feat: add MiniMax as first-class LLM provider
- Temperature auto-clamping for MiniMax models: (0, 1] range enforcement - <think> tag handling for MiniMax M2.7 reasoning output (alongside existing <thinking> support) - MiniMax configuration example in mykey_template.py - Updated README.md and GETTING_STARTED.md with MiniMax provider docs - 19 unit tests + 6 integration tests (3 live tests with MINIMAX_API_KEY) MiniMax models (M2.7, M2.7-highspeed, M2.5, M2.5-highspeed) are accessed via the standard OpenAI-compatible interface at https://api.minimax.io/v1, using the existing LLMSession with an 'oai'-prefixed config key.
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tests/test_minimax_integration.py
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tests/test_minimax_integration.py
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"""Integration tests for MiniMax provider support.
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These tests verify end-to-end MiniMax integration by mocking the HTTP layer
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while exercising the full session → stream → parse pipeline.
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To run against a real MiniMax API, set MINIMAX_API_KEY in your environment.
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"""
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import json
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import os
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import sys
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import unittest
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from unittest.mock import patch, MagicMock
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from io import BytesIO
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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def _make_sse_response(chunks, finish_reason="stop"):
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"""Build a mock SSE HTTP response from a list of text chunks."""
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lines = []
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for chunk in chunks:
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data = {
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"choices": [{"delta": {"content": chunk}}],
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}
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lines.append(f"data: {json.dumps(data)}".encode())
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# Final chunk with usage
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usage_data = {
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"choices": [{"delta": {}}],
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"usage": {"prompt_tokens": 100, "completion_tokens": 50,
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"prompt_tokens_details": {"cached_tokens": 0}},
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}
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lines.append(f"data: {json.dumps(usage_data)}".encode())
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lines.append(b"data: [DONE]")
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return lines
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class TestMiniMaxEndToEnd(unittest.TestCase):
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"""End-to-end integration test: LLMSession + ToolClient + MiniMax streaming."""
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def test_full_pipeline_with_think_tag(self):
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"""Full pipeline: LLMSession → _openai_stream → ToolClient parse with <think> tag."""
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from llmcore import LLMSession, ToolClient
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cfg = {
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'apikey': 'test-integration-key',
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'apibase': 'https://api.minimax.io/v1',
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'model': 'MiniMax-M2.7',
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'context_win': 50000,
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}
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session = LLMSession(cfg)
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client = ToolClient(session)
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sse_lines = _make_sse_response([
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"<think>Let me analyze this task step by step.\n",
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"1. First, I need to understand the request.\n",
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"2. Then, execute the appropriate action.</think>\n\n",
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"<summary>Analyzing user request</summary>\n\n",
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"I'll help you with that task.",
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])
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mock_resp = MagicMock()
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mock_resp.status_code = 200
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mock_resp.iter_lines.return_value = iter(sse_lines)
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mock_resp.__enter__ = lambda s: s
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mock_resp.__exit__ = MagicMock(return_value=False)
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with patch('llmcore.requests.post', return_value=mock_resp):
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Help me read a file."},
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]
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gen = client.chat(messages=messages, tools=None)
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chunks = []
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try:
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while True:
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chunks.append(next(gen))
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except StopIteration as e:
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response = e.value
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self.assertIsNotNone(response)
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self.assertIn("analyze this task", response.thinking)
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self.assertIn("help you with that task", response.content)
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# <think> should be stripped from content
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self.assertNotIn("<think>", response.content)
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def test_full_pipeline_with_tool_call(self):
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"""Full pipeline: MiniMax response with tool_use block."""
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from llmcore import LLMSession, ToolClient
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cfg = {
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'apikey': 'test-key',
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'apibase': 'https://api.minimax.io/v1',
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'model': 'MiniMax-M2.7',
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}
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session = LLMSession(cfg)
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client = ToolClient(session)
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sse_lines = _make_sse_response([
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"<think>I need to read the config file.</think>\n\n",
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"<summary>Reading config</summary>\n\n",
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'<tool_use>\n{"name": "file_read", "arguments": {"path": "/etc/config.json"}}\n</tool_use>',
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])
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mock_resp = MagicMock()
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mock_resp.status_code = 200
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mock_resp.iter_lines.return_value = iter(sse_lines)
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mock_resp.__enter__ = lambda s: s
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mock_resp.__exit__ = MagicMock(return_value=False)
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with patch('llmcore.requests.post', return_value=mock_resp):
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messages = [{"role": "user", "content": "Read the config file."}]
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gen = client.chat(messages=messages, tools=None)
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try:
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while True:
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next(gen)
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except StopIteration as e:
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response = e.value
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self.assertEqual(response.thinking, "I need to read the config file.")
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self.assertEqual(len(response.tool_calls), 1)
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self.assertEqual(response.tool_calls[0].function.name, "file_read")
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def test_temperature_enforced_in_request(self):
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"""Verify the actual HTTP request has clamped temperature for MiniMax."""
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from llmcore import LLMSession
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cfg = {
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'apikey': 'test-key',
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'apibase': 'https://api.minimax.io/v1',
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'model': 'MiniMax-M2.7',
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}
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session = LLMSession(cfg)
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captured = {}
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def capture_post(url, headers=None, json=None, stream=None, timeout=None, proxies=None):
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captured['json'] = json
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captured['url'] = url
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resp = MagicMock()
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resp.status_code = 200
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resp.iter_lines.return_value = iter([b'data: [DONE]'])
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resp.__enter__ = lambda s: s
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resp.__exit__ = MagicMock(return_value=False)
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return resp
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with patch('llmcore.requests.post', side_effect=capture_post):
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session.raw_msgs = [{"role": "user", "prompt": "test", "image": None}]
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gen = session.raw_ask(
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[{"role": "user", "content": "test"}],
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model='MiniMax-M2.7',
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temperature=0.0,
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)
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for _ in gen:
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pass
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self.assertAlmostEqual(captured['json']['temperature'], 0.01)
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self.assertIn('api.minimax.io', captured['url'])
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@unittest.skipUnless(
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os.environ.get('MINIMAX_API_KEY'),
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'Set MINIMAX_API_KEY to run live integration tests'
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)
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class TestMiniMaxLive(unittest.TestCase):
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"""Live integration tests against MiniMax API (requires MINIMAX_API_KEY)."""
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def test_live_chat_completion(self):
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"""Send a real chat completion to MiniMax API."""
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from llmcore import LLMSession
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cfg = {
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'apikey': os.environ['MINIMAX_API_KEY'],
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'apibase': 'https://api.minimax.io/v1',
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'model': 'MiniMax-M2.7-highspeed',
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}
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session = LLMSession(cfg)
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messages = [{"role": "user", "content": "Say 'hello' and nothing else."}]
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gen = session.raw_ask(messages, temperature=0.1)
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text = ''
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for chunk in gen:
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text += chunk
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self.assertFalse(text.startswith('Error:'), f"API returned error: {text}")
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self.assertIn('hello', text.lower())
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def test_live_tool_client_pipeline(self):
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"""Full ToolClient pipeline with real MiniMax API."""
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from llmcore import LLMSession, ToolClient
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cfg = {
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'apikey': os.environ['MINIMAX_API_KEY'],
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'apibase': 'https://api.minimax.io/v1',
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'model': 'MiniMax-M2.7-highspeed',
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'context_win': 50000,
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}
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session = LLMSession(cfg)
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client = ToolClient(session)
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messages = [{"role": "user", "content": "What is 2+2? Reply with just the number."}]
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gen = client.chat(messages=messages, tools=None)
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try:
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while True:
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next(gen)
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except StopIteration as e:
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response = e.value
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self.assertIn('4', response.content)
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def test_live_streaming_chunks(self):
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"""Verify streaming works with MiniMax API."""
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from llmcore import LLMSession
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cfg = {
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'apikey': os.environ['MINIMAX_API_KEY'],
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'apibase': 'https://api.minimax.io/v1',
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'model': 'MiniMax-M2.7-highspeed',
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}
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session = LLMSession(cfg)
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session.raw_msgs.append({"role": "user", "prompt": "Count from 1 to 5.", "image": None})
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result = session.ask("Count from 1 to 5.", stream=False)
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self.assertFalse(result.startswith('Error:'), f"API returned error: {result}")
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# Should contain at least some numbers
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for n in ['1', '2', '3']:
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self.assertIn(n, result)
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if __name__ == '__main__':
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unittest.main()
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