Runs, gRPC: RunService.Create

Статья создана

Yandex Cloud

Улучшена

Tania L.

Обновлена 24 апреля 2025 г.

gRPC request
CreateRunRequest
MessageData
Author
MessageContent
ContentPart
Text
PromptTruncationOptions
AutoStrategy
LastMessagesStrategy
CompletionOptions
Tool
SearchIndexTool
RephraserOptions
FunctionTool
Run
RunState
Error
Message
Author
MessageContent
ContentPart
Text
Citation
Source
FileChunk
SearchIndex
ExpirationConfig
TextSearchIndex
ChunkingStrategy
StaticChunkingStrategy
NgramTokenizer
StandardTokenizer
StandardAnalyzer
YandexLemmerAnalyzer
VectorSearchIndex
HybridSearchIndex
CombinationStrategy
MeanCombinationStrategy
ReciprocalRankFusionCombinationStrategy
File
ChunkContent
ToolCallList
ToolCall
FunctionCall
ContentUsage
PromptTruncationOptions
AutoStrategy
LastMessagesStrategy
CompletionOptions
Tool
SearchIndexTool
RephraserOptions
FunctionTool

Create a new run for a given assistant and thread.

gRPC request

rpc Create (CreateRunRequest) returns (Run)

CreateRunRequest

{
  "assistant_id": "string",
  "thread_id": "string",
  "labels": "map<string, string>",
  "additional_messages": [
    {
      "author": {
        "id": "string",
        "role": "string"
      },
      "labels": "map<string, string>",
      "content": {
        "content": [
          {
            // Includes only one of the fields `text`
            "text": {
              "content": "string"
            }
            // end of the list of possible fields
          }
        ]
      }
    }
  ],
  "custom_prompt_truncation_options": {
    "max_prompt_tokens": "google.protobuf.Int64Value",
    // Includes only one of the fields `auto_strategy`, `last_messages_strategy`
    "auto_strategy": "AutoStrategy",
    "last_messages_strategy": {
      "num_messages": "int64"
    }
    // end of the list of possible fields
  },
  "custom_completion_options": {
    "max_tokens": "google.protobuf.Int64Value",
    "temperature": "google.protobuf.DoubleValue"
  },
  "stream": "bool",
  "tools": [
    {
      // Includes only one of the fields `search_index`, `function`
      "search_index": {
        "search_index_ids": [
          "string"
        ],
        "max_num_results": "google.protobuf.Int64Value",
        "rephraser_options": {
          "rephraser_uri": "string"
        }
      },
      "function": {
        "name": "string",
        "description": "string",
        "parameters": "google.protobuf.Struct"
      }
      // end of the list of possible fields
    }
  ]
}

Request message for creating a new run.

Field	Description
assistant_id	string Required field. ID of the assistant for which the run is being created
thread_id	string Required field. ID of the thread associated with the run.
labels	object (map<string, string>) Set of key-value pairs to label the run.
additional_messages[]	MessageData Additional messages that will be written to the thread before the run starts.
custom_prompt_truncation_options	PromptTruncationOptions Configuration options for truncating the prompt when the token count exceeds a specified limit. If specified, these options will override the assistant's prompt truncation settings for this run.
custom_completion_options	CompletionOptions Configuration options for completion generation. If specified, these options will override the assistant's completion settings for this run.
stream	bool Enables streaming of intermediate events, such as partial messages.
tools[]	Tool List of tools that are available for the assistant to use in this run.

MessageData

Represents the data required to create or initialize a message in a thread.
This message is used, for example, to initialize a thread with some messages upon its creation.

Field	Description
author	Author Author of the message, containing details about the message's creator.
labels	object (map<string, string>) Set of key-value pairs that can be used to organize and categorize the message.
content	MessageContent Content of the message.

Author

Author of the message, containing details about the message's creator.

Field

Description

string

Unique identifier of the author. This could be either the user's ID or the assistant's ID, depending on the role.

role

string

Role of the author, indicating whether the message was created by a "user" or an "assistant".

MessageContent

Represents the content of a message, which can consist of multiple parts.

Field

Description

content[]

ContentPart

A list of content parts that make up the message.

ContentPart

ContentPart represents an individual part of the message content, which can be of various types.

Field

Description

text

Text

Text content of the message part.

Includes only one of the fields text.

Specifies the type of content that the part contains.

Text

Text represents a textual content part of a message.

Field

Description

content

string

Text content of the message.

PromptTruncationOptions

Defines the options for truncating thread messages within a prompt.

Field	Description
max_prompt_tokens	google.protobuf.Int64Value The maximum number of tokens allowed in the prompt. If the prompt exceeds this limit, the thread messages will be truncated. Default max_prompt_tokens: 7000
auto_strategy	AutoStrategy Includes only one of the fields `auto_strategy`, `last_messages_strategy`. Specifies the truncation strategy to use when the prompt exceeds the token limit.
last_messages_strategy	LastMessagesStrategy Retains only the last `num_messages` messages in the thread. If these messages exceed `max_prompt_tokens`, older messages will be further truncated to fit the limit. Includes only one of the fields `auto_strategy`, `last_messages_strategy`. Specifies the truncation strategy to use when the prompt exceeds the token limit.

AutoStrategy

Auto truncation strategy.

Field	Description
Empty

LastMessagesStrategy

Truncates the prompt by retaining only the last num_messages messages in the thread.

Field

Description

num_messages

int64

The number of most recent messages to retain in the prompt.
If these messages exceed max_prompt_tokens, older messages will be further truncated to fit the limit.

CompletionOptions

Defines the options for completion generation.

Field

Description

max_tokens

google.protobuf.Int64Value

The limit on the number of tokens used for single completion generation.
Must be greater than zero. This maximum allowed parameter value may depend on the model being used.

temperature

google.protobuf.DoubleValue

Affects creativity and randomness of responses. Should be a double number between 0 (inclusive) and 1 (inclusive).
Lower values produce more straightforward responses while higher values lead to increased creativity and randomness.
Default temperature: 0.3

Tool

Represents a general tool that can be one of several types.

Field

Description

search_index

SearchIndexTool

SearchIndexTool tool that performs search across specified indexes.

Includes only one of the fields search_index, function.

function

FunctionTool

Function tool that can be invoked by the assistant.

Includes only one of the fields search_index, function.

SearchIndexTool

Configures a tool that enables Retrieval-Augmented Generation (RAG) by allowing the assistant to search across a specified search index.

Field	Description
search_index_ids[]	string A list of search index IDs that this tool will query. Currently, only a single index ID is supported.
max_num_results	google.protobuf.Int64Value The maximum number of results to return from the search. Fewer results may be returned if necessary to fit within the prompt's token limit. This ensures that the combined prompt and search results do not exceed the token constraints.
rephraser_options	RephraserOptions Options for rephrasing user queries. Used to rewrite the last user message for search, incorporating context from the previous conversation.

RephraserOptions

Options for configuring the rephrasing the last user message for search using context from previous conversation.

Field

Description

rephraser_uri

string

Required field. The ID of the model used to rephrase the last user message for search.

FunctionTool

Represents a function tool that can be invoked by the assistant.

Field	Description
name	string The name of the function.
description	string A description of the function's purpose or behavior.
parameters	google.protobuf.Struct A JSON Schema that defines the expected parameters for the function. The schema should describe the required fields, their types, and any constraints or default values.

Run

{
  "id": "string",
  "assistant_id": "string",
  "thread_id": "string",
  "created_by": "string",
  "created_at": "google.protobuf.Timestamp",
  "labels": "map<string, string>",
  "state": {
    "status": "RunStatus",
    // Includes only one of the fields `error`, `completed_message`, `tool_call_list`
    "error": {
      "code": "int64",
      "message": "string"
    },
    "completed_message": {
      "id": "string",
      "thread_id": "string",
      "created_by": "string",
      "created_at": "google.protobuf.Timestamp",
      "author": {
        "id": "string",
        "role": "string"
      },
      "labels": "map<string, string>",
      "content": {
        "content": [
          {
            // Includes only one of the fields `text`
            "text": {
              "content": "string"
            }
            // end of the list of possible fields
          }
        ]
      },
      "status": "MessageStatus",
      "citations": [
        {
          "sources": [
            {
              // Includes only one of the fields `chunk`
              "chunk": {
                "search_index": {
                  "id": "string",
                  "folder_id": "string",
                  "name": "string",
                  "description": "string",
                  "created_by": "string",
                  "created_at": "google.protobuf.Timestamp",
                  "updated_by": "string",
                  "updated_at": "google.protobuf.Timestamp",
                  "expiration_config": {
                    "expiration_policy": "ExpirationPolicy",
                    "ttl_days": "int64"
                  },
                  "expires_at": "google.protobuf.Timestamp",
                  "labels": "map<string, string>",
                  // Includes only one of the fields `text_search_index`, `vector_search_index`, `hybrid_search_index`
                  "text_search_index": {
                    "chunking_strategy": {
                      // Includes only one of the fields `static_strategy`
                      "static_strategy": {
                        "max_chunk_size_tokens": "int64",
                        "chunk_overlap_tokens": "int64"
                      }
                      // end of the list of possible fields
                    },
                    // Includes only one of the fields `ngram_tokenizer`, `standard_tokenizer`
                    "ngram_tokenizer": {
                      "min_gram": "google.protobuf.Int64Value",
                      "max_gram": "google.protobuf.Int64Value"
                    },
                    "standard_tokenizer": "StandardTokenizer",
                    // end of the list of possible fields
                    // Includes only one of the fields `standard_analyzer`, `yandex_lemmer_analyzer`
                    "standard_analyzer": "StandardAnalyzer",
                    "yandex_lemmer_analyzer": "YandexLemmerAnalyzer"
                    // end of the list of possible fields
                  },
                  "vector_search_index": {
                    "doc_embedder_uri": "string",
                    "query_embedder_uri": "string",
                    "chunking_strategy": {
                      // Includes only one of the fields `static_strategy`
                      "static_strategy": {
                        "max_chunk_size_tokens": "int64",
                        "chunk_overlap_tokens": "int64"
                      }
                      // end of the list of possible fields
                    }
                  },
                  "hybrid_search_index": {
                    "text_search_index": {
                      "chunking_strategy": {
                        // Includes only one of the fields `static_strategy`
                        "static_strategy": {
                          "max_chunk_size_tokens": "int64",
                          "chunk_overlap_tokens": "int64"
                        }
                        // end of the list of possible fields
                      },
                      // Includes only one of the fields `ngram_tokenizer`, `standard_tokenizer`
                      "ngram_tokenizer": {
                        "min_gram": "google.protobuf.Int64Value",
                        "max_gram": "google.protobuf.Int64Value"
                      },
                      "standard_tokenizer": "StandardTokenizer",
                      // end of the list of possible fields
                      // Includes only one of the fields `standard_analyzer`, `yandex_lemmer_analyzer`
                      "standard_analyzer": "StandardAnalyzer",
                      "yandex_lemmer_analyzer": "YandexLemmerAnalyzer"
                      // end of the list of possible fields
                    },
                    "vector_search_index": {
                      "doc_embedder_uri": "string",
                      "query_embedder_uri": "string",
                      "chunking_strategy": {
                        // Includes only one of the fields `static_strategy`
                        "static_strategy": {
                          "max_chunk_size_tokens": "int64",
                          "chunk_overlap_tokens": "int64"
                        }
                        // end of the list of possible fields
                      }
                    },
                    "chunking_strategy": {
                      // Includes only one of the fields `static_strategy`
                      "static_strategy": {
                        "max_chunk_size_tokens": "int64",
                        "chunk_overlap_tokens": "int64"
                      }
                      // end of the list of possible fields
                    },
                    "normalization_strategy": "NormalizationStrategy",
                    "combination_strategy": {
                      // Includes only one of the fields `mean_combination`, `rrf_combination`
                      "mean_combination": {
                        "mean_evaluation_technique": "MeanEvaluationTechnique",
                        "weights": [
                          "double"
                        ]
                      },
                      "rrf_combination": {
                        "k": "google.protobuf.Int64Value"
                      }
                      // end of the list of possible fields
                    }
                  }
                  // end of the list of possible fields
                },
                "source_file": {
                  "id": "string",
                  "folder_id": "string",
                  "name": "string",
                  "description": "string",
                  "mime_type": "string",
                  "created_by": "string",
                  "created_at": "google.protobuf.Timestamp",
                  "updated_by": "string",
                  "updated_at": "google.protobuf.Timestamp",
                  "expiration_config": {
                    "expiration_policy": "ExpirationPolicy",
                    "ttl_days": "int64"
                  },
                  "expires_at": "google.protobuf.Timestamp",
                  "labels": "map<string, string>"
                },
                "content": {
                  "content": [
                    {
                      // Includes only one of the fields `text`
                      "text": {
                        "content": "string"
                      }
                      // end of the list of possible fields
                    }
                  ]
                }
              }
              // end of the list of possible fields
            }
          ]
        }
      ]
    },
    "tool_call_list": {
      "tool_calls": [
        {
          // Includes only one of the fields `function_call`
          "function_call": {
            "name": "string",
            "arguments": "google.protobuf.Struct"
          }
          // end of the list of possible fields
        }
      ]
    }
    // end of the list of possible fields
  },
  "usage": {
    "prompt_tokens": "int64",
    "completion_tokens": "int64",
    "total_tokens": "int64"
  },
  "custom_prompt_truncation_options": {
    "max_prompt_tokens": "google.protobuf.Int64Value",
    // Includes only one of the fields `auto_strategy`, `last_messages_strategy`
    "auto_strategy": "AutoStrategy",
    "last_messages_strategy": {
      "num_messages": "int64"
    }
    // end of the list of possible fields
  },
  "custom_completion_options": {
    "max_tokens": "google.protobuf.Int64Value",
    "temperature": "google.protobuf.DoubleValue"
  },
  "tools": [
    {
      // Includes only one of the fields `search_index`, `function`
      "search_index": {
        "search_index_ids": [
          "string"
        ],
        "max_num_results": "google.protobuf.Int64Value",
        "rephraser_options": {
          "rephraser_uri": "string"
        }
      },
      "function": {
        "name": "string",
        "description": "string",
        "parameters": "google.protobuf.Struct"
      }
      // end of the list of possible fields
    }
  ]
}

Represents a run of an assistant over a specific thread of messages.

Field	Description
id	string Unique identifier of the run.
assistant_id	string Identifier for the assistant that is being run.
thread_id	string Identifier for the thread of messages that this run is associated with.
created_by	string Identifier of the subject who created this run.
created_at	google.protobuf.Timestamp Timestamp representing when the run was created.
labels	object (map<string, string>) Set of key-value pairs that can be used to organize and categorize the run.
state	RunState Current state of the run, including its status and any associated data.
usage	ContentUsage Information about the content usage during the run, such as the number of tokens used by the completion model.
custom_prompt_truncation_options	PromptTruncationOptions Configuration options for truncating the prompt when the token count exceeds a specified limit. If specified, these options will override the assistant's prompt truncation settings for this run.
custom_completion_options	CompletionOptions Configuration options for completion generation. If specified, these options will override the assistant's completion settings for this run.
tools[]	Tool List of tools that are available for the assistant to use in this run.

RunState

Represents the current state of a run.

Field	Description
status	enum RunStatus Current status of a run. `RUN_STATUS_UNSPECIFIED`: Default unspecified status. `PENDING`: Run has been created but has not started yet. `IN_PROGRESS`: Run is currently in progress. `FAILED`: Run has failed due to an error. `COMPLETED`: Run has completed successfully. `TOOL_CALLS`: The run is waiting for tool calls to be executed and their results to be submitted.
error	Error Error information if a run has failed. Includes only one of the fields `error`, `completed_message`, `tool_call_list`. Oneof field to capture additional data depending on the state of a run.
completed_message	Message Final message generated by an assistant if a run has completed successfully. Includes only one of the fields `error`, `completed_message`, `tool_call_list`. Oneof field to capture additional data depending on the state of a run.
tool_call_list	ToolCallList A list of tool calls requested by the assistant. Includes only one of the fields `error`, `completed_message`, `tool_call_list`. Oneof field to capture additional data depending on the state of a run.

Error

Field	Description
code	int64
message	string

Message

Field	Description
id	string Unique identifier of the message.
thread_id	string ID of the thread that this message belongs to.
created_by	string Identifier of the subject who created this message.
created_at	google.protobuf.Timestamp Timestamp representing when the message was created.
author	Author Author of the message, containing details about the message's creator.
labels	object (map<string, string>) Set of key-value pairs that can be used to organize and categorize the message.
content	MessageContent Content of the message.
status	enum MessageStatus Status of the message. `MESSAGE_STATUS_UNSPECIFIED`: Unspecified message status. `COMPLETED`: Message was successfully created by a user or generated by an assistant. `TRUNCATED`: Message generation was truncated due to reaching the maximum allowed number of tokens. `FILTERED_CONTENT`: Message generation was stopped because potentially sensitive content was detected either in the prompt or in the generated response.
citations[]	Citation List of citations used to generate the message.

Author

Author of the message, containing details about the message's creator.

Field

Description

string

Unique identifier of the author. This could be either the user's ID or the assistant's ID, depending on the role.

role

string

Role of the author, indicating whether the message was created by a "user" or an "assistant".

MessageContent

Represents the content of a message, which can consist of multiple parts.

Field

Description

content[]

ContentPart

A list of content parts that make up the message.

ContentPart

ContentPart represents an individual part of the message content, which can be of various types.

Field

Description

text

Text

Text content of the message part.

Includes only one of the fields text.

Specifies the type of content that the part contains.

Text

Text represents a textual content part of a message.

Field

Description

content

string

Text content of the message.

Citation

Represents a citation used for generating a message.

Field

Description

sources[]

Source

List of sources for citation.

Source

Represents a source used for generating a message citation.

Field

Description

chunk

FileChunk

File chunk source.

Includes only one of the fields chunk.

Specifies the type of source type.

FileChunk

FileChunk represents a chunk of a file used as a source.

Field	Description
search_index	SearchIndex Search index associated with the file chunk.
source_file	File The original file from which the chunk is derived.
content	ChunkContent Content of the file chunk.

SearchIndex

Represents a search index used to store and query data, either using traditional keyword-based text search or vector-based search mechanisms.

Field	Description
id	string Unique identifier of the search index.
folder_id	string ID of the folder that the search index belongs to.
name	string Name of the search index.
description	string Description of the search index.
created_by	string Identifier of the subject who created this search index.
created_at	google.protobuf.Timestamp Timestamp representing when the search index was created.
updated_by	string Identifier of the subject who last updated this search index.
updated_at	google.protobuf.Timestamp Timestamp representing the last time this search index was updated.
expiration_config	ExpirationConfig Configuration for the expiration of the search index, defining when and how the search index will expire.
expires_at	google.protobuf.Timestamp Timestamp representing when the search index will expire.
labels	object (map<string, string>) Set of key-value pairs that can be used to organize and categorize the search index.
text_search_index	TextSearchIndex Keyword-based text search index configuration. This type of index is used for traditional text search, where documents are indexed based on their keywords. Includes only one of the fields `text_search_index`, `vector_search_index`, `hybrid_search_index`. Type of the search index. It can be either a traditional keyword-based text search or a vector-based search.
vector_search_index	VectorSearchIndex Vector-based search index configuration. This type is used for vector search, where documents are indexed using vector embeddings. Includes only one of the fields `text_search_index`, `vector_search_index`, `hybrid_search_index`. Type of the search index. It can be either a traditional keyword-based text search or a vector-based search.
hybrid_search_index	HybridSearchIndex Hybrid (vector-based + keyword-based) search index configuration This type is used for hybrid search, where documents are indexed using both keyword-based and vector-based search mechanisms. Includes only one of the fields `text_search_index`, `vector_search_index`, `hybrid_search_index`. Type of the search index. It can be either a traditional keyword-based text search or a vector-based search.

ExpirationConfig

Field

Description

expiration_policy

enum ExpirationPolicy

EXPIRATION_POLICY_UNSPECIFIED
STATIC
SINCE_LAST_ACTIVE

ttl_days

int64

TextSearchIndex

Defines the configuration for a traditional keyword-based text search index.

Field	Description
chunking_strategy	ChunkingStrategy Chunking strategy used to split text into smaller chunks before indexing. In the case of text search, tokens are individual text characters.
ngram_tokenizer	NgramTokenizer Tokenizer that generates n-grams. Includes only one of the fields `ngram_tokenizer`, `standard_tokenizer`. Tokenizer type used for text search. The tokenizer determines how the input text is broken down into tokens before indexing. If not specified, the default tokenizer configuration is applied.
standard_tokenizer	StandardTokenizer Tokenizer that generates words. Includes only one of the fields `ngram_tokenizer`, `standard_tokenizer`. Tokenizer type used for text search. The tokenizer determines how the input text is broken down into tokens before indexing. If not specified, the default tokenizer configuration is applied.
standard_analyzer	StandardAnalyzer Standard analyzer that performs common text processing operations to normalize text. Includes only one of the fields `standard_analyzer`, `yandex_lemmer_analyzer`. Analyzer type used for text search. The analyzer determines how the tokenized text is further processed before indexing. If not specified, the default analyzer configuration is applied.
yandex_lemmer_analyzer	YandexLemmerAnalyzer Specialized analyzer that uses Yandex's lemmatization technology, particularly effective for Russian and other Slavic languages. Includes only one of the fields `standard_analyzer`, `yandex_lemmer_analyzer`. Analyzer type used for text search. The analyzer determines how the tokenized text is further processed before indexing. If not specified, the default analyzer configuration is applied.

ChunkingStrategy

Defines a general strategy for chunking text into smaller segments.
Currently, only StaticChunkingStrategy is supported.

Field

Description

static_strategy

StaticChunkingStrategy

Includes only one of the fields static_strategy.

StaticChunkingStrategy

Defines a chunking strategy where chunks are created with a fixed maximum chunk size and an overlap between consecutive chunks.

Field

Description

max_chunk_size_tokens

int64

The maximum number of tokens allowed in a single chunk.
Constraints: must be within the range [100, 2048].
Default value: 800

chunk_overlap_tokens

int64

The number of tokens that should overlap between consecutive chunks.
This allows for some context from the previous chunk to be included in the next chunk.
Constraints: must be less than or equal to half of max_chunk_size_tokens.
Default value: 400

NgramTokenizer

Configuration for the NgramTokenizer, which splits text into overlapping character sequences (n-grams) of specified lengths.

Example:
Input text: hello
min_gram = 2, max_gram = 3

Generated tokens:

For n = 2 (2-character n-grams): he, el, ll, lo
For n = 3 (3-character n-grams): hel, ell, llo

Final tokens: [he, el, ll, lo, hel, ell, llo]

Field

Description

min_gram

google.protobuf.Int64Value

Minimum length of characters in a gram. Defaults to 3

max_gram

google.protobuf.Int64Value

Maximum length of characters in a gram. Defaults to 4

StandardTokenizer

A standard tokenizer that splits text on word boundaries and removes punctuation.
It follows the Unicode Text Segmentation rules as specified in Unicode Standard Annex #29.

Example:
Input text: Hello, world! How are you?
Output tokens: [Hello, world, How, are, you]

Field	Description
Empty

StandardAnalyzer

A standard analyzer that uses StandardTokenizer.

Field	Description
Empty

YandexLemmerAnalyzer

A specialized analyzer that uses Yandex's lemmatization technology to reduce words to their base forms.
Particularly effective for Russian and other Slavic languages, handling their complex morphology.
For more information, see:
https://yandex.cloud/en/docs/tutorials/dataplatform/opensearch-yandex-lemmer

Field	Description
Empty

VectorSearchIndex

Defines the configuration for a vector-based search index. This type uses embeddings to represent documents and queries.

Field	Description
doc_embedder_uri	string The ID of the model to be used for obtaining document text embeddings.
query_embedder_uri	string The ID of the model to be used for obtaining query text embeddings.
chunking_strategy	ChunkingStrategy Chunking strategy used to split text into smaller chunks before indexing. In the case of vector search, tokens are produced by the tokenizer from the embedding model.

HybridSearchIndex

Defines the configuration for a hybrid (vector-based + keyword-based) search index. This type uses both embeddings and keyword-based search to represent documents and queries.

Field	Description
text_search_index	TextSearchIndex Configuration for a traditional keyword-based text search index.
vector_search_index	VectorSearchIndex Configuration for a vector-based search index.
chunking_strategy	ChunkingStrategy Common chunking strategy that applies to both text and vector search indexes. If provided, it overrides the individual chunking strategies in both `text_search_index` and `vector_search_index`. In this case, both text and vector search will use token-based chunking, where tokens are produced by the tokenizer of the embedding model.
normalization_strategy	enum NormalizationStrategy Normalization strategy for relevance scores from different indices. Default is MIN_MAX_STRATEGY `NORMALIZATION_STRATEGY_UNSPECIFIED` `MIN_MAX`: https://en.wikipedia.org/wiki/Feature_scaling#Rescaling_(min-max_normalization) `L2`: https://en.wikipedia.org/wiki/Cosine_similarity#L2-normalized_Euclidean_distance
combination_strategy	CombinationStrategy Combination strategy for merging rankings from different indices. Default is arithmetic mean

CombinationStrategy

Combination strategy for merging rankings from different indices

Field

Description

mean_combination

MeanCombinationStrategy

Includes only one of the fields mean_combination, rrf_combination.

rrf_combination

ReciprocalRankFusionCombinationStrategy

Includes only one of the fields mean_combination, rrf_combination.

MeanCombinationStrategy

Field

Description

mean_evaluation_technique

enum MeanEvaluationTechnique

Technique for averaging relevance scores from different indices. Default is ARITHMETIC

MEAN_EVALUATION_TECHNIQUE_UNSPECIFIED
ARITHMETIC: https://en.wikipedia.org/wiki/Arithmetic_mean
GEOMETRIC: https://en.wikipedia.org/wiki/Geometric_mean
HARMONIC: https://en.wikipedia.org/wiki/Harmonic_mean

weights[]

double

Weights used for evaluating the weighted mean of relevance scores. The sum of the values must equal 1.0
If not provided, all scores are given equal weight

ReciprocalRankFusionCombinationStrategy

https://plg.uwaterloo.ca/~gvcormac/cormacksigir09-rrf.pdf

Field

Description

google.protobuf.Int64Value

The parameter k for RRFscore. Default is 60

File

Field	Description
id	string Unique identifier of the file.
folder_id	string ID of the folder that the file belongs to.
name	string Name of the file.
description	string Description of the file.
mime_type	string MIME type of the file, indicating the file's format (e.g., "application/pdf")
created_by	string Identifier of the subject who created this file.
created_at	google.protobuf.Timestamp Timestamp representing when the file was created.
updated_by	string Identifier of the subject who last updated this file.
updated_at	google.protobuf.Timestamp Timestamp representing the last time this file was updated.
expiration_config	ExpirationConfig Configuration for the expiration of the file, defining when and how the file will expire.
expires_at	google.protobuf.Timestamp Timestamp representing when the file will expire.
labels	object (map<string, string>) Set of key-value pairs that can be used to organize and categorize the file.

ChunkContent

Represents the content of a file chunk.

Field

Description

content[]

ContentPart

A list of content parts that make up the chunk.

ToolCallList

Represents a list of tool calls.

Field

Description

tool_calls[]

ToolCall

A list of tool calls to be executed.

ToolCall

Represents a call to a tool.

Field

Description

function_call

FunctionCall

Represents a call to a function.

Includes only one of the fields function_call.

FunctionCall

Represents the invocation of a function with specific arguments.

Field

Description

name

string

The name of the function being called.

arguments

google.protobuf.Struct

The structured arguments passed to the function.
These arguments must adhere to the JSON Schema defined in the corresponding function's parameters.

ContentUsage

Represents the content usage during a run, such as the number of tokens used by the completion model.

Field	Description
prompt_tokens	int64 The number of tokens used in the prompt.
completion_tokens	int64 The number of tokens used in the completion response.
total_tokens	int64 The total number of tokens used (prompt + completion).

PromptTruncationOptions

Defines the options for truncating thread messages within a prompt.

Field	Description
max_prompt_tokens	google.protobuf.Int64Value The maximum number of tokens allowed in the prompt. If the prompt exceeds this limit, the thread messages will be truncated. Default max_prompt_tokens: 7000
auto_strategy	AutoStrategy Includes only one of the fields `auto_strategy`, `last_messages_strategy`. Specifies the truncation strategy to use when the prompt exceeds the token limit.
last_messages_strategy	LastMessagesStrategy Retains only the last `num_messages` messages in the thread. If these messages exceed `max_prompt_tokens`, older messages will be further truncated to fit the limit. Includes only one of the fields `auto_strategy`, `last_messages_strategy`. Specifies the truncation strategy to use when the prompt exceeds the token limit.

AutoStrategy

Auto truncation strategy.

Field	Description
Empty

LastMessagesStrategy

Truncates the prompt by retaining only the last num_messages messages in the thread.

Field

Description

num_messages

int64

The number of most recent messages to retain in the prompt.
If these messages exceed max_prompt_tokens, older messages will be further truncated to fit the limit.

CompletionOptions

Defines the options for completion generation.

Field

Description

max_tokens

google.protobuf.Int64Value

The limit on the number of tokens used for single completion generation.
Must be greater than zero. This maximum allowed parameter value may depend on the model being used.

temperature

google.protobuf.DoubleValue

Tool

Represents a general tool that can be one of several types.

Field

Description

search_index

SearchIndexTool

SearchIndexTool tool that performs search across specified indexes.

Includes only one of the fields search_index, function.

function

FunctionTool

Function tool that can be invoked by the assistant.

Includes only one of the fields search_index, function.

SearchIndexTool

Configures a tool that enables Retrieval-Augmented Generation (RAG) by allowing the assistant to search across a specified search index.

Field	Description
search_index_ids[]	string A list of search index IDs that this tool will query. Currently, only a single index ID is supported.
max_num_results	google.protobuf.Int64Value The maximum number of results to return from the search. Fewer results may be returned if necessary to fit within the prompt's token limit. This ensures that the combined prompt and search results do not exceed the token constraints.
rephraser_options	RephraserOptions Options for rephrasing user queries. Used to rewrite the last user message for search, incorporating context from the previous conversation.

RephraserOptions

Options for configuring the rephrasing the last user message for search using context from previous conversation.

Field

Description

rephraser_uri

string

Required field. The ID of the model used to rephrase the last user message for search.

FunctionTool

Represents a function tool that can be invoked by the assistant.

Field	Description
name	string The name of the function.
description	string A description of the function's purpose or behavior.
parameters	google.protobuf.Struct A JSON Schema that defines the expected parameters for the function. The schema should describe the required fields, their types, and any constraints or default values.

Runs, gRPC: RunService.Create

gRPC requestgRPC request

CreateRunRequestCreateRunRequest

MessageDataMessageData

AuthorAuthor

MessageContentMessageContent

ContentPartContentPart

TextText

PromptTruncationOptionsPromptTruncationOptions

AutoStrategyAutoStrategy

LastMessagesStrategyLastMessagesStrategy

CompletionOptionsCompletionOptions

ToolTool

SearchIndexToolSearchIndexTool

RephraserOptionsRephraserOptions

FunctionToolFunctionTool

RunRun

RunStateRunState

ErrorError

MessageMessage

AuthorAuthor

MessageContentMessageContent

ContentPartContentPart

TextText

CitationCitation

SourceSource

FileChunkFileChunk

SearchIndexSearchIndex

ExpirationConfigExpirationConfig

TextSearchIndexTextSearchIndex

ChunkingStrategyChunkingStrategy

StaticChunkingStrategyStaticChunkingStrategy

NgramTokenizerNgramTokenizer

StandardTokenizerStandardTokenizer

StandardAnalyzerStandardAnalyzer

YandexLemmerAnalyzerYandexLemmerAnalyzer

VectorSearchIndexVectorSearchIndex

HybridSearchIndexHybridSearchIndex

CombinationStrategyCombinationStrategy

MeanCombinationStrategyMeanCombinationStrategy

ReciprocalRankFusionCombinationStrategyReciprocalRankFusionCombinationStrategy

FileFile

ChunkContentChunkContent

ToolCallListToolCallList

ToolCallToolCall

FunctionCallFunctionCall

ContentUsageContentUsage

PromptTruncationOptionsPromptTruncationOptions

AutoStrategyAutoStrategy

LastMessagesStrategyLastMessagesStrategy

CompletionOptionsCompletionOptions

ToolTool

SearchIndexToolSearchIndexTool

RephraserOptionsRephraserOptions

FunctionToolFunctionTool

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gRPC request

CreateRunRequest

MessageData

Author

MessageContent

ContentPart

Text

PromptTruncationOptions

AutoStrategy

LastMessagesStrategy

CompletionOptions

Tool

SearchIndexTool

RephraserOptions

FunctionTool

Run

RunState

Error

Message

Author

MessageContent

ContentPart

Text

Citation

Source

FileChunk

SearchIndex

ExpirationConfig

TextSearchIndex

ChunkingStrategy

StaticChunkingStrategy

NgramTokenizer

StandardTokenizer

StandardAnalyzer

YandexLemmerAnalyzer

VectorSearchIndex

HybridSearchIndex

CombinationStrategy

MeanCombinationStrategy

ReciprocalRankFusionCombinationStrategy

File

ChunkContent

ToolCallList

ToolCall

FunctionCall

ContentUsage

PromptTruncationOptions

AutoStrategy

LastMessagesStrategy

CompletionOptions

Tool

SearchIndexTool

RephraserOptions

FunctionTool