vignettes/getting-started/3/api.anthropic.com/v1/messages-441dab-POST.R

In tidyllm: Tidy Integration of Large Language Models

structure(list(method = "POST", url = "https://api.anthropic.com/v1/messages", 
    status_code = 200L, headers = structure(list(date = "Wed, 16 Oct 2024 00:52:01 GMT", 
        `content-type` = "application/json", `anthropic-ratelimit-requests-limit` = "50", 
        `anthropic-ratelimit-requests-remaining` = "49", `anthropic-ratelimit-requests-reset` = "2024-10-16T00:52:10Z", 
        `anthropic-ratelimit-tokens-limit` = "40000", `anthropic-ratelimit-tokens-remaining` = "40000", 
        `anthropic-ratelimit-tokens-reset` = "2024-10-16T00:52:01Z", 
        `request-id` = "req_01SoZo63WzaC9eP6vs7y8Sfb", `x-cloud-trace-context` = "90045c15ee7b45a1fced4842cea42ce4", 
        via = "1.1 google", `cf-cache-status` = "DYNAMIC", `x-robots-tag` = "none", 
        server = "cloudflare", `cf-ray` = "8d3410048e1e1cc9-FRA", 
        `content-encoding` = "gzip"), class = "httr2_headers"), 
    body = charToRaw("{\"id\":\"msg_01EeoWV2RPMZARvAgDyAdx7Q\",\"type\":\"message\",\"role\":\"assistant\",\"model\":\"claude-3-5-sonnet-20240620\",\"content\":[{\"type\":\"text\",\"text\":\"This plot shows a scatter plot with a linear regression line fitted to the data points. Here's an analysis of the plot and the provided data summary:\\n\\n1. Correlation: There's a strong positive linear relationship between x and y variables, as evidenced by the upward-sloping regression line and the clustering of points around it.\\n\\n2. Distribution:\\n   - X-axis: Values range from approximately -3 to 3\\n   - Y-axis: Values range from about -7 to 7\\n\\n3. Regression line: The blue line represents the best-fit linear regression line. The shaded area around it likely represents the confidence interval for the regression.\\n\\n4. Data summary:\\n   - X variable:\\n     * Range: -2.77 to 2.52\\n     * Mean: -0.06141 (close to 0)\\n     * Median: -0.17643 (slightly below 0)\\n   - Y variable:\\n     * Range: -7.07 to 6.75\\n     * Mean: 0.01294 (very close to 0)\\n     * Median: 0.20385 (slightly above 0)\\n\\n5. Spread: The interquartile range (IQR) for x is from -0.83 to 0.73, and for y is from -1.59 to 1.35, indicating a moderate spread of data.\\n\\n6. Symmetry: Both variables appear to be roughly symmetrically distributed around their means, which are close to zero. This suggests the possibility of a normal distribution for both x and y.\\n\\n7. Outliers: There are a few potential outliers, particularly at the extremes of both x and y axes, but they don't seem to strongly deviate from the overall trend.\\n\\n8. Model fit: The regression line appears to fit the data well, with most points falling close to the line and evenly distributed on both sides.\\n\\nIn conclusion, this plot demonstrates a strong positive linear relationship between x and y variables, with data that appears to be normally distributed and well-represented by the linear regression model.\"}],\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"usage\":{\"input_tokens\":494,\"output_tokens\":469}}"), 
    cache = new.env(parent = emptyenv())), class = "httr2_response")