Add provider implementations (OpenAI, Anthropic, Ollama)

src/promptforge/providers/openai.py

@@ -0,0 +1,128 @@
+import asyncio
+import time
+from typing import Any, AsyncIterator, Dict, Optional
+
+from openai import AsyncOpenAI, APIError, RateLimitError, APIConnectionError
+
+from .base import ProviderBase, ProviderResponse
+from ..core.exceptions import ProviderError
+
+
+class OpenAIProvider(ProviderBase):
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        model: str = "gpt-4",
+        temperature: float = 0.7,
+        base_url: Optional[str] = None,
+        **kwargs,
+    ):
+        super().__init__(api_key, model, temperature, **kwargs)
+        self.base_url = base_url
+        self._client: Optional[AsyncOpenAI] = None
+
+    @property
+    def name(self) -> str:
+        return "openai"
+
+    def _get_client(self) -> AsyncOpenAI:
+        if self._client is None:
+            api_key = self.api_key or self._get_api_key_from_env()
+            if not api_key:
+                raise ProviderError(
+                    "OpenAI API key not configured. "
+                    "Set OPENAI_API_KEY env var or pass api_key parameter."
+                )
+            self._client = AsyncOpenAI(api_key=api_key, base_url=self.base_url)
+        return self._client
+
+    def _get_api_key_from_env(self) -> Optional[str]:
+        import os
+        return os.environ.get("OPENAI_API_KEY")
+
+    async def complete(
+        self,
+        prompt: str,
+        system_prompt: Optional[str] = None,
+        max_tokens: Optional[int] = None,
+        **kwargs,
+    ) -> ProviderResponse:
+        start_time = time.time()
+
+        try:
+            client = self._get_client()
+
+            messages = []
+            if system_prompt:
+                messages.append({"role": "system", "content": system_prompt})
+            messages.append({"role": "user", "content": prompt})
+
+            response = await client.chat.completions.create(
+                model=self.model,
+                messages=messages,
+                temperature=self.temperature,
+                max_tokens=max_tokens,
+                **kwargs,
+            )
+
+            latency_ms = (time.time() - start_time) * 1000
+
+            return ProviderResponse(
+                content=response.choices[0].message.content or "",
+                model=self.model,
+                provider=self.name,
+                usage={
+                    "prompt_tokens": response.usage.prompt_tokens,
+                    "completion_tokens": response.usage.completion_tokens,
+                    "total_tokens": response.usage.total_tokens,
+                },
+                latency_ms=latency_ms,
+                metadata={"finish_reason": response.choices[0].finish_reason},
+            )
+        except APIError as e:
+            raise ProviderError(f"OpenAI API error: {e}")
+        except RateLimitError as e:
+            raise ProviderError(f"OpenAI rate limit exceeded: {e}")
+        except APIConnectionError as e:
+            raise ProviderError(f"OpenAI connection error: {e}")
+
+    async def stream_complete(
+        self,
+        prompt: str,
+        system_prompt: Optional[str] = None,
+        max_tokens: Optional[int] = None,
+        **kwargs,
+    ) -> AsyncIterator[str]:
+        try:
+            client = self._get_client()
+
+            messages = []
+            if system_prompt:
+                messages.append({"role": "system", "content": system_prompt})
+            messages.append({"role": "user", "content": prompt})
+
+            stream = await client.chat.completions.create(
+                model=self.model,
+                messages=messages,
+                temperature=self.temperature,
+                max_tokens=max_tokens,
+                stream=True,
+                **kwargs,
+            )
+
+            async for chunk in stream:
+                if chunk.choices[0].delta.content:
+                    yield chunk.choices[0].delta.content
+        except APIError as e:
+            raise ProviderError(f"OpenAI API error: {e}")
+
+    def validate_api_key(self) -> bool:
+        try:
+            import os
+            api_key = self.api_key or os.environ.get("OPENAI_API_KEY")
+            if not api_key:
+                return False
+            client = AsyncOpenAI(api_key=api_key)
+            return True
+        except Exception:
+            return False