f87d9f80e9
These modules are now proprietary and live in the Nextra SaaS product. xml-pipeline remains the OSS core with: - Message pump and pipeline steps - Handler contract and responses - LLM router abstraction - Native tools - Config loading - Memory/context buffer Removed: - xml_pipeline/console/ → nextra/console/ - xml_pipeline/auth/ → nextra/auth/ - xml_pipeline/server/ → nextra/server/ - Legacy files: agentserver.py, main.py, xml_listener.py The simple console example remains in examples/console/. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
106 lines
3.4 KiB
Python
106 lines
3.4 KiB
Python
"""
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Optional feature detection for xml-pipeline.
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This module checks which optional dependencies are installed and provides
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graceful degradation when features are unavailable.
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"""
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from dataclasses import dataclass, field
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from importlib.util import find_spec
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from typing import Callable
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def _check_import(module: str) -> bool:
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"""Check if a module can be imported."""
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return find_spec(module) is not None
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# Feature registry: feature_name -> (check_function, description)
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# Note: auth, server, lsp moved to Nextra (proprietary)
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FEATURES: dict[str, tuple[Callable[[], bool], str]] = {
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"anthropic": (lambda: _check_import("anthropic"), "Anthropic Claude SDK"),
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"openai": (lambda: _check_import("openai"), "OpenAI SDK"),
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"redis": (lambda: _check_import("redis"), "Redis for distributed keyvalue"),
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"search": (lambda: _check_import("duckduckgo_search"), "DuckDuckGo search"),
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"console": (lambda: _check_import("prompt_toolkit"), "Interactive console example"),
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}
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def get_available_features() -> dict[str, bool]:
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"""Return dict of feature_name -> is_available."""
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return {name: check() for name, (check, _) in FEATURES.items()}
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def is_feature_available(feature: str) -> bool:
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"""Check if a specific feature is available."""
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if feature not in FEATURES:
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return False
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check, _ = FEATURES[feature]
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return check()
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def require_feature(feature: str) -> None:
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"""Raise ImportError if feature is not available."""
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if not is_feature_available(feature):
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_, description = FEATURES.get(feature, (None, feature))
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raise ImportError(
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f"Feature '{feature}' is not installed. "
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f"Install with: pip install xml-pipeline[{feature}]"
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)
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@dataclass
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class FeatureCheck:
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"""Result of checking features against a config."""
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available: dict[str, bool] = field(default_factory=dict)
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missing: dict[str, str] = field(default_factory=dict) # feature -> reason needed
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def check_features(config) -> FeatureCheck:
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"""
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Check which optional features are needed for a config.
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Returns FeatureCheck with available features and missing ones needed by config.
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"""
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result = FeatureCheck(available=get_available_features())
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# Check LLM backends
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for backend in getattr(config, "llm_backends", []):
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provider = getattr(backend, "provider", "").lower()
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if provider == "anthropic" and not result.available.get("anthropic"):
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result.missing["anthropic"] = f"LLM backend '{backend.name}' uses Anthropic"
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if provider == "openai" and not result.available.get("openai"):
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result.missing["openai"] = f"LLM backend '{backend.name}' uses OpenAI"
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# Check tools
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for listener in getattr(config, "listeners", []):
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# If listener uses keyvalue tool and redis is configured
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# This would need more sophisticated detection based on tool config
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pass
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# Note: auth/server config sections are read but implemented in Nextra
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return result
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# Lazy import helpers for optional dependencies
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def get_redis_client():
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"""Get Redis client, or raise helpful error."""
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require_feature("redis")
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import redis
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return redis
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def get_anthropic_client():
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"""Get Anthropic client, or raise helpful error."""
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require_feature("anthropic")
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import anthropic
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return anthropic
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def get_openai_client():
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"""Get OpenAI client, or raise helpful error."""
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require_feature("openai")
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import openai
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return openai
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