mirror of
https://github.com/pewdiepie-archdaemon/odysseus.git
synced 2026-06-28 23:52:09 -04:00
nikakhalatiani
927b1f7ecf
Normalize OpenAI-compatible chat URL shapes so base /v1 endpoints route to /v1/chat/completions while already-full chat endpoints remain idempotent. Preserve native local Ollama routing for bare localhost:11434 endpoints, keep localhost:11434/v1 as OpenAI-compatible, and add focused regression coverage for provider detection, chat target URLs, and model listing from /v1. Part of #541.
325 lines
12 KiB
Python
325 lines
12 KiB
Python
"""Regression tests for native Ollama Cloud provider handling."""
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import httpx
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from src import llm_core
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def test_detects_ollama_cloud_native_provider():
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assert llm_core._detect_provider("https://ollama.com/api") == "ollama"
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assert llm_core._detect_provider("https://ollama.com/api/chat") == "ollama"
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def test_detects_bare_local_ollama_as_native_provider():
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assert llm_core._detect_provider("http://localhost:11434") == "ollama"
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assert llm_core._detect_provider("http://127.0.0.1:11434/") == "ollama"
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assert llm_core._detect_provider("http://localhost:11434/v1") == "openai"
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def test_llm_call_posts_native_ollama_payload(monkeypatch):
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seen = {}
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def fake_post(url, headers=None, json=None, timeout=None):
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seen["url"] = url
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seen["headers"] = headers
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seen["json"] = json
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seen["timeout"] = timeout
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request = httpx.Request("POST", url)
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return httpx.Response(
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200,
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request=request,
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json={"message": {"content": "OK"}, "done": True},
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)
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monkeypatch.setattr(llm_core.httpx, "post", fake_post)
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result = llm_core.llm_call(
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"https://ollama.com/api",
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"gpt-oss:120b-test",
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[{"role": "user", "content": "Say OK"}],
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temperature=0.2,
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max_tokens=7,
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headers={"Authorization": "Bearer ollama-key"},
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timeout=11,
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)
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assert result == "OK"
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assert seen["url"] == "https://ollama.com/api/chat"
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assert seen["headers"]["Authorization"] == "Bearer ollama-key"
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assert seen["json"]["stream"] is False
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assert seen["json"]["options"] == {"temperature": 0.2, "num_predict": 7}
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def test_llm_call_posts_bare_local_ollama_to_native_api(monkeypatch):
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seen = {}
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def fake_post(url, headers=None, json=None, timeout=None):
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seen["url"] = url
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seen["json"] = json
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request = httpx.Request("POST", url)
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return httpx.Response(
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200,
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request=request,
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json={"message": {"content": "OK"}, "done": True},
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)
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monkeypatch.setattr(llm_core.httpx, "post", fake_post)
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result = llm_core.llm_call(
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"http://localhost:11434",
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"llama3.2",
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[{"role": "user", "content": "Say OK"}],
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)
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assert result == "OK"
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assert seen["url"] == "http://localhost:11434/api/chat"
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assert seen["json"]["stream"] is False
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def test_openai_compatible_chat_url_shapes(monkeypatch):
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seen = []
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def fake_post(url, headers=None, json=None, timeout=None):
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seen.append(url)
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request = httpx.Request("POST", url)
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return httpx.Response(
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200,
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request=request,
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json={"choices": [{"message": {"content": "OK"}}]},
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)
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monkeypatch.setattr(llm_core.httpx, "post", fake_post)
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llm_core._response_cache.clear()
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cases = [
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("http://localhost:11434/v1", "http://localhost:11434/v1/chat/completions"),
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(
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"http://localhost:11434/v1/chat/completions",
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"http://localhost:11434/v1/chat/completions",
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),
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]
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for i, (base_url, expected_url) in enumerate(cases):
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result = llm_core.llm_call(
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base_url,
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f"openai-compatible-{i}",
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[{"role": "user", "content": f"Say OK {i}"}],
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)
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assert result == "OK"
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assert seen[-1] == expected_url
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def test_list_model_ids_from_openai_compatible_v1(monkeypatch):
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seen = {}
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def fake_get(url, headers=None, timeout=None):
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seen["url"] = url
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request = httpx.Request("GET", url)
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return httpx.Response(
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200,
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request=request,
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json={"data": [{"id": "qwen2.5-coder:7b"}]},
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)
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monkeypatch.setattr(llm_core.httpx, "get", fake_get)
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assert llm_core.list_model_ids("http://localhost:11434/v1") == ["qwen2.5-coder:7b"]
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assert seen["url"] == "http://localhost:11434/v1/models"
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# ---------------------------------------------------------------------------
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# Tool-call argument serialization for native Ollama
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#
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# Odysseus carries assistant tool calls in the OpenAI shape, where
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# `function.arguments` is a JSON *string*. Native Ollama /api/chat expects a
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# JSON *object* and rejects the string form with HTTP 400 ("Value looks like
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# object, but can't find closing '}' symbol"), aborting every follow-up
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# (tool-result) round. _build_ollama_payload must parse it back to an object.
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# ---------------------------------------------------------------------------
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def _assistant_tool_call_msgs():
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"""A canonical OpenAI-style assistant tool call + tool result, as produced by
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agent_loop._append_tool_results (arguments are a JSON string)."""
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return [
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{"role": "user", "content": "what do you know about me?"},
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{
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"role": "assistant",
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"content": None,
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"tool_calls": [
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{
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"id": "call_0",
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"type": "function",
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"function": {"name": "app_api", "arguments": '{"action": "get_memory"}'},
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}
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],
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},
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{"role": "tool", "tool_call_id": "call_0", "content": "Memory: user is James."},
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]
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def test_ollama_payload_parses_string_arguments_to_object():
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payload = llm_core._build_ollama_payload(
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"gpt-oss:120b", _assistant_tool_call_msgs(), temperature=0.0, max_tokens=0,
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)
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asst = payload["messages"][1]
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args = asst["tool_calls"][0]["function"]["arguments"]
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# The whole point: arguments must be a dict, not the JSON string.
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assert args == {"action": "get_memory"}
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assert not isinstance(args, str)
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assert asst["tool_calls"][0]["function"]["name"] == "app_api"
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assert asst["tool_calls"][0]["id"] == "call_0"
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def test_ollama_payload_drops_gemini_thought_signature():
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"""A cross-provider fallback can hand Ollama a tool call that still carries
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Gemini's opaque extra_content; it is meaningless to Ollama and must not leak."""
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msgs = _assistant_tool_call_msgs()
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msgs[1]["tool_calls"][0]["extra_content"] = {"google": {"thought_signature": "AAAA"}}
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payload = llm_core._build_ollama_payload(
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"gpt-oss:120b", msgs, temperature=0.0, max_tokens=0,
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)
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tc = payload["messages"][1]["tool_calls"][0]
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assert "extra_content" not in tc
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assert tc["function"]["arguments"] == {"action": "get_memory"}
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def test_ollama_payload_leaves_plain_messages_untouched():
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msgs = [{"role": "user", "content": "hello"}]
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payload = llm_core._build_ollama_payload("m", msgs, temperature=0.0, max_tokens=0)
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assert payload["messages"][0] == {"role": "user", "content": "hello"}
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def test_ollama_payload_tolerates_malformed_arguments():
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msgs = [{
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"role": "assistant",
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"tool_calls": [{"function": {"name": "x", "arguments": "{not json"}}],
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}]
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payload = llm_core._build_ollama_payload("m", msgs, temperature=0.0, max_tokens=0)
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# Falls back to an empty object rather than raising.
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assert payload["messages"][0]["tool_calls"][0]["function"]["arguments"] == {}
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# ---------------------------------------------------------------------------
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# num_ctx threading (issue #909)
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#
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# Ollama defaults num_ctx to 2048 when the option is omitted, so prompts
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# going to any Ollama backend are silently truncated there regardless of
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# the model's actual capability. The builder must accept a discovered
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# context length and emit options.num_ctx — but only when the value is
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# trusted and larger than 2048.
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# ---------------------------------------------------------------------------
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def test_build_ollama_payload_emits_num_ctx_when_known_and_large():
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"""num_ctx passes through when the caller supplies a trusted value
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larger than Ollama's 2048 default."""
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payload = llm_core._build_ollama_payload(
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"kimi-k2", [{"role": "user", "content": "x"}],
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temperature=0.5, max_tokens=100, num_ctx=131072,
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)
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assert payload["options"]["num_ctx"] == 131072
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def test_build_ollama_payload_emits_num_ctx_for_small_known_models():
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"""A model with a real context smaller than Ollama's 2048 default
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would OOM if Ollama used its own default. Pass the real value."""
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payload = llm_core._build_ollama_payload(
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"tiny-llm", [{"role": "user", "content": "x"}],
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temperature=0.5, max_tokens=100, num_ctx=1024,
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)
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assert payload["options"]["num_ctx"] == 1024
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def test_build_ollama_payload_omits_none_and_zero():
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"""None means the caller didn't look it up; 0 is nonsensical.
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Both should be dropped, not emitted as a 0-context request."""
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for ctx in (None, 0):
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payload = llm_core._build_ollama_payload(
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"m", [{"role": "user", "content": "x"}],
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temperature=0.5, max_tokens=100, num_ctx=ctx,
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)
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assert "num_ctx" not in payload.get("options", {}), (
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f"num_ctx={ctx} should not be emitted"
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)
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def test_build_ollama_payload_omits_default_context_fallback():
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"""get_context_length returns DEFAULT_CONTEXT (128000) when it can't
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discover the model's actual window. Emitting that as num_ctx would
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lie to Ollama for unknown models, so the builder filters it out."""
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from src.model_context import DEFAULT_CONTEXT
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payload = llm_core._build_ollama_payload(
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"unknown-llm-9001", [{"role": "user", "content": "x"}],
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temperature=0.5, max_tokens=100, num_ctx=DEFAULT_CONTEXT,
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)
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assert "num_ctx" not in payload.get("options", {})
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def test_llm_call_threads_discovered_num_ctx(monkeypatch):
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"""When get_context_length returns a real, large value, it ends up
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in the outgoing Ollama request as options.num_ctx (issue #909)."""
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monkeypatch.setattr(llm_core, "get_context_length",
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lambda url, model: 32768)
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seen = {}
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def fake_post(url, headers=None, json=None, timeout=None):
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seen["json"] = json
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request = httpx.Request("POST", url)
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return httpx.Response(
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200, request=request,
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json={"message": {"content": "OK"}, "done": True},
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)
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monkeypatch.setattr(llm_core.httpx, "post", fake_post)
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llm_core.llm_call(
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"https://ollama.com/api",
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"kimi-k2",
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[{"role": "user", "content": "Say OK"}],
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temperature=0.2,
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max_tokens=7,
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)
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assert seen["json"]["options"]["num_ctx"] == 32768
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def test_stream_llm_threads_discovered_num_ctx(monkeypatch):
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"""stream_llm goes through the same ollama branch and must also
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pass num_ctx through to the streaming request body."""
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import asyncio
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seen = {}
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def spy_build_ollama_payload(*args, **kwargs):
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seen["num_ctx"] = kwargs.get("num_ctx")
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seen["stream"] = kwargs.get("stream")
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return {
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"model": "kimi-k2",
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"messages": [{"role": "user", "content": "x"}],
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"stream": True,
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}
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monkeypatch.setattr(llm_core, "get_context_length",
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lambda url, model: 32768)
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monkeypatch.setattr(llm_core, "_build_ollama_payload",
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spy_build_ollama_payload)
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# Short-circuit before the actual HTTP call: host is "dead" → yields
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# an error SSE chunk and returns. The call to _build_ollama_payload
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# still happens before the host check, so we can inspect it.
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monkeypatch.setattr(llm_core, "_is_host_dead", lambda url: True)
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async def collect():
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return [chunk async for chunk in llm_core.stream_llm(
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"https://ollama.com/api",
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"kimi-k2",
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[{"role": "user", "content": "Say OK"}],
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temperature=0.2,
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max_tokens=7,
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)]
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out = asyncio.run(collect())
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assert seen["num_ctx"] == 32768
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assert seen["stream"] is True
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assert out # we got the SSE error chunk
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