Text Generation

• DeepSeek-V4-Flash
• DeepSeek-V4-Pro
• Qwen/Qwen3-32B
• openai/gpt-oss-120b

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Core Capabilities

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Use Cases

• Open-ended conversation: Customer support bots, FAQ assistants, and conversational agents.
• Knowledge Q&A: Enterprise knowledge bases, document retrieval, and factual or procedural answers.
• Content generation: Marketing copy, summaries, long-form articles, and creative writing.
• Instruction following: Task decomposition, step-by-step guides, and structured outputs such as lists and tables.

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Message Structure

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Key Parameters

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Description

• Parameters that control creativity
  • temperature: Controls output randomness. The value range is 0.0-2.0, and the recommended range is 0.2-0.8 to balance creativity and stability.
  • top_p: Controls the sampling range. The value range is 0.0-1.0. It can be used together with temperature to adjust creativity and stability.
• Parameters that control output
  • max_completion_tokens: Limits generation length and helps avoid truncated output.
  • stop: Sets stop sequences. Used to control where the model stops generating.
  • frequency_penalty: Repetition penalty. If output is repetitive or garbled, try adjusting this value.
  • stream=True: Returns responses as a stream. Recommended for long responses to reduce timeout risk.
• Context The maximum context length supported by each model can be viewed in Models.

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Recommendations

• If output is garbled, try adjusting temperature, top_p, and frequency_penalty.
• We recommend keeping max_completion_tokens within the maximum context length and leaving room for the input.
• If output is truncated, set a reasonable max_completion_tokens, enable stream=True, and increase the client timeout.

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Billing

• Formula: Total cost = (input tokens x input unit price) + (output tokens x output unit price).
• Pricing: Check the model detail page in Models for each model’s pricing.
• Recommendations:
  • During development, prefer free or lower-cost models.
  • For long responses, use streaming output and set max_completion_tokens appropriately.
  • For high-QPS workloads, combine concurrency control and rate limiting strategies.

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Examples

export API_KEY="YOUR_API_KEY"

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Multi-Turn Conversation

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["API_KEY"],
    base_url="https://api.scitix.ai/model-api",
)

response = client.chat.completions.create(
    model="Qwen/Qwen3-32B",
    messages=[
        {
            "role": "system",
            "content": "You are a helpful assistant. Keep answers concise.",
        },
        {
            "role": "user",
            "content": "What are the main benefits of microservices architecture?",
        },
    ],
    temperature=0.7,
    max_completion_tokens=1024,
)

print(response.choices[0].message.content)

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Data Analysis Content Generation

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["API_KEY"],
    base_url="https://api.scitix.ai/model-api",
)

response = client.chat.completions.create(
    model="MiniMaxAI/MiniMax-M2.7",
    messages=[
        {
            "role": "system",
            "content": "You are a data analysis expert. Output results in Markdown with clear sections and bullet points.",
        },
        {
            "role": "user",
            "content": "Summarize typical patterns in SaaS trial-to-paid conversion by cohort (e.g. by signup week). What metrics and recommendations would you highlight? Keep it under 300 words.",
        },
    ],
    temperature=0.5,
    max_completion_tokens=1024,
)

print(response.choices[0].message.content)

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Release Notes / Changelog

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["API_KEY"],
    base_url="https://api.scitix.ai/model-api",
)

response = client.chat.completions.create(
    model="glm-5.2",
    messages=[
        {
            "role": "system",
            "content": "You write concise release notes. Use a short intro and bullet points.",
        },
        {
            "role": "user",
            "content": "Draft release notes for v2.0 of a CLI tool. New in this version: added `config` and `run` subcommands, support for env-based config, and a `--dry-run` flag. Keep it under 150 words.",
        },
    ],
    temperature=0.5,
    max_completion_tokens=512,
)

print(response.choices[0].message.content)