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@@ -1,100 +1,84 @@
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"""
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Shared AI service for devtools.
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"""
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import requests
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import os
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from typing import List, Dict, Optional, Any
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from abc import ABC, abstractmethod
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from .config import BaseConfig
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class AIProvider(ABC):
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"""Base class for AI providers."""
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@abstractmethod
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def setup(self, config: BaseConfig) -> None:
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"""Set up the provider with configuration."""
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pass
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@abstractmethod
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def generate_completion(
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self,
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system_prompt: str,
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user_prompt: str,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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top_p: float = 0.95,
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) -> str:
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def generate_completion(self,
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system_prompt: str,
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user_prompt: str,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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top_p: float = 0.95) -> str:
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"""Generate a completion from the AI model."""
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pass
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class OpenRouterProvider(AIProvider):
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"""OpenRouter AI provider implementation."""
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def setup(self, config: BaseConfig) -> None:
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self.config = config
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self.api_key = config.get_env_or_config("OPENROUTER_API_KEY")
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if not self.api_key:
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raise ValueError(
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"OpenRouter API key not found. Please set it in config or environment."
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)
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raise ValueError("OpenRouter API key not found. Please set it in config or environment.")
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self.model = config.get("model", "mistralai/mixtral-8x7b-instruct")
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self.api_url = "https://openrouter.ai/api/v1/chat/completions"
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self.headers = {
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"Authorization": f"Bearer {self.api_key}",
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"HTTP-Referer": "https://github.com/S4NKALP/DevTools",
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"X-Title": "DevTools",
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"Content-Type": "application/json",
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"Content-Type": "application/json"
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}
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def _create_prompt(
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self, system_prompt: str, user_prompt: str
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) -> List[Dict[str, str]]:
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def _create_prompt(self, system_prompt: str, user_prompt: str) -> List[Dict[str, str]]:
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return [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt},
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{"role": "user", "content": user_prompt}
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]
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def generate_completion(
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self,
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system_prompt: str,
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user_prompt: str,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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top_p: float = 0.95,
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) -> str:
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def generate_completion(self,
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system_prompt: str,
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user_prompt: str,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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top_p: float = 0.95) -> str:
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messages = self._create_prompt(system_prompt, user_prompt)
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try:
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temp = (
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temperature
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if temperature is not None
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else float(self.config.get("temperature", 0.7))
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)
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tokens = (
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max_tokens
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if max_tokens is not None
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else int(self.config.get("max_tokens", 150))
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)
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temp = temperature if temperature is not None else float(self.config.get("temperature", 0.7))
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tokens = max_tokens if max_tokens is not None else int(self.config.get("max_tokens", 150))
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payload = {
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"model": self.model,
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"messages": messages,
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"temperature": temp,
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"max_tokens": tokens,
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"top_p": float(top_p),
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"stream": False,
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"stream": False
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}
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payload = {k: v for k, v in payload.items() if v is not None}
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response = requests.post(
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self.api_url, headers=self.headers, json=payload, timeout=30
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self.api_url,
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headers=self.headers,
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json=payload,
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timeout=30
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)
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if response.status_code != 200:
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error_msg = response.text
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try:
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@@ -104,80 +88,68 @@ class OpenRouterProvider(AIProvider):
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except:
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pass
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raise Exception(f"OpenRouter API error: {error_msg}")
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result = response.json()
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if "choices" in result and len(result["choices"]) > 0:
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return result["choices"][0]["message"]["content"].strip()
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return ""
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except Exception as e:
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raise Exception(f"AI generation failed: {str(e)}")
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class OpenAIProvider(AIProvider):
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"""OpenAI provider implementation."""
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def setup(self, config: BaseConfig) -> None:
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self.config = config
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self.api_key = config.get_env_or_config("OPENAI_API_KEY")
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if not self.api_key:
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raise ValueError(
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"OpenAI API key not found. Please set it in config or environment."
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)
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raise ValueError("OpenAI API key not found. Please set it in config or environment.")
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self.model = config.get("model", "gpt-4-turbo-preview")
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self.api_url = "https://api.openai.com/v1/chat/completions"
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self.headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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"Content-Type": "application/json"
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}
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def _create_prompt(
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self, system_prompt: str, user_prompt: str
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) -> List[Dict[str, str]]:
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def _create_prompt(self, system_prompt: str, user_prompt: str) -> List[Dict[str, str]]:
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return [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt},
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{"role": "user", "content": user_prompt}
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]
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def generate_completion(
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self,
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system_prompt: str,
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user_prompt: str,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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top_p: float = 0.95,
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) -> str:
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def generate_completion(self,
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system_prompt: str,
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user_prompt: str,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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top_p: float = 0.95) -> str:
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messages = self._create_prompt(system_prompt, user_prompt)
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try:
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temp = (
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temperature
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if temperature is not None
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else float(self.config.get("temperature", 0.7))
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)
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tokens = (
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max_tokens
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if max_tokens is not None
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else int(self.config.get("max_tokens", 150))
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)
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temp = temperature if temperature is not None else float(self.config.get("temperature", 0.7))
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tokens = max_tokens if max_tokens is not None else int(self.config.get("max_tokens", 150))
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payload = {
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"model": self.model,
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"messages": messages,
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"temperature": temp,
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"max_tokens": tokens,
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"top_p": float(top_p),
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"top_p": float(top_p)
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}
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payload = {k: v for k, v in payload.items() if v is not None}
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response = requests.post(
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self.api_url, headers=self.headers, json=payload, timeout=30
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self.api_url,
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headers=self.headers,
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json=payload,
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timeout=30
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)
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if response.status_code != 200:
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error_msg = response.text
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try:
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@@ -187,74 +159,63 @@ class OpenAIProvider(AIProvider):
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except:
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pass
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raise Exception(f"OpenAI API error: {error_msg}")
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result = response.json()
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if "choices" in result and len(result["choices"]) > 0:
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return result["choices"][0]["message"]["content"].strip()
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return ""
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except Exception as e:
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raise Exception(f"AI generation failed: {str(e)}")
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class GeminiProvider(AIProvider):
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"""Google Gemini provider implementation."""
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def setup(self, config: BaseConfig) -> None:
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self.config = config
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self.api_key = config.get_env_or_config("GOOGLE_API_KEY")
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if not self.api_key:
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raise ValueError(
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"Google API key not found. Please set it in config or environment."
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)
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raise ValueError("Google API key not found. Please set it in config or environment.")
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self.model = config.get("model", "gemini-pro")
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self.api_url = f"https://generativelanguage.googleapis.com/v1beta/models/{
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self.model
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}:generateContent"
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self.headers = {"Content-Type": "application/json"}
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self.api_url = f"https://generativelanguage.googleapis.com/v1beta/models/{self.model}:generateContent"
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self.headers = {
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"Content-Type": "application/json"
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}
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|
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def generate_completion(
|
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self,
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system_prompt: str,
|
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user_prompt: str,
|
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temperature: Optional[float] = None,
|
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max_tokens: Optional[int] = None,
|
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top_p: float = 0.95,
|
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) -> str:
|
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def generate_completion(self,
|
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system_prompt: str,
|
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user_prompt: str,
|
||||
temperature: Optional[float] = None,
|
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max_tokens: Optional[int] = None,
|
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top_p: float = 0.95) -> str:
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try:
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temp = (
|
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temperature
|
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if temperature is not None
|
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else float(self.config.get("temperature", 0.7))
|
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)
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tokens = (
|
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max_tokens
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if max_tokens is not None
|
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else int(self.config.get("max_tokens", 150))
|
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)
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|
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temp = temperature if temperature is not None else float(self.config.get("temperature", 0.7))
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tokens = max_tokens if max_tokens is not None else int(self.config.get("max_tokens", 150))
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# Combine system and user prompts for Gemini
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full_prompt = f"{system_prompt}\n\n{user_prompt}"
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payload = {
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"contents": [{"parts": [{"text": full_prompt}]}],
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"contents": [{
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"parts": [{"text": full_prompt}]
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}],
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"generationConfig": {
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"temperature": temp,
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"maxOutputTokens": tokens,
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"topP": float(top_p),
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},
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"topP": float(top_p)
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||||
}
|
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}
|
||||
|
||||
|
||||
response = requests.post(
|
||||
f"{self.api_url}?key={self.api_key}",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
timeout=30,
|
||||
timeout=30
|
||||
)
|
||||
|
||||
|
||||
if response.status_code != 200:
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||||
error_msg = response.text
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try:
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@@ -264,81 +225,69 @@ class GeminiProvider(AIProvider):
|
||||
except:
|
||||
pass
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||||
raise Exception(f"Gemini API error: {error_msg}")
|
||||
|
||||
|
||||
result = response.json()
|
||||
|
||||
|
||||
if "candidates" in result and len(result["candidates"]) > 0:
|
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return result["candidates"][0]["content"]["parts"][0]["text"].strip()
|
||||
|
||||
|
||||
return ""
|
||||
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(f"AI generation failed: {str(e)}")
|
||||
|
||||
|
||||
class ClaudeProvider(AIProvider):
|
||||
"""Anthropic Claude provider implementation."""
|
||||
|
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|
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def setup(self, config: BaseConfig) -> None:
|
||||
self.config = config
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||||
self.api_key = config.get_env_or_config("ANTHROPIC_API_KEY")
|
||||
if not self.api_key:
|
||||
raise ValueError(
|
||||
"Anthropic API key not found. Please set it in config or environment."
|
||||
)
|
||||
|
||||
raise ValueError("Anthropic API key not found. Please set it in config or environment.")
|
||||
|
||||
self.model = config.get("model", "claude-3-opus-20240229")
|
||||
self.api_url = "https://api.anthropic.com/v1/messages"
|
||||
self.headers = {
|
||||
"x-api-key": self.api_key,
|
||||
"anthropic-version": "2023-06-01",
|
||||
"content-type": "application/json",
|
||||
"content-type": "application/json"
|
||||
}
|
||||
|
||||
def _create_prompt(
|
||||
self, system_prompt: str, user_prompt: str
|
||||
) -> List[Dict[str, str]]:
|
||||
def _create_prompt(self, system_prompt: str, user_prompt: str) -> List[Dict[str, str]]:
|
||||
return [
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": user_prompt},
|
||||
{"role": "user", "content": user_prompt}
|
||||
]
|
||||
|
||||
def generate_completion(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
top_p: float = 0.95,
|
||||
) -> str:
|
||||
def generate_completion(self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
top_p: float = 0.95) -> str:
|
||||
messages = self._create_prompt(system_prompt, user_prompt)
|
||||
|
||||
|
||||
try:
|
||||
temp = (
|
||||
temperature
|
||||
if temperature is not None
|
||||
else float(self.config.get("temperature", 0.7))
|
||||
)
|
||||
tokens = (
|
||||
max_tokens
|
||||
if max_tokens is not None
|
||||
else int(self.config.get("max_tokens", 150))
|
||||
)
|
||||
|
||||
temp = temperature if temperature is not None else float(self.config.get("temperature", 0.7))
|
||||
tokens = max_tokens if max_tokens is not None else int(self.config.get("max_tokens", 150))
|
||||
|
||||
payload = {
|
||||
"model": self.model,
|
||||
"messages": messages,
|
||||
"temperature": temp,
|
||||
"max_tokens": tokens,
|
||||
"top_p": float(top_p),
|
||||
"top_p": float(top_p)
|
||||
}
|
||||
|
||||
|
||||
payload = {k: v for k, v in payload.items() if v is not None}
|
||||
|
||||
|
||||
response = requests.post(
|
||||
self.api_url, headers=self.headers, json=payload, timeout=30
|
||||
self.api_url,
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
timeout=30
|
||||
)
|
||||
|
||||
|
||||
if response.status_code != 200:
|
||||
error_msg = response.text
|
||||
try:
|
||||
@@ -348,76 +297,66 @@ class ClaudeProvider(AIProvider):
|
||||
except:
|
||||
pass
|
||||
raise Exception(f"Claude API error: {error_msg}")
|
||||
|
||||
|
||||
result = response.json()
|
||||
|
||||
|
||||
if "content" in result and len(result["content"]) > 0:
|
||||
return result["content"][0]["text"].strip()
|
||||
|
||||
|
||||
return ""
|
||||
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(f"AI generation failed: {str(e)}")
|
||||
|
||||
|
||||
class HuggingFaceProvider(AIProvider):
|
||||
"""Hugging Face provider implementation."""
|
||||
|
||||
|
||||
def setup(self, config: BaseConfig) -> None:
|
||||
self.config = config
|
||||
self.api_key = config.get_env_or_config("HUGGINGFACE_API_KEY")
|
||||
if not self.api_key:
|
||||
raise ValueError(
|
||||
"Hugging Face API key not found. Please set it in config or environment."
|
||||
)
|
||||
|
||||
raise ValueError("Hugging Face API key not found. Please set it in config or environment.")
|
||||
|
||||
self.model = config.get("model", "mistralai/Mixtral-8x7B-Instruct-v0.1")
|
||||
self.api_url = f"https://api-inference.huggingface.co/models/{self.model}"
|
||||
self.headers = {
|
||||
"Authorization": f"Bearer {self.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
def _create_prompt(self, system_prompt: str, user_prompt: str) -> str:
|
||||
# Format prompt according to model's requirements
|
||||
return f"<s>[INST] {system_prompt}\n\n{user_prompt} [/INST]"
|
||||
|
||||
def generate_completion(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
top_p: float = 0.95,
|
||||
) -> str:
|
||||
def generate_completion(self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
top_p: float = 0.95) -> str:
|
||||
try:
|
||||
temp = (
|
||||
temperature
|
||||
if temperature is not None
|
||||
else float(self.config.get("temperature", 0.7))
|
||||
)
|
||||
tokens = (
|
||||
max_tokens
|
||||
if max_tokens is not None
|
||||
else int(self.config.get("max_tokens", 150))
|
||||
)
|
||||
|
||||
temp = temperature if temperature is not None else float(self.config.get("temperature", 0.7))
|
||||
tokens = max_tokens if max_tokens is not None else int(self.config.get("max_tokens", 150))
|
||||
|
||||
prompt = self._create_prompt(system_prompt, user_prompt)
|
||||
|
||||
|
||||
payload = {
|
||||
"inputs": prompt,
|
||||
"parameters": {
|
||||
"temperature": temp,
|
||||
"max_new_tokens": tokens,
|
||||
"top_p": float(top_p),
|
||||
"return_full_text": False,
|
||||
},
|
||||
"return_full_text": False
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
response = requests.post(
|
||||
self.api_url, headers=self.headers, json=payload, timeout=30
|
||||
self.api_url,
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
timeout=30
|
||||
)
|
||||
|
||||
|
||||
if response.status_code != 200:
|
||||
error_msg = response.text
|
||||
try:
|
||||
@@ -427,21 +366,20 @@ class HuggingFaceProvider(AIProvider):
|
||||
except:
|
||||
pass
|
||||
raise Exception(f"Hugging Face API error: {error_msg}")
|
||||
|
||||
|
||||
result = response.json()
|
||||
|
||||
|
||||
if isinstance(result, list) and len(result) > 0:
|
||||
return result[0]["generated_text"].strip()
|
||||
|
||||
|
||||
return ""
|
||||
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(f"AI generation failed: {str(e)}")
|
||||
|
||||
|
||||
class AIService:
|
||||
"""Base AI service that can be extended by specific tools."""
|
||||
|
||||
|
||||
def __init__(self, config: BaseConfig):
|
||||
"""Initialize AI service with configuration."""
|
||||
self.config = config
|
||||
@@ -451,49 +389,48 @@ class AIService:
|
||||
def _get_provider(self) -> AIProvider:
|
||||
"""Get the appropriate AI provider based on configuration."""
|
||||
provider = self.config.get("provider", "openrouter").lower()
|
||||
|
||||
|
||||
providers = {
|
||||
"openrouter": OpenRouterProvider,
|
||||
"openai": OpenAIProvider,
|
||||
"gemini": GeminiProvider,
|
||||
"claude": ClaudeProvider,
|
||||
"huggingface": HuggingFaceProvider,
|
||||
"huggingface": HuggingFaceProvider
|
||||
}
|
||||
|
||||
|
||||
if provider not in providers:
|
||||
raise ValueError(
|
||||
f"Unsupported AI provider: {provider}. Supported providers: {
|
||||
', '.join(providers.keys())
|
||||
}"
|
||||
)
|
||||
|
||||
raise ValueError(f"Unsupported AI provider: {provider}. Supported providers: {', '.join(providers.keys())}")
|
||||
|
||||
return providers[provider]()
|
||||
|
||||
def generate_completion(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
top_p: float = 0.95,
|
||||
) -> str:
|
||||
def generate_completion(self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
top_p: float = 0.95) -> str:
|
||||
"""Generate a completion from the AI model."""
|
||||
return self.provider.generate_completion(
|
||||
system_prompt, user_prompt, temperature, max_tokens, top_p
|
||||
system_prompt,
|
||||
user_prompt,
|
||||
temperature,
|
||||
max_tokens,
|
||||
top_p
|
||||
)
|
||||
|
||||
def generate_batch_completions(
|
||||
self,
|
||||
system_prompt: str,
|
||||
prompts: List[str],
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
) -> List[str]:
|
||||
def generate_batch_completions(self,
|
||||
system_prompt: str,
|
||||
prompts: List[str],
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None) -> List[str]:
|
||||
"""Generate completions for multiple prompts."""
|
||||
completions = []
|
||||
for prompt in prompts:
|
||||
completion = self.generate_completion(
|
||||
system_prompt, prompt, temperature, max_tokens
|
||||
system_prompt,
|
||||
prompt,
|
||||
temperature,
|
||||
max_tokens
|
||||
)
|
||||
completions.append(completion)
|
||||
return completions
|
||||
return completions
|
||||
Reference in new issue
Block a user