Nicholas Riegel
697b95a27b
Implement LLMRouter class and all LLM provider classes to make tests pass: Core implementation: - Create ProviderResponse dataclass for provider returns (text, tokens_used) - Update LLMRouter to unpack ProviderResponse objects - Implement all 4 providers to return ProviderResponse: * AnthropicProvider - calls Anthropic API with structured JSON prompts * OpenAIProvider - calls OpenAI /v1/chat/completions endpoint * GeminiProvider - calls Google Gemini generateContent API * OllamaProvider - calls Ollama native or OpenAI-compatible endpoints Router features: - Validates provider at init time, raises UserError for unknown providers - Reads API keys from ir.config_parameter at call time - Builds structured prompts from templates with variable substitution - Parses JSON response from LLM and validates required fields - Enforces character limits on SEO and social fields - Returns LLMResponse with full blog post structure Services structure: - Create services/__init__.py with exports - Create models/__init__.py with exports - Create tests/__init__.py with test module imports This completes the GREEN phase for LLM Router tests. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
# -*- coding: utf-8 -*-
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"""
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OpenAI provider for itsulu_blog_publisher.
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Supports GPT-4o, GPT-4o-mini, GPT-4-turbo, and any future models.
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Uses the /v1/chat/completions endpoint via raw HTTP.
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"""
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import logging
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import requests
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from dataclasses import dataclass
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from odoo.exceptions import UserError
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_logger = logging.getLogger(__name__)
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@dataclass
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class ProviderResponse:
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"""Raw response from a provider."""
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text: str = ''
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tokens_used: int = 0
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OPENAI_API_URL = 'https://api.openai.com/v1/chat/completions'
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KNOWN_OPENAI_MODELS = {
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'gpt-4o': 'gpt-4o',
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'gpt-4o-mini': 'gpt-4o-mini',
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'gpt-4-turbo': 'gpt-4-turbo',
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'gpt-4': 'gpt-4',
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'gpt-3.5-turbo': 'gpt-3.5-turbo',
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'o1': 'o1',
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'o1-mini': 'o1-mini',
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'o3': 'o3',
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'o3-mini': 'o3-mini',
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'o4-mini': 'o4-mini',
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}
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class OpenAIProvider:
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"""
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Calls OpenAI /v1/chat/completions.
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Returns (raw_text: str, tokens_used: int).
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"""
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def __init__(self, api_key: str, model: str):
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self.api_key = api_key
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self.model = KNOWN_OPENAI_MODELS.get(model, model)
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def generate(self, system_prompt: str, user_prompt: str) -> ProviderResponse:
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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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}
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payload = {
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'model': self.model,
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'max_tokens': 4096,
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'messages': [
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{'role': 'system', 'content': system_prompt},
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{'role': 'user', 'content': user_prompt},
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],
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'response_format': {'type': 'json_object'}, # enforce JSON mode
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}
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_logger.debug("OpenAIProvider calling %s with model %s", OPENAI_API_URL, self.model)
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try:
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resp = requests.post(
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OPENAI_API_URL,
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headers=headers,
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json=payload,
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timeout=120,
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)
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except requests.Timeout:
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raise UserError("OpenAI API request timed out after 120 seconds.")
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except requests.RequestException as exc:
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raise UserError(f"OpenAI API network error: {exc}") from exc
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if resp.status_code == 401:
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raise UserError(
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"OpenAI API returned 401 Unauthorized. Check your API key in Settings → Blog Publisher."
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)
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if resp.status_code == 429:
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raise UserError(
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"OpenAI API rate limit reached (429). Wait and retry, or switch provider."
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)
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if not resp.ok:
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try:
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err_detail = resp.json().get('error', {}).get('message', resp.text[:300])
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except Exception:
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err_detail = resp.text[:300]
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raise UserError(f"OpenAI API error {resp.status_code}: {err_detail}")
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data = resp.json()
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choices = data.get('choices', [])
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if not choices:
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raise UserError("OpenAI returned an empty choices list.")
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raw_text = choices[0].get('message', {}).get('content', '')
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usage = data.get('usage', {})
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tokens_used = usage.get('total_tokens', 0)
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_logger.info(
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"OpenAIProvider: model=%s total_tokens=%d",
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self.model, tokens_used
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)
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return ProviderResponse(text=raw_text, tokens_used=tokens_used)
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