Initial commit: Context Manager v1.0.0

Sistema local de gestión de contexto para IA:
- Log inmutable (blockchain-style)
- Algoritmos versionados y mejorables
- Agnóstico al modelo (Anthropic, OpenAI, Ollama)
- Sistema de métricas y A/B testing

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

src/providers/ollama.py

@@ -0,0 +1,141 @@
+"""
+Adaptador para Ollama (modelos locales)
+"""
+
+import os
+import requests
+from typing import List, Dict, Any, Optional
+
+from .base import BaseProvider, ProviderResponse
+from ..models import SelectedContext, ContextSource
+
+
+class OllamaProvider(BaseProvider):
+    """Proveedor para modelos locales via Ollama"""
+
+    provider_name = "ollama"
+
+    def __init__(
+        self,
+        model: str = "llama3",
+        host: str = None,
+        port: int = None,
+        **kwargs
+    ):
+        super().__init__(model=model, **kwargs)
+
+        self.host = host or os.getenv("OLLAMA_HOST", "localhost")
+        self.port = port or int(os.getenv("OLLAMA_PORT", "11434"))
+        self.model = model
+        self.base_url = f"http://{self.host}:{self.port}"
+
+    def format_context(self, context: SelectedContext) -> List[Dict[str, str]]:
+        """
+        Formatea el contexto para Ollama.
+
+        Returns:
+            Lista de mensajes en formato Ollama
+        """
+        messages = []
+        system_parts = []
+
+        for item in context.items:
+            if item.source in [ContextSource.MEMORY, ContextSource.KNOWLEDGE,
+                              ContextSource.AMBIENT, ContextSource.DATASET]:
+                system_parts.append(item.content)
+            elif item.source == ContextSource.HISTORY:
+                role = item.metadata.get("role", "user")
+                messages.append({
+                    "role": role,
+                    "content": item.content
+                })
+
+        if system_parts:
+            messages.insert(0, {
+                "role": "system",
+                "content": "\n\n".join(system_parts)
+            })
+
+        return messages
+
+    def send_message(
+        self,
+        message: str,
+        context: SelectedContext = None,
+        system_prompt: str = None,
+        temperature: float = 0.7,
+        **kwargs
+    ) -> ProviderResponse:
+        """Envía mensaje a Ollama"""
+
+        # Formatear contexto
+        messages = self.format_context(context) if context else []
+
+        # Añadir system prompt
+        if system_prompt:
+            if messages and messages[0]["role"] == "system":
+                messages[0]["content"] = f"{system_prompt}\n\n{messages[0]['content']}"
+            else:
+                messages.insert(0, {"role": "system", "content": system_prompt})
+
+        # Añadir mensaje del usuario
+        messages.append({"role": "user", "content": message})
+
+        # Llamar a la API
+        url = f"{self.base_url}/api/chat"
+        payload = {
+            "model": self.model,
+            "messages": messages,
+            "stream": False,
+            "options": {
+                "temperature": temperature
+            }
+        }
+
+        response, latency_ms = self._measure_latency(
+            requests.post,
+            url,
+            json=payload,
+            timeout=120
+        )
+
+        response.raise_for_status()
+        data = response.json()
+
+        # Ollama no siempre retorna conteos de tokens
+        tokens_input = data.get("prompt_eval_count", self.estimate_tokens(str(messages)))
+        tokens_output = data.get("eval_count", self.estimate_tokens(data["message"]["content"]))
+
+        return ProviderResponse(
+            content=data["message"]["content"],
+            model=data.get("model", self.model),
+            tokens_input=tokens_input,
+            tokens_output=tokens_output,
+            latency_ms=latency_ms,
+            finish_reason=data.get("done_reason", "stop"),
+            raw_response={
+                "total_duration": data.get("total_duration"),
+                "load_duration": data.get("load_duration"),
+                "prompt_eval_duration": data.get("prompt_eval_duration"),
+                "eval_duration": data.get("eval_duration")
+            }
+        )
+
+    def list_models(self) -> List[str]:
+        """Lista los modelos disponibles en Ollama"""
+        response = requests.get(f"{self.base_url}/api/tags")
+        response.raise_for_status()
+        data = response.json()
+        return [m["name"] for m in data.get("models", [])]
+
+    def pull_model(self, model_name: str):
+        """Descarga un modelo en Ollama"""
+        response = requests.post(
+            f"{self.base_url}/api/pull",
+            json={"name": model_name},
+            stream=True
+        )
+        response.raise_for_status()
+        for line in response.iter_lines():
+            if line:
+                yield line.decode("utf-8")