"jf %SrSSKJr SSKJrJrJr SSKJrJ r J r J r SSK r SSK r SSKJrJrJr SSKJr SS KJr SS KJrJrJrJrJrJrJrJrJrJ r SS K!J"r" \(a SS KJ#r#J$r$J%r%J&r& S r'"SS\5r("SS\5r)"SS\5r*\"SS9"SS\55r+\"SS9"SS\55r,\"SS9"SS\55r-\"SS9"SS\ 55r.\ R^"\ \0\)S45r1S\2S'\ R^"\*5r3S \2S!'S4S"jr4S5S#jr5S6S$jr6S7S%jr7\4\S&'\5\S&'\6\S&'\7\S&'S'\S('S)\S*'S+\S,'S-\S.'S'\\+'S)\\,'S+\\-'S-\\.'S8S/jr8S9S0jr9S:S1jr:SS2.S;S3jjr;g)>tyyIN '?n`m nnr.c[U[5(aU$[RUR5n[ U[USS9$NrD)rirF)rJrerrrirrvalidated_contents r/!_narrow_native_tool_search_returnr|s>$233 6FFt||T 'AK\hu vvr.c[U[5(aU$[RUR5n[ U[USS9$r)rJrzrrrCrrs r/_narrow_tool_search_callrs<$*++ .>>tyyIN '9Zg hhr.c[U[5(aU$[RUR5n[ U[USS9$r)rJrrrrirrs r/_narrow_tool_search_returnrs>$,-- 6FFt||T ';EVbo ppr.rDzbuiltin-tool-search-call)zbuiltin-tool-callrDzbuiltin-tool-search-return)zbuiltin-tool-returnrDztool-search-call)z tool-callrDztool-search-return)z tool-returnrDcJU(a [XS9$[UUS[5S9$)uBuild a split-off `ModelResponse` carrying a subset of `original`'s parts. `first=True` keeps the original's identity-level metadata (provider response id, usage, etc.). `first=False` blanks `provider_response_id` and zeroes `usage` so downstream consumers don't double-count usage or find two responses for one API call. Other contextual fields (model name, provider name, timestamp) carry over unchanged — they're informational on a synthetic split. partsN)rprovider_response_idusage)rr)originalrfirsts r/_split_responsers- x-- !n  r.c>[URURS9$)zTranslate a server-side tool-search call to a local function-tool call. Preserves `tool_call_id` so the matching return part links up; drops `provider_*` because the local-shape part is provider-agnostic. )rC tool_call_id)rzrCrrs r/!synthesize_local_from_native_callrs!  YY&& r.c[URURURURUR S9$)aTranslate a server-side tool-search return to a local function-tool return. Preserves `tool_call_id`, `content` (the typed [`ToolSearchReturnContent`][pydantic_ai.messages.ToolSearchReturnContent]), and `metadata`; drops `provider_*` because the local-shape part is provider-agnostic. )rirmetadata timestampoutcome)rrirrrrrs r/#synthesize_local_from_native_returnrs6  &&..  r.)target_provider_namec ^/nSnUGHn[U[R5(Ga:/nSnSnURHn[U[5(a1UbUR U:waUR [U55 SnMI[U[5(amUbUR U:waZU(a UR [XEU(+S95 SnUR [R"[U5/S95 /nSnMUR U5 M U(a-SnU(a!UR [XEU(+S95 GMGGMJUR U5 GM^[U[R5(Ga[SUR55(dUR U5 GMSn /n URHn[U[5(ae[U[5(dPURS:Xa@[R "U5n [U [5(aU R U 5 Sn M}U R U5 M U (aSnUR [#XJS95 GMyUR U5 GM[%U5 GM U(aU$U$)uLTranslate any `NativeToolSearch*Part` instances in the message history into local equivalents. Returns a new list with translated copies of any messages that contain `NativeToolSearch*Part`s from a provider other than `target_provider_name`; messages without such parts are returned unchanged (no copy). Passing no target translates every native part, which is suitable for adapters without native tool search. A native-capable adapter passes its provider name so its own parts retain their exact replay shape while foreign parts take the provider-agnostic path. A native server-side tool-search exchange is a single `ModelResponse` carrying both `NativeToolSearchCallPart` (the call) and `NativeToolSearchReturnPart` (the inline server-side result). Local function-tool execution shapes the same exchange as a pair of messages — `ModelResponse(parts=[ToolSearchCallPart(...)])` followed by `ModelRequest(parts=[ToolSearchReturnPart(...)])` — because the model produces the call and the framework produces the return in a separate request turn. Each `NativeToolSearchReturnPart` acts as a flush boundary when splitting: parts before it (text, the search call itself) become a `ModelResponse`, the return becomes a `ModelRequest`, and any parts after it (downstream tool calls, more text) become a fresh `ModelResponse`. This preserves the natural turn order — e.g. a native turn `[Text, SearchCall, SearchReturn, ToolCall(weather)]` translates to four messages where the weather call sits on its own response after the search return, matching what the model would have emitted across two turns on a non-native provider. Identity-level metadata (`provider_response_id`, `usage`) is kept on the first split response only; subsequent splits get blank/zero values so downstream consumers don't double-count usage or treat one API call as two distinct responses. 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