EvoGraph/config.example.py at main · AnnaSuSu/EvoGraph · GitHub

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"""
EvoGraph Configuration
"""

import os

# ==================== LLM Configuration ====================

LLM_PROVIDERS = {
    "openai": {
        "endpoint": "https://api.openai.com/v1/chat/completions",
        "api_key": os.getenv("OPENAI_API_KEY", "your-api-key-here"),
        "model": "gpt-4o-mini",
        "headers": {}
    },
}

LLM_CONFIG = {
    "active_provider": "openai",
    "temperature": 0,
    "max_retries": 3,
    "retry_base_sec": 2.0,
    "timeout": 600,
    "load_balance_ratio": 5,
}

# ==================== Neo4j Configuration ====================

CONV_DB_MAPPING = {
    "conv-26": {
        "uri": os.getenv("NEO4J_URI", "bolt://localhost:7687"),
        "user": os.getenv("NEO4J_USER", "neo4j"),
        "password": os.getenv("NEO4J_PASSWORD", "your-password"),
        "database": "neo4j"
    },
}

NEO4J_CONFIG = CONV_DB_MAPPING["conv-26"]


def get_neo4j_config(conv_id: str = None):
    """Get Neo4j config by conversation ID"""
    if conv_id and conv_id in CONV_DB_MAPPING:
        return CONV_DB_MAPPING[conv_id]
    return NEO4J_CONFIG

# ==================== Architecture Configuration ====================

# LPM (Long-term Personalized Memory) — entity index layer
LPM_CONFIG = {
    "max_entities_in_prompt": 50,
    "summary_update_interval": 10,
}

# MTM (Mid-term Memory) — evolution lines layer
MTM_CONFIG = {
    "max_line_nodes_in_prompt": 20,
    "heat_decay_factor": 0.95,
}

# STM (Short-term Memory) — current context
STM_CONFIG = {
    "history_window": 10,       # m=10 recent notes for extraction context
    "top_k": 15,                # top-k notes returned by retrieval
}

# ==================== Entity & Relation Types ====================

ENTITY_TYPES = {
    "Person": "People (names, roles)",
    "Business": "Businesses / ventures",
    "Location": "Places (cities, venues)",
    "Event": "Events (competitions, festivals)",
    "Activity": "Activities / hobbies",
    "Artifact": "Objects / creations",
}

RELATION_TYPES = {
    "OWNS": "owns / operates",
    "STARTED": "founded",
    "WORKS_AT": "works at",
    "LEFT": "left",
    "VISITED": "visited",
    "LIVES_IN": "lives in",
    "PARTICIPATED_IN": "participated in",
    "HOSTED": "hosted",
    "ENJOYS": "enjoys",
    "PRACTICES": "practices",
    "CREATED": "created",
    "HAS": "has",
    "READING": "is reading",
    "RELATED_TO": "related to",
}

CRUD_OPS = ["CREATE", "UPDATE", "DELETE", "NOOP"]

# ==================== Embedding Configuration ====================

EMBEDDING_CONFIG = {
    "model_path": "sentence-transformers/all-MiniLM-L6-v2",
    "similarity_threshold": 0.65,
    "use_embedding": True,
}

# ==================== System Configuration ====================

SYSTEM_CONFIG = {
    "debug": False,
    "max_hops": 2,
}

DATA_PATHS = {
    "benchmark_file": "data/locomo_benchmark.json",
}