mirror of
https://github.com/open-jarvis/OpenJarvis.git
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Jon Saad-FalconandClaude Opus 4.6
301e9cd2d4
Complete implementation across six development phases (v0.1 through v1.0): - Core: Registry system, config, event bus, types (Phase 0) - Intelligence + Inference: Model routing, Ollama/vLLM/llama.cpp/Cloud engines (Phase 1) - Memory: SQLite/FAISS/ColBERT/BM25/Hybrid backends, document ingest, context injection (Phase 2) - Agents: Simple/Orchestrator/Custom/OpenClaw agents, tool system (Phase 3) - Learning: HeuristicRouter, reward functions, GRPO stub, telemetry aggregation (Phase 4) - SDK: Jarvis class, OpenClaw protocol/transport, benchmarks, Docker deployment (Phase 5) 520 tests passing, 8 skipped (optional deps). Ruff lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
103 lines
2.8 KiB
Python
103 lines
2.8 KiB
Python
"""Tests for server Pydantic models."""
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from __future__ import annotations
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import pytest
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pydantic = pytest.importorskip("pydantic")
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from openjarvis.server.models import ( # noqa: E402
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ChatCompletionChunk,
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ChatCompletionRequest,
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ChatCompletionResponse,
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ChatMessage,
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Choice,
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ChoiceMessage,
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DeltaMessage,
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ModelListResponse,
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ModelObject,
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StreamChoice,
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UsageInfo,
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)
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class TestChatCompletionRequest:
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def test_minimal(self):
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req = ChatCompletionRequest(
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model="test-model",
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messages=[ChatMessage(role="user", content="Hello")],
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)
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assert req.model == "test-model"
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assert len(req.messages) == 1
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assert req.temperature == 0.7
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assert req.stream is False
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def test_with_options(self):
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req = ChatCompletionRequest(
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model="test",
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messages=[ChatMessage(role="user", content="Hi")],
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temperature=0.1,
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max_tokens=256,
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stream=True,
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)
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assert req.temperature == 0.1
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assert req.max_tokens == 256
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assert req.stream is True
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class TestChatCompletionResponse:
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def test_defaults(self):
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resp = ChatCompletionResponse(
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model="test",
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choices=[Choice(message=ChoiceMessage(content="Hi"))],
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)
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assert resp.object == "chat.completion"
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assert resp.id.startswith("chatcmpl-")
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assert resp.created > 0
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assert len(resp.choices) == 1
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def test_usage(self):
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resp = ChatCompletionResponse(
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model="test",
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choices=[Choice(message=ChoiceMessage(content="Hi"))],
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usage=UsageInfo(prompt_tokens=5, completion_tokens=3, total_tokens=8),
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)
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assert resp.usage.total_tokens == 8
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class TestChatCompletionChunk:
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def test_defaults(self):
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chunk = ChatCompletionChunk(
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id="test-id",
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model="test",
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choices=[StreamChoice(delta=DeltaMessage(content="Hi"))],
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)
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assert chunk.object == "chat.completion.chunk"
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assert chunk.choices[0].delta.content == "Hi"
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class TestModelListResponse:
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def test_empty(self):
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resp = ModelListResponse()
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assert resp.object == "list"
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assert resp.data == []
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def test_with_models(self):
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resp = ModelListResponse(data=[
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ModelObject(id="model-a"),
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ModelObject(id="model-b"),
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])
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assert len(resp.data) == 2
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assert resp.data[0].id == "model-a"
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assert resp.data[0].object == "model"
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class TestChatMessage:
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def test_user_message(self):
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msg = ChatMessage(role="user", content="Hello")
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assert msg.role == "user"
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def test_with_tool_call_id(self):
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msg = ChatMessage(role="tool", content="result", tool_call_id="abc")
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assert msg.tool_call_id == "abc"
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