增加 openai 的模型兼容
This commit is contained in:
jwangkun
@@ -1,8 +1,14 @@
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import { Type } from "@google/genai";
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import { ModelOption, AnalysisResult, ExpertResult, ReviewResult } from '../../types';
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import { ModelOption, AnalysisResult, ExpertResult, ReviewResult, ApiProvider } from '../../types';
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import { cleanJsonString } from '../../utils';
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import { MANAGER_SYSTEM_PROMPT, MANAGER_REVIEW_SYSTEM_PROMPT } from './prompts';
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import { withRetry } from '../utils/retry';
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import { generateContent as generateOpenAIContent } from './openaiClient';
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import { getAIProvider } from '../../api';
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const isGoogleProvider = (ai: any): boolean => {
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return ai?.models?.generateContent !== undefined;
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};
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export const executeManagerAnalysis = async (
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ai: any,
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@@ -11,57 +17,86 @@ export const executeManagerAnalysis = async (
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context: string,
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budget: number
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): Promise<AnalysisResult> => {
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const managerSchema = {
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type: Type.OBJECT,
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properties: {
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thought_process: { type: Type.STRING, description: "Brief explanation of why these supplementary experts were chosen." },
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experts: {
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type: Type.ARRAY,
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items: {
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type: Type.OBJECT,
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properties: {
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role: { type: Type.STRING },
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description: { type: Type.STRING },
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temperature: { type: Type.NUMBER },
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prompt: { type: Type.STRING }
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},
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required: ["role", "description", "temperature", "prompt"]
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}
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}
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},
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required: ["thought_process", "experts"]
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};
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const isGoogle = isGoogleProvider(ai);
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try {
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const analysisResp = await withRetry(() => ai.models.generateContent({
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model: model,
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contents: `Context:\n${context}\n\nCurrent Query: "${query}"`,
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config: {
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systemInstruction: MANAGER_SYSTEM_PROMPT,
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responseMimeType: "application/json",
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responseSchema: managerSchema,
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thinkingConfig: {
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includeThoughts: true,
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thinkingBudget: budget
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if (isGoogle) {
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const managerSchema = {
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type: Type.OBJECT,
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properties: {
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thought_process: { type: Type.STRING, description: "Brief explanation of why these supplementary experts were chosen." },
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experts: {
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type: Type.ARRAY,
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items: {
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type: Type.OBJECT,
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properties: {
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role: { type: Type.STRING },
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description: { type: Type.STRING },
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temperature: { type: Type.NUMBER },
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prompt: { type: Type.STRING }
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},
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required: ["role", "description", "temperature", "prompt"]
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}
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}
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}
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}));
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const rawText = analysisResp.text || '{}';
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const cleanText = cleanJsonString(rawText);
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const analysisJson = JSON.parse(cleanText) as AnalysisResult;
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if (!analysisJson.experts || !Array.isArray(analysisJson.experts)) {
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throw new Error("Invalid schema structure");
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}
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return analysisJson;
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} catch (e) {
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console.error("Manager Analysis Error:", e);
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// Return a fallback so the process doesn't completely die if planning fails
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return {
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thought_process: "Direct processing fallback due to analysis error.",
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experts: []
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},
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required: ["thought_process", "experts"]
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};
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try {
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const analysisResp = await withRetry(() => ai.models.generateContent({
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model: model,
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contents: `Context:\n${context}\n\nCurrent Query: "${query}"`,
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config: {
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systemInstruction: MANAGER_SYSTEM_PROMPT,
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responseMimeType: "application/json",
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responseSchema: managerSchema,
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thinkingConfig: {
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includeThoughts: true,
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thinkingBudget: budget
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}
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}
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}));
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const rawText = (analysisResp as any).text || '{}';
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const cleanText = cleanJsonString(rawText);
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const analysisJson = JSON.parse(cleanText) as AnalysisResult;
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if (!analysisJson.experts || !Array.isArray(analysisJson.experts)) {
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throw new Error("Invalid schema structure");
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}
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return analysisJson;
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} catch (e) {
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console.error("Manager Analysis Error:", e);
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return {
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thought_process: "Direct processing fallback due to analysis error.",
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experts: []
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};
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}
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} else {
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try {
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const response = await generateOpenAIContent(ai, {
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model,
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systemInstruction: MANAGER_SYSTEM_PROMPT,
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content: `Context:\n${context}\n\nCurrent Query: "${query}"\n\nReturn a JSON response with this structure:\n{\n "thought_process": "...",\n "experts": [\n { "role": "...", "description": "...", "temperature": number, "prompt": "..." }\n ]\n}`,
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temperature: 0.7,
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responseFormat: 'json_object',
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thinkingConfig: {
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includeThoughts: true,
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thinkingBudget: budget
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}
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});
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const analysisJson = JSON.parse(response.text) as AnalysisResult;
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if (!analysisJson.experts || !Array.isArray(analysisJson.experts)) {
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throw new Error("Invalid schema structure");
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}
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return analysisJson;
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} catch (e) {
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console.error("Manager Analysis Error:", e);
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return {
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thought_process: "Direct processing fallback due to analysis error.",
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experts: []
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};
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}
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}
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};
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@@ -72,57 +107,78 @@ export const executeManagerReview = async (
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currentExperts: ExpertResult[],
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budget: number
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): Promise<ReviewResult> => {
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const reviewSchema = {
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type: Type.OBJECT,
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properties: {
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satisfied: { type: Type.BOOLEAN, description: "True if the experts have fully answered the query with high quality." },
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critique: { type: Type.STRING, description: "If not satisfied, explain why and what is missing." },
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next_round_strategy: { type: Type.STRING, description: "Plan for the next iteration." },
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refined_experts: {
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type: Type.ARRAY,
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description: "The list of experts for the next round. Can be the same roles or new ones.",
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items: {
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type: Type.OBJECT,
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properties: {
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role: { type: Type.STRING },
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description: { type: Type.STRING },
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temperature: { type: Type.NUMBER },
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prompt: { type: Type.STRING }
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},
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required: ["role", "description", "temperature", "prompt"]
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}
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}
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},
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required: ["satisfied", "critique"]
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};
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const expertOutputs = currentExperts.map(e =>
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const isGoogle = isGoogleProvider(ai);
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const expertOutputs = currentExperts.map(e =>
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`--- [Round ${e.round}] Expert: ${e.role} ---\nOutput: ${e.content?.slice(0, 2000)}...`
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).join('\n\n');
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const content = `User Query: "${query}"\n\nCurrent Expert Outputs:\n${expertOutputs}`;
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try {
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const resp = await withRetry(() => ai.models.generateContent({
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model: model,
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contents: content,
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config: {
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systemInstruction: MANAGER_REVIEW_SYSTEM_PROMPT,
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responseMimeType: "application/json",
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responseSchema: reviewSchema,
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thinkingConfig: {
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includeThoughts: true,
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thinkingBudget: budget
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if (isGoogle) {
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const reviewSchema = {
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type: Type.OBJECT,
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properties: {
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satisfied: { type: Type.BOOLEAN, description: "True if the experts have fully answered the query with high quality." },
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critique: { type: Type.STRING, description: "If not satisfied, explain why and what is missing." },
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next_round_strategy: { type: Type.STRING, description: "Plan for the next iteration." },
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refined_experts: {
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type: Type.ARRAY,
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description: "The list of experts for the next round. Can be the same roles or new ones.",
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items: {
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type: Type.OBJECT,
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properties: {
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role: { type: Type.STRING },
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description: { type: Type.STRING },
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temperature: { type: Type.NUMBER },
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prompt: { type: Type.STRING }
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},
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required: ["role", "description", "temperature", "prompt"]
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}
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}
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}
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}));
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},
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required: ["satisfied", "critique"]
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};
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const rawText = resp.text || '{}';
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const cleanText = cleanJsonString(rawText);
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return JSON.parse(cleanText) as ReviewResult;
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} catch (e) {
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console.error("Review Error:", e);
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// Fallback: Assume satisfied if JSON or API fails to avoid infinite loops
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return { satisfied: true, critique: "Processing Error, proceeding to synthesis." };
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try {
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const resp = await withRetry(() => ai.models.generateContent({
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model: model,
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contents: content,
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config: {
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systemInstruction: MANAGER_REVIEW_SYSTEM_PROMPT,
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responseMimeType: "application/json",
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responseSchema: reviewSchema,
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thinkingConfig: {
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includeThoughts: true,
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thinkingBudget: budget
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}
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}
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}));
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const rawText = (resp as any).text || '{}';
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const cleanText = cleanJsonString(rawText);
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return JSON.parse(cleanText) as ReviewResult;
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} catch (e) {
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console.error("Review Error:", e);
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return { satisfied: true, critique: "Processing Error, proceeding to synthesis." };
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}
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} else {
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try {
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const response = await generateOpenAIContent(ai, {
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model,
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systemInstruction: MANAGER_REVIEW_SYSTEM_PROMPT,
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content: `${content}\n\nReturn a JSON response with this structure:\n{\n "satisfied": boolean,\n "critique": "...",\n "next_round_strategy": "...",\n "refined_experts": [...]\n}`,
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temperature: 0.7,
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responseFormat: 'json_object',
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thinkingConfig: {
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includeThoughts: true,
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thinkingBudget: budget
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}
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});
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return JSON.parse(response.text) as ReviewResult;
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} catch (e) {
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console.error("Review Error:", e);
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return { satisfied: true, critique: "Processing Error, proceeding to synthesis." };
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}
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}
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};
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