manual_slop/tests/test_deepseek_provider.py

import pytest
from unittest.mock import patch, MagicMock
import ai_client

def test_deepseek_model_selection() -> None:
 """
    Verifies that ai_client.set_provider('deepseek', 'deepseek-chat') correctly updates the internal state.
    """
 ai_client.set_provider("deepseek", "deepseek-chat")
 assert ai_client._provider == "deepseek"
 assert ai_client._model == "deepseek-chat"

def test_deepseek_completion_logic() -> None:
 """
    Verifies that ai_client.send() correctly calls the DeepSeek API and returns content.
    """
 ai_client.set_provider("deepseek", "deepseek-chat")
 with patch("requests.post") as mock_post:
  mock_response = MagicMock()
  mock_response.status_code = 200
  mock_response.json.return_value = {
   "choices": [{
     "message": {"role": "assistant", "content": "DeepSeek Response"},
     "finish_reason": "stop"
    }],
   "usage": {"prompt_tokens": 10, "completion_tokens": 5}
  }
  mock_post.return_value = mock_response
  result = ai_client.send(md_content="Context", user_message="Hello", base_dir=".")
  assert result == "DeepSeek Response"
  assert mock_post.called

def test_deepseek_reasoning_logic() -> None:
 """
    Verifies that reasoning_content is captured and wrapped in <thinking> tags.
    """
 ai_client.set_provider("deepseek", "deepseek-reasoner")
 with patch("requests.post") as mock_post:
  mock_response = MagicMock()
  mock_response.status_code = 200
  mock_response.json.return_value = {
   "choices": [{
     "message": {
      "role": "assistant", 
      "content": "Final Answer", 
      "reasoning_content": "Chain of thought"
     },
     "finish_reason": "stop"
    }],
   "usage": {"prompt_tokens": 10, "completion_tokens": 20}
  }
  mock_post.return_value = mock_response
  result = ai_client.send(md_content="Context", user_message="Reasoning test", base_dir=".")
  assert "<thinking>\nChain of thought\n</thinking>" in result
  assert "Final Answer" in result

def test_deepseek_tool_calling() -> None:
 """
    Verifies that DeepSeek provider correctly identifies and executes tool calls.
    """
 ai_client.set_provider("deepseek", "deepseek-chat")
 with patch("requests.post") as mock_post, \
 patch("mcp_client.dispatch") as mock_dispatch:
 # 1. Mock first response with a tool call
  mock_resp1 = MagicMock()
  mock_resp1.status_code = 200
  mock_resp1.json.return_value = {
   "choices": [{
     "message": {
      "role": "assistant", 
      "content": "Let me read that file.",
      "tool_calls": [{
        "id": "call_123",
        "type": "function",
        "function": {
         "name": "read_file",
         "arguments": '{"path": "test.txt"}'
        }
       }]
     },
     "finish_reason": "tool_calls"
    }],
   "usage": {"prompt_tokens": 50, "completion_tokens": 10}
  }
  # 2. Mock second response (final answer)
  mock_resp2 = MagicMock()
  mock_resp2.status_code = 200
  mock_resp2.json.return_value = {
   "choices": [{
     "message": {
      "role": "assistant", 
      "content": "File content is: Hello World"
     },
     "finish_reason": "stop"
    }],
   "usage": {"prompt_tokens": 100, "completion_tokens": 20}
  }
  mock_post.side_effect = [mock_resp1, mock_resp2]
  mock_dispatch.return_value = "Hello World"
  result = ai_client.send(md_content="Context", user_message="Read test.txt", base_dir=".")
  assert "File content is: Hello World" in result
  assert mock_dispatch.called
  assert mock_dispatch.call_args[0][0] == "read_file"
  assert mock_dispatch.call_args[0][1] == {"path": "test.txt"}

def test_deepseek_streaming() -> None:
 """
    Verifies that DeepSeek provider correctly aggregates streaming chunks.
    """
 ai_client.set_provider("deepseek", "deepseek-chat")
 with patch("requests.post") as mock_post:
 # Mock a streaming response
  mock_response = MagicMock()
  mock_response.status_code = 200
  # Simulate OpenAI-style server-sent events (SSE) for streaming
  # Each line starts with 'data: ' and contains a JSON object
  chunks = [
   'data: {"choices": [{"delta": {"role": "assistant", "content": "Hello"}, "index": 0, "finish_reason": null}]}',
   'data: {"choices": [{"delta": {"content": " World"}, "index": 0, "finish_reason": null}]}',
   'data: {"choices": [{"delta": {}, "index": 0, "finish_reason": "stop"}]}',
   'data: [DONE]'
  ]
  mock_response.iter_lines.return_value = [c.encode('utf-8') for c in chunks]
  mock_post.return_value = mock_response
  result = ai_client.send(md_content="Context", user_message="Stream test", base_dir=".", stream=True)
  assert result == "Hello World"