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https://github.com/Memo-2023/mana-monorepo.git
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e757470cb0
Extends the chat-completions surface so callers can ask any provider to call named functions and get structured tool_calls back. Wired through all three provider adapters so the planner and companion can switch off the fragile JSON-parsing pathway. - Request: tools[], tool_choice, assistant tool_calls, tool-role messages with tool_call_id. - Response: MessageResponse.tool_calls, Choice.finish_reason adds "tool_calls", DeltaContent streams tool_calls. - Google provider: Tool(function_declarations=...) build, result normalised (args dict → JSON string), function_response parts on a user turn for tool-role messages. - OpenAI-compat: 1:1 passthrough of the OpenAI spec. - Ollama: /api/chat passthrough; model-level capability check via a TOOL_CAPABLE_OLLAMA_PATTERNS whitelist (llama3.1+, qwen2.5+, mistral, command-r, …) — unsupported models rejected rather than silently falling back to prose. - Router: model_supports_tools() check upfront for both streaming and non-streaming paths; ProviderCapabilityError bubbles as 400. No silent downgrade. Missing tool support = explicit error. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
47 lines
886 B
Python
47 lines
886 B
Python
"""Pydantic models for OpenAI-compatible API."""
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from .requests import (
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ChatCompletionRequest,
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EmbeddingRequest,
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FunctionSpec,
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Message,
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ToolChoice,
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ToolSpec,
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)
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from .responses import (
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ChatCompletionResponse,
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ChatCompletionStreamResponse,
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Choice,
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DeltaContent,
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EmbeddingData,
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EmbeddingResponse,
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MessageResponse,
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ModelInfo,
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ModelsResponse,
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StreamChoice,
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ToolCall,
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ToolCallFunction,
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Usage,
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)
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__all__ = [
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"ChatCompletionRequest",
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"ChatCompletionResponse",
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"ChatCompletionStreamResponse",
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"Choice",
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"DeltaContent",
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"EmbeddingData",
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"EmbeddingRequest",
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"EmbeddingResponse",
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"FunctionSpec",
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"Message",
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"MessageResponse",
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"ModelInfo",
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"ModelsResponse",
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"StreamChoice",
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"ToolCall",
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"ToolCallFunction",
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"ToolChoice",
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"ToolSpec",
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"Usage",
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]
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