new chatgpt account, free usage, doesn't say the model strangely. wanted a
different viewpoint on my small design decision.
hi chatgpt.
i drafted a c++ interface to the openai api with qwen2.5 .
I'll paste it here for completeness:
$ cat include/zinc/openai.hpp
#pragma once
#include <generator> // C++23 generator support in GCC 14+
#include <span>
#include <string>
#include <string_view>
#include <unordered_map>
#include <vector>
namespace zinc {
class OpenAI {
public:
/**
* @brief Constructor for initializing the OpenAI client.
*
* Common parameter names include:
* - max_tokens: Maximum number of tokens to generate.
* - temperature: Controls randomness of predictions.
* - top_p: Nucleus sampling parameter.
* - stop: Sequence where the model will stop generating further tokens.
* - presence_penalty: Penalizes new tokens based on their existing
frequency.
* - frequency_penalty: Penalizes new tokens based on their existing
frequency.
*
* @param url The base URL of the API endpoint (e.g.,
"https://api.openai.com";).
* @param model The model name to be used (e.g., "text-davinci-003").
* @param key The API key for authentication.
* @param defaults A span of pairs representing default parameters for
requests.
*/
OpenAI(
std::string_view url,
std::string_view model,
std::string_view key,
std::span<std::pair<std::string_view, std::string_view> const> defaults
= {}
);
/**
* @brief Destructor for the OpenAI class.
*/
~OpenAI();
struct CompletionItem {
std::string_view text; // Actual generated text
std::unordered_map<std::string_view, std::string_view> const data; //
Raw data returned by the server
operator std::string_view() const { return text; }
};
/**
* @brief Generate a single completion based on a prompt.
*/
std::generator<CompletionItem const&> gen_completion(std::string_view
prompt, std::span<std::pair<std::string_view, std::string_view> const> params =
{}) const;
/**
* @brief Generate multiple completions based on a prompt.
*
* @param completions The number of completions to generate (must be >= 2).
*/
std::generator<std::span<CompletionItem const>>
gen_completions(std::string_view prompt, size_t completions,
std::span<std::pair<std::string_view, std::string_view> const> params = {})
const;
/**
* @brief Generate a single chat completion based on a series of messages.
*
* @param messages A span of pairs representing role-content messages.
*/
std::generator<CompletionItem const&>
gen_chat(std::span<std::pair<std::string_view, std::string_view> const>
messages, std::span<std::pair<std::string_view, std::string_view> const> params
= {}) const;
/**
* @brief Generate multiple chat completions based on a series of messages.
*
* @param messages A span of pairs representing role-content messages.
* @param completions The number of completions to generate (must be >= 2).
*/
std::generator<std::span<CompletionItem const>>
gen_chats(std::span<std::pair<std::string_view, std::string_view> const>
messages, size_t completions, std::span<std::pair<std::string_view,
std::string_view> const> params = {}) const;
private:
std::string endpoint_completions_;
std::string endpoint_chats_;
std::string bearer_;
std::unordered_map<std::string, std::string> defaults_;
};
} // namespace zinc
It's an interface to the streaming api written in c++23/26, so it uses
std::generator to output the streamed response.
The problem is with the parameters being specified as strings. OpenAI's api
takes JSON parameters of various types, string, int, bool. But here the user
has to pass them all as strings. I'm not sure how they should be converted
under the hood (this is a compile error I ran into).
Initial ideas include:
- using a variant type to hold multiple types
- having multiple lists or maps or spans of parameters, one for strings, one
for numbers, one for bool
- parsing the strings the user provides
- exposing json types in the interface
Do you have any other ideas?
Basically, stay with me, give short replies, and let's figure out how to
improve this interface.
I don't really want to expose json types in the interface because then the
header gets heavier and a user needs to have the json dependency to use it.
I also don't really like parsing the strings because it's not very efficient
and direct, I like how c++ can be very efficient and direct. But I like it
better than #including the json dependencies in the header interface.
But my opinions can change!
I'm just not quite sure what to do cause I think slowly. Give me some company
around it.
ChatGPT said:
ChatGPT
Gotcha, let's work this through! Your concerns are valid, and it's great you're
thinking about efficiency and usability. Here's a quick breakdown of ideas and
trade-offs:
1. Variant Type
Use std::variant to hold std::string, int, bool, etc.
Pro: Keeps the API flexible and type-safe.
Con: Adds complexity to user code because they'll need to construct
std::variants.
2. Separate Maps/Spans for Each Type
Pass std::span<std::pair<std::string_view, int>> for numbers, another for
booleans, etc.
Pro: Clear and efficient, no parsing needed.
Con: Adds more arguments to the function signatures, and managing multiple maps
could be clunky for users.
3. String Parsing
Parse the user-provided strings to deduce the actual types at runtime.
Pro: Simple interface; users can just use strings.
Con: Inefficient, fragile, and less "C++-like."
4. Expose JSON-Like Type Without Full Dependency
Use something lightweight like a custom Variant type (or any) to represent
JSON-like data, but avoid pulling in a full JSON library.
Pro: Minimal dependency; still supports mixed types.
Con: Needs a bit of custom work on your side.
My Suggestion
Lean towards std::variant. It's modern, type-safe, and doesn't overcomplicate
things. You can provide convenience overloads or helper functions for users to
easily construct these std::variants, which keeps it approachable.
If you’re leaning away from variants or still undecided, let me know, and we’ll
explore one of the alternatives deeper. What's your gut feeling so far?
You said:
More ideas:
- we could use any like you suggest rather than variant
- the interface could accept a long exhaustive list of literal parameters
rather than an arbitrary set
- the interface could take a configuration struct with exhaustive members
instead of an arbitrary list
- the parameters could have member functions to set them rather than being
passed in the constructor
ChatGPT said:
ChatGPT
Great ideas—let's break those down quickly, too:
1. Using std::any
Pros: Extremely flexible—users can pass any type without worrying about
specifying a variant or struct.
Cons: Requires type-checking and casting at runtime. Less type-safe than
std::variant and can lead to runtime errors if misused.
2. Exhaustive List of Literal Parameters
Pros: Simple and very explicit. Users only pass what’s supported, making the
API less error-prone.
Cons: Not future-proof—adding a new parameter requires changing the API. Feels
inflexible, especially for OpenAI APIs, where parameters may change.
3. Configuration Struct with Exhaustive Members
Pros: Clear and intuitive. A single struct makes the API clean, and adding new
parameters only requires updating the struct definition. It can have default
values for unused parameters.
Cons: Users must recompile to adapt to API changes. It’s not as flexible for
dynamic cases where parameters vary across calls.
4. Using Member Functions for Parameters
Pros: Very C++-idiomatic. You can chain calls
(params.set_temperature(0.7).set_max_tokens(100)), which is neat and
user-friendly.
Cons: A bit verbose to implement. Might not be great for complex dynamic
parameter sets unless combined with a std::unordered_map for non-exhaustive
params.
My Take:
For Simplicity: Go with the configuration struct. It strikes a good balance
between clarity and future maintainability.
For Flexibility: Use member functions for parameters combined with a
std::unordered_map for arbitrary/optional params. This gives you a nice hybrid
of structured and dynamic interfaces.
You could even mix both—use a struct for common/exhaustive params and allow
"extra" parameters as a map.
What’s standing out to you? Or do you want to explore one of these in more
depth?
You said:
Another idea is we could pass a raw string of json.
ChatGPT said:
ChatGPT
Passing a raw JSON string is definitely another option! Here's the quick
breakdown for that:
Passing Raw JSON String
Pros:
Extremely flexible and future-proof. Users can pass whatever parameters they
want, even if OpenAI updates the API with new ones.
No extra code for type parsing or handling; you just forward it to the API.
Keeps your interface lightweight—no need for additional structures, variants,
or maps.
Cons:
Burdens the user with correctly formatting the JSON.
Error-prone: If the JSON string is malformed or has a typo, it could fail
silently or at runtime.
Doesn’t feel very "C++-idiomatic." Users of your API would need to resort to
string literals or JSON libraries themselves.
When It Works Well:
If your audience is already familiar with JSON (e.g., developers comfortable
with web APIs).
When you don’t want to impose strict type constraints or build a complex API
wrapper.
For power users who appreciate raw control over what they send.
When It Doesn't Work Well:
For users who expect compile-time safety and strongly typed APIs.
If you want your library to feel "native" to C++ instead of just wrapping HTTP
requests.
My Opinion:
If you’re going for simplicity and lightweight, the raw JSON option is
solid—especially since it makes the interface future-proof. However, you might
consider providing helper utilities (e.g., a configuration builder or parameter
struct) alongside it to ease the pain for less experienced users.
How do you feel about this one? Would you combine it with anything else, or
does it feel too raw?
You said:
I like the idea of a raw json string as a dependency-free universal underlying
representation. Maybe it could provide access to the raw parameters as a json
string, and have an advanced function to set it manually. But it doesn't seem
ideal as the primary, visible solution to expect users to use.
First you said you liked variant, then you said you liked the configuration
struct or parameter member functions ... what are you thinking now? do you have
any further ideas on how to do this?
ChatGPT said:
ChatGPT
I love where you’re going with this—using a raw JSON string as an underlying
mechanism while offering a cleaner, more structured interface sounds like the
best of both worlds. You're absolutely right that it shouldn’t be the primary
way for users to interact with the API, but it could act as a flexible
fallback. Let me regroup and refine based on your thoughts.
Where I Stand Now
I still think std::variant, a configuration struct, or parameter member
functions would provide the most type-safe, C++-idiomatic interface for the
"primary" user-facing approach. However, now I’m leaning toward a hybrid
approach, combining these with the raw JSON fallback for advanced use cases.
Here’s what I’m thinking:
1. Hybrid API Structure
Primary API: Use a configuration struct or member functions to manage
parameters. This provides a clean, user-friendly interface that’s easy to work
with.
Advanced/Raw API: Expose the underlying raw JSON string as a manual override
for edge cases.
Example:
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struct OpenAIParams {
std::optional<std::string> model;
std::optional<int> max_tokens;
std::optional<double> temperature;
std::optional<std::vector<std::string>> stop;
std::unordered_map<std::string, std::string> additional_params;
std::string to_json() const; // Serializes to raw JSON string
};
class OpenAI {
public:
// Primary, user-friendly API
void set_params(const OpenAIParams& params);
// Advanced: directly override raw JSON parameters
void set_raw_params(std::string_view json_string);
};
This gives users the option to either:
Use a high-level interface (clean, type-safe structs or methods).
Fall back to raw JSON for ultimate flexibility.
2. Combine Member Functions with the Struct
Make the struct extensible and let users chain parameters via member functions
(builder pattern). For example:
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OpenAIParams params;
params.set_model("gpt-4")
.set_temperature(0.7)
.set_max_tokens(100);
client.set_params(params);
3. Further Ideas
Default Configuration: Provide a default OpenAIParams instance with common
defaults. Users can tweak only what they need.
Validation Hooks: Add lightweight validation in the setter or just before
sending the request to ensure users don’t pass nonsense (e.g., negative
max_tokens).
Why This Makes Sense
Type-Safe and Flexible: Users get a clean API with compile-time guarantees
while still having the raw JSON fallback.
Future-Proof: OpenAI updates? Just update the struct or rely on raw JSON.
C++-Friendly: This strikes a balance between modern idiomatic C++ and the
practicalities of interfacing with a JSON-based API.
Your Thoughts?
Does this hybrid setup feel like a good compromise? Or do you prefer one part
of this approach over the others? Happy to adjust!
You said:
Hmm. So the idea is that the raw json string is the future-proofing.
ChatGPT said:
ChatGPT
Exactly! The raw JSON string acts as the ultimate "safety valve" for
future-proofing. Here’s why it works well:
Future-Proofing: If OpenAI adds new parameters tomorrow, users can immediately
use those by crafting their own JSON strings without waiting for updates to
your library.
Flexibility: For advanced or niche use cases, power users can bypass the
structured interface entirely and do whatever they want.
The structured interface, like the configuration struct or member functions,
then serves as the primary user-facing API, offering:
Ease of Use: It’s intuitive and type-safe for most users.
Guided Interactions: It ensures users only set valid parameters (or at least
minimizes accidental misuse).
Meanwhile, the raw JSON remains in the background, quietly providing escape
hatches.
The Flow Looks Like This:
Basic Users: Use the primary interface (OpenAIParams, setter methods, etc.) for
convenience and type safety.
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OpenAIParams params;
params.set_model("gpt-4")
.set_max_tokens(150)
.set_temperature(0.8);
client.set_params(params);
Advanced Users: Access and manipulate the raw JSON if needed:
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std::string raw_json = R"({"model": "gpt-4", "custom_param": "value"})";
client.set_raw_params(raw_json);
Interoperability: You can expose helpers to convert between the structured
representation and raw JSON (e.g., params.to_json()).
Why It’s Elegant
Power in Simplicity: Most users stick with the structured approach.
No Dependency Explosion: The library doesn’t force everyone to include a full
JSON library for trivial use cases.
Open for Power Users: Advanced users still get the raw flexibility they need,
while beginners don’t even need to think about JSON.
What’s your gut feeling now? Is this hybrid concept clicking, or does it still
feel like something’s missing?
You said:
well i'm really not sure how i want to do it.
i'm really trying with these interfaces to make them both expressive and
concise. really simple, clear things. like how there are just 4 member
functions, and the streaming is handled by std::generator. i'm hesistant to
make it really large with heavy configuration structs. one of the things i'm
weighing is the value of literal parameters vs the flexibility of a general map
or span ...
ChatGPT said:
ChatGPT
I see where you're coming from, and it’s admirable that you want to keep things
minimal, expressive, and clear. You’re prioritizing lightweight interfaces that
fit with modern C++ idioms, and that’s a great goal. Let’s keep refining with
those principles in mind.
Literal Parameters vs. General Maps/Spans
Here’s the core trade-off:
Literal Parameters: Simple, type-safe, and concise.
Pro: Clear at the call site, expressive (gen_completion(prompt, max_tokens,
temperature)).
Con: Becomes unwieldy if there are many parameters or if parameters evolve over
time.
General Maps/Spans: Flexible and future-proof.
Pro: Users can pass anything. Easy to adapt to API changes without needing to
modify your interface.
Con: Less expressive—users lose type safety and readability
(gen_completion(prompt, {{"max_tokens", "100"}, {"temperature", "0.7"}})).
Possible Hybrid Ideas
If you're torn between expressiveness and flexibility, here are a few ways to
balance them:
1. Minimal Literal Parameters + General Map for Extras
Keep a small number of core, common parameters as literal arguments.
Use a general std::span<std::pair<std::string_view, std::string_view>> (or
similar) for optional/custom parameters.
Example:
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std::generator<CompletionItem const&> gen_completion(
std::string_view prompt,
int max_tokens = 100,
double temperature = 0.7,
std::span<std::pair<std::string_view, std::string_view> const> extras = {}
) const;
Users can call it concisely for 99% of cases:
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client.gen_completion("Tell me a joke", 150, 0.8);
Advanced users can add arbitrary parameters via extras:
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client.gen_completion(
"Tell me a joke",
150,
0.8,
{{"stop", "\n"}, {"presence_penalty", "0.6"}}
);
2. Small Literal API + Raw JSON for Advanced
Use concise literal parameters for common cases.
Provide a separate function for advanced JSON-based configuration.
Example:
cpp
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std::generator<CompletionItem const&> gen_completion(
std::string_view prompt,
int max_tokens = 100,
double temperature = 0.7
) const;
std::generator<CompletionItem const&> gen_completion_raw(std::string_view
raw_json) const;
Users stick with the literal, expressive API unless they have edge cases:
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client.gen_completion("Explain C++ concepts", 200, 0.6);
Advanced users can use the raw function for anything:
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client.gen_completion_raw(R"({"prompt": "Explain C++", "stop": "\n", "model":
"gpt-4"})");
3. Literal Parameters with Implicit Fallbacks
This is a middle ground where a general map backs literal parameters:
Parameters not explicitly passed as arguments get picked up from the map.
Example:
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std::generator<CompletionItem const&> gen_completion(
std::string_view prompt,
std::optional<int> max_tokens = std::nullopt,
std::optional<double> temperature = std::nullopt,
std::span<std::pair<std::string_view, std::string_view> const> extras = {}
) const;
Users set specific parameters or rely on defaults:
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client.gen_completion("Write me a haiku", 50, 0.5);
The map is still there for edge cases:
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client.gen_completion(
"Write me a haiku",
std::nullopt,
0.5,
{{"frequency_penalty", "0.3"}}
);
What This Gives You
Conciseness: Literal parameters stay lightweight and expressive for common
cases.
Flexibility: The map or JSON fallback ensures you’re not boxed in by literal
parameters.
Minimal Interface Growth: No need for large configuration structs or a
sprawling number of member functions.
How does this feel? Leaning toward one of these? Or does it spark a new idea?
You said:
in your examples you still use a string_view:string_view map .
maybe i like the std::variant or std::any solution. i'm hesitant to add another
header to the public interface, but maybe the simplicity and expressiveness is
worth it. most of the other solutions just seem really verbose. i think they'd
make the header a lot less clear and direct. meanwhile i'm not sure that raw
json is user-friendly enough.
ChatGPT said:
ChatGPT
I think you're onto something. If the goal is to keep the header clear and
concise while improving type safety and user-friendliness, using std::variant
or std::any could strike the right balance. Let’s break this down.
Why std::variant or std::any?
Conciseness: Keeps the parameter representation clear without introducing
verbose configuration structs or function overloads.
Expressiveness: Allows parameters to be passed in their native types (int,
bool, double, std::string, etc.), avoiding unnecessary string conversions.
Flexibility: Users can specify a wide range of parameters without hardcoding
them in the interface.
std::variant vs std::any
std::variant
Pros:
Compile-time type safety. You define a closed set of allowable types
(std::variant<int, double, bool, std::string>).
Avoids runtime errors when accessing parameters.
Better performance since the type is known upfront.
Cons:
Slightly more verbose (you must define all valid types).
Adding new types in the future means modifying the variant definition.
std::any
Pros:
Fully flexible—users can pass any type, making it more future-proof.
Minimal constraints on API evolution.
Cons:
Runtime type safety—errors will occur if the user retrieves a value with the
wrong type.
Slightly heavier since it requires type erasure at runtime.
How It Could Look
Here’s an updated version of your interface using std::variant (though you can
swap it with std::any if preferred):
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#include <variant> // For std::variant
#include <unordered_map>
#include <string>
#include <string_view>
#include <vector>
#include <generator>
namespace zinc {
class OpenAI {
public:
using ParamValue = std::variant<int, double, bool, std::string>;
OpenAI(std::string_view url, std::string_view model, std::string_view key,
std::unordered_map<std::string, ParamValue> defaults = {});
~OpenAI();
struct CompletionItem {
std::string_view text;
std::unordered_map<std::string, ParamValue> data;
operator std::string_view() const { return text; }
};
std::generator<CompletionItem const&>
gen_completion(std::string_view prompt,
std::unordered_map<std::string, ParamValue> params = {})
const;
std::generator<std::span<CompletionItem const>>
gen_completions(std::string_view prompt, size_t completions,
std::unordered_map<std::string, ParamValue> params = {})
const;
std::generator<CompletionItem const&>
gen_chat(std::span<std::pair<std::string_view, std::string_view>> messages,
std::unordered_map<std::string, ParamValue> params = {}) const;
std::generator<std::span<CompletionItem const>>
gen_chats(std::span<std::pair<std::string_view, std::string_view>> messages,
size_t completions,
std::unordered_map<std::string, ParamValue> params = {}) const;
private:
std::string endpoint_completions_;
std::string endpoint_chats_;
std::string bearer_;
std::unordered_map<std::string, ParamValue> defaults_;
};
} // namespace zinc
How It’s Used
Pass Parameters Directly in Native Types:
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std::unordered_map<std::string, OpenAI::ParamValue> params = {
{"max_tokens", 150},
{"temperature", 0.8},
{"stop", std::string("\n")}
};
client.gen_completion("Tell me a joke", params);
No Extra Headers for Users: The API doesn’t expose a dependency-heavy JSON
library, and users interact naturally with the C++ STL.
Flexibility:
OpenAI adds a new parameter? No problem—users can include it without needing
library updates.
Invalid type? The user gets a compile-time or runtime error depending on
whether you use std::variant or std::any.
Key Benefits
Minimal Impact on the Header: A single type alias (using ParamValue) keeps the
interface clean.
Efficient: No runtime string parsing, and std::variant avoids overhead if the
type is known.
Readable: Users pass parameters in an intuitive way without needing JSON or
verbose structs.
Do You Like This Direction?
This feels in line with your preference for clarity, conciseness, and a direct
style. Do you like the balance here, or is there something else you’d tweak?
You said:
yeah i think this is the way to go
looking at how you did it, you typedef'd the varint, but maybe typedef'ing a
ParamMap or such would make the member functions much more clear by having
fewer characters used by the exotic custom parameter option.
Now, in the implementation, right now it's using nlohmann::json, but the
library depends on boost so i thought i might remove nlohmann::json and instead
use boost json. but i'm not that familiar with either one these days.
do you know offhand what types boost and nlohmann use for json values?
ChatGPT said:
ChatGPT
Great idea about typedef’ing a ParamMap! It will definitely clean up the
function signatures and make them more readable.
Now, regarding the JSON libraries:
nlohmann::json
JSON Type: nlohmann::json
Essentially a dynamic type that can act as an array, object, string, number,
boolean, or null.
Similar to a variant internally but much more extensive.
Access and Assignment:
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nlohmann::json j;
j["key"] = 42;
j["pi"] = 3.14;
j["valid"] = true;
std::string s = j.dump(); // Convert to string
Boost JSON
JSON Type: boost::json::value
A single dynamic type that represents any JSON value (object, array, string,
number, boolean, or null).
Similar to nlohmann::json but optimized for efficiency.
Object Type: boost::json::object (key-value pairs like a std::map).
Access and Assignment:
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boost::json::value jv =
boost::json::parse(R"({"key":42,"pi":3.14,"valid":true})");
boost::json::object& obj = jv.as_object();
obj["key"] = 99; // Modify a value
std::string s = boost::json::serialize(jv); // Convert to string
Comparison
Feature nlohmann::json Boost.JSON
Type nlohmann::json boost::json::value
Object Type Internally uses std::map or std::unordered_map (default)
Explicit boost::json::object
Parsing nlohmann::json::parse() boost::json::parse()
Serialization json.dump() boost::json::serialize()
Performance Slower (focuses on ease of use) Faster (focuses on efficiency)
Dependency Footprint Header-only Requires Boost but is lighter than
other Boost components
Compile Times Heavier due to templates Lighter due to simpler design
Transitioning to Boost.JSON
If you're already using Boost, switching to boost::json makes sense because:
It reduces dependencies (nlohmann::json would no longer be needed).
Boost.JSON has better performance characteristics, especially in
resource-constrained environments.
However, if nlohmann::json is deeply integrated into your current
implementation, it’s worth considering the migration cost.
Types You’d Use in Implementation
Here’s how you’d map your ParamMap and variant to these libraries:
Using nlohmann::json:
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using ParamMap = std::unordered_map<std::string, nlohmann::json>;
You can directly assign to nlohmann::json since it’s dynamic:
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ParamMap params = {{"max_tokens", 150}, {"temperature", 0.8}, {"stop", "\n"}};
Using boost::json:
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using ParamMap = std::unordered_map<std::string, boost::json::value>;
Similarly dynamic but requires converting basic types to boost::json::value:
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ParamMap params = {
{"max_tokens", boost::json::value(150)},
{"temperature", boost::json::value(0.8)},
{"stop", boost::json::value("\n")}
};
My Take
If Boost is already part of your project, Boost.JSON is a natural fit:
You get better performance and integration without additional dependencies.
The migration cost is manageable since the APIs are quite similar.
If you’d like, I can help sketch out a basic implementation using Boost.JSON!
You said:
what do nlohmann and boost do for number?
ChatGPT said:
ChatGPT
Both nlohmann::json and boost::json support number types, but they handle them
differently in terms of storage and precision. Here's a detailed breakdown:
nlohmann::json
Number Representation:
nlohmann::json stores numbers dynamically. It can distinguish between:
int (signed integer, usually 32-bit or 64-bit depending on platform).
uint (unsigned integer, similarly platform-dependent).
double (floating-point number, 64-bit precision).
Type Checking:
You can query the type of a number with functions like is_number_integer(),
is_number_unsigned(), or is_number_float().
Example:
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nlohmann::json j;
j["int_value"] = 42; // Stored as an int
j["float_value"] = 3.14; // Stored as a double
j["unsigned_value"] = 123u; // Stored as unsigned int
if (j["int_value"].is_number_integer()) {
int value = j["int_value"]; // Access as int
}
Precision:
For floating-point numbers, it uses standard double precision (64-bit IEEE 754).
Integer storage is adaptive (no arbitrary precision).
Boost.JSON
Number Representation:
boost::json simplifies number handling by storing all numbers as:
64-bit signed integer (std::int64_t) for integers.
64-bit double for floating-point numbers.
There’s no distinction between signed/unsigned integers; all are stored as
std::int64_t.
Type Checking:
You can check whether a number is an integer or floating-point:
is_int64(): Check if it's a 64-bit signed integer.
is_double(): Check if it's a floating-point number.
Example:
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boost::json::value jv;
jv = 42; // Stored as int64_t
jv = 3.14; // Stored as double
if (jv.is_int64()) {
std::int64_t value = jv.as_int64(); // Access as int64_t
} else if (jv.is_double()) {
double value = jv.as_double(); // Access as double
}
Precision:
Floating-point numbers use double precision (64-bit IEEE 754).
Integers are strictly std::int64_t (signed).
Key Differences
Feature nlohmann::json Boost.JSON
Integer Types Supports both int and unsigned int dynamically Always
std::int64_t (signed 64-bit integer)
Floating-Point Types Always double (64-bit) Always double (64-bit)
Type Granularity Distinguishes int, unsigned int, and double
Simplifies to int64_t and double
Memory Usage More dynamic due to fine-grained type distinctions More
compact since it uses fewer types
Practical Considerations
nlohmann::json:
If you need finer-grained distinctions (e.g., between signed/unsigned
integers), it’s more versatile.
Useful for APIs or systems where the exact type matters (e.g., unsigned IDs).
Boost.JSON:
If simplicity and performance are priorities, its focus on just int64_t and
double makes it faster and lighter.
Works well for most JSON use cases where strict unsigned/signed separation
isn’t needed.
Do you think Boost.JSON's simpler model fits your needs better? It can reduce
edge cases for type handling while staying performant.
You said:
ok i'm going to draft a new interface using std::variant<> with string,
int/int64, double, and bool. i guess i'll try using std::string_view instead of
std::string until i run into issues. i do think your example of using an
unordered map instead of a span might make sense, it's just easier for the user
to use maps themselves. i'm not certain. anyway here i go.
ChatGPT said:
ChatGPT
Sounds like a solid plan! Using std::variant for flexibility while keeping it
type-safe and lightweight should make your interface clean and expressive.
Here's a quick recap of key points to consider as you draft:
1. Parameter Type with std::variant
Define a typedef to make the parameter map concise and readable:
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using ParamValue = std::variant<std::string_view, int64_t, double, bool>;
using ParamMap = std::unordered_map<std::string_view, ParamValue>;
2. std::string_view vs std::string
std::string_view: Lightweight, non-owning reference to strings. Great for
efficiency, but be careful if the input string goes out of scope.
When to switch to std::string:
If you need to ensure the parameter values live independently of the caller.
If you need to store values that are generated or manipulated internally.
3. Span vs Map
std::unordered_map:
Easier for users since they can work directly with a map.
Built-in key lookups.
std::span:
Efficient for raw lists, but users need to construct a span or pass arrays
explicitly.
If simplicity for the user is your goal, a map will feel more natural.
4. Handling the Variant in the Implementation
Make sure your implementation converts the std::variant values to JSON (e.g.,
Boost.JSON or nlohmann::json) seamlessly:
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boost::json::object json_params;
for (const auto& [key, value] : user_params) {
std::visit([&](const auto& val) {
json_params[key] = val; // Boost.JSON handles type conversion here
}, value);
}
5. Validation and Default Parameters
You can embed validation or defaults in the constructor or processing logic:
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if (params.contains("max_tokens")) {
auto max_tokens = std::get<int64_t>(params["max_tokens"]); // Example
validation
}
You're striking a balance between simplicity and power here, and you're making
thoughtful design choices. Go for it! When you're ready, feel free to share
your draft—I’d love to help refine it. 🚀
