Create model_manager.py

model_manager.py

@@ -0,0 +1,71 @@
+# model_manager.py
+from transformers import pipeline
+import asyncio
+
+class ModelManager:
+    def __init__(self, cache_dir="./model_cache"):
+        self.models = {}
+        self.models_loaded = False
+        self.cache_dir = cache_dir
+
+    async def load_models_async(self):
+        async def load(key, model_name):
+            try:
+                self.models[key] = pipeline(
+                    "text-generation",
+                    model=model_name,
+                    device="cpu",
+                    model_kwargs={"cache_dir": self.cache_dir}
+                )
+            except Exception as e:
+                self.models[key] = None
+        tasks = [
+            load("chat","microsoft/DialoGPT-small"),
+            load("code","microsoft/CodeGPT-small-py"),
+            load("creative","microsoft/DialoGPT-small"),
+        ]
+        await asyncio.gather(*tasks)
+        self.models_loaded = True
+
+    def get_model_for_task(self, task_type):
+        mapping = {
+            "CONVERSATION": self.models.get("chat"),
+            "CODE_GENERATION": self.models.get("code"),
+            "CREATIVE_WRITING": self.models.get("creative"),
+        }
+        return mapping.get(task_type, self.models.get("chat"))
+
+
+# api_agent.py
+import requests
+
+class APIAgent:
+    def __init__(self, config):
+        self.config = config  # debe contener keys ya cargadas desde /config
+        self.session = requests.Session()
+
+    def call_openai(self, prompt, system_message=""):
+        key = self.config.get("openai_api_key", "")
+        if not key:
+            return None
+        url = "https://api.openai.com/v1/chat/completions"
+        headers = {"Authorization": f"Bearer {key}", "Content-Type": "application/json"}
+        payload = {"model":"gpt-3.5-turbo", "messages":[{"role":"system","content":system_message},{"role":"user","content":prompt}], "temperature": self.config.get("temperature", 0.7), "max_tokens": self.config.get("max_tokens", 600)}
+        r = self.session.post(url, headers=headers, json=payload, timeout=self.config.get("timeout", 30))
+        if r.ok:
+            return r.json()["choices"][0]["message"]["content"]
+        return None
+
+    def call_deepseek(self, prompt, system_message=""):
+        key = self.config.get("deepseek_api_key", "")
+        if not key:
+            return None
+        # similar a OpenAI: payload adaptado
+        url = "https://api.deepseek.com/v1/chat/completions"
+        headers = {"Authorization": f"Bearer {key}", "Content-Type": "application/json"}
+        payload = {"model":"deepseek-chat","messages":[{"role":"system","content":system_message},{"role":"user","content":prompt}]}
+        r = self.session.post(url, headers=headers, json=payload, timeout=self.config.get("timeout", 30))
+        if r.ok:
+            return r.json()["choices"][0]["message"]["content"]
+        return None
+