ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter3/memobase/config.py

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+"""
+Configuration for Memobase Agent with Kimi K3 Model
+"""
+
+import os
+from pathlib import Path
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+
+def _openrouter_model_id(model) -> str:
+    """Map a provider-native model name to an OpenRouter model id, used by the
+    universal OpenRouter fallback. An explicit OPENROUTER_MODEL env var wins."""
+    override = os.getenv("OPENROUTER_MODEL")
+    if override:
+        return override
+    m = (model or "").strip()
+    if not m:
+        return "openai/gpt-5.6-luna"
+    if "/" in m:
+        return m
+    ml = m.lower()
+    if ml.startswith(("gpt-", "o1", "o3", "o4", "chatgpt")):
+        return "openai/" + m
+    if ml.startswith("claude-"):
+        return "anthropic/claude-opus-4.8"
+    if ml.startswith("kimi"):
+        # kimi-k3 is not on OpenRouter; moonshotai/kimi-k2.6 is the closest hosted id.
+        return "moonshotai/kimi-k2.6"
+    return "openai/gpt-5.6-luna"
+
+
+# Chat model configuration (Kimi by default; DashScope/Bailian aliases supported)
+LLM_PROVIDER = os.getenv("LLM_PROVIDER", "kimi").lower()
+LLM_PROVIDER = {"qwen": "dashscope", "bailian": "dashscope"}.get(LLM_PROVIDER, LLM_PROVIDER)
+if LLM_PROVIDER == "dashscope":
+    KIMI_API_KEY = os.getenv("DASHSCOPE_API_KEY", "")
+    KIMI_BASE_URL = os.getenv(
+        "DASHSCOPE_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1"
+    )
+    KIMI_MODEL = os.getenv("MODEL_NAME", "qwen3.7-plus")
+else:
+    KIMI_API_KEY = os.getenv("KIMI_API_KEY", "") or os.getenv("MOONSHOT_API_KEY", "")
+    KIMI_BASE_URL = "https://api.moonshot.cn/v1"
+    KIMI_MODEL = os.getenv("MODEL_NAME", "kimi-k3")  # Kimi K3 model identifier
+
+# Universal OpenRouter fallback: primary key (KIMI/MOONSHOT) absent but
+# OPENROUTER_API_KEY present -> route the chat LLM through OpenRouter.
+if not KIMI_API_KEY and os.getenv("OPENROUTER_API_KEY"):
+    KIMI_API_KEY = os.getenv("OPENROUTER_API_KEY")
+    KIMI_BASE_URL = "https://openrouter.ai/api/v1"
+    KIMI_MODEL = _openrouter_model_id(KIMI_MODEL)
+
+# Model Parameters
+MODEL_TEMPERATURE = 0.7
+MODEL_MAX_TOKENS = 4096
+MODEL_TOP_P = 0.95
+
+# Context Window Configuration
+CONTEXT_WINDOW_SIZE = 128000  # Experiment context budget (K3 itself supports up to 1M tokens)
+MAX_MEMORY_ENTRIES = 100
+MEMORY_COMPRESSION_THRESHOLD = 50  # Compress when memory exceeds this
+
+# Memobase Configuration
+MEMOBASE_CONFIG = {
+    "memory_types": [
+        "episodic",      # Task-specific memories
+        "semantic",      # General knowledge
+        "procedural",    # Learned procedures and patterns
+        "working"        # Short-term working memory
+    ],
+    "retention_policy": "adaptive",  # adaptive, fixed, or decay
+    "compression_strategy": "hierarchical",  # hierarchical, summary, or selective
+    "storage_backend": "local",  # local, redis, or postgresql
+}
+
+# LOCOMO Benchmark Configuration
+LOCOMO_CONFIG = {
+    "benchmark_path": Path("benchmarks/locomo"),
+    "evaluation_metrics": [
+        "task_completion",
+        "reasoning_accuracy",
+        "memory_utilization",
+        "context_efficiency",
+        "adaptation_score"
+    ],
+    "task_categories": [
+        "multi_turn_reasoning",
+        "long_context_qa",
+        "task_planning",
+        "knowledge_integration",
+        "tool_usage"
+    ],
+    "max_turns": 20,
+    "timeout_seconds": 300
+}
+
+# Memory Database Configuration
+MEMORY_DB_PATH = Path("memory_store")
+MEMORY_DB_PATH.mkdir(exist_ok=True)
+
+# Logging Configuration
+LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO")
+LOG_FILE = Path("logs") / "memobase_agent.log"
+LOG_FORMAT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+
+# Agent Configuration
+AGENT_CONFIG = {
+    "name": "MemobaseAgent",
+    "version": "1.0.0",
+    "capabilities": [
+        "long_term_memory",
+        "context_compression",
+        "adaptive_learning",
+        "tool_calling",
+        "multi_turn_reasoning"
+    ],
+    "max_retries": 3,
+    "retry_delay": 1.0,
+}
+
+# Tool Configuration
+ENABLE_WEB_SEARCH = True
+ENABLE_CODE_EXECUTION = True
+ENABLE_FILE_OPERATIONS = True
+ENABLE_DATABASE_ACCESS = True
+
+# Performance Optimization
+BATCH_SIZE = 10
+CACHE_ENABLED = True
+CACHE_TTL = 3600  # 1 hour
+PARALLEL_PROCESSING = True
+MAX_WORKERS = 4
+
+# Experimental Features
+ENABLE_MEMORY_CONSOLIDATION = True  # Consolidate memories during idle time
+ENABLE_PREDICTIVE_CACHING = True    # Pre-fetch likely needed memories
+ENABLE_ADAPTIVE_COMPRESSION = True  # Adjust compression based on usage patterns