feat: Implement AgentChatWidget for conversational AI interaction and add ASCII logo support
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@@ -11,15 +11,18 @@
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#include "absl/strings/strip.h"
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#ifdef YAZE_WITH_JSON
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#include <filesystem>
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#include <fstream>
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#include "httplib.h"
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#include "nlohmann/json.hpp"
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namespace fs = std::filesystem;
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#endif
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namespace yaze {
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namespace cli {
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GeminiAIService::GeminiAIService(const GeminiConfig& config)
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: config_(config) {
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: config_(config), function_calling_enabled_(true) {
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// Load command documentation into prompt builder
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if (auto status = prompt_builder_.LoadResourceCatalogue(""); !status.ok()) {
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std::cerr << "⚠️ Failed to load agent prompt catalogue: "
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@@ -36,6 +39,71 @@ GeminiAIService::GeminiAIService(const GeminiConfig& config)
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}
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}
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void GeminiAIService::EnableFunctionCalling(bool enable) {
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function_calling_enabled_ = enable;
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}
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std::vector<std::string> GeminiAIService::GetAvailableTools() const {
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return {
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"resource_list",
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"dungeon_list_sprites",
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"overworld_find_tile",
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"overworld_describe_map",
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"overworld_list_warps"
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};
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}
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std::string GeminiAIService::BuildFunctionCallSchemas() {
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#ifndef YAZE_WITH_JSON
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return "[]"; // Empty array if JSON not available
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#else
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// Search for function_schemas.json in multiple locations
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const std::vector<std::string> search_paths = {
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"assets/agent/function_schemas.json",
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"../assets/agent/function_schemas.json",
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"../../assets/agent/function_schemas.json",
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};
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fs::path schema_path;
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bool found = false;
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for (const auto& candidate : search_paths) {
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fs::path resolved = fs::absolute(candidate);
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if (fs::exists(resolved)) {
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schema_path = resolved;
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found = true;
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break;
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}
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}
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if (!found) {
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std::cerr << "⚠️ Function schemas file not found. Tried paths:" << std::endl;
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for (const auto& path : search_paths) {
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std::cerr << " - " << fs::absolute(path).string() << std::endl;
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}
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return "[]"; // Return empty array as fallback
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}
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// Load and parse the JSON file
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std::ifstream file(schema_path);
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if (!file.is_open()) {
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std::cerr << "⚠️ Failed to open function schemas file: "
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<< schema_path.string() << std::endl;
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return "[]";
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}
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try {
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nlohmann::json schemas_json;
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file >> schemas_json;
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return schemas_json.dump();
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} catch (const nlohmann::json::exception& e) {
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std::cerr << "⚠️ Failed to parse function schemas JSON: "
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<< e.what() << std::endl;
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return "[]";
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}
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#endif
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}
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std::string GeminiAIService::BuildSystemInstruction() {
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// Fallback prompt if enhanced prompting is disabled
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// Use PromptBuilder's basic system instruction
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@@ -140,6 +208,18 @@ absl::StatusOr<AgentResponse> GeminiAIService::GenerateResponse(
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{"responseMimeType", "application/json"}
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}}
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};
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// Add function calling tools if enabled
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if (function_calling_enabled_) {
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try {
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nlohmann::json tools = nlohmann::json::parse(BuildFunctionCallSchemas());
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request_body["tools"] = {{
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{"function_declarations", tools}
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}};
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} catch (const nlohmann::json::exception& e) {
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std::cerr << "⚠️ Failed to parse function schemas: " << e.what() << std::endl;
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}
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}
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httplib::Headers headers = {
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{"Content-Type", "application/json"},
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@@ -37,12 +37,19 @@ class GeminiAIService : public AIService {
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// Health check
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absl::Status CheckAvailability();
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// Function calling support
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void EnableFunctionCalling(bool enable = true);
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std::vector<std::string> GetAvailableTools() const;
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private:
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std::string BuildSystemInstruction();
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std::string BuildFunctionCallSchemas();
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absl::StatusOr<AgentResponse> ParseGeminiResponse(
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const std::string& response_body);
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bool function_calling_enabled_ = true;
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GeminiConfig config_;
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PromptBuilder prompt_builder_;
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};
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