Ilia Alshanetsky
d7bff81757
* chore: fix YAML error in argument-hint * add codex auth support to responses API * Use gpt-5.1-codex-mini as default model for Codex auth Add CODEX_FALLBACK_MODELS chain (gpt-5.1-codex-mini → gpt-5.2) for Codex endpoint which doesn't support standard OpenAI models like gpt-4o-mini. Adds model fallback retry on 400 errors in the Codex search path. Also adds test_codex_auth.py with 22 unit tests covering JWT decoding, auth resolution, SSE parsing, and payload building. * Pass .env credentials to Bird Node subprocesses for X auth On platforms without browser cookie access (e.g. WSL2), Bird's vendored Node.js module cannot read AUTH_TOKEN/CT0 from Firefox or Chrome cookie stores. The .env config file already supports these values, but they were only loaded into the Python config dict — never exported to the environment of Node subprocesses. - Add AUTH_TOKEN/CT0 to env.py config key loading - Add set_credentials()/\_subprocess_env() to bird_x.py to inject credentials into the env dict passed to subprocess.run/Popen - Call set_credentials() in main() before Bird auth detection --------- Co-authored-by: Justin Williams <jblwilliams@gmail.com>
459 lines
15 KiB
Python
459 lines
15 KiB
Python
"""Bird X search client - vendored Twitter GraphQL search for /last30days v2.1.
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Uses a vendored subset of @steipete/bird v0.8.0 (MIT License) to search X
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via Twitter's GraphQL API. No external `bird` CLI binary needed - just Node.js 22+.
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"""
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import json
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import os
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import signal
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import shutil
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import subprocess
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import sys
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from pathlib import Path
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from datetime import datetime
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from typing import Any, Dict, List, Optional, Tuple
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# Path to the vendored bird-search wrapper
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_BIRD_SEARCH_MJS = Path(__file__).parent / "vendor" / "bird-search" / "bird-search.mjs"
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# Depth configurations: number of results to request
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DEPTH_CONFIG = {
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"quick": 12,
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"default": 30,
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"deep": 60,
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}
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# Module-level credentials injected from .env config
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_credentials: Dict[str, str] = {}
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def set_credentials(auth_token: Optional[str], ct0: Optional[str]):
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"""Inject AUTH_TOKEN/CT0 from .env config so Node subprocesses can use them."""
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if auth_token:
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_credentials['AUTH_TOKEN'] = auth_token
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if ct0:
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_credentials['CT0'] = ct0
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def _subprocess_env() -> Dict[str, str]:
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"""Build env dict for Node subprocesses, merging injected credentials."""
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env = os.environ.copy()
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env.update(_credentials)
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return env
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def _log(msg: str):
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"""Log to stderr."""
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sys.stderr.write(f"[Bird] {msg}\n")
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sys.stderr.flush()
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def _extract_core_subject(topic: str) -> str:
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"""Extract core subject from verbose query for X search.
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X search is literal keyword AND matching — all words must appear.
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Aggressively strip question/meta/research words to keep only the
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core product/concept name (2-3 words max).
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"""
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text = topic.lower().strip()
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# Phase 1: Strip multi-word prefixes (longest first)
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prefixes = [
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'what are the best', 'what is the best', 'what are the latest',
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'what are people saying about', 'what do people think about',
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'how do i use', 'how to use', 'how to',
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'what are', 'what is', 'tips for', 'best practices for',
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]
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for p in prefixes:
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if text.startswith(p + ' '):
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text = text[len(p):].strip()
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break
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# Phase 2: Strip multi-word suffixes
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suffixes = [
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'best practices', 'use cases', 'prompt techniques',
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'prompting techniques', 'prompting tips',
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]
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for s in suffixes:
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if text.endswith(' ' + s):
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text = text[:-len(s)].strip()
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break
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# Phase 3: Filter individual noise words
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_noise = {
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# Question/filler words
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'a', 'an', 'the', 'is', 'are', 'was', 'were', 'and', 'or',
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'of', 'in', 'on', 'for', 'with', 'about', 'to',
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'people', 'saying', 'think', 'said', 'lately',
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# Research/meta descriptors
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'best', 'top', 'good', 'great', 'awesome', 'killer',
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'latest', 'new', 'news', 'update', 'updates',
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'practices', 'features', 'guide', 'tutorial',
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'recommendations', 'advice', 'review', 'reviews',
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'usecases', 'examples', 'comparison', 'versus', 'vs',
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# Prompting meta words
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'prompt', 'prompts', 'prompting', 'techniques', 'tips',
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'tricks', 'methods', 'strategies', 'approaches',
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# Action words
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'using', 'uses', 'use',
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}
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words = text.split()
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result = [w for w in words if w not in _noise]
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return ' '.join(result[:3]) or topic.lower().strip() # Max 3 words
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def is_bird_installed() -> bool:
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"""Check if vendored Bird search module is available.
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Returns:
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True if bird-search.mjs exists and Node.js 22+ is in PATH.
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"""
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if not _BIRD_SEARCH_MJS.exists():
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return False
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return shutil.which("node") is not None
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def is_bird_authenticated() -> Optional[str]:
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"""Check if X credentials are available (env vars or browser cookies).
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Returns:
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Auth source string if authenticated, None otherwise.
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"""
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if not is_bird_installed():
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return None
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try:
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result = subprocess.run(
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["node", str(_BIRD_SEARCH_MJS), "--whoami"],
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capture_output=True,
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text=True,
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timeout=15,
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env=_subprocess_env(),
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)
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if result.returncode == 0 and result.stdout.strip():
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return result.stdout.strip().split('\n')[0]
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return None
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except (subprocess.TimeoutExpired, FileNotFoundError, subprocess.SubprocessError):
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return None
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def check_npm_available() -> bool:
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"""Check if npm is available (kept for API compatibility).
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Returns:
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True if 'npm' command is available in PATH, False otherwise.
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"""
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return shutil.which("npm") is not None
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def install_bird() -> Tuple[bool, str]:
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"""No-op - Bird search is vendored in v2.1, no installation needed.
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Returns:
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Tuple of (success, message).
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"""
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if is_bird_installed():
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return True, "Bird search is bundled with /last30days v2.1 - no installation needed."
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if not shutil.which("node"):
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return False, "Node.js 22+ is required for X search. Install Node.js first."
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return False, f"Vendored bird-search.mjs not found at {_BIRD_SEARCH_MJS}"
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def get_bird_status() -> Dict[str, Any]:
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"""Get comprehensive Bird search status.
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Returns:
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Dict with keys: installed, authenticated, username, can_install
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"""
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installed = is_bird_installed()
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auth_source = is_bird_authenticated() if installed else None
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return {
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"installed": installed,
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"authenticated": auth_source is not None,
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"username": auth_source, # Now returns auth source (e.g., "Safari", "env AUTH_TOKEN")
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"can_install": True, # Always vendored in v2.1
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}
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def _run_bird_search(query: str, count: int, timeout: int) -> Dict[str, Any]:
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"""Run a search using the vendored bird-search.mjs module.
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Args:
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query: Full search query string (including since: filter)
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count: Number of results to request
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timeout: Timeout in seconds
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Returns:
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Raw Bird JSON response or error dict.
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"""
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cmd = [
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"node", str(_BIRD_SEARCH_MJS),
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query,
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"--count", str(count),
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"--json",
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]
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# Use process groups for clean cleanup on timeout/kill
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preexec = os.setsid if hasattr(os, 'setsid') else None
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try:
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proc = subprocess.Popen(
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cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True,
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preexec_fn=preexec,
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env=_subprocess_env(),
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)
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# Register for cleanup tracking (if available)
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try:
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from last30days import register_child_pid, unregister_child_pid
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register_child_pid(proc.pid)
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except ImportError:
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pass
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try:
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stdout, stderr = proc.communicate(timeout=timeout)
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except subprocess.TimeoutExpired:
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# Kill the entire process group
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try:
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os.killpg(os.getpgid(proc.pid), signal.SIGTERM)
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except (ProcessLookupError, PermissionError, OSError):
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proc.kill()
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proc.wait(timeout=5)
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return {"error": f"Search timed out after {timeout}s", "items": []}
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finally:
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try:
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from last30days import unregister_child_pid
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unregister_child_pid(proc.pid)
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except (ImportError, Exception):
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pass
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if proc.returncode != 0:
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error = stderr.strip() if stderr else "Bird search failed"
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return {"error": error, "items": []}
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output = stdout.strip() if stdout else ""
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if not output:
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return {"items": []}
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return json.loads(output)
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except json.JSONDecodeError as e:
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return {"error": f"Invalid JSON response: {e}", "items": []}
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except Exception as e:
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return {"error": str(e), "items": []}
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def search_x(
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topic: str,
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from_date: str,
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to_date: str,
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depth: str = "default",
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) -> Dict[str, Any]:
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"""Search X using Bird CLI with automatic retry on 0 results.
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Args:
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topic: Search topic
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from_date: Start date (YYYY-MM-DD)
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to_date: End date (YYYY-MM-DD) - unused but kept for API compatibility
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depth: Research depth - "quick", "default", or "deep"
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Returns:
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Raw Bird JSON response or error dict.
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"""
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count = DEPTH_CONFIG.get(depth, DEPTH_CONFIG["default"])
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timeout = 30 if depth == "quick" else 45 if depth == "default" else 60
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# Extract core subject - X search is literal, not semantic
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core_topic = _extract_core_subject(topic)
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query = f"{core_topic} since:{from_date}"
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_log(f"Searching: {query}")
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response = _run_bird_search(query, count, timeout)
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# Check if we got results
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items = parse_bird_response(response)
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# Retry with fewer keywords if 0 results and query has 3+ words
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core_words = core_topic.split()
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if not items and len(core_words) > 2:
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shorter = ' '.join(core_words[:2])
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_log(f"0 results for '{core_topic}', retrying with '{shorter}'")
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query = f"{shorter} since:{from_date}"
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response = _run_bird_search(query, count, timeout)
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return response
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def search_handles(
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handles: List[str],
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topic: Optional[str],
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from_date: str,
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count_per: int = 5,
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) -> List[Dict[str, Any]]:
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"""Search specific X handles for topic-related content.
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Runs targeted Bird searches using `from:handle topic` syntax.
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Used in Phase 2 supplemental search after entity extraction.
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Args:
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handles: List of X handles to search (without @)
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topic: Search topic (core subject), or None for unfiltered search
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from_date: Start date (YYYY-MM-DD)
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count_per: Results to request per handle
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Returns:
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List of raw item dicts (same format as parse_bird_response output).
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"""
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all_items = []
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core_topic = _extract_core_subject(topic) if topic else None
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for handle in handles:
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handle = handle.lstrip("@")
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if core_topic:
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query = f"from:{handle} {core_topic} since:{from_date}"
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else:
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query = f"from:{handle} since:{from_date}"
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cmd = [
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"node", str(_BIRD_SEARCH_MJS),
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query,
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"--count", str(count_per),
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"--json",
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]
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preexec = os.setsid if hasattr(os, 'setsid') else None
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try:
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proc = subprocess.Popen(
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cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True,
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preexec_fn=preexec,
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)
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try:
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stdout, stderr = proc.communicate(timeout=15)
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except subprocess.TimeoutExpired:
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try:
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os.killpg(os.getpgid(proc.pid), signal.SIGTERM)
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except (ProcessLookupError, PermissionError, OSError):
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proc.kill()
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proc.wait(timeout=5)
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_log(f"Handle search timed out for @{handle}")
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continue
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if proc.returncode != 0:
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_log(f"Handle search failed for @{handle}: {(stderr or '').strip()}")
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continue
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output = (stdout or "").strip()
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if not output:
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continue
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response = json.loads(output)
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items = parse_bird_response(response)
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all_items.extend(items)
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except json.JSONDecodeError:
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_log(f"Invalid JSON from handle search for @{handle}")
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except Exception as e:
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_log(f"Handle search error for @{handle}: {e}")
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return all_items
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def parse_bird_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""Parse Bird response to match xai_x output format.
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Args:
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response: Raw Bird JSON response
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Returns:
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List of normalized item dicts matching xai_x.parse_x_response() format.
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"""
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items = []
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# Check for errors
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if "error" in response and response["error"]:
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_log(f"Bird error: {response['error']}")
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return items
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# Bird returns a list of tweets directly or under a key
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raw_items = response if isinstance(response, list) else response.get("items", response.get("tweets", []))
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if not isinstance(raw_items, list):
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return items
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for i, tweet in enumerate(raw_items):
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if not isinstance(tweet, dict):
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continue
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# Extract URL - Bird uses permanent_url or we construct from id
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url = tweet.get("permanent_url") or tweet.get("url", "")
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if not url and tweet.get("id"):
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# Try different field structures Bird might use
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author = tweet.get("author", {}) or tweet.get("user", {})
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screen_name = author.get("username") or author.get("screen_name", "")
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if screen_name:
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url = f"https://x.com/{screen_name}/status/{tweet['id']}"
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if not url:
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continue
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# Parse date from created_at/createdAt (e.g., "Wed Jan 15 14:30:00 +0000 2026")
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date = None
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created_at = tweet.get("createdAt") or tweet.get("created_at", "")
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if created_at:
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try:
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# Try ISO format first (e.g., "2026-02-03T22:33:32Z")
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# Check for ISO date separator, not just "T" (which appears in "Tue")
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if len(created_at) > 10 and created_at[10] == "T":
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dt = datetime.fromisoformat(created_at.replace("Z", "+00:00"))
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else:
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# Twitter format: "Wed Jan 15 14:30:00 +0000 2026"
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dt = datetime.strptime(created_at, "%a %b %d %H:%M:%S %z %Y")
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date = dt.strftime("%Y-%m-%d")
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except (ValueError, TypeError):
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pass
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# Extract user info (Bird uses author.username, older format uses user.screen_name)
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author = tweet.get("author", {}) or tweet.get("user", {})
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author_handle = author.get("username") or author.get("screen_name", "") or tweet.get("author_handle", "")
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# Build engagement dict (Bird uses camelCase: likeCount, retweetCount, etc.)
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engagement = {
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"likes": tweet.get("likeCount") or tweet.get("like_count") or tweet.get("favorite_count"),
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"reposts": tweet.get("retweetCount") or tweet.get("retweet_count"),
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"replies": tweet.get("replyCount") or tweet.get("reply_count"),
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"quotes": tweet.get("quoteCount") or tweet.get("quote_count"),
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}
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# Convert to int where possible
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for key in engagement:
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if engagement[key] is not None:
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try:
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engagement[key] = int(engagement[key])
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except (ValueError, TypeError):
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engagement[key] = None
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# Build normalized item
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item = {
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"id": f"X{i+1}",
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"text": str(tweet.get("text", tweet.get("full_text", ""))).strip()[:500],
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"url": url,
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"author_handle": author_handle.lstrip("@"),
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"date": date,
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"engagement": engagement if any(v is not None for v in engagement.values()) else None,
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"why_relevant": "", # Bird doesn't provide relevance explanations
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"relevance": 0.7, # Default relevance, let score.py re-rank
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}
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items.append(item)
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return items |