chore: initial commit (sources + docs, ignore build artifacts and secrets)

mulit_agent/tests/test_image_attachments.py

@@ -0,0 +1,94 @@
+import base64
+import json
+
+import pytest
+
+from mulit_agent_app.domain.attachments import TaskAttachment
+from mulit_agent_app.infrastructure.controller_session import ControllerSession
+from mulit_agent_app.infrastructure.openai_compatible_provider import OpenAICompatibleProvider
+from mulit_agent_app.infrastructure.provider_factory import AnthropicProvider, GeminiProvider
+
+
+def image(media_type="image/png"):
+    return {"name": "sample.png", "media_type": media_type, "data_url": f"data:{media_type};base64,{base64.b64encode(b'image').decode()}"}
+
+
+def test_session_rejects_malformed_excessive_and_oversized_attachments():
+    with pytest.raises((TypeError, ValueError)):
+        ControllerSession._validated_attachments([{"name": "x"}])
+    with pytest.raises((TypeError, ValueError)):
+        ControllerSession._validated_attachments([image()] * 11)
+    huge = base64.b64encode(b"x" * (12 * 1024 * 1024 + 1)).decode()
+    with pytest.raises((TypeError, ValueError)):
+        ControllerSession._validated_attachments([{**image(), "data_url": f"data:image/png;base64,{huge}"}])
+
+
+class Credentials:
+    def load_llm_api_key(self):
+        return "test-key"
+
+
+class Response:
+    def __enter__(self): return self
+    def __exit__(self, *_): return False
+    def read(self): return json.dumps({"choices": [{"message": {"content": "ok"}}], "content": [{"text": "ok"}], "candidates": [{"content": {"parts": [{"text": "ok"}]}}]}).encode()
+
+
+def test_provider_image_payloads(monkeypatch):
+    captured = []
+    def fake_urlopen(request, timeout):
+        captured.append(json.loads(request.data.decode()))
+        return Response()
+    monkeypatch.setattr("mulit_agent_app.infrastructure.openai_compatible_provider.urlopen", fake_urlopen)
+    monkeypatch.setattr("mulit_agent_app.infrastructure.provider_factory.urlopen", fake_urlopen)
+    attachment = TaskAttachment("sample.png", "image/png", image()["data_url"])
+    assert OpenAICompatibleProvider("https://example/v1", "model", Credentials()).generate("look", (attachment,)) == "ok"
+    assert AnthropicProvider("https://example", "model", Credentials()).generate("look", (attachment,)) == "ok"
+    assert GeminiProvider("https://example", "model", Credentials()).generate("look", (attachment,)) == "ok"
+    assert captured[0]["messages"][0]["content"][1]["type"] == "image_url"
+    assert captured[1]["messages"][0]["content"][1]["source"]["type"] == "base64"
+    assert captured[2]["contents"][0]["parts"][1]["inline_data"]["mime_type"] == "image/png"
+
+
+def test_anthropic_and_gemini_complete_local_tool_calls(monkeypatch):
+    responses = {
+        "anthropic": [
+            {"content": [{"type": "tool_use", "id": "anthropic-call", "input": {"command": "Write-Output anth"}}]},
+            {"content": [{"type": "text", "text": "Anthropic 已执行。"}]},
+        ],
+        "gemini": [
+            {"candidates": [{"content": {"parts": [{"functionCall": {"name": "run_powershell", "args": {"command": "Write-Output gem"}}}]}}]},
+            {"candidates": [{"content": {"parts": [{"text": "Gemini 已执行。"}]}}]},
+        ],
+    }
+    captured: list[dict[str, object]] = []
+
+    class ToolResponse:
+        def __init__(self, payload):
+            self.payload = payload
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *_):
+            return False
+
+        def read(self):
+            return json.dumps(self.payload).encode()
+
+    def fake_urlopen(request, timeout):
+        body = json.loads(request.data.decode())
+        captured.append(body)
+        provider = "anthropic" if request.full_url.endswith("/messages") else "gemini"
+        return ToolResponse(responses[provider].pop(0))
+
+    monkeypatch.setattr("mulit_agent_app.infrastructure.provider_factory.urlopen", fake_urlopen)
+    invoked: list[str] = []
+    anthropic = AnthropicProvider("https://example", "model", Credentials())
+    gemini = GeminiProvider("https://example", "model", Credentials())
+
+    assert anthropic.generate("执行", tool_executor=lambda command: invoked.append(command) or "已执行") == "Anthropic 已执行。"
+    assert gemini.generate("执行", tool_executor=lambda command: invoked.append(command) or "已执行") == "Gemini 已执行。"
+    assert invoked == ["Write-Output anth", "Write-Output gem"]
+    assert captured[0]["tools"]
+    assert captured[2]["tools"]