Minor fixes

agentstuff/sentiment_agent/config.py

@@ -0,0 +1,70 @@
+"""Configuration and safety limits for the sentiment agent.
+
+All guardrails are centralized here so they can be tuned from one place
+or overridden via CLI flags / env vars.
+"""
+
+from __future__ import annotations
+
+import os
+from dataclasses import dataclass, field
+
+
+@dataclass(frozen=True)
+class RateLimitConfig:
+    """Per-platform rate limiting."""
+
+    requests_per_minute: int = 10
+    burst_size: int = 3  # max concurrent requests
+    cooldown_after_429: float = 30.0  # seconds to wait after a 429
+
+
+@dataclass(frozen=True)
+class SafetyConfig:
+    """Top-level safety rails for the agent."""
+
+    # --- Agent-level limits ---
+    max_turns: int = 20
+    max_budget_usd: float = 0.50  # hard cap on Claude API spend per run
+    max_total_api_calls: int = 50  # across ALL platforms combined
+    max_results_per_call: int = 50  # cap the `limit` param sent to any API
+
+    # --- Per-platform rate limits ---
+    bluesky_rate: RateLimitConfig = field(default_factory=lambda: RateLimitConfig(
+        requests_per_minute=10, burst_size=2,
+    ))
+    reddit_rate: RateLimitConfig = field(default_factory=lambda: RateLimitConfig(
+        requests_per_minute=10, burst_size=2,
+    ))
+    hackernews_rate: RateLimitConfig = field(default_factory=lambda: RateLimitConfig(
+        requests_per_minute=15, burst_size=3,  # HN Algolia is more generous
+    ))
+
+    # --- Content size limits ---
+    max_post_text_chars: int = 2000  # truncate individual posts beyond this
+    max_total_content_bytes: int = 500_000  # ~500KB total data gathered before agent stops
+
+    # --- Timeout ---
+    api_timeout_seconds: float = 15.0
+
+    # --- Credibility thresholds ---
+    min_credibility_score: float = 0.3  # posts below this are flagged/excluded
+    flag_bot_threshold: float = 0.5  # posts between min and this are flagged but included
+
+    @classmethod
+    def from_env(cls) -> SafetyConfig:
+        """Build config with env var overrides.
+
+        Env vars: SENTIMENT_MAX_TURNS, SENTIMENT_MAX_BUDGET_USD,
+        SENTIMENT_MAX_API_CALLS, SENTIMENT_MIN_CREDIBILITY.
+        """
+        kwargs: dict = {}
+        if v := os.environ.get("SENTIMENT_MAX_TURNS"):
+            kwargs["max_turns"] = int(v)
+        if v := os.environ.get("SENTIMENT_MAX_BUDGET_USD"):
+            kwargs["max_budget_usd"] = float(v)
+        if v := os.environ.get("SENTIMENT_MAX_API_CALLS"):
+            kwargs["max_total_api_calls"] = int(v)
+        if v := os.environ.get("SENTIMENT_MIN_CREDIBILITY"):
+            kwargs["min_credibility_score"] = float(v)
+        return cls(**kwargs)