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"""
AI Client Manager - Unified interface for multiple LLM providers
Supports Anthropic Claude, Google Gemini, and OpenAI
"""
import os
from typing import Optional, Dict, Any, List
from enum import Enum
import anthropic
import google.generativeai as genai
from openai import OpenAI
from src.config import config
class Provider(str, Enum):
"""Supported AI providers"""
ANTHROPIC = "anthropic"
GOOGLE = "google"
OPENAI = "openai"
class AIClient:
"""Unified AI client supporting multiple providers"""
def __init__(self):
"""Initialize all available clients"""
self.anthropic_client: Optional[anthropic.Anthropic] = None
self.google_client: Optional[Any] = None
self.openai_client: Optional[OpenAI] = None
self._initialize_clients()
def _initialize_clients(self):
"""Initialize available AI clients based on API keys"""
# Anthropic Claude - read directly from environment
anthropic_key = os.getenv("ANTHROPIC_API_KEY")
if anthropic_key:
try:
self.anthropic_client = anthropic.Anthropic(api_key=anthropic_key)
print(f"✅ Anthropic client initialized (key: {anthropic_key[:10]}...)")
except Exception as e:
print(f"❌ Failed to initialize Anthropic client: {e}")
else:
print("⚠️ ANTHROPIC_API_KEY not found in environment")
# Google Gemini - read directly from environment
google_key = os.getenv("GOOGLE_API_KEY")
if google_key:
try:
genai.configure(api_key=google_key)
self.google_client = genai
print(f"✅ Google client initialized (key: {google_key[:10]}...)")
except Exception as e:
print(f"❌ Failed to initialize Google client: {e}")
else:
print("⚠️ GOOGLE_API_KEY not found in environment")
# OpenAI - read directly from environment
openai_key = os.getenv("OPENAI_API_KEY")
if openai_key:
try:
self.openai_client = OpenAI(api_key=openai_key)
print(f"✅ OpenAI client initialized (key: {openai_key[:10]}...)")
except Exception as e:
print(f"❌ Failed to initialize OpenAI client: {e}")
else:
print("⚠️ OPENAI_API_KEY not found in environment")
def generate(
self,
prompt: str,
provider: Optional[Provider] = None,
model: Optional[str] = None,
temperature: float = 0.7,
max_tokens: int = 2000,
system_prompt: Optional[str] = None,
) -> str:
"""
Generate text using specified provider
Args:
prompt: User prompt
provider: AI provider to use (defaults to config)
model: Model name (defaults to config)
temperature: Sampling temperature
max_tokens: Maximum tokens to generate
system_prompt: System prompt for context
Returns:
Generated text
"""
# Use defaults from config if not specified
if provider is None:
provider = Provider(config.model.primary_provider)
if model is None:
model = config.model.primary_model
# Route to appropriate provider
if provider == Provider.ANTHROPIC:
return self._generate_anthropic(prompt, model, temperature, max_tokens, system_prompt)
elif provider == Provider.GOOGLE:
return self._generate_google(prompt, model, temperature, max_tokens, system_prompt)
elif provider == Provider.OPENAI:
return self._generate_openai(prompt, model, temperature, max_tokens, system_prompt)
else:
raise ValueError(f"Unsupported provider: {provider}")
def _generate_anthropic(
self,
prompt: str,
model: str,
temperature: float,
max_tokens: int,
system_prompt: Optional[str],
) -> str:
"""Generate using Anthropic Claude"""
if not self.anthropic_client:
# Try to re-initialize from environment
anthropic_key = os.getenv("ANTHROPIC_API_KEY")
if anthropic_key:
print(f"Re-initializing Anthropic client with key: {anthropic_key[:10]}...")
try:
self.anthropic_client = anthropic.Anthropic(api_key=anthropic_key)
print("✅ Anthropic client re-initialized successfully")
except Exception as e:
raise RuntimeError(f"Failed to re-initialize Anthropic client: {e}")
else:
raise RuntimeError("Anthropic client not initialized. Set ANTHROPIC_API_KEY in HF Spaces Secrets.")
messages = [{"role": "user", "content": prompt}]
kwargs = {
"model": model,
"messages": messages,
"temperature": temperature,
"max_tokens": max_tokens,
}
if system_prompt:
kwargs["system"] = system_prompt
try:
response = self.anthropic_client.messages.create(**kwargs)
return response.content[0].text
except Exception as e:
raise RuntimeError(f"Anthropic API error: {e}")
def _generate_google(
self,
prompt: str,
model: str,
temperature: float,
max_tokens: int,
system_prompt: Optional[str],
) -> str:
"""Generate using Google Gemini"""
if not self.google_client:
raise RuntimeError("Google client not initialized")
try:
gemini_model = self.google_client.GenerativeModel(model)
generation_config = {
"temperature": temperature,
"max_output_tokens": max_tokens,
}
# Combine system prompt and user prompt
full_prompt = prompt
if system_prompt:
full_prompt = f"{system_prompt}\n\n{prompt}"
response = gemini_model.generate_content(
full_prompt,
generation_config=generation_config
)
return response.text
except Exception as e:
raise RuntimeError(f"Google API error: {e}")
def _generate_openai(
self,
prompt: str,
model: str,
temperature: float,
max_tokens: int,
system_prompt: Optional[str],
) -> str:
"""Generate using OpenAI"""
if not self.openai_client:
raise RuntimeError("OpenAI client not initialized")
messages = []
if system_prompt:
messages.append({"role": "system", "content": system_prompt})
messages.append({"role": "user", "content": prompt})
try:
response = self.openai_client.chat.completions.create(
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
)
return response.choices[0].message.content
except Exception as e:
raise RuntimeError(f"OpenAI API error: {e}")
def generate_with_memory(
self,
prompt: str,
context: str,
provider: Optional[Provider] = None,
model: Optional[str] = None,
) -> str:
"""
Generate with long context using memory model (Gemini 2.0)
Args:
prompt: User prompt
context: Long context/memory to include
provider: Provider to use (defaults to memory provider)
model: Model to use (defaults to memory model)
Returns:
Generated text
"""
# Use memory provider by default
if provider is None:
provider = Provider(config.model.memory_provider)
if model is None:
model = config.model.memory_model
# Combine context and prompt
full_prompt = f"""# Campaign Context
{context}
# Current Query
{prompt}
Please answer based on the campaign context provided."""
return self.generate(
prompt=full_prompt,
provider=provider,
model=model,
temperature=config.model.balanced_temp,
max_tokens=config.model.max_tokens_memory,
)
def generate_creative(self, prompt: str, system_prompt: Optional[str] = None) -> str:
"""Generate creative content (characters, stories, etc.)"""
return self.generate(
prompt=prompt,
temperature=config.model.creative_temp,
max_tokens=config.model.max_tokens_generation,
system_prompt=system_prompt,
)
def generate_precise(self, prompt: str, system_prompt: Optional[str] = None) -> str:
"""Generate precise content (rules, stats, etc.)"""
return self.generate(
prompt=prompt,
temperature=config.model.precise_temp,
max_tokens=config.model.max_tokens_generation,
system_prompt=system_prompt,
)
def is_available(self, provider: Provider) -> bool:
"""Check if provider is available"""
if provider == Provider.ANTHROPIC:
return self.anthropic_client is not None
elif provider == Provider.GOOGLE:
return self.google_client is not None
elif provider == Provider.OPENAI:
return self.openai_client is not None
return False
# Global client instance
_client: Optional[AIClient] = None
def get_ai_client() -> AIClient:
"""Get or create global AI client instance"""
global _client
if _client is None:
_client = AIClient()
return _client
# Convenience functions
def generate_text(
prompt: str,
temperature: float = 0.7,
max_tokens: int = 2000,
system_prompt: Optional[str] = None,
) -> str:
"""Quick text generation"""
client = get_ai_client()
return client.generate(prompt, temperature=temperature, max_tokens=max_tokens, system_prompt=system_prompt)
def generate_creative_text(prompt: str, system_prompt: Optional[str] = None) -> str:
"""Quick creative text generation"""
client = get_ai_client()
return client.generate_creative(prompt, system_prompt=system_prompt)
def generate_precise_text(prompt: str, system_prompt: Optional[str] = None) -> str:
"""Quick precise text generation"""
client = get_ai_client()
return client.generate_precise(prompt, system_prompt=system_prompt)
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