m3taversal
7bfce6b706
Pulled from /opt/teleo-eval/telegram/ on VPS. Includes: - bot.py (92K), kb_retrieval.py, kb_tools.py (agentic retrieval) - retrieval.py (RRF merge, query decomposition, entity traversal) - response.py (system prompt builder, response parser) - agent_config.py, agent_runner.py (multi-agent template unit support) - approval_stages.py, approvals.py, digest.py (approval workflow) - eval_checks.py, eval.py (response quality checks) - output_gate.py, x_publisher.py, x_client.py, x_search.py (X pipeline) - market_data.py, worktree_lock.py (utilities) - rio.yaml, theseus.yaml (agent configs) These files were deployed to VPS but never committed to the repo. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
112 lines
3.4 KiB
Python
112 lines
3.4 KiB
Python
#!/usr/bin/env python3
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"""Market data API client for live token prices.
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Calls Ben's teleo-ai-api endpoint for ownership coin prices.
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Used by the Telegram bot to give Rio real-time market context.
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Epimetheus owns this module. Rhea: static API key pattern.
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"""
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import logging
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from pathlib import Path
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import aiohttp
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logger = logging.getLogger("market-data")
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API_URL = "https://teleo-ai-api-257133920458.us-east4.run.app/v0/chat/tool/market-data"
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API_KEY_FILE = "/opt/teleo-eval/secrets/market-data-key"
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# Cache: avoid hitting the API on every message
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_cache: dict[str, dict] = {} # token_name → {data, timestamp}
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CACHE_TTL = 300 # 5 minutes
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def _load_api_key() -> str | None:
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"""Load the market-data API key from secrets."""
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try:
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return Path(API_KEY_FILE).read_text().strip()
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except Exception:
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logger.warning("Market data API key not found at %s", API_KEY_FILE)
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return None
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async def get_token_price(token_name: str) -> dict | None:
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"""Fetch live market data for a token.
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Returns dict with price, market_cap, volume, etc. or None on failure.
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Caches results for CACHE_TTL seconds.
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"""
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import time
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token_upper = token_name.upper().strip("$")
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# Check cache
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cached = _cache.get(token_upper)
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if cached and time.time() - cached["timestamp"] < CACHE_TTL:
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return cached["data"]
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key = _load_api_key()
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if not key:
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return None
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try:
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async with aiohttp.ClientSession() as session:
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async with session.post(
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API_URL,
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headers={
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"X-Internal-Key": key,
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"Content-Type": "application/json",
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},
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json={"token": token_upper},
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timeout=aiohttp.ClientTimeout(total=10),
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) as resp:
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if resp.status >= 400:
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logger.warning("Market data API %s → %d", token_upper, resp.status)
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return None
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data = await resp.json()
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# Cache the result
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_cache[token_upper] = {
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"data": data,
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"timestamp": time.time(),
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}
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return data
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except Exception as e:
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logger.warning("Market data API error for %s: %s", token_upper, e)
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return None
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def format_price_context(data: dict, token_name: str) -> str:
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"""Format market data into a concise string for the LLM prompt."""
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if not data:
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return ""
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# API returns a "result" text field with pre-formatted data
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result_text = data.get("result", "")
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if result_text:
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return result_text
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# Fallback for structured JSON responses
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parts = [f"Live market data for {token_name}:"]
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price = data.get("price") or data.get("current_price")
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if price:
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parts.append(f"Price: ${price}")
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mcap = data.get("market_cap") or data.get("marketCap")
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if mcap:
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if isinstance(mcap, (int, float)) and mcap > 1_000_000:
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parts.append(f"Market cap: ${mcap/1_000_000:.1f}M")
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else:
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parts.append(f"Market cap: {mcap}")
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volume = data.get("volume") or data.get("volume_24h")
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if volume:
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parts.append(f"24h volume: ${volume}")
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change = data.get("price_change_24h") or data.get("change_24h")
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if change:
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parts.append(f"24h change: {change}")
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return " | ".join(parts) if len(parts) > 1 else ""
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