Language Models

SAGEA's language models provide advanced reasoning capabilities with contextual memory and multilingual support for natural conversations and complex problem-solving.

Overview

Our language models are designed for real-world applications requiring sophisticated understanding, reasoning, and generation capabilities across multiple languages and domains.

Key Capabilities

🧠 Advanced Reasoning

Complex logical reasoning and problem-solving capabilities

💭 Contextual Memory

Maintains conversation context across long interactions

🌍 Multilingual

Native support for diverse languages and dialects

🎯 Domain Adaptation

Fine-tune models for specific domains and use cases

Quick Start

import sagea
 
# Initialize chat client
client = sagea.ChatClient(api_key="your-api-key")
 
# Send a message
response = client.chat(
    messages=[
        {"role": "user", "content": "Explain quantum computing"}
    ],
    model="sagea-chat"
)
 
print(response.content)

Available Models

SAGEA-Chat

General-purpose conversational model:

Balanced performance: Optimized for general conversations
Fast response times: Low-latency for real-time applications
Cost-effective: Efficient pricing for high-volume use

SAGEA-Reasoning

Advanced model for complex reasoning tasks:

Deep analysis: Enhanced logical reasoning capabilities
Problem-solving: Step-by-step solution generation
Research assistance: Academic and technical analysis

Features

Conversation Management

Maintain context across long conversations:

# Start a conversation
conversation = client.start_conversation()
 
# Add messages with maintained context
response1 = conversation.add_message("What is machine learning?")
response2 = conversation.add_message("How does it relate to AI?")
response3 = conversation.add_message("Give me a practical example")

Streaming Responses

Get real-time streaming for better user experience:

for chunk in client.stream_chat(
    messages=[{"role": "user", "content": "Write a story about AI"}],
    model="sagea-chat"
):
    print(chunk.content, end="")

Function Calling

Enable models to call external functions:

response = client.chat(
    messages=[{"role": "user", "content": "What's the weather like?"}],
    functions=[{
        "name": "get_weather",
        "description": "Get current weather",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {"type": "string"}
            }
        }
    }]
)