|
| 1 | +"""LLM client interfaces and implementations.""" |
| 2 | + |
| 3 | +import logging |
| 4 | +from abc import ABC, abstractmethod |
| 5 | +from typing import Any, Dict, Optional, Union |
| 6 | + |
| 7 | +from kit.models.base import LLMError |
| 8 | +from kit.models.config import AnthropicConfig, GoogleConfig, OpenAIConfig |
| 9 | +from kit.models.llm_utils import count_openai_chat_tokens |
| 10 | + |
| 11 | +# Conditionally import google.genai |
| 12 | +try: |
| 13 | + import google.genai as genai |
| 14 | + from google.genai import types as genai_types |
| 15 | +except ImportError: |
| 16 | + genai = None # type: ignore |
| 17 | + genai_types = None # type: ignore |
| 18 | + |
| 19 | +logger = logging.getLogger(__name__) |
| 20 | + |
| 21 | +# Constants |
| 22 | +OPENAI_MAX_PROMPT_TOKENS = 15000 # Max tokens for the prompt to OpenAI |
| 23 | + |
| 24 | + |
| 25 | +class LLMClient(ABC): |
| 26 | + """Base class for LLM clients.""" |
| 27 | + |
| 28 | + @abstractmethod |
| 29 | + def generate_completion(self, system_prompt: str, user_prompt: str, model_name: Optional[str] = None) -> str: |
| 30 | + """Generate a completion from the LLM. |
| 31 | +
|
| 32 | + Args: |
| 33 | + system_prompt: The system prompt to use. |
| 34 | + user_prompt: The user prompt to use. |
| 35 | + model_name: Optional model name to override the default. |
| 36 | +
|
| 37 | + Returns: |
| 38 | + The generated completion text. |
| 39 | +
|
| 40 | + Raises: |
| 41 | + LLMError: If there was an error generating the completion. |
| 42 | + """ |
| 43 | + pass |
| 44 | + |
| 45 | + @staticmethod |
| 46 | + def create_client(config: Union[OpenAIConfig, AnthropicConfig, GoogleConfig]) -> "LLMClient": |
| 47 | + """Factory method to create an appropriate LLM client. |
| 48 | +
|
| 49 | + Args: |
| 50 | + config: The LLM configuration to use. |
| 51 | +
|
| 52 | + Returns: |
| 53 | + An LLMClient instance. |
| 54 | +
|
| 55 | + Raises: |
| 56 | + TypeError: If config is None or an unsupported configuration type. |
| 57 | + LLMError: If there was an error initializing the client. |
| 58 | + """ |
| 59 | + # Require a valid config |
| 60 | + if config is None: |
| 61 | + raise TypeError("LLM configuration must be provided") |
| 62 | + |
| 63 | + if isinstance(config, OpenAIConfig): |
| 64 | + return OpenAIClient(config) |
| 65 | + elif isinstance(config, AnthropicConfig): |
| 66 | + return AnthropicClient(config) |
| 67 | + elif isinstance(config, GoogleConfig): |
| 68 | + return GoogleClient(config) |
| 69 | + else: |
| 70 | + raise TypeError(f"Unsupported LLM configuration type: {type(config)}") |
| 71 | + |
| 72 | + |
| 73 | +class OpenAIClient(LLMClient): |
| 74 | + """Client for OpenAI's API.""" |
| 75 | + |
| 76 | + def __init__(self, config: OpenAIConfig): |
| 77 | + """Initialize with OpenAI configuration. |
| 78 | +
|
| 79 | + Args: |
| 80 | + config: The OpenAI configuration. |
| 81 | +
|
| 82 | + Raises: |
| 83 | + LLMError: If the OpenAI SDK is not available. |
| 84 | + """ |
| 85 | + self.config = config |
| 86 | + try: |
| 87 | + from openai import OpenAI |
| 88 | + |
| 89 | + if self.config.base_url: |
| 90 | + self.client = OpenAI(api_key=self.config.api_key, base_url=self.config.base_url) |
| 91 | + else: |
| 92 | + self.client = OpenAI(api_key=self.config.api_key) |
| 93 | + except ImportError: |
| 94 | + raise LLMError("OpenAI SDK (openai) not available. Please install it.") |
| 95 | + |
| 96 | + def generate_completion(self, system_prompt: str, user_prompt: str, model_name: Optional[str] = None) -> str: |
| 97 | + """Generate a completion using OpenAI's API. |
| 98 | +
|
| 99 | + Args: |
| 100 | + system_prompt: The system prompt to use. |
| 101 | + user_prompt: The user prompt to use. |
| 102 | + model_name: Optional model name to override the config's model. |
| 103 | +
|
| 104 | + Returns: |
| 105 | + The generated completion text. |
| 106 | +
|
| 107 | + Raises: |
| 108 | + LLMError: If there was an error generating the completion. |
| 109 | + """ |
| 110 | + # Use provided model_name or fall back to config |
| 111 | + actual_model = model_name if model_name is not None else self.config.model |
| 112 | + |
| 113 | + messages_for_api = [ |
| 114 | + {"role": "system", "content": system_prompt}, |
| 115 | + {"role": "user", "content": user_prompt}, |
| 116 | + ] |
| 117 | + |
| 118 | + # Check token count |
| 119 | + prompt_token_count = count_openai_chat_tokens(messages_for_api, actual_model) |
| 120 | + if prompt_token_count is not None and prompt_token_count > OPENAI_MAX_PROMPT_TOKENS: |
| 121 | + return f"Completion generation failed: OpenAI prompt too large ({prompt_token_count} tokens). Limit is {OPENAI_MAX_PROMPT_TOKENS} tokens." |
| 122 | + |
| 123 | + try: |
| 124 | + response = self.client.chat.completions.create( |
| 125 | + model=actual_model, |
| 126 | + messages=messages_for_api, |
| 127 | + temperature=self.config.temperature, |
| 128 | + max_tokens=self.config.max_tokens, |
| 129 | + ) |
| 130 | + |
| 131 | + if response.usage: |
| 132 | + logger.debug(f"OpenAI API usage: {response.usage}") |
| 133 | + |
| 134 | + return response.choices[0].message.content |
| 135 | + except Exception as e: |
| 136 | + logger.error(f"Error communicating with OpenAI API: {e}") |
| 137 | + raise LLMError(f"Error communicating with OpenAI API: {e}") from e |
| 138 | + |
| 139 | + |
| 140 | +class AnthropicClient(LLMClient): |
| 141 | + """Client for Anthropic's API.""" |
| 142 | + |
| 143 | + def __init__(self, config: AnthropicConfig): |
| 144 | + """Initialize with Anthropic configuration. |
| 145 | +
|
| 146 | + Args: |
| 147 | + config: The Anthropic configuration. |
| 148 | +
|
| 149 | + Raises: |
| 150 | + LLMError: If the Anthropic SDK is not available. |
| 151 | + """ |
| 152 | + self.config = config |
| 153 | + try: |
| 154 | + from anthropic import Anthropic |
| 155 | + |
| 156 | + self.client = Anthropic(api_key=self.config.api_key) |
| 157 | + except ImportError: |
| 158 | + raise LLMError("Anthropic SDK (anthropic) not available. Please install it.") |
| 159 | + |
| 160 | + def generate_completion(self, system_prompt: str, user_prompt: str, model_name: Optional[str] = None) -> str: |
| 161 | + """Generate a completion using Anthropic's API. |
| 162 | +
|
| 163 | + Args: |
| 164 | + system_prompt: The system prompt to use. |
| 165 | + user_prompt: The user prompt to use. |
| 166 | + model_name: Optional model name to override the config's model. |
| 167 | +
|
| 168 | + Returns: |
| 169 | + The generated completion text. |
| 170 | +
|
| 171 | + Raises: |
| 172 | + LLMError: If there was an error generating the completion. |
| 173 | + """ |
| 174 | + # Use provided model_name or fall back to config |
| 175 | + actual_model = model_name if model_name is not None else self.config.model |
| 176 | + |
| 177 | + try: |
| 178 | + response = self.client.messages.create( |
| 179 | + model=actual_model, |
| 180 | + system=system_prompt, |
| 181 | + messages=[{"role": "user", "content": user_prompt}], |
| 182 | + max_tokens=self.config.max_tokens, |
| 183 | + temperature=self.config.temperature, |
| 184 | + ) |
| 185 | + |
| 186 | + return response.content[0].text |
| 187 | + except Exception as e: |
| 188 | + logger.error(f"Error communicating with Anthropic API: {e}") |
| 189 | + raise LLMError(f"Error communicating with Anthropic API: {e}") from e |
| 190 | + |
| 191 | + |
| 192 | +class GoogleClient(LLMClient): |
| 193 | + """Client for Google's Generative AI API.""" |
| 194 | + |
| 195 | + def __init__(self, config: GoogleConfig): |
| 196 | + """Initialize with Google configuration. |
| 197 | +
|
| 198 | + Args: |
| 199 | + config: The Google configuration. |
| 200 | +
|
| 201 | + Raises: |
| 202 | + LLMError: If the Google Gen AI SDK is not available. |
| 203 | + """ |
| 204 | + self.config = config |
| 205 | + if genai is None: |
| 206 | + raise LLMError("Google Gen AI SDK (google-genai) not available. Please install it.") |
| 207 | + |
| 208 | + try: |
| 209 | + self.client = genai.Client(api_key=self.config.api_key) |
| 210 | + except Exception as e: |
| 211 | + raise LLMError(f"Error initializing Google Gen AI client: {e}") from e |
| 212 | + |
| 213 | + def generate_completion(self, system_prompt: str, user_prompt: str, model_name: Optional[str] = None) -> str: |
| 214 | + """Generate a completion using Google's Generative AI API. |
| 215 | +
|
| 216 | + Args: |
| 217 | + system_prompt: The system prompt to use (Note: currently not used by Google's API directly). |
| 218 | + user_prompt: The user prompt to use. |
| 219 | + model_name: Optional model name to override the config's model. |
| 220 | +
|
| 221 | + Returns: |
| 222 | + The generated completion text. |
| 223 | +
|
| 224 | + Raises: |
| 225 | + LLMError: If there was an error generating the completion. |
| 226 | + """ |
| 227 | + # Use provided model_name or fall back to config |
| 228 | + actual_model = model_name if model_name is not None else self.config.model |
| 229 | + |
| 230 | + if genai_types is None: |
| 231 | + raise LLMError( |
| 232 | + "Google Gen AI SDK (google-genai) types not available. SDK might not be installed correctly." |
| 233 | + ) |
| 234 | + |
| 235 | + # Prepare generation config from model_kwargs |
| 236 | + generation_config_params: Dict[str, Any] = ( |
| 237 | + self.config.model_kwargs.copy() if self.config.model_kwargs is not None else {} |
| 238 | + ) |
| 239 | + |
| 240 | + if self.config.temperature is not None: |
| 241 | + generation_config_params["temperature"] = self.config.temperature |
| 242 | + if self.config.max_output_tokens is not None: |
| 243 | + generation_config_params["max_output_tokens"] = self.config.max_output_tokens |
| 244 | + |
| 245 | + final_sdk_params = generation_config_params if generation_config_params else None |
| 246 | + |
| 247 | + # TODO: Incorporate system_prompt into user_prompt for Google models |
| 248 | + # Since Google models don't have a direct system prompt parameter, |
| 249 | + # we might need to combine them or use a different approach |
| 250 | + |
| 251 | + try: |
| 252 | + response = self.client.models.generate_content( |
| 253 | + model=actual_model, contents=user_prompt, generation_config=final_sdk_params |
| 254 | + ) |
| 255 | + |
| 256 | + # Check for blocked prompt |
| 257 | + if ( |
| 258 | + hasattr(response, "prompt_feedback") |
| 259 | + and response.prompt_feedback |
| 260 | + and response.prompt_feedback.block_reason |
| 261 | + ): |
| 262 | + logger.warning(f"Google LLM prompt blocked. Reason: {response.prompt_feedback.block_reason}") |
| 263 | + return f"Completion generation failed: Prompt blocked by API (Reason: {response.prompt_feedback.block_reason})" |
| 264 | + |
| 265 | + # Check for empty response |
| 266 | + if not response.text: |
| 267 | + logger.warning(f"Google LLM returned no text. Response: {response}") |
| 268 | + return "Completion generation failed: No text returned by API." |
| 269 | + |
| 270 | + return response.text |
| 271 | + except Exception as e: |
| 272 | + logger.error(f"Error communicating with Google Gen AI API: {e}") |
| 273 | + raise LLMError(f"Error communicating with Google Gen AI API: {e}") from e |
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