Migration from Docker to Standalone Python Server (#73)
* Migration from docker to standalone server Migration handling Fixed tests Use simpler in-memory storage Support for concurrent logging to disk Simplified direct connections to localhost * Migration from docker / redis to standalone script Updated tests Updated run script Fixed requirements Use dotenv Ask if user would like to install MCP in Claude Desktop once Updated docs * More cleanup and references to docker removed * Cleanup * Comments * Fixed tests * Fix GitHub Actions workflow for standalone Python architecture - Install requirements-dev.txt for pytest and testing dependencies - Remove Docker setup from simulation tests (now standalone) - Simplify linting job to use requirements-dev.txt - Update simulation tests to run directly without Docker Fixes unit test failures in CI due to missing pytest dependency. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * Remove simulation tests from GitHub Actions - Removed simulation-tests job that makes real API calls - Keep only unit tests (mocked, no API costs) and linting - Simulation tests should be run manually with real API keys - Reduces CI costs and complexity GitHub Actions now only runs: - Unit tests (569 tests, all mocked) - Code quality checks (ruff, black) 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * Fixed tests * Fixed tests --------- Co-authored-by: Claude <noreply@anthropic.com>
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Beehive Innovations
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@@ -151,10 +151,6 @@ class OpenAICompatibleProvider(ModelProvider):
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if hostname in ["localhost", "127.0.0.1", "::1"]:
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return True
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# Check for Docker internal hostnames (like host.docker.internal)
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if hostname and ("docker.internal" in hostname or "host.docker.internal" in hostname):
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return True
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# Check for private network ranges (local network)
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if hostname:
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try:
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@@ -201,26 +197,70 @@ class OpenAICompatibleProvider(ModelProvider):
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def client(self):
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"""Lazy initialization of OpenAI client with security checks and timeout configuration."""
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if self._client is None:
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client_kwargs = {
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"api_key": self.api_key,
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}
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import os
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if self.base_url:
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client_kwargs["base_url"] = self.base_url
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import httpx
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if self.organization:
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client_kwargs["organization"] = self.organization
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# Temporarily disable proxy environment variables to prevent httpx from detecting them
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original_env = {}
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proxy_env_vars = ["HTTP_PROXY", "HTTPS_PROXY", "ALL_PROXY", "http_proxy", "https_proxy", "all_proxy"]
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# Add default headers if any
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if self.DEFAULT_HEADERS:
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client_kwargs["default_headers"] = self.DEFAULT_HEADERS.copy()
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for var in proxy_env_vars:
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if var in os.environ:
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original_env[var] = os.environ[var]
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del os.environ[var]
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# Add configured timeout settings
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if hasattr(self, "timeout_config") and self.timeout_config:
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client_kwargs["timeout"] = self.timeout_config
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logging.debug(f"OpenAI client initialized with custom timeout: {self.timeout_config}")
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try:
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# Create a custom httpx client that explicitly avoids proxy parameters
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timeout_config = (
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self.timeout_config
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if hasattr(self, "timeout_config") and self.timeout_config
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else httpx.Timeout(30.0)
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)
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self._client = OpenAI(**client_kwargs)
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# Create httpx client with minimal config to avoid proxy conflicts
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# Note: proxies parameter was removed in httpx 0.28.0
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http_client = httpx.Client(
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timeout=timeout_config,
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follow_redirects=True,
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)
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# Keep client initialization minimal to avoid proxy parameter conflicts
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client_kwargs = {
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"api_key": self.api_key,
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"http_client": http_client,
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}
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if self.base_url:
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client_kwargs["base_url"] = self.base_url
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if self.organization:
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client_kwargs["organization"] = self.organization
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# Add default headers if any
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if self.DEFAULT_HEADERS:
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client_kwargs["default_headers"] = self.DEFAULT_HEADERS.copy()
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logging.debug(f"OpenAI client initialized with custom httpx client and timeout: {timeout_config}")
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# Create OpenAI client with custom httpx client
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self._client = OpenAI(**client_kwargs)
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except Exception as e:
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# If all else fails, try absolute minimal client without custom httpx
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logging.warning(f"Failed to create client with custom httpx, falling back to minimal config: {e}")
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try:
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minimal_kwargs = {"api_key": self.api_key}
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if self.base_url:
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minimal_kwargs["base_url"] = self.base_url
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self._client = OpenAI(**minimal_kwargs)
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except Exception as fallback_error:
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logging.error(f"Even minimal OpenAI client creation failed: {fallback_error}")
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raise
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finally:
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# Restore original proxy environment variables
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for var, value in original_env.items():
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os.environ[var] = value
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return self._client
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@@ -480,7 +520,7 @@ class OpenAICompatibleProvider(ModelProvider):
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# Log retry attempt
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logging.warning(
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f"{self.FRIENDLY_NAME} API error for model {model_name}, attempt {attempt + 1}/{max_retries}: {str(e)}. Retrying in {delay}s..."
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f"{self.FRIENDLY_NAME} error for model {model_name}, attempt {attempt + 1}/{max_retries}: {str(e)}. Retrying in {delay}s..."
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)
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time.sleep(delay)
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@@ -738,19 +778,11 @@ class OpenAICompatibleProvider(ModelProvider):
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# Handle data URL: data:image/png;base64,iVBORw0...
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return {"type": "image_url", "image_url": {"url": image_path}}
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else:
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# Handle file path - translate for Docker environment
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from utils.file_utils import translate_path_for_environment
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translated_path = translate_path_for_environment(image_path)
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logging.debug(f"Translated image path from '{image_path}' to '{translated_path}'")
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if not os.path.exists(translated_path):
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logging.warning(f"Image file not found: {translated_path} (original: {image_path})")
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# Handle file path
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if not os.path.exists(image_path):
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logging.warning(f"Image file not found: {image_path}")
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return None
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# Use translated path for all subsequent operations
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image_path = translated_path
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# Detect MIME type from file extension using centralized mappings
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from utils.file_types import get_image_mime_type
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