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S}SYjjjr4SbSSSSSSSS SSX. S~SZjjjr5SbSSSSSSSS[.SS\jjjr6SbSSSSSSSS[.SS]jjjr7SbSS^jjr8SbSS_jjr9S`r:U=r;$)riAuPPregel manages the runtime behavior for LangGraph applications. ## Overview Pregel combines [**actors**](https://en.wikipedia.org/wiki/Actor_model) and **channels** into a single application. **Actors** read data from channels and write data to channels. Pregel organizes the execution of the application into multiple steps, following the **Pregel Algorithm**/**Bulk Synchronous Parallel** model. Each step consists of three phases: - **Plan**: Determine which **actors** to execute in this step. For example, in the first step, select the **actors** that subscribe to the special **input** channels; in subsequent steps, select the **actors** that subscribe to channels updated in the previous step. - **Execution**: Execute all selected **actors** in parallel, until all complete, or one fails, or a timeout is reached. During this phase, channel updates are invisible to actors until the next step. - **Update**: Update the channels with the values written by the **actors** in this step. Repeat until no **actors** are selected for execution, or a maximum number of steps is reached. ## Actors An **actor** is a `PregelNode`. It subscribes to channels, reads data from them, and writes data to them. It can be thought of as an **actor** in the Pregel algorithm. `PregelNodes` implement LangChain's Runnable interface. ## Channels Channels are used to communicate between actors (`PregelNodes`). Each channel has a value type, an update type, and an update function – which takes a sequence of updates and modifies the stored value. Channels can be used to send data from one chain to another, or to send data from a chain to itself in a future step. LangGraph provides a number of built-in channels: ### Basic channels: LastValue and Topic - `LastValue`: The default channel, stores the last value sent to the channel, useful for input and output values, or for sending data from one step to the next - `Topic`: A configurable PubSub Topic, useful for sending multiple values between *actors*, or for accumulating output. Can be configured to deduplicate values, and/or to accumulate values over the course of multiple steps. ### Advanced channels: Context and BinaryOperatorAggregate - `Context`: exposes the value of a context manager, managing its lifecycle. Useful for accessing external resources that require setup and/or teardown. eg. `client = Context(httpx.Client)` - `BinaryOperatorAggregate`: stores a persistent value, updated by applying a binary operator to the current value and each update sent to the channel, useful for computing aggregates over multiple steps. eg. `total = BinaryOperatorAggregate(int, operator.add)` ## Examples Most users will interact with Pregel via a [StateGraph (Graph API)][langgraph.graph.StateGraph] or via an [entrypoint (Functional API)][langgraph.func.entrypoint]. However, for **advanced** use cases, Pregel can be used directly. If you're not sure whether you need to use Pregel directly, then the answer is probably no - you should use the Graph API or Functional API instead. These are higher-level interfaces that will compile down to Pregel under the hood. Here are some examples to give you a sense of how it works: Example: Single node application ```python from langgraph.channels import EphemeralValue from langgraph.pregel import Pregel, NodeBuilder node1 = ( NodeBuilder().subscribe_only("a") .do(lambda x: x + x) .write_to("b") ) app = Pregel( nodes={"node1": node1}, channels={ "a": EphemeralValue(str), "b": EphemeralValue(str), }, input_channels=["a"], output_channels=["b"], ) app.invoke({"a": "foo"}) ``` ```con {'b': 'foofoo'} ``` Example: Using multiple nodes and multiple output channels ```python from langgraph.channels import LastValue, EphemeralValue from langgraph.pregel import Pregel, NodeBuilder node1 = ( NodeBuilder().subscribe_only("a") .do(lambda x: x + x) .write_to("b") ) node2 = ( NodeBuilder().subscribe_to("b") .do(lambda x: x["b"] + x["b"]) .write_to("c") ) app = Pregel( nodes={"node1": node1, "node2": node2}, channels={ "a": EphemeralValue(str), "b": LastValue(str), "c": EphemeralValue(str), }, input_channels=["a"], output_channels=["b", "c"], ) app.invoke({"a": "foo"}) ``` ```con {'b': 'foofoo', 'c': 'foofoofoofoo'} ``` Example: Using a Topic channel ```python from langgraph.channels import LastValue, EphemeralValue, Topic from langgraph.pregel import Pregel, NodeBuilder node1 = ( NodeBuilder().subscribe_only("a") .do(lambda x: x + x) .write_to("b", "c") ) node2 = ( NodeBuilder().subscribe_only("b") .do(lambda x: x + x) .write_to("c") ) app = Pregel( nodes={"node1": node1, "node2": node2}, channels={ "a": EphemeralValue(str), "b": EphemeralValue(str), "c": Topic(str, accumulate=True), }, input_channels=["a"], output_channels=["c"], ) app.invoke({"a": "foo"}) ``` ```pycon {"c": ["foofoo", "foofoofoofoo"]} ``` Example: Using a BinaryOperatorAggregate channel ```python from langgraph.channels import EphemeralValue, BinaryOperatorAggregate from langgraph.pregel import Pregel, NodeBuilder node1 = ( NodeBuilder().subscribe_only("a") .do(lambda x: x + x) .write_to("b", "c") ) node2 = ( NodeBuilder().subscribe_only("b") .do(lambda x: x + x) .write_to("c") ) def reducer(current, update): if current: return current + " | " + update else: return update app = Pregel( nodes={"node1": node1, "node2": node2}, channels={ "a": EphemeralValue(str), "b": EphemeralValue(str), "c": BinaryOperatorAggregate(str, operator=reducer), }, input_channels=["a"], output_channels=["c"], ) app.invoke({"a": "foo"}) ``` ```con {'c': 'foofoo | foofoofoofoo'} ``` Example: Introducing a cycle This example demonstrates how to introduce a cycle in the graph, by having a chain write to a channel it subscribes to. Execution will continue until a None value is written to the channel. ```python from langgraph.channels import EphemeralValue from langgraph.pregel import Pregel, NodeBuilder, ChannelWriteEntry example_node = ( NodeBuilder() .subscribe_only("value") .do(lambda x: x + x if len(x) < 10 else None) .write_to(ChannelWriteEntry(channel="value", skip_none=True)) ) app = Pregel( nodes={"example_node": example_node}, channels={ "value": EphemeralValue(str), }, input_channels=["value"], output_channels=["value"], ) app.invoke({"value": "a"}) ``` ```con {'value': 'aaaaaaaaaaaaaaaa'} ``` dict[str, PregelNode]nodesz)dict[str, BaseChannel | ManagedValueSpec]rvaluesr stream_modeFr stream_eagerstr | Sequence[str]output_channelsNstr | Sequence[str] | Nonestream_channelsAll | Sequence[str]interrupt_after_nodesinterrupt_before_nodesinput_channels float | None step_timeoutdebugrz checkpointerBaseStore | NonestoreBaseCache | NonecacherzSequence[RetryPolicy]rrrtype[ContextT] | Nonecontext_schemaRunnableConfig | Noneconfig LangGraphrrMapping[str, Sequence[str]]trigger_to_nodesT) auto_validaterrrrrrrrrrrrrrrrc URS[5=n[La4[R"S[SS9 Uc[ [ [U5nUR5VVs0sH.unnU[U[5(aUR5OU_M0 snnUl U=(d 0Ul [UR;a9[UR[[5(d[!S[S35e[["SS9UR['X@lXPlX`lXplXlXlXlXlU bU O [55UlXlXlXl[U[>5(aU4OUUl UUl!UUl"UUl#U=(d 0Ul$UUl%U(aURM5 ggs snnf) N config_typezU`config_type` is deprecated and will be removed. 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Args: namespace: The namespace to filter the subgraphs by. recurse: Whether to recurse into the subgraphs. If `False`, only the immediate subgraphs will be returned. Returns: An iterator of the `(namespace, subgraph)` pairs. Nrrc3D># UHupT[U3U4v M g7fr)rA)rnsrs rr'Pregel.get_subgraphs..s0 %DA!6&!-q1%s rz)rr startswithrrrlenr)rr{r|rgraphrs @rrPregel.get_subgraphss****,JD$$ ++D11*.DNN1%TEu9$+%$+%7z%88 ,$-c$i!mo$>  $)$7$7&/%8% '-&s$A#C*C C!0CC CcH# URXS9H up4X447v M g7f)r~rzN)r)rr{r|rrs rr&Pregel.aget_subgraphss*,,y,RJD* Ss "cUSS:aZURS5(aCURS5nX!S['[USR 55US['ggg)z1Migrate a saved checkpoint to new channel layout.r pending_sendschannel_valueschannel_versionsN)rpoprDmaxr)r checkpointrs r_migrate_checkpointPregel._migrate_checkpointsh c?Q :>>/#B#B(2(GM2?' ( /47-.5575J) *5 1$C rcU(d[0SUSSSSSS9$URUR5 URR SS5S-nUS-n[ UR UR5upx[URUR=(d /URUUURUUSUR[UR[5(a UROSSS9 n [UR!55n UR["R [$S 5n 0n U R'5Hn U R(U ;aMU R([*U R,3nU (a U [.U3nU(d4["S UR["S [$U00nXU R,'M["[0US UR["S [$U00nXR(R3USS 9XR,'M UR=(d /Vs/sHoS [4:XdMUSSPM sn=n(a4[7URU[9S[:U/5/SUR<5 U(aUR(aURHAunnnU[>[@4;aMUU ;aM!U URBREUU45 MC U R'5Vs/sHnURB(dMUPM sn=n(a#[7URUUSUR<5 [GU R'5URU URH5n[[KXpRH5[MS U R'555[OURUR5URURS[OURPUR5U[MUV Vs/sHoRRHnUPM M snn 55$s snfs snfs snn f)Nrrnextrr created_at parent_configtasks interruptssteprr T for_executionrrmanager thread_idrrc3^# UH#oR(aMURv M% g7frwritesrrts rr1Pregel._prepare_state_snapshot..LF"5QXX&!&&"5--ts)*rrrrrr]rr[pending_writesrrrrrrdictrr/r2rrr@idrAr3 get_staterBrYrWr>rr=r?rrrrrurctupler*rr)rrsavedr|apply_pending_writesrstoprmanaged next_tasksr parent_ns task_statestasktask_nsw null_writestidrrrrtasks_with_writesrJs r_prepare_state_snapshotPregel._prepare_state_snapshots "     !1!12~~!!&"-1ax4 MM     (     &B JJ   LL  **d//1DEE!!! &++-. LL&**+CRH AC %%'Dyy ) F8DGG95G&Kxy9#U\\$%7 %D0' (.DGG$/#U\\$%7 %D0'(1';'E'Ed(F( GG$3(<!//525 5a19MEAabE5  ;    !"e["=>%%   E$8$8"11 Q **j(3&&--q!f5 2 %/$5$5$7D$7q188$7DDuD$$htT=R=R+        % %   ($=$= > F*"3"3"5F F u~~ > NN   T " !4!4enn E  !2L!2OOq1O1!2L M  9 "E&Ms5Q  Q  Q$Q!Qc # U(d[0SUSSSSSS9$URUR5 URR SS5S-nUS-n[ UR UR5upx[URUR=(d /URUUURUUSUR[UR[5(a UROSSS9 n UR5V V s0sShvN upX_MN Os sn n fn n n UR[ R ["S 5n 0nU R%5HnUR&U ;aMUR&[(UR*3nU (a U [,U3nU(d4[ S UR[ S ["U00nXUR*'M[ [.US UR[ S ["U00nXR&R1USS 9IShvN XR*'M UR=(d /Vs/sHnUS [2:XdMUSSPM Os snfsn=n(a4[5URU[7S[8U/5/SUR:5 U(aUR(aURHAunnnU[<[>4;aMUU ;aM!U UR@RCUU45 MC U R%5Vs/sHnUR@(dMUPM Os snfsn=n(a#[5URUUSUR:5 [EU R%5URUURF5n[[IXpRF5[KS U R%555[MURUR5URURS[MURNUR5U[KUVVs/sHoRPHnUPM M Os snnfsnn55$7f)Nrrrrrr Trrrrrc3^# UH#oR(aMURv M% g7frrrs rr2Pregel._aprepare_state_snapshot..rrr))rrrrrr]rr[rrrrrrrr&r/r2rrr@rrAr3 aget_staterBrYrWr>rr=r?rrrrrurcrr*rr)rrrr|rrrrrrrgrrrrrrrrrrrrrrJs r_aprepare_state_snapshotPregel._aprepare_state_snapshotUs "     !1!12~~!!&"-1ax4 MM     (     &B JJ   LL  **d//1DEE!!! &-1,?,?,ABBDAQTBB BLL&**+CRH AC %%'Dyy ) F8DGG95G&Kxy9#U\\$%7 %D0' (.DGG$/#U\\$%7 %D0'.7yy-A-L-Ld.M.(( GG$3(<!//525 5a19MEAabE5  ;    !"e["=>%%   E$8$8"11 Q **j(3&&--q!f5 2 %/$5$5$7D$7q188$7DDuD$$htT=R=R+        % %   ($=$= > F*"3"3"5F F u~~ > NN   T " !4!4enn E  !2L!2OOq1O1!2L M  suDRD DD DDDDDR+H.,,RI7- I76B?R5MMC=RQ10Rrct[U5[R[UR5nU(d [ S5eU[R[ S5=n(ad[U[;aS[U5nURUSS9H%upgUR[U[U05US9s $ [ SUS35eUR(a[URU5OUnURSLa?[[U[[ 5n[U[[ [U5005nU[[n [!U [5(d[U 5U[['UR#U5n UR%UU U(aUOS[&U[;S 9$) #Get the current state of the graph.No checkpointer setrTrzr Subgraph not foundNr|r)r(r/rr3rrr2r-rrr,rr)rrr<r get_tuplerr1 rrrr checkpoint_nsrecast_pregelnsrrs rrPregel.get_states4A3H3N3R3R #T%6%64 23 3$D\--.FK KM K%VD\9)-8F!//&$/O ''&v0G/VW'(P !9VHJ!?@@7;{{t{{F3    $c6$<(@ABB" 8:Nr:RSTF4L!56 )S))14YF4L- .&&v.++  $-L4!9!M ,  rc# [U5[R[UR5nU(d [ S5eU[R[ S5=n(aa[U[;aP[U5nURUSS9ShvN upgUR[U[U05US9IShvN s $UR(a[URU5OUnURSLa?[[U[[ 5n[U[[ [U5005nU[[n [!U [5(d[U 5U[['UR#U5IShvN n UR%UU U(aUOS[&U[;S 9IShvN $GN0GN [ SUS35eNKN7f) rrrTrzNrrrr)r(r/rr3rrr2r-r&rr,rr)rrr<r aget_tuplerr1rs rrPregel.aget_states4A3H3N3R3R #T%6%64 23 3$D\--.FK KM K%VD\9)-8F#'#6#6QU#6#V Aia#..&v0G/VW'/8<{{t{{F3    $c6$<(@ABB" 8:Nr:RSTF4L!56 )S))14YF4L- ."--f5522  $-L4!9!M 3   ' A$W !9VHJ!?@@6 s[BG#GG G&G#G CG#G0G#G!G# G G#G#!G#filterbeforelimitc ## [U5nU[R[UR5nU(d [ S5eU[R[ S5=n(an[U[;a][U5nURUSS9H/upU R[U[U05UUUS9ShvN g [ SUS35e[URU[[ U[[U[[5005n[URXXBS 95H!n UR!U RU 5v M# gN7f) z*Get the history of the state of the graph.rrTrzrNrrrrr)r(r/rr3rrr2r-rget_state_historyr,r)rr<rrr) rrrrrrrrrrcheckpoint_tuples rrPregel.get_state_history!siv&39$<3C3C #T%6%64 23 3$D\--.FK KM K%VD\9)-8F!//&$/O !33&v0G/VW!! 4 P!9VHJ!?@@ KK ,m(#fTl;O.P*Q   !%   f5  P! .. '')9 ! +sB?EEBEc &# [U5n[U5[R[UR5nU(d [ S5eU[R[ S5=n(ai[U[;aX[U5nURUSS9ShvN upU R[U[U05UUUS9ShvN n U 7v M[URU[[ U[[U[[5005nURXXBS 9V s/sShvN n U PM NNn g [ SUS35eN Os sn fsn H+n UR!U RU 5IShvN 7v M- g7f) z9Asynchronously get the history of the state of the graph.rrTrzNrrrr)r(r/rr3rrr2r-r&aget_state_historyr,r)rr<ralistr) rrrrrrrrrrstaterrs rrPregel.aget_state_historyTsv&3@3H3N3R3R #T%6%64 23 3$D\--.FK KM K%VD\9)-8F#'#6#6QU#6#V Aia#)#<#<&v0G/VW!! $=$ %  K  KK ,m(#fTl;O.P*Q   (--U.! !  1 A $$W!9VHJ!?@@! !  55 '')9  ! sBF E$D>%E(%F EEEAF/E1E5E 6E9E>EEFEE+FF Fc^^ ^ [U5[R[TR5m T (d [ S5e[ U5S:Xa [ S5e[SU55(a [ S5eU[R[S5=n(af[U[;aU[U5nTRUSS9H'upVUR[U[T 05U5s $ [ S US 35eS U U U4S jjm [U[[U[[505nUH nT "Xx5nM U$) aApply updates to the graph state in bulk. Requires a checkpointer to be set. Args: config: The config to apply the updates to. supersteps: A list of supersteps, each including a list of updates to apply sequentially to a graph state. Each update is a tuple of the form `(values, as_node, task_id)` where `task_id` is optional. Raises: ValueError: If no checkpointer is set or no updates are provided. InvalidUpdateError: If an invalid update is provided. Returns: RunnableConfig: The updated config. rrNo supersteps providedc3># UHn[U5S:Hv M g7frNrrus rr+Pregel.bulk_update_state../Jqs1v{JNo updates providedrTrzrrc >[T/RU5nT-RU5nUbT/RUR5 U(a[ UR5O [ 5nU(aURSR5O0nU(aURRSS5OSn[U[U[R[S505nU(a[X#R[5n[T/RU5upUSSSupU GcU [:XGa[!U5S:a [#S5eUGbG[%UUR&=(d /T/R(UU URUS-US -S T/R*T-SS 9 n UR&=(d /V s/sHn U S[,:XdMU SSPM sn =n(a4[/UU[1S [2U/5/T-R4T/R65 UR&=(d /H?unnnU[8[:4;aMX;aM XR<R?UU45 MA [/UUU RA5T-R4T/R65 T-RCU[EXHU5S US-U(aURRS05O0S.[GUUS55n[IUU(aUR5$S5$U [2:XGab[!U5S:a [#S5e[K[MT/RNU 55=n(Ga [/UU[1S [2U/5/T-R4T/R65 U(a!URRS5bUS-OSnT-RCU[EXHU5SUU(aURRS05O0S.[GUUS55nT-RQUU[S[U[WUS5[2555 [IUU(aUR5$S5$[#ST/RN35eU S:XGa4[!U5S:a [#S5eUc [#S5e[EUSU5nT-RCURX=(d [UR[ZS05USUS-URRS05S.05n[]U [^5(Gaq[!U 5S:Gaa[%UUR&=(d /T/R(UU UUS-US-S T/R*T-SS 9 n [a[^5n[a[^5nU RA5H+nUURbR?URd5 M- U Hun[]U[f5(d[#SUS35eUSSupUU nUU n[!U5nU[!U5:aUUOSnUU R?[iXUS95 Mw T."[IUUR5URA5VVs/sHnUHnUPM M snn5$[IUUR5$[a[J5nUGbUR&Gb[%UUR&T/R(UU URUS-US -S T/R*T-SS 9 n U RA5H+n UU RbR?U Rd5 M- UR&=(d /V s/sHoS[,:XdMU SSPM sn =n(a4[/UU[1S [2U/5/T-R4T/R65 UR&H?unnnU[8[:4;aMX;aM XR<R?UU45 MA U RA5V s/sHn U R<(dMU PM sn =n!(a#[/UUU!T-R4T/R65 /n"[!U5S:XGaQUSupnU c2[!T/R(5S:Xa[kT/R(5Sn OU cn[mSUSRA555(dF[]T/RN[R5(a&T/RNT/R(;a T/RNn ObU c_[oU/4SjUSRq555n#U#(a2[!U#5S:Xa U#SSn OU#SSU#SS:waU#SSn U c [#S 5eU T/R(;a[#S!U S"35eU"R?XU45 OLUHFupnU c [#S#5eU T/R(;a[#S!U S"35eU"R?XU45 MH /n$/n%U"GHWupn&T/R(U Rrn'U'(d[#S!U S$35e[K5n([1S U U([:/5nURU [K55n)U&=(d< U)(aU)Ru5O$[S[U[WUS5[:55nU$R?U5 U%R?U5 [!U'5S:a[wU'6OU'Sn*U*RyU [{UT/RbS%-[|U(R~[U[[[[S/USSUUS-5UU U50S&95 GMZ [U%U$5HUunnUR<V s/sHoS[:wdMU PM n+n U(dM9U+(dMBT-RQUU+U5 MW [/UUU$T-R4T/R65 [EXHUS-5nT-RCUUS US-U(aURRS05O0S.[GXTS55n[U%U$5HMunnUR<V s/sHoS[:XdMU PM sn =n,(dM:T-RQUU,U5 MO [IUU(aUR5$S5$s sn fs snnfs sn fs sn fs sn fs sn f)'Nrrrrrr r1Cannot apply multiple updates when clearing stateTrrrparentssourcerr4Cannot apply multiple updates when updating as inputinputrReceived no input writes for __copy__,Cannot copy checkpoint with multiple updates%Cannot copy a non-existent checkpointforkrInvalid update item:  when copying checkpointras_nodetask_idc3V# UHnUR5HnUv M M! g7fr)r)rvvrs rrFPregel.bulk_update_state..perform_superstep..s*1BYY[(Bs') versions_seenc3># UH4upUTR;dMUR5HnX14v M M6 g7frrrrrseenrrs rrrC/'JGA ?"&A"/'J?"?!Ambiguous update, specify as_nodeNode  does not exist2as_node is required when applying multiple updates has no writers UpdateStaterun_namerC)Gr(rrrrr^r`r6rrr,r2r/r]rrQrrTr[rrrrBrYrWr>get_next_versionrr=r?rrrputr_rkr*rrbr put_writesrrrrr1rrrrrr rranysortedr flat_writerspopleftrinvoker+r9rr;r6r rZrXr'rC)0 input_configupdatesrrrcheckpoint_previous_versionsrcheckpoint_configrrrrrrrrrr next_config input_writes next_stepnext_checkpointtasks_group_by user_group_byritem user_group tasks_group target_idxrlstnode_to_task_idsrr valid_updateslast_seen_by_node run_tasks run_task_idsprovided_task_idrrprepared_task_idsrunchannel_writes push_writesrperform_supersteprs0 rr63Pregel.bulk_update_state..perform_supersteps #4;; =F **62E (()9)9:5: 0 01@P@R @E  !3499;" )6;5>>%%fb1D 2,fTl.>.>0"/! $6v||D?Q$R! 8 ! H&aj!nOF~'S.w>#5#5i#DSU -4"#56  ,5>B %w>#5#5i#D   fd++F a!3',,2  #qq&*"jj%1 $ "J&1%6NBMdBSM * 1 1 3&tyy188A!4!')$99"4"7v=U V#+/r(%27%; &4W&= %(_  *C ,<<( 3!% &g.55'vPWX%!',-,[%..I)6)=)=)?P)?#CDC)?P ,KHH7B%6H  U%9%9%E/((JJLL1H1H"&**!-   $**,A$QVV,33ADD9- $)#7#7#=2#=##=a1AUEAabE#=#;!" )"e["EF$55-- "'!5!5ICAUI.. , O**111a&9 "6 )3(9(9(;H(;1qxxQ(;HH5H " $55-- RTM7|q +21:(?s4::!';#DJJ/2G_S1(9@@B1.. #4#6#6<< //4::="&"5"5_(./'1/'B'H'H'J/)%)01Q6&7&:1&=G.r2159J29Nq9QQ&7&;A&>G?,-PQQ$**,,uWI_-MNN$$gw%?@07,FW0Pdjj005 1QRR!(('7)CD1813I&(L5B1!1**W-::,uWI_-MNN16'GVi[I%5$8$8%'$J!*(&--/U4 4(8#99EF   &##G,47L14D&0'RS*  !%]!:,V]].+W * +$($&$+$&$($($(1H!"!) ' $. &)6C`"%\9!= -1[[!I[aDDL![!I5^^ ++,=~wW "> --%%  +:JJ&**!& 1HDIu~~11)R@r )0=O2P K"%\9!= .2kk"JkqTT\1k"JJ;J ++KgN"> ( uU^^W WRVW WG '\Q:#"IT"J4#KsB9s1 s1 s6 7s< s<3t t0ttt %t rrrzSequence[StateUpdate]rr)r(r/rr3rrrrr2r-rbulk_update_stater,r<r) rr superstepsrrrrcurrent_config supersteprr6s ` @@rr9Pregel.bulk_update_statesn(4A3H3N3R3R #T%6%64 23 3 z?a 56 6 /J/ / /23 3$D\--.FK KM K%VD\9)-8F!//&$/O //&v0G/VWP !9VHJ!?@@[ X([ X3H[ X [ X[ Xz , )3vd|

# UHn[U5S:Hv M g7frrrs rr,Pregel.abulk_update_state..{rrrrTrzNrrc># [T/RU5nT.RU5IShvN nUbT/RUR5 U(a[ UR5O [ 5nU(aURSR5O0nU(aURRSS5OSn[U[U[R[S505nU(a[X#R[5n[T/RU5upUSSSupU GcU [:XGa[!U5S:a [#S5eUGbG[%UUR&=(d /T/R(UU URUS-US -S T/R*T.SS 9 n UR&=(d /V s/sHn U S[,:XdMU SSPM sn =n(a4[/UU[1S [2U/5/T.R4T/R65 UR&=(d /H?unnnU[8[:4;aMX;aM XR<R?UU45 MA [/UUU RA5T.R4T/R65 T.RCU[EXHU5S US-U(aURRS05O0S.[GXTS55IShvN n[IUU(aUR5$S5$U [2:XGar[!U5S:a [#S5e[K[MT/RNU 55=n(Ga[/UU[1S [2U/5/T.R4T/R65 U(a!URRS5bUS-OSnT.RCU[EXHU5SUU(aURRS05O0S.[GUUS55IShvN nT.RQUU[S[U[WUS5[2555IShvN [IUU(aUR5$S5$[#ST/RN35eU S:XGaQ[!U5S:a [#S5eUc [#S5e[EUSU5nT.RCURX=(d [UR[ZS05USUS-URRS05S.05IShvN n[]U [^5(Gay[!U 5S:Gai[%UUR&=(d /T/R(UU UUS-US-S T/R*T.SS 9 n [a[^5n[a[^5nU RA5H+nUURbR?URd5 M- U Hun[]U[f5(d[#SUS35eUSSupUU nUU n[!U5nU[!U5:aUUOSnUU R?[iXUS95 Mw T-"[IUUR5URA5VVs/sHnUHnUPM M snn5IShvN $[IUU(aUR5$S5$[a[J5nUGbUR&Gb[%UUR&T/R(UU URUS-US -S T/R*T.SS 9 n U RA5H+n UU RbR?U Rd5 M- UR&=(d /V s/sHoS[,:XdMU SSPM sn =n(a4[/UU[1S [2U/5/T.R4T/R65 UR&H?unnnU[8[:4;aMX;aM XR<R?UU45 MA U RA5V s/sHn U R<(dMU PM sn =n!(a#[/UUU!T.R4T/R65 /n"[!U5S:XGa0USupnU c2[!T/R(5S:Xa[kT/R(5Sn OU cMU(dF[]T/RN[R5(a&T/RNT/R(;a T/RNn ObU c_[mU/4SjUSRo555n#U#(a2[!U#5S:Xa U#SSn OU#SSU#SS:waU#SSn U c [#S5eU T/R(;a[#S U S!35eU"R?XU45 OLUHFupnU c [#S"5eU T/R(;a[#S U S!35eU"R?XU45 MH /n$/n%U"GH_upn&T/R(U Rpn'U'(d[#S U S#35e[K5n([1S U U([:/5nURU [K55n)U&=(d< U)(aU)Rs5O$[S[U[WUS5[:55nU$R?U5 U%R?U5 [!U'5S:a[uU'6OU'Sn*U*RwU [yUT/RbS$-[zU(R|[~U[[[[S/USSUUS-5UU U50S%95IShvN GMb [U%U$5H]unnUR<V s/sHoS[:wdMU PM n+n U(dM9U+(dMBT.RQUU+U5IShvN M_ [/UUU$T.R4T/R65 [EXHUS-5nT.RCUUS US-U(aURRS05O0S.[GXTS55IShvN n[U%U$5HUunnUR<V s/sHoS[:XdMU PM sn =n,(dM:T.RQUU,U5IShvN MW [IUU(aUR5$S5$G Ns sn fG N7G NGNGNs snnfGNts sn fs sn fGNs sn fGNDNs sn fNd7f)&Nrrrrrr rrrTrrrrrrrrrrrrrrrrrc3># UH4upUTR;dMUR5HnX14v M M6 g7frrrs rrHPregel.abulk_update_state..aperform_superstep..r r rr r rrrrrr)Fr(rrrrr^r`r6rrr,r2r/r]rrQrrTr[rrrrBrYrWr>rrr=r?rrraputr_rkr*rrbr aput_writesrrrrr1rrrrrr rrrrrrrainvoker+r9rr;r6r rZrXr'rC)0rrrrrrrr rrrrrrrrrrr!r"r#r$r%r&rr'r(r)r*rr+r,rrr-r.r/r0r1rrr2r3r4r5aperform_supersteprrs0 rrG5Pregel.abulk_update_state..aperform_superstepsX #4;; =F&11&99E (()9)9:5: 0 01@P@R @E  !3499;" )6;5>>%%fb1D 2,fTl.>.>0"/! $6v||D?Q$R! 8 ! H&aj!nOF~'S.w>#5#5i#DSU -4AS6T %  ,5>B %w>#5#5i#D  %  fd++F a!3',,2  #qq&*"jj%1 $ "J&1%6NBMdBSM * 1 1 3&tyy188A!4!')$99"4"7v=U V#+/r(%27%; &4W&= %(_  *C ,<<( 3!% &g.55'vPWX#!'*"4,[%..I)6)=)=)?P)?#CDC)?P" ,5>B 7B%6H  U%9%9%E/((JJLL1H1H"&**!-   $**,A$QVV,33ADD9- $)#7#7#=2#=##=a1AUEAabE#=#;!" )"e["EF$55-- "'!5!5ICAUI.. , O**111a&9 "6 )3(9(9(;H(;1qxxQ(;HH5H " $55-- RTM7|q +21:(?s4::!';#DJJ/2G_U"4#6#6<< //4::="&"5"5_(./'1/'B'H'H'J/)%)01Q6&7&:1&=G.r2159J29Nq9QQ&7&;A&>G?,-PQQ$**,,uWI_-MNN$$gw%?@07,FW0Pdjj005 1QRR!(('7)CD1813I&(L5B1!1**W-::,uWI_-MNN16'GVi[I%5$8$8%'$J!*(&--/U4 4(8#99EF   &##G,47L14D&0'RS*kk !%]!:,V]].+W * +$($&$+$&$($($(1H!"!) ' $. &)6C`"%\9!= -1[[!I[aDDL![!I5^^&22)>7 "> --%%  +:JJ , 1 1!& 1HDIu~~11)R@r )0=O2P ! K"%\9!= .2kk"JkqTT\1k"JJ;J&22; WUUU">( uU^^W WRVW Wc :b'8 L#"6 |QB# IP<"J #KUs2+u)t.Fu)t1 t1!Du)?t6D&u)&t9'=u)$t<%C u)t?E-u)3u u)uC u)5u  u Bu)1u uLu)+u,)u)u)u/u):u)u)uBu)!u "$u)u"u" u),u)u',u)1u)9u)<u)?u)u) u)u) u)"u)r8)r(r/rr3rrrrr2r-r&abulk_update_stater,r<r) rrr:rrrrr;r<rGrs ` @@rrIPregel.abulk_update_state^s(4A3H3N3R3R #T%6%64 23 3 z?a 56 6 /J/ / /23 3$D\--.FK KM K%VD\9)-8F#'#6#6QU#6#V Aia#66&v0G/VWV X(V X3HV X V XV Xp , )3vd|

URU[X#U5//5$)zUpdate the state of the graph with the given values, as if they came from node `as_node`. If `as_node` is not provided, it will be set to the last node that updated the state, if not ambiguous. )r9rrrrrrs r update_statePregel.update_state, s$%%f FW0U/V.WXXrcZ# URU[X#U5//5IShvN $N7f)zAsynchronously update the state of the graph with the given values, as if they came from node `as_node`. If `as_node` is not provided, it will be set to the last node that updated the state, if not ambiguous. N)rIrrLs r aupdate_statePregel.aupdate_state9 s6,, k&7;<=    s "+)+) durabilitycUSS:a [S5eUc URnO[X@R5 U=(d URnU=(d UR n[ U[5(dU1nO [U5n[ U[5(aURU5 OURU5 URSLaSn OU[UR[05;aU[[n O&URSLa [!S5eURn U (a%UR[5(d [S5e["UR[05;aU[["R$n O UR$n [&UR[05;aU[[&n O UR(n Uc*UR[05R[*S5nUUUUU U U U4$) Nrecursion_limitrz"recursion_limit must be at least 1FTz1checkpointer=True cannot be used for root graphs.zoCheckpointer requires one or more of the following 'configurable' keys: thread_id, checkpoint_ns, checkpoint_idasync)rrurmrrrrrsetraddrrr3rr/ RuntimeErrorr8rr0rr4) rrr print_mode output_keysinterrupt_beforeinterrupt_afterrR stream_modesrrrs r _defaultsPregel._defaultsH s( # $q (AB B  33K +}} 5+Jt/J/J)GT-G-G+t,,'=L{+L j# & &   Z (    +    %7;L $ 4(< <!$<(?@L   $ &RS S,,L  4 0 0@  D"!5 5&,Tl3E&F&L&LEJJE vzz$3 3&,Tl3C&DEJJE  D"-112GQJ          r) contextrrYrZr[r\rRrrc + ^#^$^%# U RS5=n b3[R"S[SS9 U b [ S5eU (aSOSn Uc/Ub [ UR[ 05;aS O URnU (dUR(aS S /n[5m$[URU5n[U5nURSUURS UR55URS 5S 9nURUUUUUUU S9unnnnnnnnUcU b[R"S5 UR SLa7[#[$U[ [&5n[)U5U[ [&'SU;a[#[$S-U[ R[&55nUR*R-[/T$R0U U(a[3UR5[655OSS95 SU;a S3U$4SjjnO1[8U[ ;aU[ [:R<nOS3SjnU bUU[ [>'[A[CURDU5UUSS9nU[ R[:[F5nURIU5nUU[ [:'[KU40S[MT$R0U5_SU_SU_SU_SU_SURN_SURP_SU_SURR_S URT_S!U_S"U_S#U_S$U_S%URV_S&URX_S'URZ_S(UR\_6m#[_U[ R[`[bRd"T#Rf55[bRd"T#Rh5U[ R[j5S)9nU (a$T#RlT#R[ [8'SnURn(dU (d SU;dSU;a;Sm%T#RpRsT$RtRv5 S4U#U$U%4S*jjnT#Ry5(GaT#R{5H(nT#R}UR~URSS+9 M* URyT#RR5Vs/sHnUR(aMUPM snURUT#RS,9H1n [XEU T$R[R5ShvN M3 T#R5 US-:XaT#RR5 T#Ry5(aGMSSS5 [XEU T$R[R5ShvN T#RS.:Xa*[S/US0S13[RS29n![U!5eURT#R5 gs snfN!,(df  N=fNr![an"URU"5 eSn"A"ff=f7f)5a[ Stream graph steps for a single input. Args: input: The input to the graph. config: The configuration to use for the run. context: The static context to use for the run. !!! version-added "Added in version 0.6.0" stream_mode: The mode to stream output, defaults to `self.stream_mode`. Options are: - `"values"`: Emit all values in the state after each step, including interrupts. When used with functional API, values are emitted once at the end of the workflow. - `"updates"`: Emit only the node or task names and updates returned by the nodes or tasks after each step. If multiple updates are made in the same step (e.g. multiple nodes are run) then those updates are emitted separately. - `"custom"`: Emit custom data from inside nodes or tasks using `StreamWriter`. - `"messages"`: Emit LLM messages token-by-token together with metadata for any LLM invocations inside nodes or tasks. Will be emitted as 2-tuples `(LLM token, metadata)`. - `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by `get_state()`. - `"tasks"`: Emit events when tasks start and finish, including their results and errors. You can pass a list as the `stream_mode` parameter to stream multiple modes at once. The streamed outputs will be tuples of `(mode, data)`. See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details. print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way. output_keys: The keys to stream, defaults to all non-context channels. interrupt_before: Nodes to interrupt before, defaults to all nodes in the graph. interrupt_after: Nodes to interrupt after, defaults to all nodes in the graph. durability: The durability mode for the graph execution, defaults to `"async"`. Options are: - `"sync"`: Changes are persisted synchronously before the next step starts. - `"async"`: Changes are persisted asynchronously while the next step executes. - `"exit"`: Changes are persisted only when the graph exits. subgraphs: Whether to stream events from inside subgraphs, defaults to False. If `True`, the events will be emitted as tuples `(namespace, data)`, or `(namespace, mode, data)` if `stream_mode` is a list, where `namespace` is a tuple with the path to the node where a subgraph is invoked, e.g. `("parent_node:", "child_node:")`. See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details. Yields: The output of each step in the graph. The output shape depends on the `stream_mode`. checkpoint_duringNW`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.r r aCannot use both `checkpoint_during` and `durability` parameters. Please use `durability` instead.rUexitrrrrun_idrrfrrYrZr[r\rR;`durability` has no effect when no checkpointer is present.Tmessagesrcustomc>TR[[5[[R [ 5SS5SU45 gNrrl)rrrPr/r2splitrA)rstreams r stream_writer$Pregel.stream..stream_writer sLJJ! * T 23K L R R$*!""%2!' % rcgrrrs rrqrr& rr`rrqpreviousrprrrrrrrZ input_keys stream_keysr[r\rrRrmigrate_checkpointrr)submitr node_finishedcr>TbTR5(aTRTR5mT$T$r)doner{wait)looprpwaitersr get_waiter!Pregel.stream..get_waiterg s.!>V[[]]%)[[%=F#)M#)Mrcachedtimeoutr schedule_tasksync out_of_stepsRecursion limit of rTr reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.message error_coderrrr)rzconcurrent.futures.Future[None])Trrrrrr;r/rrrGr(rron_chain_startrGr^rrrr2r-inheritable_handlersrrfrrrorAr:r8rqr4rw_coerce_contextrrvmergererurrrrurrrrrjr7weakref WeakMethodr{rr5rprstackcallback_countreleasetickmatch_cached_writes output_writesrrrrr accept_push_outputqueueEmpty after_tick_put_checkpoint_futresultstatusrUrRGRAPH_RECURSION_LIMITrS on_chain_endoutput BaseExceptionon_chain_error)&rrrr`rrYrZr[r\rRrrrrbcallback_manager run_managerr]interrupt_before_interrupt_after_rrr durability_rns_rqruntimeparent_runtimerunnerrrrrmsgerrprs& @@@rrp Pregel.stream s z"(,?!@ @  M MMi4  % w%66J   %*< 4QS@T*T%%  DJJ#X.Jt{{F3:6B&55  J 8::h' 6 l '%'!1 /% ! # (> Q  D(#vd|,DEF9Mb9Qt 56\)3:vd|'7'78P'QR0077) !>A% &(9":t<'  #fTl2 &t -? @ N N %6At 23'(;(;WE+ G $D\--.@/RN$**73G/6F4L+ ,%fjj,?    * jjmm( ..!55"3!1$' "&!6!6!"$(#;#;#$"..%&"..'(%!$<++0'2D2DT[[2Q '11$//B"(,"2"23K"L ;?;;DKK%&78SW %% !\1</@DFJJ'' (=(=>**iikk $ 8 8 :**477DKK*M!;#[[$(JJ$5$5$7H$7qqxx$7H $ 1 1#-&*&6&6 )$+'Y EKK$OO%"f,00779!iikk{^FJJ   {{n,*-f5F.G-HIMM )>> *#..  $ $T[[ 1;I O^     & &q )  swDY)IY%FX2'X+ X+ AX2X0A X21YYAY*Y)+X22 Y<Y Y&Y!!Y&&Y)c ^(^)^*# U RS5=n b3[R"S[SS9 U b [ S5eU (aSOSn Uc/Ub [ UR[ 05;aS O URnU (dUR(aS S /n[5m)[R"5m([[[/S4[T(R T)R"55n[%UR&U5n[)U5nUR+SUURS UR-55URS 5S 9IShvN n[.b[1SUR25S5OSnUR5UUUUUUU S9unnnnnnnnUcU b[R"S5 UR6SLa7[[8U[ [:5n[=U5U[ [:'SU;av[[8S-U[ R[:55nUR>RA[CUU U(a[EURG[H55OSS95 S7U(U)4SjjnSU;a S7U(U)4SjjnO1[JU[ ;aU[ [LRNnOS7SjnU bUU[ [P'[S[UURVU5UUSS9nU[ R[L[X5nUR[U5nUU[ [L'[]U40S[_T)R"U5_SU_SU_SU_SU_SUR`_S URb_S!U_S"URd_S#URf_S$U_S%U_S&U_S'U_S(URh_S)URj_S*URl_S+URn_6IShvN n[qU[ R[r[tRv"URx55[tRv"URz5UU[ R[|5S,9nU (a$[_UU5UR&[ [J'Sn Sn!UR~(dU (d SU;dSU;aSm*S8U(U)U*4S-jjn S9U)U*4S.jjn!UR5(aUR5IShvN H(n"URU"RU"RSS/9 M* URURR5V#s/sHn#U#R(aMU#PM sn#URU URS09ShvN n$[UUU T)R[R5Hn%U%7v M M>U!bU!"5IShvN SSS5IShvN [UUU T)R[R5Hn%U%7v M WRS2:Xa*[S3US4S53[RS69n&[U&5eURUR5IShvN gGN&GNGNs sn#fN UR5 US1:Xa-[[RUR5IShvN UR5(aGMGN!GN!U!bU!"5IShvN ff=fGN !,IShvN (df  GN6=fN![a4n'[R"URU'55IShvN eSn'A'ff=f7f):a Asynchronously stream graph steps for a single input. Args: input: The input to the graph. config: The configuration to use for the run. context: The static context to use for the run. !!! version-added "Added in version 0.6.0" stream_mode: The mode to stream output, defaults to `self.stream_mode`. Options are: - `"values"`: Emit all values in the state after each step, including interrupts. When used with functional API, values are emitted once at the end of the workflow. - `"updates"`: Emit only the node or task names and updates returned by the nodes or tasks after each step. If multiple updates are made in the same step (e.g. multiple nodes are run) then those updates are emitted separately. - `"custom"`: Emit custom data from inside nodes or tasks using `StreamWriter`. - `"messages"`: Emit LLM messages token-by-token together with metadata for any LLM invocations inside nodes or tasks. Will be emitted as 2-tuples `(LLM token, metadata)`. - `"debug"`: Emit debug events with as much information as possible for each step. You can pass a list as the `stream_mode` parameter to stream multiple modes at once. The streamed outputs will be tuples of `(mode, data)`. See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details. print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way. output_keys: The keys to stream, defaults to all non-context channels. interrupt_before: Nodes to interrupt before, defaults to all nodes in the graph. interrupt_after: Nodes to interrupt after, defaults to all nodes in the graph. durability: The durability mode for the graph execution, defaults to `"async"`. Options are: - `"sync"`: Changes are persisted synchronously before the next step starts. - `"async"`: Changes are persisted asynchronously while the next step executes. - `"exit"`: Changes are persisted only when the graph exits. subgraphs: Whether to stream events from inside subgraphs, defaults to False. If `True`, the events will be emitted as tuples `(namespace, data)`, or `(namespace, mode, data)` if `stream_mode` is a list, where `namespace` is a tuple with the path to the node where a subgraph is invoked, e.g. `("parent_node:", "child_node:")`. See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details. Yields: The output of each step in the graph. The output shape depends on the `stream_mode`. rbNrcr r rdrUrerrrrfrgc3# UH5n[U[5(dM[U[5(aM1Sv M7 g7f)TN)rrrf)rhs rr!Pregel.astream.. s61!!%>?'q*?@D1s ?? ?FrhriTrjrkc>TRTR[[5[[ R [5SS5SU45 grncall_soon_threadsafe put_nowaitrrPr/r2rorAraiolooprps rrq%Pregel.astream..stream_writer3 sT,,%%&L./GHNNvV # ! rrlc>TRTR[[5[[ R [5SS5SU45 grnrrs rrqrC sW00))! * T 23K L R R$*!""%2!' % rcgrrrts rrqrT rurrvrprrrrrrrZrxryr[r\rrRrrzrr)r{r use_astreamr|c>TbTR5(a8TRTR55mSU4SjjnTRU5 T$)Nc>TULaSmggrr)rrs r_clear2Pregel.astream..get_waiter.._clear s#)Q;-1F$/r)rasyncio.Task[None]rr)r~ create_taskradd_done_callback)rrrprs rr"Pregel.astream..get_waiter sB!>V[[]]%,%8%8%GF2 #44V<% rc># [R"[5 [TS5(aTRR 5 SSS5 TnSmUb^UR 5(dHUR5 [R"[R5 UIShvN SSS5 ggg!,(df  Nt=fN !,(df  g=f7f)z?Wake pending waiter and/or cancel+await to avoid pending tasks.rN) contextlibsuppress Exceptionhasattrrrr~cancelr(CancelledError)rrprs r_cleanup_waiter'Pregel.astream.._cleanup_waiter s(00;&vx88 & 5 5 7<#!%=HHJ!+!4!4W5K5K!L&'"M!L2:= <;!("M!LsGC,B8 AC"C (C )C - C8 CC C  CCrrrrrrTrrr)rrr)Zrrrrrr;r/rrrFr(get_running_looprrrtr rrr(rrrrGrrhandlersr^rrr2r-rrrfrrorAr:r8rqr4rwrrrvrrdrurrrrurrrrrjr7rrr{rr5rramatch_cached_writesrrratickrrr aaccept_pushr get_nowait QueueEmptyrFuturerrrUrRrrSrrrshieldr)+rrrr`rrYrZr[r\rRrrrrb stream_putrr do_streamr]rrrrrrrrrqrrrrrrrrrorrrrprs+ @@@rastreamPregel.astream s=x"(,?!@ @  M MMi4  % w%66J   %*< 4QS@T*T%%  DJJ#X.J**, k]D( ) G00&2C2C D t{{F3@H,;;  J 8::h' <  ")4 (11   ^ '%'!1 /% ! # (> Q  D(#vd|,DEF9Mb9Qt 56\)3:vd|'7'78P'QR0077)"!>A% &(9":t  <'  #fTl2 &t -? @ N N %6At 23'(;(;WE+ G $D\--.@/RN$**73G/6F4L+ ,&%f&7&7F    * jjmm( ..!55"3!1$' "&!6!6!"$(#;#;#$"..%&"..'(%!$<++0'2D2DT[[2Q '11$//B )"(,"2"23K"L ;I"L<DKK%&78GK HL%% !\1</9=F & & ( (&0))++*.*C*C*E$E$ED ..tww D.Q%F'-||(, (9(9(;L(;1188Q(;L$($5$5'1*.*;*; (4((!&- + * ) & 1 1 ' 2 2 &'(&'2-///SX!!"" {{n,*-f5F.G-HIMM )>> *#..**4;;7 7 7_ ^b%FM(()&&0"&w~~t7O7O"PPP+))++20'2-///3Q@ 8 ..!;!;A!>? ? ?  s*E]&Y;*]&I#\%$Y>%\%(C&\([,7Z8A[,Z (Z .[, Z Z Z 6[, \[)\ \%%\&B\%5\#6\%:]&>\%[,[, Z  >[, [  [,)\,\:[= ;\\\%\ \  \  \%% ]#/(]]]]##]&r`rrYrZr[r\rRc UbUO URnSn /n /n UR"UU4UUS:XaSS/OUUUUUU S.U D6HnUS:Xa[U5S:Xa![[[ [ 4U5unnO/[[[[S4[ [ 4U5unnnUS:Xa@[U[5(a+UR[5=nbU RU5 MUS:XaUn MMU RU5 M US:Xa2U (a)[U [5(a 0U E[U 0E$[U 0$U $U $)a Run the graph with a single input and config. Args: input: The input data for the graph. It can be a dictionary or any other type. config: The configuration for the graph run. context: The static context to use for the run. !!! version-added "Added in version 0.6.0" stream_mode: The stream mode for the graph run. print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way. output_keys: The output keys to retrieve from the graph run. interrupt_before: The nodes to interrupt the graph run before. interrupt_after: The nodes to interrupt the graph run after. durability: The durability mode for the graph execution, defaults to `"async"`. Options are: - `"sync"`: Changes are persisted synchronously before the next step starts. - `"async"`: Changes are persisted asynchronously while the next step executes. - `"exit"`: Changes are persisted only when the graph exits. **kwargs: Additional keyword arguments to pass to the graph run. Returns: The output of the graph run. If `stream_mode` is `"values"`, it returns the latest output. If `stream_mode` is not `"values"`, it returns a list of output chunks. Nrrrr .)rrprrrrrrrrrr?rrrrrr`rrYrZr[r\rRrlatestchunksrchunkmodepayloadrintss rr Pregel.invoke svL&1%?($AtWI%"7D11!(Y!77D%%d+X%$F& e$=  @ ( ""&$//6v5y*5$Z0 MMrc # UbUO URnSn /n /n UR"UU4UUS:XaSS/OUUUUUU S.U D6ShvN nUS:Xa[U5S:Xa![[[ [ 4U5unnO/[[[[S4[ [ 4U5unnnUS:Xa@[U[5(a+UR[5=nbU RU5 MUS:XaUn MMU RU5 MN US:Xa2U (a)[U [5(a 0U E[U 0E$[U 0$U $U $7f)aAsynchronously invoke the graph on a single input. Args: input: The input data for the computation. It can be a dictionary or any other type. config: The configuration for the computation. context: The static context to use for the run. !!! version-added "Added in version 0.6.0" stream_mode: The stream mode for the computation. print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way. output_keys: The output keys to include in the result. interrupt_before: The nodes to interrupt before. interrupt_after: The nodes to interrupt after. durability: The durability mode for the graph execution, defaults to `"async"`. Options are: - `"sync"`: Changes are persisted synchronously before the next step starts. - `"async"`: Changes are persisted asynchronously while the next step executes. - `"exit"`: Changes are persisted only when the graph exits. **kwargs: Additional keyword arguments. Returns: The result of the computation. If `stream_mode` is `"values"`, it returns the latest value. If `stream_mode` is `"chunks"`, it returns a list of chunks. Nrrrr .)rrrrrrrrrrrr?rrrs rrFPregel.ainvokeA sN&1%?($AtWI%"7D11!(Y!77D%%d+X%$F& e$= %  @ ( ""&$//6v5y*5$Z0 MMs*>EDDDC ED;Ec^UR(d [S5eU=(d URR5n/nUHKnX0R;dMUR [ [ URU5=(d SU45 MM URRU5 g)z$Clear the cache for the given nodes.3No cache is set for this graph. Cannot clear cache. __dynamic__N)rrrrcrr.r\clearrr namespacesrs r clear_cachePregel.clear_cache szzRS S**,. Dzz!!!'#DJJt$45F $rcz# UR(d [S5eU=(d URR5n/nUHKnX0R;dMUR [ [ URU5=(d SU45 MM URRU5IShvN gN7f)z3Asynchronously clear the cache for the given nodes.rrN)rrrrcrr.r\aclearrs r aclear_cachePregel.aclear_cache szzRS S**,. Dzz!!!'#DJJt$45Fjj +++sAB;AB;3B94B;)rrrrrrrrrrrrrrrrrrrr).rz#dict[str, PregelNode | NodeBuilder]rz0dict[str, BaseChannel | ManagedValueSpec] | Nonerrrrrrrrrrrrrrrrrrr bool | NonerBaseCheckpointSaver | Nonerrrrrz#RetryPolicy | Sequence[RetryPolicy]rrrrrrrz"Mapping[str, Sequence[str]] | NonerrrUnpack[DeprecatedKwargs]rrr)rrrz int | boolrr)rrrr)rdict[str, Any] | Nonerr$)rrrrrr$)rr$)rASequence[str] | Nonertype[BaseModel])rArrr)rr)rr)rrrr)rrrr)rz Sequence[str])rr)r{ str | Noner|rrz$Iterator[tuple[str, PregelProtocol]])r{rr|rrz)AsyncIterator[tuple[str, PregelProtocol]])rrrr)NF) rrrzCheckpointTuple | Noner|rrrrr)rrrrrr) rrrrrrr int | NonerzIterator[StateSnapshot]) rrrrrrrrrzAsyncIterator[StateSnapshot])rrr:zSequence[Sequence[StateUpdate]]rr)NN) rrrzdict[str, Any] | Any | Nonerrrrrr) rrrdict[str, Any] | Anyrrrrrr)rrr!StreamMode | Sequence[StreamMode]rYrrZrr[All | Sequence[str] | Noner\rrRDurability | Nonerztuple[set[StreamMode], str | Sequence[str], All | Sequence[str], All | Sequence[str], BaseCheckpointSaver | None, BaseStore | None, BaseCache | None, Durability])rInputT | Command | Nonerrr`ContextT | Noner(StreamMode | Sequence[StreamMode] | NonerYrrZrr[rr\rrRrrrrrrrrzIterator[dict[str, Any] | Any])rrrrr`r rr rYrrZrr[rr\rrRrrrrrrrrz#AsyncIterator[dict[str, Any] | Any])rrrrr`r rrrYrrZrr[rr\rrRrrrrr)rrrr)!%L,%;"E "/"E "0*,L',O'+L$+S,0N)0Z$(F !(D#11#"*"6:5768%)!37"&"&<>+/04(,?C/E3EC E  E  EE-E4E 3E!4E,E#EE1E  !E" #E$:%E&)'E(.)E*&+E,=-E./E061E2 3EP/3 JO + =G  :/3( JO( +( =G( ( T '  f@DO O,V 26 *. *  *  * **  /3*+* * ))/3+ "/3*+* *     *.u%&%8<% -%P*.u&8< 2 /3%* u u &u , u # u  u v/3%* v v &v , v # v  v r J6J0J5J4J&JJJ+J (J^)-N $(@D8:267;6:(,!N&N&N ! N > N6N0N5N4N&NNN+N -Nf )-U $("*8:267;6:(,U&U&U ! U  U6U0U5U4U&UU Ut)-V $("*8:267;6:(,V&V&V ! V  V6V0V5V4V&VV Vp%&,,rrc[[5nUR5H+up#URHnXR U5 M M- [ U5$)z0Index from a trigger to nodes that depend on it.)rrrrrr)rrrrtriggers rr<r< sL4?4Ekkm }}G  % , ,T 2%$  !!rc ## U"5upVnXa;aU(aGU(a@[SR[SUS35[SUS3SS9[ U5455 O2[SR[SUS35[ U5455 X`;aOU(a[ U[ 5(aXVU4v O,[ U[ 5(aXg4v OU(aXW4v OUv M!Ua gf=f7f)N []z[graph=yellow)color)printjoinrprqr-rr)rrYstream_subgraphsgetter empty_excrrrs rrr s   & Bg  BHH+avQK8,wrd!_HM MHH+avQK8 M  J{D$A$A))K..o%!m# C    s(C6 C*CC6*C30C62C33C6cUcgUcU$[U[5=(d [U5n[U[5(aU(aU"S0UD6$[ [ U5$)awCoerce context input to the appropriate schema type. If context is a dict and context_schema is a dataclass or pydantic model, we coerce. Else, we return the context as-is. Args: context_schema: The schema type to coerce to (BaseModel, dataclass, or TypedDict) context: The context value to coerce Returns: The coerced context value or None if context is None Nr)rXr"r rrrr)rr`schema_is_classs rrr s_ ;|@O'4  _((( ' ""r)rrrr) rrrYrrrrz.Callable[[], tuple[tuple[str, ...], str, Any]]rztype[Exception]rr )rrr`rrr ) __future__rr( concurrentconcurrent.futuresrrrr collectionsrrcollections.abcrrrr r r dataclassesr functoolsr inspectrtypingrrrruuidrrlangchain_core.globalsrlangchain_core.runnablesrlangchain_core.runnables.baserrlangchain_core.runnables.configrrrlangchain_core.runnables.graphrlanggraph.cache.baserlanggraph.checkpoint.baserrr langgraph.store.baser!pydanticr"r#typing_extensionsr$r%r&r'langgraph._internal._configr(r)r*r+r,r-langgraph._internal._constantsr.r/r0r1r2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDlanggraph._internal._pydanticrElanggraph._internal._queuerFrGlanggraph._internal._runnablerHrIrJrKlanggraph._internal._typingrLrMlanggraph.channels.baserNlanggraph.channels.topicrOlanggraph.configrPlanggraph.constantsrQlanggraph.errorsrRrSrTrUlanggraph.managed.baserVlanggraph.pregel._algorWrXrYrZr[langgraph.pregel._callr\langgraph.pregel._checkpointr]r^r_r`langgraph.pregel._drawralanggraph.pregel._iorbrclanggraph.pregel._looprdrelanggraph.pregel._messagesrflanggraph.pregel._readrgrhlanggraph.pregel._retryrilanggraph.pregel._runnerrjlanggraph.pregel._utilsrklanggraph.pregel._validaterlrmlanggraph.pregel._writernrolanggraph.pregel.debugrprqrrlanggraph.pregel.protocolrsrtrulanggraph.runtimervrwlanggraph.typesrxryrzr{r|r}r~rrrlanggraph.typingrrrrlanggraph.warningsr!langchain_core.tracers._streamingr ImportError__all__rrrr<rrrrrrSs" *% ,8 1* ++DD27 B/*'# 4. .9B<</1<DCTTQQ6   ?>:%K $w'#- _ _ D|-,68VW45 FHfg -.|-,~["(2(1(( ; (  (  (V#)#47##{b% $%s*II I