Model Constants

from synkro.models import OpenAI, Anthropic, Google, Local, LocalModel

from synkro.models import OpenAI

# GPT-5 Series (Latest)
OpenAI.GPT_52        # "gpt-5.2" - Flagship: human-like dialogue, agentic tool-calling
OpenAI.GPT_5_MINI    # "gpt-5-mini" - Balanced cost and intelligence, primary workhorse
OpenAI.GPT_5_NANO    # "gpt-5-nano" - Extremely low latency, high-volume basic tasks

# GPT-4 Series (Legacy)
OpenAI.GPT_41        # "gpt-4.1" - Legacy flagship
OpenAI.GPT_4O        # "gpt-4o"
OpenAI.GPT_4O_MINI   # "gpt-4o-mini"

# Reasoning Models
OpenAI.O3            # "o3" - Advanced reasoning
OpenAI.O3_MINI       # "o3-mini" - Compact reasoning
OpenAI.O1            # "o1" - Original reasoning
OpenAI.O1_MINI       # "o1-mini" - Compact original reasoning

from synkro import create_pipeline
from synkro.models import OpenAI

pipeline = create_pipeline(
    model=OpenAI.GPT_5_MINI,      # Generation
    grading_model=OpenAI.GPT_52,  # Verification (use stronger model)
)

from synkro.models import Anthropic

# Claude 4.5 (Latest)
Anthropic.CLAUDE_45_OPUS    # Premium: State-of-the-art for coding and agents
Anthropic.CLAUDE_45_SONNET  # Standard: Default model, faster and context-aware
Anthropic.CLAUDE_45_HAIKU   # Light: High-speed, cost-effective

# Claude 4 (Previous Gen)
Anthropic.CLAUDE_4_SONNET   # "claude-sonnet-4-20250514"
Anthropic.CLAUDE_4_OPUS     # "claude-opus-4-20250514"

# Claude 3.5 (Legacy)
Anthropic.CLAUDE_35_SONNET  # "claude-3-5-sonnet-20241022"
Anthropic.CLAUDE_35_HAIKU   # "claude-3-5-haiku-20241022"

from synkro import create_pipeline
from synkro.models import Anthropic

pipeline = create_pipeline(
    model=Anthropic.CLAUDE_45_SONNET,
    grading_model=Anthropic.CLAUDE_45_OPUS,
)

from synkro.models import Google

# Gemini 3 (Latest)
Google.GEMINI_3_PRO    # "gemini/gemini-3-pro"
Google.GEMINI_3_FLASH  # "gemini/gemini-3-flash"

# Gemini 2.5
Google.GEMINI_25_PRO   # "gemini/gemini-2.5-pro"
Google.GEMINI_25_FLASH # "gemini/gemini-2.5-flash"

# Gemini 2
Google.GEMINI_2_FLASH      # "gemini/gemini-2.0-flash"
Google.GEMINI_2_FLASH_LITE # "gemini/gemini-2.0-flash-lite"

from synkro import create_pipeline
from synkro.models import Google

pipeline = create_pipeline(
    model=Google.GEMINI_25_FLASH,
    grading_model=Google.GEMINI_25_PRO,
)

from synkro.models import Local, LocalModel

# Using Local helper
model = Local.llama("llama3.2:latest")
model = Local.mistral("mistral:latest")
model = Local.deepseek("deepseek-r1:8b")

# Direct LocalModel
model = LocalModel("my-custom-model")

from synkro import create_pipeline
from synkro.models import Local

pipeline = create_pipeline(
    model=Local.llama("llama3.2:latest"),
    grading_model=Local.llama("llama3.2:70b"),
    base_url="http://localhost:11434/v1",
)

from synkro import create_pipeline
from synkro.models import LocalModel

pipeline = create_pipeline(
    model=LocalModel("meta-llama/Llama-3.2-8B-Instruct"),
    base_url="http://localhost:8000/v1",
)

from synkro import create_pipeline

# OpenAI-compatible string
pipeline = create_pipeline(model="gpt-4o-mini")

# Any model string
pipeline = create_pipeline(model="custom-model-name")

# OpenAI
export OPENAI_API_KEY="sk-..."

# Anthropic
export ANTHROPIC_API_KEY="sk-ant-..."

# Google
export GOOGLE_API_KEY="..."
# or
export GEMINI_API_KEY="..."

import os
os.environ["OPENAI_API_KEY"] = "sk-..."