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Copy file name to clipboardExpand all lines: docs/AdhocExecuteRequest.md
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**collection_identifiers** | **List[str]** | Collection identifiers (names or IDs) to query. Can be collection names or IDs. Names are automatically resolved. Can be empty for query-only inference mode (e.g., LLM query analysis without documents). | [optional]
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**input_schema** | [**Dict[str, RetrieverInputSchemaFieldInput]**](RetrieverInputSchemaFieldInput.md) | REQUIRED. Input schema defining expected inputs. Each key is an input name, value is a RetrieverInputSchemaField. |
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**stages** | [**List[StageConfig]**](StageConfig.md) | REQUIRED. Ordered list of stage configurations. At least one stage is required for execution. |
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**inputs** | **Dict[str, object]** | REQUIRED. Input values matching the input_schema. These values are passed to stages for parameterization. |
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**inputs** | **object** | REQUIRED. Input values matching the input_schema. These values are passed to stages for parameterization. |
**stream** | **bool** | Enable streaming execution to receive real-time stage updates via Server-Sent Events (SSE). NOT REQUIRED - defaults to False for standard execution. When stream=True: - Response Content-Type: text/event-stream - Events emitted: stage_start, stage_complete, stage_error, execution_complete, execution_error - Each event is formatted as: data: {json}\\n\\n - StreamStageEvent contains: event_type, execution_id, stage_name, stage_index, total_stages, documents (intermediate), statistics, budget_used When to use streaming: - Progress tracking for multi-stage pipelines - Displaying intermediate results as stages complete - Real-time budget and performance monitoring - Debugging pipeline execution When to skip streaming: - Single-stage or fast pipelines (<100ms) - No need for intermediate results - Minimizing overhead is critical | [optional][default to False]
Copy file name to clipboardExpand all lines: docs/AlgorithmParams.md
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**eps** | **float** | Maximum distance for DBSCAN cluster extraction method | [optional]
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**min_samples** | **int** | Number of samples in a neighborhood for a point to be considered a core point | [optional][default to 5]
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**metric** | **str** | Metric to use for distance computation | [optional][default to 'minkowski']
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**metric_params** | **Dict[str, object]** | Additional keyword arguments for the metric function | [optional]
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**metric_params** | **object** | Additional keyword arguments for the metric function | [optional]
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**leaf_size** | **int** | Leaf size passed to BallTree or KDTree | [optional][default to 30]
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**p** | **float** | Parameter for the Minkowski metric | [optional][default to 2]
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**n_jobs** | **int** | Number of parallel jobs to run (-1 means using all processors) | [optional][default to 1]
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**assign_labels** | **str** | Strategy to assign labels in the embedding space ('kmeans' or 'discretize') | [optional][default to 'kmeans']
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**degree** | **float** | Degree of the polynomial kernel. Ignored by other kernels | [optional][default to 3]
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**coef0** | **float** | Zero coefficient for polynomial and sigmoid kernels | [optional][default to 1]
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**kernel_params** | **Dict[str, object]** | Parameters for the kernel function | [optional]
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**kernel_params** | **object** | Parameters for the kernel function | [optional]
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**covariance_type** | **str** | Type of covariance parameters ('full', 'tied', 'diag', 'spherical') | [optional][default to 'full']
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**reg_covar** | **float** | Regularization added to the diagonal of covariance | [optional][default to 1.0E-6]
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**init_params** | **str** | Method used to initialize weights, means and covariances ('kmeans' or 'random') | [optional][default to 'kmeans']
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