GUI Created, Dark Mode Created, npm script added, styling changed, Decoupled from Claude made more open source.

src/llm/providers/claude.py

@@ -0,0 +1,103 @@
+"""Claude provider adapter."""
+
+from __future__ import annotations
+
+import os
+from typing import Any
+
+from anthropic import Anthropic
+
+from llm.core.interface import (
+    AuthenticationError,
+    ContextLengthError,
+    LLMProvider,
+    RateLimitError,
+)
+from llm.core.types import LLMInput, LLMOutput, Message, ModelInfo, ProviderType, ToolCall
+
+
+class ClaudeProvider(LLMProvider):
+    provider_type = ProviderType.CLAUDE
+
+    def __init__(self, api_key: str | None = None, base_url: str | None = None) -> None:
+        self.client = Anthropic(api_key=api_key or os.environ.get("ANTHROPIC_API_KEY"), base_url=base_url)
+        self._models = [
+            ModelInfo(
+                name="claude-opus-4-5",
+                provider=ProviderType.CLAUDE,
+                supports_tools=True,
+                supports_vision=True,
+                max_tokens=8192,
+                context_window=200000,
+            ),
+            ModelInfo(
+                name="claude-sonnet-4-7",
+                provider=ProviderType.CLAUDE,
+                supports_tools=True,
+                supports_vision=True,
+                max_tokens=8192,
+                context_window=200000,
+            ),
+            ModelInfo(
+                name="claude-haiku-4-7",
+                provider=ProviderType.CLAUDE,
+                supports_tools=True,
+                supports_vision=False,
+                max_tokens=4096,
+                context_window=200000,
+            ),
+        ]
+
+    def generate(self, input: LLMInput) -> LLMOutput:
+        try:
+            params: dict[str, Any] = {
+                "model": input.model or "claude-sonnet-4-7",
+                "messages": [msg.to_dict() for msg in input.messages],
+                "temperature": input.temperature,
+            }
+            if input.max_tokens:
+                params["max_tokens"] = input.max_tokens
+            if input.tools:
+                params["tools"] = [tool.to_dict() for tool in input.tools]
+
+            response = self.client.messages.create(**params)
+
+            tool_calls = None
+            if response.content and hasattr(response.content[0], "type"):
+                if response.content[0].type == "tool_use":
+                    tool_calls = [
+                        ToolCall(
+                            id=getattr(response.content[0], "id", ""),
+                            name=getattr(response.content[0], "name", ""),
+                            arguments=getattr(response.content[0].input, "__dict__", {}),
+                        )
+                    ]
+
+            return LLMOutput(
+                content=response.content[0].text if response.content else "",
+                tool_calls=tool_calls,
+                model=response.model,
+                usage={
+                    "input_tokens": response.usage.input_tokens,
+                    "output_tokens": response.usage.output_tokens,
+                },
+                stop_reason=response.stop_reason,
+            )
+        except Exception as e:
+            msg = str(e)
+            if "401" in msg or "authentication" in msg.lower():
+                raise AuthenticationError(msg, provider=ProviderType.CLAUDE) from e
+            if "429" in msg or "rate_limit" in msg.lower():
+                raise RateLimitError(msg, provider=ProviderType.CLAUDE) from e
+            if "context" in msg.lower() and "length" in msg.lower():
+                raise ContextLengthError(msg, provider=ProviderType.CLAUDE) from e
+            raise
+
+    def list_models(self) -> list[ModelInfo]:
+        return self._models.copy()
+
+    def validate_config(self) -> bool:
+        return bool(self.client.api_key)
+
+    def get_default_model(self) -> str:
+        return "claude-sonnet-4-7"