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2 Commits
Author SHA1 Message Date
0b140110d8 Make OpenAI-compat and Ollama engine streaming truly async (#626)
The OpenAI-compat and Ollama engines exposed stream()/stream_full() as async def but iterated a synchronous httpx.Client.iter_lines() internally, blocking the single event loop on every inter-token read (serializing concurrent chats; one wedged upstream read froze the whole API). Convert both to a shared AsyncHTTPEngineMixin using httpx.AsyncClient + aiter_lines() with a per-event-loop pooled client and the configured timeout applied; map mid-stream transport errors (RemoteProtocolError/ReadError) to EngineConnectionError via a deliberately narrow set that keeps CancelledError/GeneratorExit propagating; handle non-2xx explicitly (incl. 3xx and a typed EngineContextLengthError for context-window overflow 400s); switch litellm streaming to acompletion; and offload the blocking non-streaming handlers and websocket generate() to asyncio.to_thread. No public API change. Strong MockTransport-based tests, including a pin that the async path never touches the sync client. Complements #618.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-06 14:10:22 -07:00
b39dbedcc4 feat: fix external MCP server integration and add streaming tool-call support
Rebased and cleaned-up version of PR #113 by @mricharz, resolved against
current main (including Codex engine, Gemini thought_signature, and
agent manager fixes merged since the original PR).

MCP Transport & Client:
- StreamableHTTPTransport with session tracking, SSE parsing, timeouts
- MCPClient.initialize() sends proper MCP handshake (protocolVersion,
  capabilities, clientInfo) + notifications/initialized
- Fix StdioTransport constructor: command=[command] + args
- MCPRequest.to_dict() with notification support (id=None)

External MCP Discovery:
- _discover_external_mcp supports both url (HTTP) and command (stdio)
- Per-server include_tools / exclude_tools filtering
- MCP clients persisted on JarvisSystem for runtime lifetime

Streaming Tool-Call Support (stream_full):
- StreamChunk dataclass in _stubs.py (content, tool_calls, finish_reason, usage)
- Default stream_full() on InferenceEngine ABC wraps stream() for backward compat
- _OpenAICompatibleEngine.stream_full() with SSE parsing
- CloudEngine: _stream_full_openai (OpenAI/OpenRouter/MiniMax/Codex routing)
               _stream_full_anthropic (event-based → OpenAI delta format)
- InstrumentedEngine, MultiEngine: stream_full delegation
- GuardrailsEngine: stream_full with post-hoc security scanning (FIXED:
  original PR bypassed output scanning — now accumulates and scans like stream())

Other improvements:
- _prepare_anthropic_messages() extracted to eliminate duplication
- Default tool_choice=auto when tools are provided (OpenAI compat engines)
- MCP tool injection into managed agent streaming path
- Documentation: docs/user-guide/mcp-external-servers.md

Tests: ~59 new tests across 8 test files, all passing.

Closes PR #113

Co-Authored-By: mricharz <mricharz@users.noreply.github.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 18:09:54 +00:00