feat: AI patient onboarding backend and documentation

2026-08-27 12:15:09 +05:30
parent b9440772d1
commit 59c1372fe3
49 changed files with 4012 additions and 0 deletions
@@ -0,0 +1,69 @@
+import json
+from app.config import ANTHROPIC_API_KEY, ANTHROPIC_MODEL
+
+
+class ClaudeClient:
+
+    def __init__(self):
+        self.api_key = ANTHROPIC_API_KEY
+        self.model = ANTHROPIC_MODEL
+
+    async def validate_extraction(
+        self,
+        patient_context: dict,
+        specialty_config: dict,
+        conversation_history: list,
+        extracted_data: dict,
+    ) -> dict:
+        if not self.api_key or self.api_key == "your_claude_key":
+            return {
+                "valid": True,
+                "missing": [],
+                "recommendation": "continue",
+                "hallucinations_detected": False,
+            }
+
+        try:
+            from anthropic import AsyncAnthropic
+            client = AsyncAnthropic(api_key=self.api_key)
+
+            prompt = f"""
+You are a senior clinical auditor and AI quality control specialist.
+Your task is to validate whether the extracted patient data accurately reflects the actual patient conversation without hallucination or omitted critical criteria.
+
+PATIENT CONTEXT:
+{json.dumps(patient_context, indent=2)}
+
+SPECIALTY REQUIREMENTS:
+{json.dumps(specialty_config, indent=2)}
+
+CONVERSATION HISTORY:
+{json.dumps(conversation_history, indent=2)}
+
+PROPOSED EXTRACTED STATE:
+{json.dumps(extracted_data, indent=2)}
+
+Return ONLY a JSON response:
+{{
+    "valid": true/false,
+    "missing": ["list of critical missing focus items for this specialty, if any"],
+    "recommendation": "continue or ask_severity or ask_duration etc.",
+    "hallucinations_detected": false
+}}
+"""
+            response = await client.messages.create(
+                model=self.model,
+                max_tokens=1024,
+                system="You are a clinical AI quality controller. Output only valid JSON.",
+                messages=[{"role": "user", "content": prompt}],
+            )
+            content = response.content[0].text
+            return json.loads(content)
+        except Exception as e:
+            print(f"[Claude Validation Error]: {e}")
+            return {
+                "valid": True,
+                "missing": [],
+                "recommendation": "continue",
+                "hallucinations_detected": False,
+            }