_entities)
if context_message: # Only add if there's actual context to share
conversation.add_message(role="user", text=context_message)
if context_message:
conversation.add_message(role="system", text=context_message)
self.logger.info(f"Added context message: {context_message}")
return True
# Replace the example usage code at the bottom with this chat interface:
def main():
# Create a conversation and add the plugin
conversation = sm.create_conversation(llm_model="gpt-4", llm_provider="openai")
plugin = EnhancedContextPlugin()
conversation = sm.create_conversation(
llm_model="gpt-4o-mini", llm_provider="openai"
)
plugin = EnhancedContextPlugin(verbose=False) # Set verbose here
conversation.add_plugin(plugin)
# Add initial context if available