Copy files from models/deepseek-ai/DeepSeek-V4-Pro-0813

encoding/test_encoding_dsv4.py

@@ -0,0 +1,89 @@
+"""
+Test suite for DeepSeek-V4 Encoding.
+
+Run: python test_encoding_dsv4.py
+"""
+
+import json
+import os
+
+from encoding_dsv4 import encode_messages, parse_message_from_completion_text
+
+TESTS_DIR = os.path.join(os.path.dirname(__file__), "tests")
+
+
+def test_case_1():
+    """Thinking mode with tool calls (multi-turn, tool results merged into user)."""
+    with open(os.path.join(TESTS_DIR, "test_input_1.json")) as f:
+        td = json.load(f)
+        messages = td["messages"]
+        messages[0]["tools"] = td["tools"]
+    gold = open(os.path.join(TESTS_DIR, "test_output_1.txt")).read()
+    prompt = encode_messages(messages, thinking_mode="thinking")
+    assert prompt == gold
+
+    # Parse: assistant turn with tool call
+    marker = "<｜Assistant｜><think>"
+    first_start = prompt.find(marker) + len(marker)
+    first_end = prompt.find("<｜User｜>", first_start)
+    parsed_tc = parse_message_from_completion_text(prompt[first_start:first_end], thinking_mode="thinking")
+    assert parsed_tc["reasoning_content"] == "The user wants to know the weather in Beijing. I should use the get_weather tool."
+    assert parsed_tc["content"] == ""
+    assert len(parsed_tc["tool_calls"]) == 1
+    assert parsed_tc["tool_calls"][0]["function"]["name"] == "get_weather"
+    assert json.loads(parsed_tc["tool_calls"][0]["function"]["arguments"]) == {"location": "Beijing", "unit": "celsius"}
+
+    # Parse: final assistant turn with content
+    last_start = prompt.rfind(marker) + len(marker)
+    parsed_final = parse_message_from_completion_text(prompt[last_start:], thinking_mode="thinking")
+    assert parsed_final["reasoning_content"] == "Got the weather data. Let me format a nice response."
+    assert "22°C" in parsed_final["content"]
+    assert parsed_final["tool_calls"] == []
+
+    print("  [PASS] case 1: thinking with tools (encode + parse)")
+
+
+def test_case_2():
+    """Thinking mode without tools (drop_thinking removes earlier reasoning)."""
+    messages = json.load(open(os.path.join(TESTS_DIR, "test_input_2.json")))
+    gold = open(os.path.join(TESTS_DIR, "test_output_2.txt")).read()
+    prompt = encode_messages(messages, thinking_mode="thinking")
+    assert prompt == gold
+
+    # Parse: last assistant turn
+    marker = "<｜Assistant｜><think>"
+    last_start = prompt.rfind(marker) + len(marker)
+    parsed = parse_message_from_completion_text(prompt[last_start:], thinking_mode="thinking")
+    assert parsed["reasoning_content"] == "The user asks about the capital of France. It is Paris."
+    assert parsed["content"] == "The capital of France is Paris."
+    assert parsed["tool_calls"] == []
+
+    # Verify drop_thinking: first assistant's reasoning should be absent
+    assert "The user said hello" not in prompt
+
+    print("  [PASS] case 2: thinking without tools (encode + parse)")
+
+
+def test_case_3():
+    """Interleaved thinking + search (developer with tools, latest_reminder)."""
+    messages = json.load(open(os.path.join(TESTS_DIR, "test_input_3.json")))
+    gold = open(os.path.join(TESTS_DIR, "test_output_3.txt")).read()
+    assert encode_messages(messages, thinking_mode="thinking") == gold
+    print("  [PASS] case 3: interleaved thinking + search")
+
+
+def test_case_4():
+    """Quick instruction task with latest_reminder (chat mode, action task)."""
+    messages = json.load(open(os.path.join(TESTS_DIR, "test_input_4.json")))
+    gold = open(os.path.join(TESTS_DIR, "test_output_4.txt")).read()
+    assert encode_messages(messages, thinking_mode="chat") == gold
+    print("  [PASS] case 4: quick instruction task")
+
+
+if __name__ == "__main__":
+    print("Running DeepSeek-V4 Encoding Tests...\n")
+    test_case_1()
+    test_case_2()
+    test_case_3()
+    test_case_4()
+    print("\nAll 4 tests passed!")