Enable GoogleGenAI extension (#111)

CHANGELOG.md

@@ -8,6 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 - Added support for `aigenerate` with Anthropic API. Preset model aliases are `claudeo`, `claudes`, and `claudeh`, for Claude 3 Opus, Sonnet, and Haiku, respectively.
+- Enabled the GoogleGenAI extension since `GoogleGenAI.jl` is now officially registered. You can use `aigenerate` by setting the model to `gemini` and providing the `GOOGLE_API_KEY` environment variable.
 
 ### Fixed
 

Project.toml

@@ -1,7 +1,7 @@
 name = "PromptingTools"
 uuid = "670122d1-24a8-4d70-bfce-740807c42192"
 authors = ["J S @svilupp and contributors"]
-version = "0.16.1"
+version = "0.17.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -17,11 +17,13 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [weakdeps]
+GoogleGenAI = "903d41d1-eaca-47dd-943b-fee3930375ab"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [extensions]
+GoogleGenAIPromptingToolsExt = ["GoogleGenAI"]
 MarkdownPromptingToolsExt = ["Markdown"]
 RAGToolsExperimentalExt = ["SparseArrays", "LinearAlgebra"]
 

README.md

@@ -99,6 +99,7 @@ For more practical examples, see the `examples/` folder and the [Advanced Exampl
   - [Package Interface](#package-interface)
   - [Frequently Asked Questions](#frequently-asked-questions)
     - [Why OpenAI](#why-openai)
+    - [What if I cannot access OpenAI?](#what-if-i-cannot-access-openai)
     - [Data Privacy and OpenAI](#data-privacy-and-openai)
     - [Creating OpenAI API Key](#creating-openai-api-key)
     - [Setting OpenAI Spending Limits](#setting-openai-spending-limits)
@@ -673,6 +674,13 @@ There will be situations not or cannot use it (eg, privacy, cost, etc.). In that
 
 Note: To get started with [Ollama.ai](https://ollama.ai/), see the [Setup Guide for Ollama](#setup-guide-for-ollama) section below.
 
+### What if I cannot access OpenAI?
+
+There are many alternatives:
+
+- **Other APIs**: MistralAI, Anthropic, Google, Together, Fireworks, Voyager (the latter ones tend to give free credits upon joining!)
+- **Locally-hosted models**: Llama.cpp/Llama.jl, Ollama, vLLM (see the examples and the corresponding docs)
+
 ### Data Privacy and OpenAI
 
 At the time of writing, OpenAI does NOT use the API calls for training their models.

docs/Project.toml

@@ -2,6 +2,7 @@
 DataFramesMeta = "1313f7d8-7da2-5740-9ea0-a2ca25f37964"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DocumenterVitepress = "4710194d-e776-4893-9690-8d956a29c365"
+GoogleGenAI = "903d41d1-eaca-47dd-943b-fee3930375ab"
 HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
 JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

docs/src/examples/working_with_google_ai_studio.md

@@ -6,20 +6,12 @@ Get an API key from [here](https://ai.google.dev/). If you see a documentation p
 
 Save the API key in your environment as `GOOGLE_API_KEY`.
 
-We'll need `GoogleGenAI.jl` package:
+We'll need `GoogleGenAI` package:
 
 ````julia
-using Pkg; Pkg.add(url="https://github.com/tylerjthomas9/GoogleGenAI.jl/")
+using Pkg; Pkg.add("GoogleGenAI")
 ````
 
-> [!WARNING]
-> This tutorial is DISABLED FOR NOW, because GoogleGenAI.jl is NOT a registered package yet and, hence, we cannot have an extension for it.
-> 
-> If you want to use Google models, you need to install GoogleGenAI and add the following file to `[extensions]` section in Project.toml:
-> `GoogleGenAIPromptingToolsExt = ["GoogleGenAI"]
->
-> Save the Project.toml changes and restart Julia. You can now use GoogleGenAI models with PromptingTools as shown below.
-
 You can now use the Gemini-1.0-Pro model like any other model in PromptingTools. We **only support `aigenerate`** at the moment.
 
 Let's import PromptingTools:

docs/src/frequently_asked_questions.md

@@ -8,6 +8,13 @@ There will be situations not or cannot use it (eg, privacy, cost, etc.). In that
 
 Note: To get started with [Ollama.ai](https://ollama.ai/), see the [Setup Guide for Ollama](#setup-guide-for-ollama) section below.
 
+### What if I cannot access OpenAI?
+
+There are many alternatives:
+
+- **Other APIs**: MistralAI, Anthropic, Google, Together, Fireworks, Voyager (the latter ones tend to give free credits upon joining!)
+- **Locally-hosted models**: Llama.cpp/Llama.jl, Ollama, vLLM (see the examples and the corresponding docs)
+
 ## Data Privacy and OpenAI
 
 At the time of writing, OpenAI does NOT use the API calls for training their models.

ext/GoogleGenAIPromptingToolsExt.jl

@@ -9,23 +9,9 @@ const PT = PromptingTools
 function PromptingTools.ggi_generate_content(prompt_schema::PT.AbstractGoogleSchema,
         api_key::AbstractString, model_name::AbstractString,
         conversation; http_kwargs, api_kwargs...)
-    ## Build the provider
-    provider = GoogleGenAI.GoogleProvider(; api_key)
-    url = "$(provider.base_url)/models/$model_name:generateContent?key=$(provider.api_key)"
-    generation_config = Dict{String, Any}()
-    for (key, value) in api_kwargs
-        generation_config[string(key)] = value
-    end
-
-    body = Dict("contents" => conversation,
-        "generationConfig" => generation_config)
-    response = HTTP.post(url; headers = Dict("Content-Type" => "application/json"),
-        body = JSON3.write(body), http_kwargs...)
-    if response.status >= 200 && response.status < 300
-        return GoogleGenAI._parse_response(response)
-    else
-        error("Request failed with status $(response.status): $(String(response.body))")
-    end
+    ## TODO: Ignores http_kwargs for now, needs upstream change
+    r = GoogleGenAI.generate_content(api_key, model_name, conversation; api_kwargs...)
+    return r
 end
 
 end # end of module

src/llm_anthropic.jl

@@ -260,3 +260,7 @@ function aiscan(prompt_schema::AbstractAnthropicSchema, prompt::ALLOWED_PROMPT_T
         kwargs...)
     error("Anthropic schema does not yet support aiscan. Please use OpenAISchema instead.")
 end
+function aiimage(prompt_schema::AbstractAnthropicSchema, prompt::ALLOWED_PROMPT_TYPE;
+        kwargs...)
+    error("Anthropic schema does not yet support aiimage. Please use OpenAISchema instead.")
+end

src/llm_google.jl

@@ -20,7 +20,7 @@ function render(schema::AbstractGoogleSchema,
     messages_replaced = render(NoSchema(), messages; conversation, kwargs...)
 
     ## Second pass: convert to the OpenAI schema
-    conversation = Dict{String, Any}[]
+    conversation = Dict{Symbol, Any}[]
 
     # replace any handlebar variables in the messages
     for msg in messages_replaced
@@ -32,21 +32,21 @@ function render(schema::AbstractGoogleSchema,
         elseif msg isa AIMessage
             "model"
         end
-        push!(conversation, Dict("role" => role, "parts" => [Dict("text" => msg.content)]))
+        push!(conversation, Dict(:role => role, :parts => [Dict("text" => msg.content)]))
     end
     ## Merge any subsequent UserMessages
-    merged_conversation = Dict{String, Any}[]
+    merged_conversation = Dict{Symbol, Any}[]
     # run n-1 times, look at the current item and the next one
     i = 1
     while i <= (length(conversation) - 1)
         next_i = i + 1
-        if conversation[i]["role"] == "user" && conversation[next_i]["role"] == "user"
+        if conversation[i][:role] == "user" && conversation[next_i][:role] == "user"
             ## Concat the user messages to together, put two newlines
-            txt1 = conversation[i]["parts"][1]["text"]
-            txt2 = conversation[next_i]["parts"][1]["text"]
+            txt1 = conversation[i][:parts][1]["text"]
+            txt2 = conversation[next_i][:parts][1]["text"]
             merged_text = isempty(txt1) || isempty(txt2) ? txt1 * txt2 :
                           txt1 * "\n\n" * txt2
-            new_msg = Dict("role" => "user", "parts" => [Dict("text" => merged_text)])
+            new_msg = Dict(:role => "user", :parts => [Dict("text" => merged_text)])
             push!(merged_conversation, new_msg)
             i += 2
         else
@@ -178,7 +178,7 @@ function aigenerate(prompt_schema::AbstractGoogleSchema, prompt::ALLOWED_PROMPT_
         output_token_estimate = length(r.text)
         msg = AIMessage(;
             content = r.text |> strip,
-            status = 200,
+            status = convert(Int, r.response_status),
             ## for google it's CHARACTERS, not tokens
             tokens = (input_token_estimate, output_token_estimate),
             elapsed = time)
@@ -198,3 +198,24 @@ function aigenerate(prompt_schema::AbstractGoogleSchema, prompt::ALLOWED_PROMPT_
 
     return output
 end
+
+function aiembed(prompt_schema::AbstractGoogleSchema, prompt::ALLOWED_PROMPT_TYPE;
+        kwargs...)
+    error("Google schema does not yet support aiembed. Please use OpenAISchema instead.")
+end
+function aiclassify(prompt_schema::AbstractGoogleSchema, prompt::ALLOWED_PROMPT_TYPE;
+        kwargs...)
+    error("Google schema does not yet support aiclassify. Please use OpenAISchema instead.")
+end
+function aiextract(prompt_schema::AbstractGoogleSchema, prompt::ALLOWED_PROMPT_TYPE;
+        kwargs...)
+    error("Google schema does not yet support aiextract. Please use OpenAISchema instead.")
+end
+function aiscan(prompt_schema::AbstractGoogleSchema, prompt::ALLOWED_PROMPT_TYPE;
+        kwargs...)
+    error("Google schema does not yet support aiscan. Please use OpenAISchema instead.")
+end
+function aiimage(prompt_schema::AbstractGoogleSchema, prompt::ALLOWED_PROMPT_TYPE;
+        kwargs...)
+    error("Google schema does not yet support aiimage. Please use OpenAISchema instead.")
+end

src/llm_interface.jl

@@ -246,7 +246,7 @@ struct GoogleSchema <: AbstractGoogleSchema end
 "Echoes the user's input back to them. Used for testing the implementation"
 @kwdef mutable struct TestEchoGoogleSchema <: AbstractGoogleSchema
     text::Any
-    status::Integer
+    response_status::Integer
     model_id::String = ""
     inputs::Any = nothing
 end

test/llm_anthropic.jl

@@ -153,4 +153,12 @@ end
     @test schema2.inputs.system == "Act as a helpful AI assistant"
     @test schema2.inputs.messages == [Dict("role" => "user", "content" => "Hello World")]
     @test schema2.model_id == "claude-3-sonnet-20240229"
-end
+end
+
+@testset "not implemented ai* functions" begin
+    @test_throws ErrorException aiembed(AnthropicSchema(), "prompt")
+    @test_throws ErrorException aiextract(AnthropicSchema(), "prompt")
+    @test_throws ErrorException aiclassify(AnthropicSchema(), "prompt")
+    @test_throws ErrorException aiscan(AnthropicSchema(), "prompt")
+    @test_throws ErrorException aiimage(AnthropicSchema(), "prompt")
+end