0.3.0

Author: pwwang

.Rbuildignore

@@ -2,6 +2,8 @@
 ^pkgdown\/.+
 ^CRAN-SUBMISSION$
 ^cran-comments\.md$
+^vignettes\/articles$
+^vignettes\/Rplots\.pdf$
 ^docs/\.nojekyll$
 ^\.github\/.+
 ^\.github$

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: scplotter
 Title: Publication Quality Plots for Single Cell Data Analysis
-Version: 0.2.2
+Version: 0.3.0
 Authors@R:
     person("Panwen", "Wang", , "pwwang@pwwang.com", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-4614-8970"))

conda/meta.yaml

@@ -1,10 +1,9 @@
 package:
   name: r-scplotter
-  version: 0.2.2
+  version: 0.3.0
 
 source:
-  git_url: https://github.com/pwwang/scplotter
-  git_rev: 0.2.2
+  path: ..
 
 build:
   number: 1
@@ -15,6 +14,7 @@ build:
 requirements:
   host:
     - r-base
+    - r-callr
     - r-circlize
     - r-clustree
     - r-concaveman
@@ -43,18 +43,22 @@ requirements:
     - r-stringr
     - r-tidyr
     - bioconda::bioconductor-complexheatmap
-    - pwwang::r-plotthis
     - pwwang::r-gglogger
+    - pwwang::r-plotthis
+    - pwwang::r-tidyprompt
     - pwwang::bioconductor-screpertoire
 
   run:
     - r-base
+    - r-callr
     - r-circlize
     - r-clustree
     - r-concaveman
     - r-dplyr
     - r-ggalluvial
     - r-ggforce
+    - r-ggnewscale
+    - r-ggplot2
     - r-ggpubr
     - r-ggraph
     - r-ggridges
@@ -66,11 +70,18 @@ requirements:
     - r-metap
     - r-igraph
     - r-inext
+    - r-r6
+    - r-rlang
+    - r-scales
     - r-scattermore
     - r-seurat
     - r-seuratobject
+    - r-stringr
+    - r-tidyr
     - bioconda::bioconductor-complexheatmap
+    - pwwang::r-gglogger
     - pwwang::r-plotthis
+    - pwwang::r-tidyprompt
     - pwwang::bioconductor-screpertoire
 
 test:

vignettes/Visualizing_data_with_LLMs.Rmd

@@ -16,6 +16,7 @@ knitr::opts_chunk$set(
 
 ```{r setup}
 library(scplotter)
+api_key_set <- !identical(Sys.getenv("OPENAI_API_KEY"), "")
 ```
 
 # Introduction
@@ -26,7 +27,7 @@ This vignette demonstrates how to use the `scplotter` package to visualize data
 
 `scplotter` uses `tidyprompt` to provide a unified interface for different LLM providers. You can set up your preferred LLM provider using one of the [wrappers](https://tjarkvandemerwe.github.io/tidyprompt/reference/index.html#llm-providers-chat-history) provided by `tidyprompt`.
 
-```{r}
+```{r, eval = api_key_set}
 # Set up LLM provider
 provider <- tidyprompt::llm_provider_openai(
     parameters = list(model = "gpt-4o-mini", stream = getOption("tidyprompt.stream", TRUE)),
@@ -44,15 +45,15 @@ By default, `chat` will detects the data used for visualization from the `.Globa
 
 You can also ask to list the available data:
 
-```{r}
+```{r, eval = api_key_set}
 chat$ask("List the available data that can be used for visualization.")
 # or you can do it explicitly
 # chat$list_data()
 ```
 
 To set up the data manually, you can use the `set_data()` method.
 
-```{r}
+```{r, eval = api_key_set}
 chat$set_data(scplotter::cellphonedb_res)
 # To let the LLM to detect the data from the prompt again:
 chat$set_data(NULL)
@@ -64,7 +65,7 @@ To use your own data, you can either set the data manually or use the `set_data(
 
 You can list the available functions by using the `list_tools()` method.
 
-```{r}
+```{r, eval = api_key_set}
 chat$list_tools()
 # or you can ask the LLM to list the available functions
 # chat$ask("List the available functions for visualizing data.")
@@ -75,20 +76,20 @@ The tool used for the visualization is determined by the LLM automatically from
 # Visualize the data
 You can visualize the data by using the `ask()` method. The LLM will automatically detect the data and the function to be used for visualization.
 
-```{r fig.width=7, fig.height=5}
+```{r, eval = api_key_set, fig.width=7, fig.height=5}
 chat$ask("Generate a cell-cell communication plot for the cellphonedb_res data.")
 ```
 
-```{r fig.width=7, fig.height=6}
+```{r, eval = api_key_set, fig.width=7, fig.height=6}
 # Previous conversation is memorized
 chat$ask("Do a heatmap instead")
 ```
 
-```{r fig.width=7, fig.height=6}
+```{r, eval = api_key_set, fig.width=7, fig.height=6}
 chat$ask("Add a title to the plot: 'Cell-Cell Communication Plot'")
 ```
 
-```{r}
+```{r, eval = api_key_set}
 # To fetch the previous conversation
 # Note that the response from the LLM is simplified in the history
 chat$get_history()
@@ -101,7 +102,7 @@ chat$clear_history()
 
 You can set `verbose` to `TRUE` for all conversations when constructing the `chat` object. This will print the prompt and the response from the LLM.
 
-```{r fig.width=7, fig.height=5}
+```{r, eval = api_key_set, fig.width=7, fig.height=5}
 chat <- SCPlotterChat$new(
     provider = provider,
     verbose = TRUE
@@ -111,7 +112,7 @@ chat$ask("Generate a cell-cell communication plot for the cellphonedb_res data."
 
 To only debug a single conversation, you can set `verbose` to `TRUE` in the `ask()` method.
 
-```{r fig.width=7, fig.height=5}
+```{r, eval = api_key_set, fig.width=7, fig.height=5}
 chat <- SCPlotterChat$new(
     provider = provider,
     verbose = FALSE