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"""
Standalone model inference and client management for AnyCoder Backend API.
No Gradio dependencies - works with FastAPI/backend only.
"""
import os
from typing import Optional
from openai import OpenAI
from mistralai import Mistral
# Import genai for Gemini (legacy - no longer used with Poe API)
try:
from google import genai
from google.genai import types
GEMINI_AVAILABLE = True
except ImportError:
GEMINI_AVAILABLE = False
def get_inference_client(model_id: str, provider: str = "auto"):
"""
Return an appropriate client based on model_id.
Returns OpenAI-compatible client for all models or raises error if not configured.
"""
if model_id == "gemini-3.0-pro":
# Use Poe (OpenAI-compatible) client for Gemini 3.0 Pro
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "qwen3-30b-a3b-instruct-2507":
# Use DashScope OpenAI client
return OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
elif model_id == "qwen3-30b-a3b-thinking-2507":
# Use DashScope OpenAI client for Thinking model
return OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
elif model_id == "qwen3-coder-30b-a3b-instruct":
# Use DashScope OpenAI client for Coder model
return OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
elif model_id == "gpt-5":
# Use Poe (OpenAI-compatible) client for GPT-5 model
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "gpt-5.1":
# Use Poe (OpenAI-compatible) client for GPT-5.1 model
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "gpt-5.1-instant":
# Use Poe (OpenAI-compatible) client for GPT-5.1 Instant model
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "gpt-5.1-codex":
# Use Poe (OpenAI-compatible) client for GPT-5.1 Codex model
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "gpt-5.1-codex-mini":
# Use Poe (OpenAI-compatible) client for GPT-5.1 Codex Mini model
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "grok-4":
# Use Poe (OpenAI-compatible) client for Grok-4 model
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "Grok-Code-Fast-1":
# Use Poe (OpenAI-compatible) client for Grok-Code-Fast-1 model
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "claude-opus-4.1":
# Use Poe (OpenAI-compatible) client for Claude-Opus-4.1
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "claude-sonnet-4.5":
# Use Poe (OpenAI-compatible) client for Claude-Sonnet-4.5
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "claude-haiku-4.5":
# Use Poe (OpenAI-compatible) client for Claude-Haiku-4.5
return OpenAI(
api_key=os.getenv("POE_API_KEY"),
base_url="https://api.poe.com/v1"
)
elif model_id == "qwen3-max-preview":
# Use DashScope International OpenAI client for Qwen3 Max Preview
return OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
elif model_id.startswith("openrouter/"):
# OpenRouter models
return OpenAI(
api_key=os.getenv("OPENROUTER_API_KEY"),
base_url="https://openrouter.ai/api/v1",
)
elif model_id == "MiniMaxAI/MiniMax-M2":
# Use HuggingFace Router with Novita provider for MiniMax M2 model
return OpenAI(
base_url="https://router.huggingface.co/v1",
api_key=os.getenv("HF_TOKEN"),
default_headers={"X-HF-Bill-To": "huggingface"}
)
elif model_id == "step-3":
# Use StepFun API client for Step-3 model
return OpenAI(
api_key=os.getenv("STEP_API_KEY"),
base_url="https://api.stepfun.com/v1"
)
elif model_id == "codestral-2508" or model_id == "mistral-medium-2508":
# Use Mistral client for Mistral models
return Mistral(api_key=os.getenv("MISTRAL_API_KEY"))
elif model_id == "gemini-2.5-flash":
# Use Google Gemini (OpenAI-compatible) client
return OpenAI(
api_key=os.getenv("GEMINI_API_KEY"),
base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)
elif model_id == "gemini-2.5-pro":
# Use Google Gemini Pro (OpenAI-compatible) client
return OpenAI(
api_key=os.getenv("GEMINI_API_KEY"),
base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)
elif model_id == "gemini-flash-latest":
# Use Google Gemini Flash Latest (OpenAI-compatible) client
return OpenAI(
api_key=os.getenv("GEMINI_API_KEY"),
base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)
elif model_id == "gemini-flash-lite-latest":
# Use Google Gemini Flash Lite Latest (OpenAI-compatible) client
return OpenAI(
api_key=os.getenv("GEMINI_API_KEY"),
base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)
elif model_id == "kimi-k2-turbo-preview":
# Use Moonshot AI (OpenAI-compatible) client for Kimi K2 Turbo (Preview)
return OpenAI(
api_key=os.getenv("MOONSHOT_API_KEY"),
base_url="https://api.moonshot.ai/v1",
)
elif model_id == "moonshotai/Kimi-K2-Thinking":
# Use HuggingFace Router with Novita provider
return OpenAI(
base_url="https://router.huggingface.co/v1",
api_key=os.getenv("HF_TOKEN"),
default_headers={"X-HF-Bill-To": "huggingface"}
)
elif model_id == "moonshotai/Kimi-K2-Instruct":
# Use HuggingFace Router with Groq provider
return OpenAI(
base_url="https://router.huggingface.co/v1",
api_key=os.getenv("HF_TOKEN"),
default_headers={"X-HF-Bill-To": "huggingface"}
)
elif model_id.startswith("deepseek-ai/"):
# DeepSeek models via HuggingFace Router with Novita provider
return OpenAI(
base_url="https://router.huggingface.co/v1",
api_key=os.getenv("HF_TOKEN"),
default_headers={"X-HF-Bill-To": "huggingface"}
)
elif model_id.startswith("zai-org/GLM-4"):
# GLM models via HuggingFace Router
return OpenAI(
base_url="https://router.huggingface.co/v1",
api_key=os.getenv("HF_TOKEN"),
default_headers={"X-HF-Bill-To": "huggingface"}
)
elif model_id == "stealth-model-1":
# Use stealth model with generic configuration
api_key = os.getenv("STEALTH_MODEL_1_API_KEY")
if not api_key:
raise ValueError("STEALTH_MODEL_1_API_KEY environment variable is required")
base_url = os.getenv("STEALTH_MODEL_1_BASE_URL")
if not base_url:
raise ValueError("STEALTH_MODEL_1_BASE_URL environment variable is required")
return OpenAI(
api_key=api_key,
base_url=base_url,
)
else:
# Unknown model - try HuggingFace Inference API
return OpenAI(
base_url="https://api-inference.huggingface.co/v1",
api_key=os.getenv("HF_TOKEN")
)
def get_real_model_id(model_id: str) -> str:
"""Get the real model ID with provider suffixes if needed"""
if model_id == "stealth-model-1":
# Get the real model ID from environment variable
real_model_id = os.getenv("STEALTH_MODEL_1_ID")
if not real_model_id:
raise ValueError("STEALTH_MODEL_1_ID environment variable is required")
return real_model_id
elif model_id == "zai-org/GLM-4.6":
# GLM-4.6 requires provider suffix in model string for API calls
return "zai-org/GLM-4.6:zai-org"
elif model_id == "MiniMaxAI/MiniMax-M2":
# MiniMax M2 needs Novita provider suffix
return "MiniMaxAI/MiniMax-M2:novita"
elif model_id == "moonshotai/Kimi-K2-Thinking":
# Kimi K2 Thinking needs Novita provider
return "moonshotai/Kimi-K2-Thinking:novita"
elif model_id == "moonshotai/Kimi-K2-Instruct":
# Kimi K2 Instruct needs Groq provider
return "moonshotai/Kimi-K2-Instruct:groq"
elif model_id.startswith("deepseek-ai/DeepSeek-V3"):
# DeepSeek V3 models need Novita provider
return f"{model_id}:novita"
elif model_id == "zai-org/GLM-4.5":
# GLM-4.5 needs fireworks-ai provider
return "zai-org/GLM-4.5:fireworks-ai"
return model_id
def create_gemini3_messages(messages: list) -> tuple:
"""
Convert OpenAI-style messages to Gemini 3 format.
Returns (contents, tools, config)
"""
if not GEMINI_AVAILABLE:
raise ImportError("google-genai package required for Gemini 3")
contents = []
system_prompt = None
for msg in messages:
if msg['role'] == 'system':
system_prompt = msg['content']
elif msg['role'] in ['user', 'assistant']:
contents.append(
types.Content(
role="user" if msg['role'] == 'user' else "model",
parts=[types.Part.from_text(text=msg['content'])]
)
)
# Add system prompt as first user message if exists
if system_prompt:
contents.insert(0, types.Content(
role="user",
parts=[types.Part.from_text(text=f"System instructions: {system_prompt}")]
))
# Configure tools and thinking
tools = [types.Tool(googleSearch=types.GoogleSearch())]
config = types.GenerateContentConfig(
thinkingConfig=types.ThinkingConfig(thinkingLevel="HIGH"),
tools=tools,
max_output_tokens=16384
)
return contents, config
def is_native_sdk_model(model_id: str) -> bool:
"""Check if model uses native SDK (not OpenAI-compatible)"""
return False # All models now use OpenAI-compatible APIs
def is_mistral_model(model_id: str) -> bool:
"""Check if model uses Mistral SDK"""
return model_id in ["codestral-2508", "mistral-medium-2508"]
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