feat: v3.0.0 - intelligent search, GitHub person/project mode, ELI5, 13+ sources
v3 rewrites the search engine from the ground up: - Intelligent pre-research: resolves X handles, GitHub repos, subreddits, TikTok hashtags, and YouTube channels before searching - GitHub person-mode: PR velocity, top repos by stars, release notes - GitHub project-mode: live star counts, README, releases, top issues - ELI5 mode: plain language synthesis, no jargon - 13+ sources: Reddit, X, YouTube, TikTok, Instagram, HN, Polymarket, GitHub, Threads, Pinterest, Perplexity, Bluesky, Web - Free Reddit comments via public JSON (no API key needed) - Fun judge v2: humor scoring baked into narrative - Cookie consent before browser scanning - 10,000 free ScrapeCreators calls - 1,012 tests Thank you to the community contributors whose issues and PRs shaped v3: @uppinote20 (#143), @zerone0x (#134, #136), @thinkun (#116), @thomasmktong (#124), @fanispoulinakisai-boop (#100), @pejmanjohn (#78), @zl190 (#115), @hnshah (#84, #85, #86) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@@ -5,13 +5,24 @@ import re
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import sys
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from typing import Any, Dict, List, Optional
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from . import http
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from . import http, log
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def _safe_text(val) -> str:
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"""Extract text from string or localized object."""
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if isinstance(val, str):
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return val
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if isinstance(val, dict):
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return str(val.get("text", val.get("en", "")))
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return str(val) if val is not None else ""
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def _log(msg: str):
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log.source_log("xAI", msg, tty_only=False)
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def _log_error(msg: str):
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"""Log error to stderr."""
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sys.stderr.write(f"[X ERROR] {msg}\n")
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sys.stderr.flush()
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log.source_log("xAI ERROR", msg, tty_only=False)
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# xAI uses responses endpoint with Agent Tools API
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XAI_RESPONSES_URL = "https://api.x.ai/v1/responses"
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@@ -173,7 +184,7 @@ def parse_x_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
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data = json.loads(json_match.group())
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items = data.get("items", [])
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except json.JSONDecodeError:
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pass
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_log(f"Failed to parse xAI response JSON: {output_text[:200]}")
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# Validate and clean items
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clean_items = []
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@@ -190,20 +201,20 @@ def parse_x_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
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eng_raw = item.get("engagement")
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if isinstance(eng_raw, dict):
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engagement = {
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"likes": int(eng_raw.get("likes", 0)) if eng_raw.get("likes") else None,
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"reposts": int(eng_raw.get("reposts", 0)) if eng_raw.get("reposts") else None,
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"replies": int(eng_raw.get("replies", 0)) if eng_raw.get("replies") else None,
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"quotes": int(eng_raw.get("quotes", 0)) if eng_raw.get("quotes") else None,
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"likes": int(eng_raw["likes"]) if eng_raw.get("likes") is not None else None,
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"reposts": int(eng_raw["reposts"]) if eng_raw.get("reposts") is not None else None,
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"replies": int(eng_raw["replies"]) if eng_raw.get("replies") is not None else None,
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"quotes": int(eng_raw["quotes"]) if eng_raw.get("quotes") is not None else None,
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}
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clean_item = {
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"id": f"X{i+1}",
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"text": str(item.get("text", "")).strip()[:500], # Truncate long text
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"text": _safe_text(item.get("text", "")).strip()[:500], # Truncate long text
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"url": url,
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"author_handle": str(item.get("author_handle", "")).strip().lstrip("@"),
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"author_handle": _safe_text(item.get("author_handle", "")).strip().lstrip("@"),
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"date": item.get("date"),
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"engagement": engagement,
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"why_relevant": str(item.get("why_relevant", "")).strip(),
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"why_relevant": _safe_text(item.get("why_relevant", "")).strip(),
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"relevance": min(1.0, max(0.0, float(item.get("relevance", 0.5)))),
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}
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