fix: resolve CI linting and type errors

src/promptforge/providers/ollama.py

@@ -1,6 +1,9 @@
-import asyncio
+"""Ollama provider implementation for local models."""
+
+import json
 import time
 from typing import Any, AsyncIterator, Dict, Optional
+
 import httpx
 
 from .base import ProviderBase, ProviderResponse
@@ -8,20 +11,35 @@ from ..core.exceptions import ProviderError
 
 
 class OllamaProvider(ProviderBase):
+    """Ollama local model provider."""
+
     def __init__(
         self,
+        api_key: Optional[str] = None,
         model: str = "llama2",
         temperature: float = 0.7,
         base_url: str = "http://localhost:11434",
         **kwargs,
     ):
-        super().__init__(None, model, temperature, **kwargs)
+        """Initialize Ollama provider."""
+        super().__init__(api_key, model, temperature, **kwargs)
         self.base_url = base_url.rstrip('/')
+        self._client: Optional[httpx.AsyncClient] = None
 
     @property
     def name(self) -> str:
         return "ollama"
 
+    def _get_client(self) -> httpx.AsyncClient:
+        """Get or create HTTP client."""
+        if self._client is None:
+            self._client = httpx.AsyncClient(timeout=120.0)
+        return self._client
+
+    def _get_api_url(self, endpoint: str) -> str:
+        """Get full URL for an endpoint."""
+        return f"{self.base_url}/{endpoint.lstrip('/')}"
+
     async def complete(
         self,
         prompt: str,
@@ -29,78 +47,133 @@ class OllamaProvider(ProviderBase):
         max_tokens: Optional[int] = None,
         **kwargs,
     ) -> ProviderResponse:
+        """Send completion request to Ollama."""
         start_time = time.time()
 
         try:
-            async with httpx.AsyncClient() as client:
-                payload = {
-                    "model": self.model,
-                    "prompt": prompt,
-                    "stream": False,
-                    "options": {
-                        "temperature": self.temperature,
-                    }
-                }
-                if max_tokens:
-                    payload["options"]["num_predict"] = max_tokens
+            client = self._get_client()
 
-                response = await client.post(
-                    f"{self.base_url}/api/generate",
-                    json=payload,
-                    timeout=120.0
-                )
+            messages = []
+            if system_prompt:
+                messages.append({"role": "system", "content": system_prompt})
+            messages.append({"role": "user", "content": prompt})
 
-                response.raise_for_status()
-                data = response.json()
+            payload: Dict[str, Any] = {
+                "model": self.model,
+                "messages": messages,
+                "stream": False,
+                "options": {
+                    "temperature": self.temperature,
+                },
+            }
 
-                latency_ms = (time.time() - start_time) * 1000
+            if max_tokens:
+                payload["options"]["num_predict"] = max_tokens
 
-                return ProviderResponse(
-                    content=data.get("response", ""),
-                    model=self.model,
-                    provider=self.name,
-                    latency_ms=latency_ms,
-                )
-        except httpx.HTTPStatusError as e:
-            raise ProviderError(f"Ollama HTTP error: {e}")
-        except httpx.RequestError as e:
+            response = await client.post(
+                self._get_api_url("/api/chat"),
+                json=payload,
+            )
+            response.raise_for_status()
+            data = response.json()
+
+            latency_ms = (time.time() - start_time) * 1000
+
+            content = ""
+            for msg in data.get("message", {}).get("content", ""):
+                if isinstance(msg, str):
+                    content += msg
+                elif isinstance(msg, dict):
+                    content += msg.get("content", "")
+
+            return ProviderResponse(
+                content=content,
+                model=self.model,
+                provider=self.name,
+                usage={
+                    "prompt_tokens": data.get("prompt_eval_count", 0),
+                    "completion_tokens": data.get("eval_count", 0),
+                    "total_tokens": data.get("prompt_eval_count", 0) + data.get("eval_count", 0),
+                },
+                latency_ms=latency_ms,
+                metadata={
+                    "done": data.get("done", False),
+                },
+            )
+        except httpx.HTTPError as e:
             raise ProviderError(f"Ollama connection error: {e}")
 
-    async def stream_complete(
+    async def stream_complete(  # type: ignore[override]
         self,
         prompt: str,
         system_prompt: Optional[str] = None,
         max_tokens: Optional[int] = None,
         **kwargs,
     ) -> AsyncIterator[str]:
+        """Stream completion from Ollama."""
         try:
-            async with httpx.AsyncClient() as client:
-                payload = {
-                    "model": self.model,
-                    "prompt": prompt,
-                    "stream": True,
-                    "options": {
-                        "temperature": self.temperature,
-                    }
-                }
-                if max_tokens:
-                    payload["options"]["num_predict"] = max_tokens
+            client = self._get_client()
 
-                async with client.stream(
-                    "POST",
-                    f"{self.base_url}/api/generate",
-                    json=payload,
-                    timeout=120.0
-                ) as response:
-                    async for line in response.aiter_lines():
-                        import json
+            messages = []
+            if system_prompt:
+                messages.append({"role": "system", "content": system_prompt})
+            messages.append({"role": "user", "content": prompt})
+
+            payload: Dict[str, Any] = {
+                "model": self.model,
+                "messages": messages,
+                "stream": True,
+                "options": {
+                    "temperature": self.temperature,
+                },
+            }
+
+            if max_tokens:
+                payload["options"]["num_predict"] = max_tokens
+
+            async with client.stream(
+                "POST",
+                self._get_api_url("/api/chat"),
+                json=payload,
+            ) as response:
+                async for line in response.aiter_lines():
+                    if line:
                         data = json.loads(line)
-                        if "response" in data:
-                            yield data["response"]
-        except httpx.HTTPStatusError as e:
-            raise ProviderError(f"Ollama HTTP error: {e}")
-        except httpx.RequestError as e:
+                        if "message" in data:
+                            content = data["message"].get("content", "")
+                            if content:
+                                yield content
+        except httpx.HTTPError as e:
             raise ProviderError(f"Ollama connection error: {e}")
 
+    async def pull_model(self, model: Optional[str] = None) -> bool:
+        """Pull a model from Ollama registry."""
+        try:
+            client = self._get_client()
+            target_model = model or self.model
+
+            async with client.stream(
+                "POST",
+                self._get_api_url("/api/pull"),
+                json={"name": target_model, "stream": False},
+            ) as response:
+                response.raise_for_status()
+                return True
+        except httpx.HTTPError:
+            return False
+
     def validate_api_key(self) -> bool:
+        """Ollama doesn't use API keys, always returns True."""
         return True
+
+    def list_models(self) -> list[str]:
+        """List available Ollama models."""
+        return [
+            "llama2",
+            "llama2-uncensored",
+            "mistral",
+            "mixtral",
+            "codellama",
+            "deepseek-coder",
+            "neural-chat",
+        ]