Sergey Kulik
beb17f1ea0
lint PR / linter (push) Has been cancelled
GitOrigin-RevId: bf7b49270b31b4e793d220f5f2b791b34e3521e5
95 lines
3.6 KiB
YAML
95 lines
3.6 KiB
YAML
# This YAML configuration file sets up the TwelveLabs video RAG template.
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# It indexes videos by turning them into text with the TwelveLabs Pegasus model,
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# embedding that text with the TwelveLabs Marengo model, and serving a RAG
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# question-answering endpoint on top.
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# You can learn more about the YAML syntax here:
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# https://pathway.com/developers/templates/configure-yaml
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# $sources defines the data sources read and indexed in the RAG.
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# Here we read video files from the local `data` directory. The connector emits
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# raw bytes, which the TwelveLabs parser sends to Pegasus for analysis.
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# You can learn more about configuring data sources here:
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# https://pathway.com/developers/templates/yaml-examples/data-sources-examples
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$sources:
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- !pw.io.fs.read
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path: data
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format: binary
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with_metadata: true
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# Uncomment to use the Google Drive connector to index videos from a Drive folder.
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# - !pw.io.gdrive.read
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# object_id: $DRIVE_ID
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# service_user_credentials_file: gdrive_indexer.json
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# file_name_pattern:
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# - "*.mp4"
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# - "*.mov"
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# object_size_limit: null
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# with_metadata: true
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# refresh_interval: 30
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# The parser turns each video into text using the TwelveLabs Pegasus model.
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# The TWELVELABS_API_KEY environment variable must be set (see .env.example).
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# You can customize the prompt to extract exactly what your application needs.
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$parser: !pw.xpacks.llm.parsers.TwelveLabsVideoParser
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model: "pegasus1.5"
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max_tokens: 2048
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cache_strategy: !pw.udfs.DefaultCache {}
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# Uncomment so that a single malformed video does not halt the pipeline:
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# on_error: "skip"
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# prompt: "Describe this video, focusing on the products that appear and any prices shown."
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# The embedder converts the parsed text into 512-dimensional multimodal
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# embeddings using the TwelveLabs Marengo model.
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$embedder: !pw.xpacks.llm.embedders.MarengoEmbedder
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model: "marengo3.0"
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cache_strategy: !pw.udfs.DefaultCache {}
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retry_strategy: !pw.udfs.ExponentialBackoffRetryStrategy {}
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# Splits the parsed video descriptions into chunks for indexing.
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$splitter: !pw.xpacks.llm.splitters.TokenCountSplitter
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max_tokens: 400
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# The LLM used to answer questions over the indexed video descriptions.
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# The list of available Pathway LLM wrappers is available here:
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# https://pathway.com/developers/api-docs/pathway-xpacks-llm/llms
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$llm: !pw.xpacks.llm.llms.OpenAIChat
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model: "gpt-4.1-mini"
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retry_strategy: !pw.udfs.ExponentialBackoffRetryStrategy
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max_retries: 6
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cache_strategy: !pw.udfs.DefaultCache {}
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temperature: 0
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capacity: 8
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async_mode: "fully_async"
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# Builds the in-memory vector index over the Marengo embeddings.
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$retriever_factory: !pw.indexing.UsearchKnnFactory
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reserved_space: 1000
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embedder: $embedder
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metric: !pw.indexing.USearchMetricKind.COS
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# Stores and retrieves the indexed video descriptions.
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$document_store: !pw.xpacks.llm.document_store.DocumentStore
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docs: $sources
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parser: $parser
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splitter: $splitter
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retriever_factory: $retriever_factory
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# The RAG question-answering component served over HTTP.
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question_answerer: !pw.xpacks.llm.question_answering.BaseRAGQuestionAnswerer
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llm: $llm
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indexer: $document_store
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# You can set the number of documents to be included as the context of the query
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# search_topk: 6
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# You can use your own prompt for querying.
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# prompt_template: "Given these documents: {context}, please answer the question: {query}"
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# Change host and port of the webserver by uncommenting these lines
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# host: "0.0.0.0"
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# port: 8000
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# By default, caching is enabled for UDFs with cache_strategy set.
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# You can disable it by uncommenting the following line.
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# persistence_mode: null
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