feat(ai): implement DeepSeek provider with streaming and reasoning support

tests/test_deepseek_provider.py

@@ -0,0 +1,139 @@
+import pytest
+from unittest.mock import patch, MagicMock
+import ai_client
+
+def test_deepseek_model_selection():
+    """
+    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():
+    """
+    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():
+    """
+    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():
+    """
+    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():
+    """
+    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"