curo1305
beb5b5e49d
- Creates backend/ai/provider_config.py as a pure data module (no provider imports) - ProviderConfig(BaseModel) with extra=forbid: provider_id, api_key, base_url, model, context_chars - PROVIDER_DEFAULTS dict with all 10 providers and verbatim base_url/model/context_chars from RESEARCH.md - SUPPORTS_JSON_MODE dict with gemini=False per JSON Compatibility Matrix (D-02)
108 lines
3.3 KiB
Python
108 lines
3.3 KiB
Python
"""ProviderConfig Pydantic model and per-provider defaults.
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Loaded by get_provider() in ai/__init__.py; populated by load_provider_config()
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in services/ai_config.py.
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This file is a pure data module — it does NOT import any provider class.
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"""
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from __future__ import annotations
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from typing import Optional
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from pydantic import BaseModel
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class ProviderConfig(BaseModel):
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"""Typed configuration for a single AI provider instance.
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Fields:
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provider_id: One of the keys in PROVIDER_DEFAULTS (e.g. "openai", "groq").
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api_key: Decrypted API key; empty string for local providers (Ollama, LMStudio).
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base_url: Override for the provider's base URL; None means use the default.
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model: Model name; empty string means use the default from PROVIDER_DEFAULTS.
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context_chars: Character budget for input truncation; 0 means use the default.
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"""
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model_config = {"extra": "forbid"}
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provider_id: str
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api_key: str = ""
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base_url: Optional[str] = None
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model: str = ""
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context_chars: int = 8000
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# Named preset defaults for all 10 supported providers.
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# Values are [ASSUMED] approximations based on well-known context window sizes.
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# Admins can override all fields via the system_settings DB table (D-04).
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PROVIDER_DEFAULTS: dict[str, dict] = {
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"openai": {
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"base_url": None,
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"model": "gpt-4o",
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"context_chars": 120_000,
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},
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"anthropic": {
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"base_url": None,
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"model": "claude-sonnet-4-6",
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"context_chars": 180_000,
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},
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"gemini": {
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"base_url": "https://generativelanguage.googleapis.com/v1beta/openai/",
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"model": "gemini-2.0-flash",
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"context_chars": 800_000,
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},
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"groq": {
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"base_url": "https://api.groq.com/openai/v1",
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"model": "llama-3.3-70b-versatile",
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"context_chars": 128_000,
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},
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"xai": {
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"base_url": "https://api.x.ai/v1",
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"model": "grok-3-mini",
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"context_chars": 128_000,
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},
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"deepseek": {
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"base_url": "https://api.deepseek.com",
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"model": "deepseek-chat",
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"context_chars": 60_000,
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},
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"openrouter": {
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"base_url": "https://openrouter.ai/api/v1",
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"model": "anthropic/claude-3.5-sonnet",
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"context_chars": 180_000,
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},
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"mistral": {
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"base_url": "https://api.mistral.ai/v1",
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"model": "mistral-large-latest",
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"context_chars": 128_000,
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},
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"ollama": {
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"base_url": "http://host.docker.internal:11434/v1",
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"model": "llama3.2",
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"context_chars": 8_000,
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},
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"lmstudio": {
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"base_url": "http://host.docker.internal:1234/v1",
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"model": "gemma-4-e4b-it",
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"context_chars": 8_000,
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},
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}
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# Whether the provider honours response_format={"type": "json_object"}.
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# Gemini's OpenAI-compat endpoint does NOT support the string form (D-02/D-03).
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# Ollama and LMStudio accept the parameter but some models ignore it — the
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# GenericOpenAIProvider always wraps the raw response with parse_classification()
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# regardless, so they are left as True (the parameter is still sent).
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SUPPORTS_JSON_MODE: dict[str, bool] = {
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"openai": True,
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"anthropic": True,
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"gemini": False,
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"groq": True,
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"xai": True,
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"deepseek": True,
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"openrouter": True,
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"mistral": True,
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"ollama": True,
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"lmstudio": True,
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}
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