fix: Change Ollama default URL to host.docker.internal for Docker compatibility

- Changed default Ollama URL from localhost:11434 to host.docker.internal:11434
- This allows Docker containers to connect to Ollama running on the host machine
- Updated in backend services, frontend components, migration scripts, and documentation
- Most users run Archon in Docker but Ollama as a local binary, making this a better default
This commit is contained in:
John Fitzpatrick 2025-09-20 13:36:33 -07:00
parent 035f90e721
commit d4e80a945a
7 changed files with 13 additions and 13 deletions

View File

@ -595,7 +595,7 @@ const OllamaConfigurationPanel: React.FC<OllamaConfigurationPanelProps> = ({
value={tempUrls[instance.id] !== undefined ? tempUrls[instance.id] : instance.baseUrl}
onChange={(e) => handleUrlChange(instance.id, e.target.value)}
onBlur={() => handleUrlBlur(instance.id)}
placeholder="http://localhost:11434"
placeholder="http://host.docker.internal:11434"
className={cn(
"text-sm",
tempUrls[instance.id] !== undefined && tempUrls[instance.id] !== instance.baseUrl

View File

@ -61,11 +61,11 @@ export const RAGSettings = ({
// Instance configurations
const [llmInstanceConfig, setLLMInstanceConfig] = useState({
name: '',
url: ragSettings.LLM_BASE_URL || 'http://localhost:11434/v1'
url: ragSettings.LLM_BASE_URL || 'http://host.docker.internal:11434/v1'
});
const [embeddingInstanceConfig, setEmbeddingInstanceConfig] = useState({
name: '',
url: ragSettings.OLLAMA_EMBEDDING_URL || 'http://localhost:11434/v1'
url: ragSettings.OLLAMA_EMBEDDING_URL || 'http://host.docker.internal:11434/v1'
});
// Update instance configs when ragSettings change (after loading from database)
@ -932,7 +932,7 @@ export const RAGSettings = ({
className="text-green-400 border-green-400 mb-1"
onClick={() => {
// Quick setup: configure both instances with default values
const defaultUrl = 'http://localhost:11434/v1';
const defaultUrl = 'http://host.docker.internal:11434/v1';
const defaultName = 'Default Ollama';
setLLMInstanceConfig({ name: defaultName, url: defaultUrl });
setEmbeddingInstanceConfig({ name: defaultName, url: defaultUrl });
@ -1680,7 +1680,7 @@ export const RAGSettings = ({
});
}
}}
placeholder="http://localhost:11434/v1"
placeholder="http://host.docker.internal:11434/v1"
/>
{/* Convenience checkbox for single host setup */}
@ -1753,7 +1753,7 @@ export const RAGSettings = ({
label="Instance URL"
value={embeddingInstanceConfig.url}
onChange={(e) => setEmbeddingInstanceConfig({...embeddingInstanceConfig, url: e.target.value})}
placeholder="http://localhost:11434/v1"
placeholder="http://host.docker.internal:11434/v1"
/>
</div>

View File

@ -320,7 +320,7 @@ EMBEDDING_MODEL=text-embedding-004
### Ollama (Local/Private)
```bash
LLM_PROVIDER=ollama
LLM_BASE_URL=http://localhost:11434/v1
LLM_BASE_URL=http://host.docker.internal:11434/v1
MODEL_CHOICE=llama2
EMBEDDING_MODEL=nomic-embed-text
# Pros: Privacy, no API costs

View File

@ -94,7 +94,7 @@ INSERT INTO archon_settings (key, encrypted_value, is_encrypted, category, descr
-- LLM Provider configuration settings
INSERT INTO archon_settings (key, value, is_encrypted, category, description) VALUES
('LLM_PROVIDER', 'openai', false, 'rag_strategy', 'LLM provider to use: openai, ollama, or google'),
('LLM_BASE_URL', NULL, false, 'rag_strategy', 'Custom base URL for LLM provider (mainly for Ollama, e.g., http://localhost:11434/v1)'),
('LLM_BASE_URL', NULL, false, 'rag_strategy', 'Custom base URL for LLM provider (mainly for Ollama, e.g., http://host.docker.internal:11434/v1)'),
('EMBEDDING_MODEL', 'text-embedding-3-small', false, 'rag_strategy', 'Embedding model for vector search and similarity matching (required for all embedding operations)')
ON CONFLICT (key) DO NOTHING;

View File

@ -475,7 +475,7 @@ class CredentialService:
def _get_provider_base_url(self, provider: str, rag_settings: dict) -> str | None:
"""Get base URL for provider."""
if provider == "ollama":
return rag_settings.get("LLM_BASE_URL", "http://localhost:11434/v1")
return rag_settings.get("LLM_BASE_URL", "http://host.docker.internal:11434/v1")
elif provider == "google":
return "https://generativelanguage.googleapis.com/v1beta/openai/"
return None # Use default for OpenAI

View File

@ -203,7 +203,7 @@ async def _get_optimal_ollama_instance(instance_type: str | None = None,
return embedding_url if embedding_url.endswith('/v1') else f"{embedding_url}/v1"
# Default to LLM base URL for chat operations
fallback_url = rag_settings.get("LLM_BASE_URL", "http://localhost:11434")
fallback_url = rag_settings.get("LLM_BASE_URL", "http://host.docker.internal:11434")
return fallback_url if fallback_url.endswith('/v1') else f"{fallback_url}/v1"
except Exception as e:
@ -211,11 +211,11 @@ async def _get_optimal_ollama_instance(instance_type: str | None = None,
# Final fallback to localhost only if we can't get RAG settings
try:
rag_settings = await credential_service.get_credentials_by_category("rag_strategy")
fallback_url = rag_settings.get("LLM_BASE_URL", "http://localhost:11434")
fallback_url = rag_settings.get("LLM_BASE_URL", "http://host.docker.internal:11434")
return fallback_url if fallback_url.endswith('/v1') else f"{fallback_url}/v1"
except Exception as fallback_error:
logger.error(f"Could not retrieve fallback configuration: {fallback_error}")
return "http://localhost:11434/v1"
return "http://host.docker.internal:11434/v1"
async def get_embedding_model(provider: str | None = None) -> str:

View File

@ -23,7 +23,7 @@ _provider_cache: dict[str, tuple[Any, float]] = {}
_CACHE_TTL_SECONDS = 300 # 5 minutes
# Default Ollama instance URL (configurable via environment/settings)
DEFAULT_OLLAMA_URL = "http://localhost:11434"
DEFAULT_OLLAMA_URL = "http://host.docker.internal:11434"
# Model pattern detection for dynamic capabilities (no hardcoded model names)
CHAT_MODEL_PATTERNS = ["llama", "qwen", "mistral", "codellama", "phi", "gemma", "vicuna", "orca"]