feat: pannello Settings con 4 sezioni flessibili + provider custom
- Redesign Settings: Testi, Immagini, Video, Voiceover — sezioni separate - Ogni sezione ha dropdown provider + API key + campo opzionale modello - Opzione "Personalizzato" con campo Base URL libero per qualsiasi servizio - LLM: aggiunto OpenRouter + provider custom OpenAI-compatible - Backend: OpenAICompatibleProvider unifica OpenAI/OpenRouter/custom - Router content: passa llm_base_url a get_llm_provider Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Michele
@@ -63,7 +63,8 @@ def generate_content(request: GenerateContentRequest, db: Session = Depends(get_
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}
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# Create LLM provider and generate text
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llm = get_llm_provider(provider_name, api_key, model)
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base_url = _get_setting(db, "llm_base_url")
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llm = get_llm_provider(provider_name, api_key, model, base_url=base_url)
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text = generate_post_text(
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character=char_dict,
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llm_provider=llm,
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@@ -1,8 +1,8 @@
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"""
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Multi-LLM abstraction layer.
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Supports Claude (Anthropic), OpenAI, and Gemini via direct HTTP calls using httpx.
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Each provider implements the same interface for text generation.
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Supports Claude (Anthropic), OpenAI, Gemini, OpenRouter, and any
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OpenAI-compatible custom endpoint via direct HTTP calls using httpx.
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"""
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from abc import ABC, abstractmethod
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@@ -14,6 +14,8 @@ DEFAULT_MODELS = {
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"claude": "claude-sonnet-4-20250514",
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"openai": "gpt-4o-mini",
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"gemini": "gemini-2.0-flash",
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"openrouter": "openai/gpt-4o-mini",
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"custom": "",
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}
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TIMEOUT = 60.0
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@@ -28,15 +30,7 @@ class LLMProvider(ABC):
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@abstractmethod
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def generate(self, prompt: str, system: str = "") -> str:
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"""Generate text from a prompt.
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Args:
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prompt: The user prompt / message.
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system: Optional system prompt for context and behavior.
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Returns:
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Generated text string.
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"""
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"""Generate text from a prompt."""
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...
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@@ -67,7 +61,6 @@ class ClaudeProvider(LLMProvider):
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response = client.post(self.API_URL, headers=headers, json=payload)
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response.raise_for_status()
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data = response.json()
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# Claude returns content as a list of content blocks
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content_blocks = data.get("content", [])
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return "".join(
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block.get("text", "") for block in content_blocks if block.get("type") == "text"
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@@ -80,15 +73,27 @@ class ClaudeProvider(LLMProvider):
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raise RuntimeError(f"Claude API request failed: {e}") from e
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class OpenAIProvider(LLMProvider):
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"""OpenAI provider via Chat Completions API."""
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class OpenAICompatibleProvider(LLMProvider):
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"""OpenAI Chat Completions-compatible provider.
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API_URL = "https://api.openai.com/v1/chat/completions"
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Used for OpenAI, OpenRouter, and any custom OpenAI-compatible endpoint.
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Set base_url to point to any compatible API.
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"""
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def __init__(self, api_key: str, model: str | None = None):
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super().__init__(api_key, model or DEFAULT_MODELS["openai"])
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DEFAULT_BASE_URL = "https://api.openai.com/v1"
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def __init__(
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self,
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api_key: str,
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model: str | None = None,
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base_url: str | None = None,
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default_model: str = "gpt-4o-mini",
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):
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super().__init__(api_key, model or default_model)
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self.base_url = (base_url or self.DEFAULT_BASE_URL).rstrip("/")
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def generate(self, prompt: str, system: str = "") -> str:
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url = f"{self.base_url}/chat/completions"
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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@@ -106,16 +111,16 @@ class OpenAIProvider(LLMProvider):
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try:
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with httpx.Client(timeout=TIMEOUT) as client:
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response = client.post(self.API_URL, headers=headers, json=payload)
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response = client.post(url, headers=headers, json=payload)
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response.raise_for_status()
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data = response.json()
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return data["choices"][0]["message"]["content"]
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except httpx.HTTPStatusError as e:
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raise RuntimeError(
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f"OpenAI API error {e.response.status_code}: {e.response.text}"
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f"API error {e.response.status_code}: {e.response.text}"
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) from e
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except httpx.RequestError as e:
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raise RuntimeError(f"OpenAI API request failed: {e}") from e
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raise RuntimeError(f"API request failed: {e}") from e
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class GeminiProvider(LLMProvider):
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@@ -131,7 +136,6 @@ class GeminiProvider(LLMProvider):
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params = {"key": self.api_key}
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headers = {"Content-Type": "application/json"}
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# Build contents; Gemini uses a parts-based structure
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parts: list[dict] = []
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if system:
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parts.append({"text": f"{system}\n\n{prompt}"})
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@@ -140,9 +144,7 @@ class GeminiProvider(LLMProvider):
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payload = {
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"contents": [{"parts": parts}],
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"generationConfig": {
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"maxOutputTokens": 2048,
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},
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"generationConfig": {"maxOutputTokens": 2048},
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}
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try:
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@@ -165,30 +167,57 @@ class GeminiProvider(LLMProvider):
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def get_llm_provider(
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provider_name: str, api_key: str, model: str | None = None
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provider_name: str,
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api_key: str,
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model: str | None = None,
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base_url: str | None = None,
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) -> LLMProvider:
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"""Factory function to get an LLM provider instance.
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"""Factory: returns an LLMProvider instance.
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Args:
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provider_name: One of 'claude', 'openai', 'gemini'.
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provider_name: 'claude', 'openai', 'gemini', 'openrouter', or 'custom'.
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api_key: API key for the provider.
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model: Optional model override. Uses default if not specified.
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model: Optional model override.
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base_url: Optional base URL override (used for 'openrouter' and 'custom').
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Returns:
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An LLMProvider instance.
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Raises:
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ValueError: If provider_name is not supported.
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An LLMProvider instance ready to generate text.
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"""
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providers = {
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"claude": ClaudeProvider,
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"openai": OpenAIProvider,
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"gemini": GeminiProvider,
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}
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provider_cls = providers.get(provider_name.lower())
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if provider_cls is None:
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supported = ", ".join(providers.keys())
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raise ValueError(
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f"Unknown LLM provider '{provider_name}'. Supported: {supported}"
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name = provider_name.lower()
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if name == "claude":
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return ClaudeProvider(api_key=api_key, model=model)
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if name == "openai":
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return OpenAICompatibleProvider(
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api_key=api_key,
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model=model,
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base_url="https://api.openai.com/v1",
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default_model=DEFAULT_MODELS["openai"],
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)
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return provider_cls(api_key=api_key, model=model)
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if name == "gemini":
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return GeminiProvider(api_key=api_key, model=model)
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if name == "openrouter":
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return OpenAICompatibleProvider(
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api_key=api_key,
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model=model,
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base_url=base_url or "https://openrouter.ai/api/v1",
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default_model=DEFAULT_MODELS["openrouter"],
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)
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if name == "custom":
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if not base_url:
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raise ValueError("Provider 'custom' richiede un base_url configurato nelle impostazioni.")
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return OpenAICompatibleProvider(
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api_key=api_key,
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model=model,
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base_url=base_url,
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default_model=model or "",
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)
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raise ValueError(
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f"Provider LLM '{provider_name}' non supportato. "
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f"Usa: claude, openai, gemini, openrouter, custom."
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)
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