> ## Documentation Index > Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt > Use this file to discover all available pages before exploring further. # Run hybrid search on a single index > Run hybrid search on one Pinecone index storing a dense and a sparse vector per record, weighting the two signals client-side with an alpha value. Store a dense vector and a sparse vector on each record in a single Pinecone index, then query both signals in one request. Pinecone combines them server-side. Because sparse (BM25-style) scores are unbounded, you set the balance between the two signals client-side, by scaling the query vectors before the request (an `alpha` weighting). This is the Vectors API single-index hybrid pattern. ## Normalize sparse and dense values A single index that stores both vector types doesn't reconcile their score ranges. Dense-vector scores fall in a bounded range (roughly `[-1, 1]` for `dotproduct` on unit-norm embeddings), while BM25-style sparse weights are unbounded and can run into double digits. Without explicit weighting, the sparse component dominates the combined score. To make the two signals comparable, apply a **convex combination** at query time using an `alpha` parameter: * `combined = alpha * dense + (1 - alpha) * sparse` * `alpha = 1.0` ranks by dense only (pure semantic). * `alpha = 0.0` ranks by sparse only (pure keyword). * `alpha = 0.5` weights the two signals equally. Pinecone applies this weighting by **scaling the query vectors before sending them to the index** (the index itself stores raw values). Use the [`hybrid_score_norm`](#hybrid-single-5-alpha) helper documented in the walkthrough below; it multiplies the dense values by `alpha` and the sparse values by `1 - alpha`, so the underlying dotproduct produces the desired combination. ### Choosing alpha There's no universal best value — alpha depends on your data and query distribution. Reasonable starting points: * **`alpha = 0.75`** (dense-leaning) — a good default for natural-language queries on conversational or document-style content. * **`alpha = 0.5`** (balanced) — useful when keyword and semantic signals contribute equally (e.g., mixed exact-match and synonym queries). * **`alpha = 0.25`** (sparse-leaning) — good for queries with high keyword specificity (product SKUs, technical IDs, named entities). We recommend evaluating multiple alpha values against a labeled relevance set drawn from your own workload. ## Set up and search To perform hybrid search with a single index that stores both dense and sparse vectors, follow these steps: To store both dense and sparse vectors in a single index, use the [`create_index`](/reference/api/2026-04/control-plane/create_index) operation, setting the `vector_type` to `dense` and the `metric` to `dotproduct`. This is the only combination that supports dense/sparse search on a single index. ```python Python theme={null} from pinecone.grpc import PineconeGRPC as Pinecone from pinecone import ServerlessSpec pc = Pinecone(api_key="YOUR_API_KEY") index_name = "hybrid-index" if not pc.has_index(index_name): pc.create_index( name=index_name, vector_type="dense", dimension=1024, metric="dotproduct", spec=ServerlessSpec( cloud="aws", region="us-east-1" ) ) ``` Use Pinecone's [hosted embedding models](/guides/index-data/create-an-index#embedding-models) to [convert data into dense and sparse vectors](/reference/api/latest/inference/generate-embeddings). ```python Python [expandable] theme={null} # Define the records data = [ { "_id": "vec1", "chunk_text": "Apple Inc. issued a $10 billion corporate bond in 2023." }, { "_id": "vec2", "chunk_text": "ETFs tracking the S&P 500 outperformed active funds last year." }, { "_id": "vec3", "chunk_text": "Tesla's options volume surged after the latest earnings report." }, { "_id": "vec4", "chunk_text": "Dividend aristocrats are known for consistently raising payouts." }, { "_id": "vec5", "chunk_text": "The Federal Reserve raised interest rates by 0.25% to curb inflation." }, { "_id": "vec6", "chunk_text": "Unemployment hit a record low of 3.7% in Q4 of 2024." }, { "_id": "vec7", "chunk_text": "The CPI index rose by 6% in July 2024, raising concerns about purchasing power." }, { "_id": "vec8", "chunk_text": "GDP growth in emerging markets outpaced developed economies." }, { "_id": "vec9", "chunk_text": "Amazon's acquisition of MGM Studios was valued at $8.45 billion." }, { "_id": "vec10", "chunk_text": "Alphabet reported a 20% increase in advertising revenue." }, { "_id": "vec11", "chunk_text": "ExxonMobil announced a special dividend after record profits." }, { "_id": "vec12", "chunk_text": "Tesla plans a 3-for-1 stock split to attract retail investors." }, { "_id": "vec13", "chunk_text": "Credit card APRs reached an all-time high of 22.8% in 2024." }, { "_id": "vec14", "chunk_text": "A 529 college savings plan offers tax advantages for education." }, { "_id": "vec15", "chunk_text": "Emergency savings should ideally cover 6 months of expenses." }, { "_id": "vec16", "chunk_text": "The average mortgage rate rose to 7.1% in December." }, { "_id": "vec17", "chunk_text": "The SEC fined a hedge fund $50 million for insider trading." }, { "_id": "vec18", "chunk_text": "New ESG regulations require companies to disclose climate risks." }, { "_id": "vec19", "chunk_text": "The IRS introduced a new tax bracket for high earners." }, { "_id": "vec20", "chunk_text": "Compliance with GDPR is mandatory for companies operating in Europe." }, { "_id": "vec21", "chunk_text": "What are the best-performing green bonds in a rising rate environment?" }, { "_id": "vec22", "chunk_text": "How does inflation impact the real yield of Treasury bonds?" }, { "_id": "vec23", "chunk_text": "Top SPAC mergers in the technology sector for 2024." }, { "_id": "vec24", "chunk_text": "Are stablecoins a viable hedge against currency devaluation?" }, { "_id": "vec25", "chunk_text": "Comparison of Roth IRA vs 401(k) for high-income earners." }, { "_id": "vec26", "chunk_text": "Stock splits and their effect on investor sentiment." }, { "_id": "vec27", "chunk_text": "Tech IPOs that disappointed in their first year." }, { "_id": "vec28", "chunk_text": "Impact of interest rate hikes on bank stocks." }, { "_id": "vec29", "chunk_text": "Growth vs. value investing strategies in 2024." }, { "_id": "vec30", "chunk_text": "The role of artificial intelligence in quantitative trading." }, { "_id": "vec31", "chunk_text": "What are the implications of quantitative tightening on equities?" }, { "_id": "vec32", "chunk_text": "How does compounding interest affect long-term investments?" }, { "_id": "vec33", "chunk_text": "What are the best assets to hedge against inflation?" }, { "_id": "vec34", "chunk_text": "Can ETFs provide better diversification than mutual funds?" }, { "_id": "vec35", "chunk_text": "Unemployment hit at 2.4% in Q3 of 2024." }, { "_id": "vec36", "chunk_text": "Unemployment is expected to hit 2.5% in Q3 of 2024." }, { "_id": "vec37", "chunk_text": "In Q3 2025 unemployment for the prior year was revised to 2.2%"}, { "_id": "vec38", "chunk_text": "Emerging markets witnessed increased foreign direct investment as global interest rates stabilized." }, { "_id": "vec39", "chunk_text": "The rise in energy prices significantly impacted inflation trends during the first half of 2024." }, { "_id": "vec40", "chunk_text": "Labor market trends show a declining participation rate despite record low unemployment in 2024." }, { "_id": "vec41", "chunk_text": "Forecasts of global supply chain disruptions eased in late 2024, but consumer prices remained elevated due to persistent demand." }, { "_id": "vec42", "chunk_text": "Tech sector layoffs in Q3 2024 have reshaped hiring trends across high-growth industries." }, { "_id": "vec43", "chunk_text": "The U.S. dollar weakened against a basket of currencies as the global economy adjusted to shifting trade balances." }, { "_id": "vec44", "chunk_text": "Central banks worldwide increased gold reserves to hedge against geopolitical and economic instability." }, { "_id": "vec45", "chunk_text": "Corporate earnings in Q4 2024 were largely impacted by rising raw material costs and currency fluctuations." }, { "_id": "vec46", "chunk_text": "Economic recovery in Q2 2024 relied heavily on government spending in infrastructure and green energy projects." }, { "_id": "vec47", "chunk_text": "The housing market saw a rebound in late 2024, driven by falling mortgage rates and pent-up demand." }, { "_id": "vec48", "chunk_text": "Wage growth outpaced inflation for the first time in years, signaling improved purchasing power in 2024." }, { "_id": "vec49", "chunk_text": "China's economic growth in 2024 slowed to its lowest level in decades due to structural reforms and weak exports." }, { "_id": "vec50", "chunk_text": "AI-driven automation in the manufacturing sector boosted productivity but raised concerns about job displacement." }, { "_id": "vec51", "chunk_text": "The European Union introduced new fiscal policies in 2024 aimed at reducing public debt without stifling growth." }, { "_id": "vec52", "chunk_text": "Record-breaking weather events in early 2024 have highlighted the growing economic impact of climate change." }, { "_id": "vec53", "chunk_text": "Cryptocurrencies faced regulatory scrutiny in 2024, leading to volatility and reduced market capitalization." }, { "_id": "vec54", "chunk_text": "The global tourism sector showed signs of recovery in late 2024 after years of pandemic-related setbacks." }, { "_id": "vec55", "chunk_text": "Trade tensions between the U.S. and China escalated in 2024, impacting global supply chains and investment flows." }, { "_id": "vec56", "chunk_text": "Consumer confidence indices remained resilient in Q2 2024 despite fears of an impending recession." }, { "_id": "vec57", "chunk_text": "Startups in 2024 faced tighter funding conditions as venture capitalists focused on profitability over growth." }, { "_id": "vec58", "chunk_text": "Oil production cuts in Q1 2024 by OPEC nations drove prices higher, influencing global energy policies." }, { "_id": "vec59", "chunk_text": "The adoption of digital currencies by central banks increased in 2024, reshaping monetary policy frameworks." }, { "_id": "vec60", "chunk_text": "Healthcare spending in 2024 surged as governments expanded access to preventive care and pandemic preparedness." }, { "_id": "vec61", "chunk_text": "The World Bank reported declining poverty rates globally, but regional disparities persisted." }, { "_id": "vec62", "chunk_text": "Private equity activity in 2024 focused on renewable energy and technology sectors amid shifting investor priorities." }, { "_id": "vec63", "chunk_text": "Population aging emerged as a critical economic issue in 2024, especially in advanced economies." }, { "_id": "vec64", "chunk_text": "Rising commodity prices in 2024 strained emerging markets dependent on imports of raw materials." }, { "_id": "vec65", "chunk_text": "The global shipping industry experienced declining freight rates in 2024 due to overcapacity and reduced demand." }, { "_id": "vec66", "chunk_text": "Bank lending to small and medium-sized enterprises surged in 2024 as governments incentivized entrepreneurship." }, { "_id": "vec67", "chunk_text": "Renewable energy projects accounted for a record share of global infrastructure investment in 2024." }, { "_id": "vec68", "chunk_text": "Cybersecurity spending reached new highs in 2024, reflecting the growing threat of digital attacks on infrastructure." }, { "_id": "vec69", "chunk_text": "The agricultural sector faced challenges in 2024 due to extreme weather and rising input costs." }, { "_id": "vec70", "chunk_text": "Consumer spending patterns shifted in 2024, with a greater focus on experiences over goods." }, { "_id": "vec71", "chunk_text": "The economic impact of the 2008 financial crisis was mitigated by quantitative easing policies." }, { "_id": "vec72", "chunk_text": "In early 2024, global GDP growth slowed, driven by weaker exports in Asia and Europe." }, { "_id": "vec73", "chunk_text": "The historical relationship between inflation and unemployment is explained by the Phillips Curve." }, { "_id": "vec74", "chunk_text": "The World Trade Organization's role in resolving disputes was tested in 2024." }, { "_id": "vec75", "chunk_text": "The collapse of Silicon Valley Bank raised questions about regulatory oversight in 2024." }, { "_id": "vec76", "chunk_text": "The cost of living crisis has been exacerbated by stagnant wage growth and rising inflation." }, { "_id": "vec77", "chunk_text": "Supply chain resilience became a top priority for multinational corporations in 2024." }, { "_id": "vec78", "chunk_text": "Consumer sentiment surveys in 2024 reflected optimism despite high interest rates." }, { "_id": "vec79", "chunk_text": "The resurgence of industrial policy in Q1 2024 focused on decoupling critical supply chains." }, { "_id": "vec80", "chunk_text": "Technological innovation in the fintech sector disrupted traditional banking in 2024." }, { "_id": "vec81", "chunk_text": "The link between climate change and migration patterns is increasingly recognized." }, { "_id": "vec82", "chunk_text": "Renewable energy subsidies in 2024 reduced the global reliance on fossil fuels." }, { "_id": "vec83", "chunk_text": "The economic fallout of geopolitical tensions was evident in rising defense budgets worldwide." }, { "_id": "vec84", "chunk_text": "The IMF's 2024 global outlook highlighted risks of stagflation in emerging markets." }, { "_id": "vec85", "chunk_text": "Declining birth rates in advanced economies pose long-term challenges for labor markets." }, { "_id": "vec86", "chunk_text": "Digital transformation initiatives in 2024 drove productivity gains in the services sector." }, { "_id": "vec87", "chunk_text": "The U.S. labor market's resilience in 2024 defied predictions of a severe recession." }, { "_id": "vec88", "chunk_text": "New fiscal measures in the European Union aimed to stabilize debt levels post-pandemic." }, { "_id": "vec89", "chunk_text": "Venture capital investments in 2024 leaned heavily toward AI and automation startups." }, { "_id": "vec90", "chunk_text": "The surge in e-commerce in 2024 was facilitated by advancements in logistics technology." }, { "_id": "vec91", "chunk_text": "The impact of ESG investing on corporate strategies has been a major focus in 2024." }, { "_id": "vec92", "chunk_text": "Income inequality widened in 2024 despite strong economic growth in developed nations." }, { "_id": "vec93", "chunk_text": "The collapse of FTX highlighted the volatility and risks associated with cryptocurrencies." }, { "_id": "vec94", "chunk_text": "Cyberattacks targeting financial institutions in 2024 led to record cybersecurity spending." }, { "_id": "vec95", "chunk_text": "Automation in agriculture in 2024 increased yields but displaced rural workers." }, { "_id": "vec96", "chunk_text": "New trade agreements signed 2022 will make an impact in 2024"}, ] ``` ```python Python theme={null} # Convert the chunk_text into dense vectors dense_embeddings = pc.inference.embed( model="llama-text-embed-v2", inputs=[d['chunk_text'] for d in data], parameters={"input_type": "passage", "truncate": "END"} ) # Convert the chunk_text into sparse vectors sparse_embeddings = pc.inference.embed( model="pinecone-sparse-english-v0", inputs=[d['chunk_text'] for d in data], parameters={"input_type": "passage", "truncate": "END"} ) ``` Use the [`upsert`](/reference/api/latest/data-plane/upsert) operation, specifying dense values in the `value` parameter and sparse values in the `sparse_values` parameter. Only indexes that store dense vectors with the [dotproduct distance metric](/guides/index-data/indexing-overview#dotproduct) accept records that also have sparse vectors. Upserting such records into an index with a different distance metric will succeed, but querying will return an error. ```Python Python theme={null} # Target the index # To get the unique host for an index, # see https://docs.pinecone.io/guides/manage-data/target-an-index index = pc.Index(host="INDEX_HOST") # Each record contains an ID, a dense vector, a sparse vector, and the original text as metadata records = [] for d, de, se in zip(data, dense_embeddings, sparse_embeddings): records.append({ "id": d['_id'], "values": de['values'], "sparse_values": {'indices': se['sparse_indices'], 'values': se['sparse_values']}, "metadata": {'text': d['chunk_text']} }) # Upsert the records into the index index.upsert( vectors=records, namespace="example-namespace" ) ``` Use the [`embed`](/reference/api/latest/inference/generate-embeddings) operation to convert your query into a dense vector and a sparse vector, and then use the [`query`](/reference/api/latest/data-plane/query) operation to search the index for the 40 most relevant records. ```Python Python theme={null} query = "Q3 2024 us economic data" # Convert the query into a dense vector dense_query_embedding = pc.inference.embed( model="llama-text-embed-v2", inputs=query, parameters={"input_type": "query", "truncate": "END"} ) # Convert the query into a sparse vector sparse_query_embedding = pc.inference.embed( model="pinecone-sparse-english-v0", inputs=query, parameters={"input_type": "query", "truncate": "END"} ) for d, s in zip(dense_query_embedding, sparse_query_embedding): query_response = index.query( namespace="example-namespace", top_k=40, vector=d['values'], sparse_vector={'indices': s['sparse_indices'], 'values': s['sparse_values']}, include_values=False, include_metadata=True ) print(query_response) ``` ```python Response [expandable] theme={null} {'matches': [{'id': 'vec35', 'metadata': {'text': 'Unemployment hit at 2.4% in Q3 of 2024.'}, 'score': 7.92519569, 'values': []}, {'id': 'vec46', 'metadata': {'text': 'Economic recovery in Q2 2024 relied ' 'heavily on government spending in ' 'infrastructure and green energy projects.'}, 'score': 7.86733627, 'values': []}, {'id': 'vec36', 'metadata': {'text': 'Unemployment is expected to hit 2.5% in Q3 ' 'of 2024.'}, 'score': 7.82636, 'values': []}, {'id': 'vec42', 'metadata': {'text': 'Tech sector layoffs in Q3 2024 have ' 'reshaped hiring trends across high-growth ' 'industries.'}, 'score': 7.79465914, 'values': []}, {'id': 'vec49', 'metadata': {'text': "China's economic growth in 2024 slowed to " 'its lowest level in decades due to ' 'structural reforms and weak exports.'}, 'score': 7.46323156, 'values': []}, {'id': 'vec63', 'metadata': {'text': 'Population aging emerged as a critical ' 'economic issue in 2024, especially in ' 'advanced economies.'}, 'score': 7.29055929, 'values': []}, {'id': 'vec92', 'metadata': {'text': 'Income inequality widened in 2024 despite ' 'strong economic growth in developed ' 'nations.'}, 'score': 6.51210213, 'values': []}, {'id': 'vec52', 'metadata': {'text': 'Record-breaking weather events in early ' '2024 have highlighted the growing economic ' 'impact of climate change.'}, 'score': 6.4125514, 'values': []}, {'id': 'vec62', 'metadata': {'text': 'Private equity activity in 2024 focused on ' 'renewable energy and technology sectors ' 'amid shifting investor priorities.'}, 'score': 4.8084693, 'values': []}, {'id': 'vec89', 'metadata': {'text': 'Venture capital investments in 2024 leaned ' 'heavily toward AI and automation ' 'startups.'}, 'score': 4.7974205, 'values': []}, {'id': 'vec57', 'metadata': {'text': 'Startups in 2024 faced tighter funding ' 'conditions as venture capitalists focused ' 'on profitability over growth.'}, 'score': 4.72518444, 'values': []}, {'id': 'vec37', 'metadata': {'text': 'In Q3 2025 unemployment for the prior year ' 'was revised to 2.2%'}, 'score': 4.71824408, 'values': []}, {'id': 'vec69', 'metadata': {'text': 'The agricultural sector faced challenges ' 'in 2024 due to extreme weather and rising ' 'input costs.'}, 'score': 4.66726208, 'values': []}, {'id': 'vec60', 'metadata': {'text': 'Healthcare spending in 2024 surged as ' 'governments expanded access to preventive ' 'care and pandemic preparedness.'}, 'score': 4.62045908, 'values': []}, {'id': 'vec55', 'metadata': {'text': 'Trade tensions between the U.S. and China ' 'escalated in 2024, impacting global supply ' 'chains and investment flows.'}, 'score': 4.59764862, 'values': []}, {'id': 'vec51', 'metadata': {'text': 'The European Union introduced new fiscal ' 'policies in 2024 aimed at reducing public ' 'debt without stifling growth.'}, 'score': 4.57397079, 'values': []}, {'id': 'vec70', 'metadata': {'text': 'Consumer spending patterns shifted in ' '2024, with a greater focus on experiences ' 'over goods.'}, 'score': 4.55043507, 'values': []}, {'id': 'vec87', 'metadata': {'text': "The U.S. labor market's resilience in 2024 " 'defied predictions of a severe recession.'}, 'score': 4.51785707, 'values': []}, {'id': 'vec90', 'metadata': {'text': 'The surge in e-commerce in 2024 was ' 'facilitated by advancements in logistics ' 'technology.'}, 'score': 4.47754288, 'values': []}, {'id': 'vec78', 'metadata': {'text': 'Consumer sentiment surveys in 2024 ' 'reflected optimism despite high interest ' 'rates.'}, 'score': 4.46246624, 'values': []}, {'id': 'vec53', 'metadata': {'text': 'Cryptocurrencies faced regulatory scrutiny ' 'in 2024, leading to volatility and reduced ' 'market capitalization.'}, 'score': 4.4435873, 'values': []}, {'id': 'vec45', 'metadata': {'text': 'Corporate earnings in Q4 2024 were largely ' 'impacted by rising raw material costs and ' 'currency fluctuations.'}, 'score': 4.43836403, 'values': []}, {'id': 'vec82', 'metadata': {'text': 'Renewable energy subsidies in 2024 reduced ' 'the global reliance on fossil fuels.'}, 'score': 4.43601322, 'values': []}, {'id': 'vec94', 'metadata': {'text': 'Cyberattacks targeting financial ' 'institutions in 2024 led to record ' 'cybersecurity spending.'}, 'score': 4.41334057, 'values': []}, {'id': 'vec47', 'metadata': {'text': 'The housing market saw a rebound in late ' '2024, driven by falling mortgage rates and ' 'pent-up demand.'}, 'score': 4.39900732, 'values': []}, {'id': 'vec41', 'metadata': {'text': 'Forecasts of global supply chain ' 'disruptions eased in late 2024, but ' 'consumer prices remained elevated due to ' 'persistent demand.'}, 'score': 4.37389421, 'values': []}, {'id': 'vec84', 'metadata': {'text': "The IMF's 2024 global outlook highlighted " 'risks of stagflation in emerging markets.'}, 'score': 4.37335157, 'values': []}, {'id': 'vec96', 'metadata': {'text': 'New trade agreements signed 2022 will make ' 'an impact in 2024'}, 'score': 4.33860636, 'values': []}, {'id': 'vec79', 'metadata': {'text': 'The resurgence of industrial policy in Q1 ' '2024 focused on decoupling critical supply ' 'chains.'}, 'score': 4.33784199, 'values': []}, {'id': 'vec6', 'metadata': {'text': 'Unemployment hit a record low of 3.7% in ' 'Q4 of 2024.'}, 'score': 4.33008051, 'values': []}, {'id': 'vec65', 'metadata': {'text': 'The global shipping industry experienced ' 'declining freight rates in 2024 due to ' 'overcapacity and reduced demand.'}, 'score': 4.3228569, 'values': []}, {'id': 'vec64', 'metadata': {'text': 'Rising commodity prices in 2024 strained ' 'emerging markets dependent on imports of ' 'raw materials.'}, 'score': 4.32269621, 'values': []}, {'id': 'vec95', 'metadata': {'text': 'Automation in agriculture in 2024 ' 'increased yields but displaced rural ' 'workers.'}, 'score': 4.31127262, 'values': []}, {'id': 'vec86', 'metadata': {'text': 'Digital transformation initiatives in 2024 ' 'drove productivity gains in the services ' 'sector.'}, 'score': 4.30181122, 'values': []}, {'id': 'vec66', 'metadata': {'text': 'Bank lending to small and medium-sized ' 'enterprises surged in 2024 as governments ' 'incentivized entrepreneurship.'}, 'score': 4.27241945, 'values': []}, {'id': 'vec58', 'metadata': {'text': 'Oil production cuts in Q1 2024 by OPEC ' 'nations drove prices higher, influencing ' 'global energy policies.'}, 'score': 4.21715498, 'values': []}, {'id': 'vec80', 'metadata': {'text': 'Technological innovation in the fintech ' 'sector disrupted traditional banking in ' '2024.'}, 'score': 4.17712116, 'values': []}, {'id': 'vec75', 'metadata': {'text': 'The collapse of Silicon Valley Bank raised ' 'questions about regulatory oversight in ' '2024.'}, 'score': 4.16192341, 'values': []}, {'id': 'vec56', 'metadata': {'text': 'Consumer confidence indices remained ' 'resilient in Q2 2024 despite fears of an ' 'impending recession.'}, 'score': 4.15782213, 'values': []}, {'id': 'vec67', 'metadata': {'text': 'Renewable energy projects accounted for a ' 'record share of global infrastructure ' 'investment in 2024.'}, 'score': 4.14623, 'values': []}], 'namespace': 'example-namespace', 'usage': {'read_units': 9}} ``` For a conceptual overview of why this normalization is needed, see [Normalize sparse and dense values](#normalize-sparse-and-dense-values). Because Pinecone views your sparse-dense vector as a single vector, it does not offer a built-in parameter to adjust the weight of a query's dense part against its sparse part; the index is agnostic to density or sparsity of coordinates in your vectors. You may, however, incorporate a linear weighting scheme by customizing your query vector, as demonstrated in the function below. The following example transforms vector values using an alpha parameter. ```Python Python theme={null} def hybrid_score_norm(dense, sparse, alpha: float): """Hybrid score using a convex combination alpha * dense + (1 - alpha) * sparse Args: dense: Array of floats representing sparse: a dict of `indices` and `values` alpha: scale between 0 and 1 """ if alpha < 0 or alpha > 1: raise ValueError("Alpha must be between 0 and 1") hs = { 'indices': sparse['indices'], 'values': [v * (1 - alpha) for v in sparse['values']] } return [v * alpha for v in dense], hs ``` The following example transforms a vector using the above function, then queries a Pinecone index. ```Python Python theme={null} sparse_vector = { 'indices': [10, 45, 16], 'values': [0.5, 0.5, 0.2] } dense_vector = [0.1, 0.2, 0.3] hdense, hsparse = hybrid_score_norm(dense_vector, sparse_vector, alpha=0.75) query_response = index.query( namespace="example-namespace", top_k=10, vector=hdense, sparse_vector=hsparse ) ```