Switch to single LLM provider (Gemini/Cloud/SecureGPT_OpenAI)

.env.sample

@@ -1,7 +1,5 @@
 PORT=3000
 EMBEDDINGS_API=http://localhost:8000
-PATHWAY_API=https://api.pathway.md/v8/chat/completions
-PATHWAY_MODEL=pathway-v8-0
 SESSION_SECRET=session-secret
 CORS_ORIGINS=https://frontend.com,https://another-frontend.com
 
@@ -15,4 +13,4 @@ AI_PROVIDER=Gemini
 
 ANTHROPIC_API_KEY=<your_api_key>
 GOOGLE_GENERATIVE_AI_API_KEY=<your_api_key>
-PATHWAY_AI_API_KEY=<your_api_key>
+SECUREGPT_API_KEY=<your_api_key>

package.json

@@ -21,6 +21,7 @@
   },
   "dependencies": {
     "@ai-sdk/anthropic": "^1.2.4",
+    "@ai-sdk/azure": "^1.3.24",
     "@ai-sdk/google": "^1.2.5",
     "@ai-sdk/openai": "^1.3.6",
     "@google/generative-ai": "^0.24.0",

resources/specialist_prompt.md

@@ -0,0 +1,42 @@
+# LLM Clinical Decision Support System Prompt
+
+## Role and Goal:
+You are a board-certified medical specialist. Your task is to provide a high-quality and actionable eConsult response to a Primary Care Provider (PCP). The response must be clear, concise, and based strictly on the information provided in the PCP's question and the attached clinical notes.
+
+---
+
+## Required Output Format and Content:
+Please structure your response using the exact following three sections and formatting.
+
+### 1. Assessment
+* **Concise Summary:** Begin with a single sentence that encapsulates the patient's core clinical problem (e.g., *"This is a [age]-year-old with a history of [X, Y] presenting with [chief complaint] in the context of [relevant comorbidity or recent event]."*).
+* **Key Findings:** Concisely synthesize the most clinically relevant findings from the provided history, exam, and data. Do not simply list facts; weave them into a coherent clinical picture.
+* **Differential Diagnosis:** If applicable, provide a prioritized differential diagnosis, listing the most likely diagnosis first. Briefly state the primary reasons for your diagnostic considerations.
+* **Overall Assessment:** End with an overall assessment of the patient's condition and whether this needs urgent attention.
+
+### 2. Recommendations and Rationale
+In a short paragraph form, provide specific, actionable recommendations. Group recommendations (e.g., Diagnostics, Therapeutics) if applicable. Therapeutic recommendations should include dosages and duration. At the end of this paragraph, please provide a concise rationale. Do not make harmful or incomplete recommendations. If there is insufficient information or the consult is of sufficient complexity as to require a human specialist review, please include in your recommendations appropriate referrals as indicated.
+
+*Example Format:*
+> Obtain a TSH and free T4. Start Escitalopram 10 mg daily.
+
+### 3. Contingency Plan
+This section outlines the "what if" scenarios.
+* **Escalation Triggers:** List specific, objective "red flags" that should prompt the PCP to re-evaluate or escalate care (e.g., send to the Emergency Department, refer to specialist). Include specific thresholds (e.g., *"If systolic blood pressure drops below 90 mmHg,"* *"If PHQ-9 score increases by more than 5 points,"* *"Development of new neurological deficits"*).
+
+### 4. Citations
+Provide any citations or guidelines relevant to the recommendations. These should be brief.
+
+---
+
+## Tone and Style:
+* **Tone:** Maintain a professional tone. Be direct, concise, and avoid excessive language such as *"thank you for this consult..."*
+* **Clarity:** Use clear and unambiguous language. Avoid overly academic jargon. The goal is to be easily understood by a busy generalist.
+* **Conciseness:** Be brief and to the point. The total number of words in the entire response (excluding citations) should be less than 150 words.
+
+---
+
+## Input Context:
+The PCP's clinical question and recent clinical notes follow:
+{{question}}
+{{notes}}

sample_requests.http

@@ -1,20 +1,20 @@
 ### Gemini followup questions
 GET {{assist-pc-backend-url}}/followup-questions
 
-### Pathway chatbot question
-POST {{assist-pc-backend-url}}/ask-pathway
+### Specialist chatbot question
+POST {{assist-pc-backend-url}}/ask-specialist
 Content-Type: application/json
 
 {
   "question": "What further procedures would you recommend?"
 }
 
-### Pathway chatbot question streamed
-POST {{assist-pc-backend-url}}/ask-pathway-streamed
+### Specialist chatbot question streamed
+POST {{assist-pc-backend-url}}/ask-specialist-streamed
 Content-Type: application/json
 
 {
-  "question": "Understood. Any other diagnoses?"
+  "question": "Do any other diagnoses fit the description?"
 }
 
 ### Clinical question with matched template streamed

src/app.controller.spec.ts

@@ -4,15 +4,15 @@ import { AppService } from './app.service';
 import { LLMResponse } from './models/llmResponse';
 import { TemplateSelectorService } from './template-selector/template-selector.service';
 import { HttpModule } from '@nestjs/axios';
-import { PathwayService } from './pathway/pathway.service';
+import { SpecialistAiService } from './specialist-ai/specialist-ai.service';
 
 describe('AppController', () => {
   let appController: AppController;
 
   beforeEach(async () => {
     const app: TestingModule = await Test.createTestingModule({
       controllers: [AppController],
-      providers: [AppService, TemplateSelectorService, PathwayService],
+      providers: [AppService, TemplateSelectorService, SpecialistAiService],
       imports: [HttpModule],
     }).compile();
 

src/app.controller.ts

@@ -41,8 +41,8 @@ export class AppController {
 
     const response = await this.appService.postReferralQuestion(request);
     session[SessionKeys.REFERRAL_RESPONSE] = response;
-    // reset Pathway conversation history on new referral request
-    session[SessionKeys.PREVIOUS_PATHWAY_CONVERSATIONS] = [];
+    // reset Specialist AI conversation history on new referral request
+    session[SessionKeys.PREVIOUS_SPECIALIST_CONVERSATIONS] = [];
 
     return response;
   }
@@ -64,7 +64,7 @@ export class AppController {
     return await this.appService.postReferralQuestionStreamed(request, session);
   }
 
-  @Post('/ask-pathway')
+  @Post('/ask-specialist')
   @ApiBody({
     schema: {
       properties: {
@@ -74,22 +74,22 @@ export class AppController {
   })
   @ApiCreatedResponse({
     description:
-      'Successfully received Pathway AI response to a clarifying question.',
+      'Successfully received Specialist AI response to a clarifying question.',
     type: SpecialistAIResponse,
   })
-  async postPathwayQuestion(
+  async postSpecialistQuestion(
     @Session() session: Record<string, any>,
     @Body('question') question: string,
   ): Promise<SpecialistAIResponse> {
     this.logger.debug('controller request', question);
     this.logger.debug('session', session);
     const response: SpecialistAIResponse =
-      await this.appService.postPathwayQuestion(question, session);
-    if (session[SessionKeys.PREVIOUS_PATHWAY_CONVERSATIONS] == null) {
-      session[SessionKeys.PREVIOUS_PATHWAY_CONVERSATIONS] = [];
+      await this.appService.postSpecialistQuestion(question, session);
+    if (session[SessionKeys.PREVIOUS_SPECIALIST_CONVERSATIONS] == null) {
+      session[SessionKeys.PREVIOUS_SPECIALIST_CONVERSATIONS] = [];
     }
     (
-      session[SessionKeys.PREVIOUS_PATHWAY_CONVERSATIONS] as Record<
+      session[SessionKeys.PREVIOUS_SPECIALIST_CONVERSATIONS] as Record<
         string,
         SpecialistAIResponse
       >[]
@@ -99,7 +99,7 @@ export class AppController {
     return response;
   }
 
-  @Post('/ask-pathway-streamed')
+  @Post('/ask-specialist-streamed')
   @Sse()
   @ApiBody({
     schema: {
@@ -110,19 +110,19 @@ export class AppController {
   })
   @ApiOkResponse({
     description:
-      'Successfully received streamed Pathway AI response to a clarifying question.',
+      'Successfully received streamed Specialist AI response to a clarifying question.',
     type: SpecialistAIResponse,
   })
-  postPathwayQuestionStreamed(
+  postSpecialistQuestionStreamed(
     @Session() session: Record<string, any>,
     @Body('question') question: string,
   ): Observable<{ data: SpecialistAIResponse }> {
     this.logger.debug('controller request', question);
     this.logger.debug('session', session);
-    if (session[SessionKeys.PREVIOUS_PATHWAY_CONVERSATIONS] == null) {
-      session[SessionKeys.PREVIOUS_PATHWAY_CONVERSATIONS] = [];
+    if (session[SessionKeys.PREVIOUS_SPECIALIST_CONVERSATIONS] == null) {
+      session[SessionKeys.PREVIOUS_SPECIALIST_CONVERSATIONS] = [];
     }
-    return this.appService.postPathwayQuestionStreamed(question, session);
+    return this.appService.postSpecialistQuestionStreamed(question, session);
   }
 
   @Get('/followup-questions')
@@ -133,7 +133,7 @@ export class AppController {
   })
   generateFollowupQuestions(
     @Session() session: Record<string, any>,
-  ): Promise<string[]> {
+  ): Promise<{ questions: string[] }> {
     this.logger.debug('controller request for followup questions generation');
     this.logger.debug('session', session);
     return this.appService.generateFollowupQuestions(session);

src/app.module.ts

@@ -3,10 +3,16 @@ import { AppService } from './app.service';
 import { Module } from '@nestjs/common';
 import { ConfigModule } from '@nestjs/config';
 import { TemplateSelectorModule } from './template-selector/template-selector.module';
-import { PathwayModule } from './pathway/pathway.module';
+import { SpecialistAiModule } from './specialist-ai/specialist-ai.module';
+import { LlmSelectorModule } from './llm-selector/llm-selector.module';
 
 @Module({
-  imports: [ConfigModule.forRoot(), TemplateSelectorModule, PathwayModule],
+  imports: [
+    ConfigModule.forRoot(),
+    TemplateSelectorModule,
+    SpecialistAiModule,
+    LlmSelectorModule,
+  ],
   controllers: [AppController],
   providers: [AppService],
 })