From 991bd161f0aaf10c7e921643ac445de706ad29d1 Mon Sep 17 00:00:00 2001
From: Claude AI <claude@anthropic.com>
Date: Thu, 29 Jan 2026 11:13:15 +0000
Subject: [PATCH] feat(fase4): add AI response and sentiment nodes

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
---
 services/flow-engine/app/config.py         |   5 +
 services/flow-engine/app/nodes/__init__.py |  18 +++-
 services/flow-engine/app/nodes/ai.py       | 117 +++++++++++++++++++++
 3 files changed, 137 insertions(+), 3 deletions(-)
 create mode 100644 services/flow-engine/app/nodes/ai.py

diff --git a/services/flow-engine/app/config.py b/services/flow-engine/app/config.py
index deb0f28..bd5a365 100644
--- a/services/flow-engine/app/config.py
+++ b/services/flow-engine/app/config.py
@@ -5,6 +5,11 @@ from functools import lru_cache
 class Settings(BaseSettings):
     DATABASE_URL: str = "postgresql://whatsapp_admin:password@localhost:5432/whatsapp_central"
     REDIS_URL: str = "redis://localhost:6379"
+
+    # OpenAI
+    OPENAI_API_KEY: str = ""
+    OPENAI_MODEL: str = "gpt-3.5-turbo"
+
     API_GATEWAY_URL: str = "http://localhost:8000"
     WHATSAPP_CORE_URL: str = "http://localhost:3001"
 
diff --git a/services/flow-engine/app/nodes/__init__.py b/services/flow-engine/app/nodes/__init__.py
index 43e097f..8d0a748 100644
--- a/services/flow-engine/app/nodes/__init__.py
+++ b/services/flow-engine/app/nodes/__init__.py
@@ -1,6 +1,18 @@
+from app.nodes.advanced import (
+    DelayExecutor,
+    GoToExecutor,
+    LoopExecutor,
+    RandomExecutor,
+    SwitchExecutor,
+)
+from app.nodes.ai import AIResponseExecutor, AISentimentExecutor
 from app.nodes.base import NodeExecutor, NodeRegistry
 from app.nodes.basic import (
-    TriggerExecutor, MessageExecutor, ButtonsExecutor,
-    WaitInputExecutor, SetVariableExecutor, ConditionExecutor
+    ButtonsExecutor,
+    ConditionExecutor,
+    MessageExecutor,
+    SetVariableExecutor,
+    TriggerExecutor,
+    WaitInputExecutor,
 )
-from app.nodes.script import JavaScriptExecutor, HttpRequestExecutor
+from app.nodes.script import HttpRequestExecutor, JavaScriptExecutor
diff --git a/services/flow-engine/app/nodes/ai.py b/services/flow-engine/app/nodes/ai.py
new file mode 100644
index 0000000..c660e28
--- /dev/null
+++ b/services/flow-engine/app/nodes/ai.py
@@ -0,0 +1,117 @@
+from typing import Any, Optional
+
+import httpx
+
+from app.config import get_settings
+from app.context import FlowContext
+from app.nodes.base import NodeExecutor
+
+settings = get_settings()
+
+
+class AIResponseExecutor(NodeExecutor):
+    """Generate AI response using OpenAI"""
+
+    async def execute(
+        self, config: dict, context: FlowContext, session: Any
+    ) -> Optional[str]:
+        prompt = context.interpolate(config.get("prompt", ""))
+        system_prompt = config.get("system_prompt", "Eres un asistente útil.")
+        output_variable = config.get("output_variable", "_ai_response")
+        max_tokens = config.get("max_tokens", 500)
+        temperature = config.get("temperature", 0.7)
+
+        if not settings.OPENAI_API_KEY:
+            context.set("_ai_error", "OpenAI API key not configured")
+            return "error"
+
+        if not prompt:
+            return "error"
+
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": prompt},
+        ]
+
+        if config.get("include_history", False):
+            history = context.get("_conversation_history") or []
+            messages = (
+                [{"role": "system", "content": system_prompt}]
+                + history
+                + [{"role": "user", "content": prompt}]
+            )
+
+        async with httpx.AsyncClient() as client:
+            response = await client.post(
+                "https://api.openai.com/v1/chat/completions",
+                headers={
+                    "Authorization": f"Bearer {settings.OPENAI_API_KEY}",
+                    "Content-Type": "application/json",
+                },
+                json={
+                    "model": settings.OPENAI_MODEL,
+                    "messages": messages,
+                    "max_tokens": max_tokens,
+                    "temperature": temperature,
+                },
+                timeout=30,
+            )
+
+            if response.status_code != 200:
+                context.set("_ai_error", response.text)
+                return "error"
+
+            data = response.json()
+            ai_response = data["choices"][0]["message"]["content"]
+            context.set(output_variable, ai_response)
+            return "success"
+
+
+class AISentimentExecutor(NodeExecutor):
+    """Analyze sentiment of user message"""
+
+    async def execute(
+        self, config: dict, context: FlowContext, session: Any
+    ) -> Optional[str]:
+        text = context.get(config.get("variable", "")) or context.message.get(
+            "content", ""
+        )
+        output_variable = config.get("output_variable", "_sentiment")
+
+        if not settings.OPENAI_API_KEY or not text:
+            return "neutral"
+
+        async with httpx.AsyncClient() as client:
+            response = await client.post(
+                "https://api.openai.com/v1/chat/completions",
+                headers={
+                    "Authorization": f"Bearer {settings.OPENAI_API_KEY}",
+                    "Content-Type": "application/json",
+                },
+                json={
+                    "model": "gpt-3.5-turbo",
+                    "messages": [
+                        {
+                            "role": "system",
+                            "content": "Analyze the sentiment. Reply with only one word: positive, negative, or neutral",
+                        },
+                        {"role": "user", "content": text},
+                    ],
+                    "max_tokens": 10,
+                    "temperature": 0,
+                },
+                timeout=15,
+            )
+
+            if response.status_code != 200:
+                return "neutral"
+
+            data = response.json()
+            sentiment = data["choices"][0]["message"]["content"].lower().strip()
+            context.set(output_variable, sentiment)
+
+            if "positive" in sentiment:
+                return "positive"
+            if "negative" in sentiment:
+                return "negative"
+            return "neutral"