feat: add Portkey provider support and null-content guard to AI abstraction layer

Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com>

app/config.py

@@ -35,6 +35,13 @@ class Settings(BaseSettings):
     openrouter_api_key: Optional[str] = None
     openrouter_base_url: str = "https://openrouter.ai/api/v1"
 
+    # Portkey AI gateway settings (used when ai_provider="portkey")
+    # See https://portkey.ai for setup instructions
+    portkey_api_key: Optional[str] = None
+    portkey_virtual_key: Optional[str] = None   # Routes to a specific provider via Portkey vault
+    portkey_config: Optional[str] = None         # Portkey Config ID for advanced routing rules
+    portkey_base_url: str = "https://api.portkey.ai/v1"
+
     # Azure OpenAI API version (used when ai_provider="azure")
     azure_openai_api_version: str = "2024-02-01"
     workdir: str

app/utils/ai_provider.py

@@ -3,8 +3,8 @@
 
 This module provides a pluggable abstraction for various AI model providers,
 allowing the platform to work with OpenAI, Azure OpenAI, Anthropic Claude,
-Google Gemini, Ollama (local LLMs), OpenRouter, and any LiteLLM-compatible
+Google Gemini, Ollama (local LLMs), OpenRouter, Portkey, and any
-provider without being locked to a single vendor.
+LiteLLM-compatible provider without being locked to a single vendor.
 
 Provider selection is controlled by the ``AI_PROVIDER`` environment variable.
 See the Configuration Guide for full details on each provider's settings.
@@ -14,9 +14,36 @@ import logging
 from abc import ABC, abstractmethod
 from typing import Any, Dict, List, Optional
 
+from app.config import settings
+
 logger = logging.getLogger(__name__)
 
 
+def _require_text_content(content: Optional[str]) -> str:
+    """Raise a clear error if the AI response contains no text content.
+
+    This can happen when the model returns a tool/function call instead of
+    a plain text message.  All DocuElevate prompts expect a plain-text or
+    JSON response, so ``None`` content is always an unexpected condition.
+
+    Args:
+        content: The ``message.content`` value from the completion response.
+
+    Returns:
+        The original string, guaranteed non-None.
+
+    Raises:
+        ValueError: If *content* is ``None``.
+    """
+    if content is None:
+        raise ValueError(
+            "AI provider returned a response with no text content (content=None). "
+            "This may occur when the model generates a tool call instead of a plain text reply. "
+            "Ensure the model and prompt are configured for text/JSON output."
+        )
+    return content
+
+
 class AIProvider(ABC):
     """Abstract base class for AI chat completion providers.
 
@@ -80,7 +107,8 @@ class OpenAIProvider(AIProvider):
             temperature=temperature,
             **kwargs,
         )
-        return completion.choices[0].message.content
+        _content = completion.choices[0].message.content
+        return _require_text_content(_content)
 
 
 class AzureOpenAIProvider(AIProvider):
@@ -108,7 +136,8 @@ class AzureOpenAIProvider(AIProvider):
             temperature=temperature,
             **kwargs,
         )
-        return completion.choices[0].message.content
+        _content = completion.choices[0].message.content
+        return _require_text_content(_content)
 
 
 class AnthropicProvider(AIProvider):
@@ -139,7 +168,8 @@ class AnthropicProvider(AIProvider):
             api_key=self._api_key,
             **kwargs,
         )
-        return response.choices[0].message.content
+        _content = response.choices[0].message.content
+        return _require_text_content(_content)
 
 
 class GeminiProvider(AIProvider):
@@ -170,7 +200,8 @@ class GeminiProvider(AIProvider):
             api_key=self._api_key,
             **kwargs,
         )
-        return response.choices[0].message.content
+        _content = response.choices[0].message.content
+        return _require_text_content(_content)
 
 
 class OllamaProvider(AIProvider):
@@ -210,7 +241,8 @@ class OllamaProvider(AIProvider):
             temperature=temperature,
             **kwargs,
         )
-        return completion.choices[0].message.content
+        _content = completion.choices[0].message.content
+        return _require_text_content(_content)
 
 
 class OpenRouterProvider(AIProvider):
@@ -243,7 +275,74 @@ class OpenRouterProvider(AIProvider):
             temperature=temperature,
             **kwargs,
         )
-        return completion.choices[0].message.content
+        _content = completion.choices[0].message.content
+        return _require_text_content(_content)
+
+
+class PortkeyProvider(AIProvider):
+    """Portkey AI gateway (https://portkey.ai).
+
+    Portkey is an AI gateway that provides observability, caching, automatic
+    retries, fallbacks, and load balancing across 200+ LLMs via a single
+    OpenAI-compatible endpoint.
+
+    Required settings:
+        ``PORTKEY_API_KEY`` – your Portkey account API key.
+
+    Optional settings:
+        ``PORTKEY_VIRTUAL_KEY`` – a Portkey *Virtual Key* that maps to the
+        credentials of a specific provider stored in your Portkey vault.
+        When set, you do not need to expose the underlying provider's API key
+        in your environment.
+
+        ``PORTKEY_CONFIG`` – a saved Portkey *Config* ID (e.g.
+        ``pc-my-config-abc123``) that applies advanced routing rules such as
+        fallbacks and load balancing.
+
+        ``PORTKEY_BASE_URL`` – override the gateway endpoint.
+        Default: ``https://api.portkey.ai/v1``.
+
+    The model name should match what the underlying provider expects (e.g.
+    ``gpt-4o`` for OpenAI, ``claude-3-5-sonnet-20241022`` for Anthropic via a
+    virtual key).
+    """
+
+    def __init__(
+        self,
+        api_key: str,
+        virtual_key: Optional[str] = None,
+        config: Optional[str] = None,
+        base_url: str = "https://api.portkey.ai/v1",
+    ) -> None:
+        import openai
+
+        portkey_headers: Dict[str, str] = {"x-portkey-api-key": api_key}
+        if virtual_key:
+            portkey_headers["x-portkey-virtual-key"] = virtual_key
+        if config:
+            portkey_headers["x-portkey-config"] = config
+
+        self._client = openai.OpenAI(
+            api_key=api_key,
+            base_url=base_url,
+            default_headers=portkey_headers,
+        )
+
+    def chat_completion(
+        self,
+        messages: List[Dict[str, str]],
+        model: str,
+        temperature: float = 0,
+        **kwargs: Any,
+    ) -> str:
+        completion = self._client.chat.completions.create(
+            model=model,
+            messages=messages,
+            temperature=temperature,
+            **kwargs,
+        )
+        _content = completion.choices[0].message.content
+        return _require_text_content(_content)
 
 
 class LiteLLMProvider(AIProvider):
@@ -283,7 +382,8 @@ class LiteLLMProvider(AIProvider):
             completion_kwargs["api_base"] = self._api_base
         completion_kwargs.update(kwargs)
         response = litellm.completion(**completion_kwargs)
-        return response.choices[0].message.content
+        _content = response.choices[0].message.content
+        return _require_text_content(_content)
 
 
 def get_ai_provider() -> AIProvider:
@@ -300,8 +400,6 @@ def get_ai_provider() -> AIProvider:
         ValueError: If the configured provider name is not recognised.
         ValueError: If required credentials for the selected provider are absent.
     """
-    from app.config import settings
-
     provider = settings.ai_provider.lower()
     logger.debug(f"Creating AI provider: {provider}")
 
@@ -333,6 +431,15 @@ def get_ai_provider() -> AIProvider:
             api_key=settings.openrouter_api_key,
             base_url=settings.openrouter_base_url,
         )
+    elif provider == "portkey":
+        if not settings.portkey_api_key:
+            raise ValueError("PORTKEY_API_KEY must be set when AI_PROVIDER='portkey'")
+        return PortkeyProvider(
+            api_key=settings.portkey_api_key,
+            virtual_key=settings.portkey_virtual_key,
+            config=settings.portkey_config,
+            base_url=settings.portkey_base_url,
+        )
     elif provider == "litellm":
         return LiteLLMProvider(
             api_key=settings.openai_api_key or None,
@@ -341,5 +448,5 @@ def get_ai_provider() -> AIProvider:
     else:
         raise ValueError(
             f"Unknown AI provider: '{provider}'. "
-            "Supported providers: openai, azure, anthropic, gemini, ollama, openrouter, litellm"
+            "Supported providers: openai, azure, anthropic, gemini, ollama, openrouter, portkey, litellm"
         )

docs/ConfigurationGuide.md

@@ -302,11 +302,154 @@ SECURITY_HEADER_CSP_VALUE="default-src 'self'; script-src 'self' https://trusted
 - [Deployment Guide - Security Headers](DeploymentGuide.md#security-headers) for Traefik/Nginx examples
 - [SECURITY_AUDIT.md](../SECURITY_AUDIT.md#infrastructure-security) for security rationale
 
-### OpenAI & Azure Document Intelligence
+### AI Provider & Model Selection
+
+DocuElevate supports multiple AI providers for metadata extraction and OCR text refinement. Select the provider via `AI_PROVIDER` and configure the matching credentials below.
+
+| **Variable**      | **Description**                                                       | **Default**        |
+|-------------------|-----------------------------------------------------------------------|--------------------|
+| `AI_PROVIDER`     | Active AI provider. See supported values below.                       | `openai`           |
+| `AI_MODEL`        | Model name for the selected provider. Falls back to `OPENAI_MODEL` when not set. | *(unset)* |
+| `OPENAI_MODEL`    | Default model name (used when `AI_MODEL` is not set).                 | `gpt-4o-mini`      |
+
+**Supported `AI_PROVIDER` values**: `openai`, `azure`, `anthropic`, `gemini`, `ollama`, `openrouter`, `portkey`, `litellm`
+
+---
+
+#### OpenAI (default)
+
+| **Variable**          | **Description**                                  | **Default**                      |
+|-----------------------|--------------------------------------------------|----------------------------------|
+| `OPENAI_API_KEY`      | OpenAI API key.                                  | *(required)*                     |
+| `OPENAI_BASE_URL`     | API base URL. Change for compatible proxies.     | `https://api.openai.com/v1`      |
+
+```bash
+AI_PROVIDER=openai
+OPENAI_API_KEY=sk-...
+OPENAI_MODEL=gpt-4o-mini
+```
+
+#### Azure OpenAI
+
+| **Variable**                  | **Description**                              | **Default**    |
+|-------------------------------|----------------------------------------------|----------------|
+| `OPENAI_API_KEY`              | Azure OpenAI API key.                        | *(required)*   |
+| `OPENAI_BASE_URL`             | Azure resource endpoint URL.                 | *(required)*   |
+| `AZURE_OPENAI_API_VERSION`    | Azure OpenAI API version string.             | `2024-02-01`   |
+
+```bash
+AI_PROVIDER=azure
+OPENAI_API_KEY=<azure-key>
+OPENAI_BASE_URL=https://my-resource.openai.azure.com
+AI_MODEL=gpt-4o   # deployment name in Azure
+```
+
+#### Anthropic Claude
+
+| **Variable**        | **Description**          |
+|---------------------|--------------------------|
+| `ANTHROPIC_API_KEY` | Anthropic API key.       |
+
+```bash
+AI_PROVIDER=anthropic
+ANTHROPIC_API_KEY=sk-ant-...
+AI_MODEL=claude-3-5-sonnet-20241022
+```
+
+#### Google Gemini
+
+| **Variable**      | **Description**            |
+|-------------------|----------------------------|
+| `GEMINI_API_KEY`  | Google AI Studio API key.  |
+
+```bash
+AI_PROVIDER=gemini
+GEMINI_API_KEY=AIza...
+AI_MODEL=gemini-1.5-pro
+```
+
+#### Ollama (local LLMs – CPU-friendly)
+
+Run models locally using [Ollama](https://ollama.com). Recommended for CPU-only deployments:
+
+| **Variable**       | **Description**                         | **Default**               |
+|--------------------|-----------------------------------------|---------------------------|
+| `OLLAMA_BASE_URL`  | Ollama server URL.                      | `http://localhost:11434`  |
+
+```bash
+AI_PROVIDER=ollama
+OLLAMA_BASE_URL=http://ollama:11434   # Docker service name
+AI_MODEL=llama3.2                     # or qwen2.5, phi3, etc.
+```
+
+Recommended models for document processing on CPU:
+
+- **`llama3.2`** (3B) – good balance of speed and JSON output quality
+- **`qwen2.5`** (3B/7B) – excellent at structured extraction
+- **`phi3`** (3.8B) – strong reasoning, very fast on CPU
+
+#### OpenRouter
+
+[OpenRouter](https://openrouter.ai) provides access to 100+ models from a single endpoint using the `provider/model` name format.
+
+| **Variable**            | **Description**                     | **Default**                       |
+|-------------------------|-------------------------------------|-----------------------------------|
+| `OPENROUTER_API_KEY`    | OpenRouter API key.                 | *(required)*                      |
+| `OPENROUTER_BASE_URL`   | Override the gateway URL.           | `https://openrouter.ai/api/v1`    |
+
+```bash
+AI_PROVIDER=openrouter
+OPENROUTER_API_KEY=sk-or-...
+AI_MODEL=anthropic/claude-3.5-sonnet
+```
+
+#### Portkey AI Gateway
+
+[Portkey](https://portkey.ai) is an AI gateway that adds observability, caching, fallbacks, and load balancing across 200+ models behind a single OpenAI-compatible endpoint.
+
+| **Variable**          | **Description**                                                                                          | **Default**                      |
+|-----------------------|----------------------------------------------------------------------------------------------------------|----------------------------------|
+| `PORTKEY_API_KEY`     | Portkey account API key.                                                                                 | *(required)*                     |
+| `PORTKEY_VIRTUAL_KEY` | Optional Virtual Key (stores provider credentials in Portkey vault, keeping them out of your env file). | *(unset)*                        |
+| `PORTKEY_CONFIG`      | Optional saved Config ID (e.g. `pc-fallback-abc123`) for routing rules, fallbacks, and load balancing. | *(unset)*                        |
+| `PORTKEY_BASE_URL`    | Override the Portkey gateway URL (for self-hosted deployments).                                         | `https://api.portkey.ai/v1`      |
+
+```bash
+AI_PROVIDER=portkey
+PORTKEY_API_KEY=pk-...
+PORTKEY_VIRTUAL_KEY=vk-openai-abc123   # optional – routes to your OpenAI key stored in Portkey
+AI_MODEL=gpt-4o
+```
+
+Using a Config for fallback routing:
+```bash
+AI_PROVIDER=portkey
+PORTKEY_API_KEY=pk-...
+PORTKEY_CONFIG=pc-fallback-config-xyz  # applies your saved routing rules
+AI_MODEL=gpt-4o
+```
+
+#### LiteLLM (aggregator proxy)
+
+[LiteLLM](https://litellm.ai) provides a unified `provider/model` interface for 100+ LLMs including OpenAI, Anthropic, Gemini, Cohere, Ollama, and many more.
+
+| **Variable**       | **Description**                                 | **Default**                   |
+|--------------------|-------------------------------------------------|-------------------------------|
+| `OPENAI_API_KEY`   | API key forwarded to LiteLLM (provider-specific). | *(depends on model)*        |
+| `OPENAI_BASE_URL`  | Optional proxy/gateway URL.                     | `https://api.openai.com/v1`   |
+
+```bash
+AI_PROVIDER=litellm
+AI_MODEL=anthropic/claude-3-5-sonnet-20241022
+OPENAI_API_KEY=sk-ant-...   # passed as the api_key to LiteLLM
+```
+
+---
+
+### Azure Document Intelligence
 
 | **Variable**                     | **Description**                          | **How to Obtain**                                                        |
 |---------------------------------|------------------------------------------|--------------------------------------------------------------------------|
-| `OPENAI_API_KEY`                | OpenAI API key for GPT metadata extraction. | [OpenAI API keys](https://platform.openai.com/account/api-keys)             |
 | `AZURE_DOCUMENT_INTELLIGENCE_KEY` | Azure Document Intelligence API key for OCR. | [Azure Portal](https://portal.azure.com/) |
 | `AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT` | Endpoint URL for Azure Doc Intelligence API. | [Azure Portal](https://portal.azure.com/) |
 

tests/test_ai_provider.py

@@ -14,6 +14,8 @@ from app.utils.ai_provider import (
     OllamaProvider,
     OpenAIProvider,
     OpenRouterProvider,
+    PortkeyProvider,
+    _require_text_content,
     get_ai_provider,
 )
 
@@ -40,6 +42,37 @@ def _make_litellm_response(content: str) -> MagicMock:
     return resp
 
 
+def _make_none_content_response() -> MagicMock:
+    """Build a mock response where message.content is None (e.g. tool call)."""
+    msg = SimpleNamespace(content=None)
+    choice = SimpleNamespace(message=msg)
+    resp = MagicMock()
+    resp.choices = [choice]
+    return resp
+
+
+# ---------------------------------------------------------------------------
+# _require_text_content helper
+# ---------------------------------------------------------------------------
+
+@pytest.mark.unit
+class TestRequireTextContent:
+    """Tests for the _require_text_content guard helper."""
+
+    def test_returns_non_none_string_unchanged(self):
+        """Returns the string as-is when content is not None."""
+        assert _require_text_content("hello") == "hello"
+
+    def test_returns_empty_string_unchanged(self):
+        """Returns an empty string as-is (empty ≠ None)."""
+        assert _require_text_content("") == ""
+
+    def test_raises_value_error_when_none(self):
+        """Raises ValueError with descriptive message when content is None."""
+        with pytest.raises(ValueError, match="content=None"):
+            _require_text_content(None)
+
+
 # ---------------------------------------------------------------------------
 # Abstract base class
 # ---------------------------------------------------------------------------
@@ -129,6 +162,20 @@ class TestOpenAIProvider:
         assert call_kwargs["max_tokens"] == 100
         assert call_kwargs["temperature"] == 0.7
 
+    @patch("openai.OpenAI")
+    def test_chat_completion_raises_on_none_content(self, mock_openai_cls):
+        """chat_completion raises ValueError when the response content is None."""
+        mock_client = MagicMock()
+        mock_client.chat.completions.create.return_value = _make_none_content_response()
+        mock_openai_cls.return_value = mock_client
+
+        provider = OpenAIProvider(api_key="sk-test")
+        with pytest.raises(ValueError, match="content=None"):
+            provider.chat_completion(
+                messages=[{"role": "user", "content": "test"}],
+                model="gpt-4o-mini",
+            )
+
 
 # ---------------------------------------------------------------------------
 # AzureOpenAIProvider
@@ -343,6 +390,97 @@ class TestOpenRouterProvider:
         assert result == "Router response"
 
 
+# ---------------------------------------------------------------------------
+# PortkeyProvider
+# ---------------------------------------------------------------------------
+
+@pytest.mark.unit
+class TestPortkeyProvider:
+    """Tests for PortkeyProvider."""
+
+    @patch("openai.OpenAI")
+    def test_initialises_with_required_api_key(self, mock_openai_cls):
+        """Provider passes x-portkey-api-key header and uses default gateway URL."""
+        PortkeyProvider(api_key="pk-key")
+        call_kwargs = mock_openai_cls.call_args[1]
+        assert call_kwargs["base_url"] == "https://api.portkey.ai/v1"
+        assert call_kwargs["api_key"] == "pk-key"
+        assert call_kwargs["default_headers"]["x-portkey-api-key"] == "pk-key"
+
+    @patch("openai.OpenAI")
+    def test_sets_virtual_key_header_when_provided(self, mock_openai_cls):
+        """Provider includes x-portkey-virtual-key header when virtual_key is set."""
+        PortkeyProvider(api_key="pk-key", virtual_key="vk-abc123")
+        call_kwargs = mock_openai_cls.call_args[1]
+        assert call_kwargs["default_headers"]["x-portkey-virtual-key"] == "vk-abc123"
+
+    @patch("openai.OpenAI")
+    def test_omits_virtual_key_header_when_not_provided(self, mock_openai_cls):
+        """Provider does not include x-portkey-virtual-key header when virtual_key is None."""
+        PortkeyProvider(api_key="pk-key")
+        call_kwargs = mock_openai_cls.call_args[1]
+        assert "x-portkey-virtual-key" not in call_kwargs["default_headers"]
+
+    @patch("openai.OpenAI")
+    def test_sets_config_header_when_provided(self, mock_openai_cls):
+        """Provider includes x-portkey-config header when config is set."""
+        PortkeyProvider(api_key="pk-key", config="pc-my-config-xyz")
+        call_kwargs = mock_openai_cls.call_args[1]
+        assert call_kwargs["default_headers"]["x-portkey-config"] == "pc-my-config-xyz"
+
+    @patch("openai.OpenAI")
+    def test_omits_config_header_when_not_provided(self, mock_openai_cls):
+        """Provider does not include x-portkey-config header when config is None."""
+        PortkeyProvider(api_key="pk-key")
+        call_kwargs = mock_openai_cls.call_args[1]
+        assert "x-portkey-config" not in call_kwargs["default_headers"]
+
+    @patch("openai.OpenAI")
+    def test_uses_custom_base_url(self, mock_openai_cls):
+        """Provider forwards a custom gateway base URL."""
+        PortkeyProvider(api_key="pk-key", base_url="https://my-portkey-instance.example.com/v1")
+        call_kwargs = mock_openai_cls.call_args[1]
+        assert call_kwargs["base_url"] == "https://my-portkey-instance.example.com/v1"
+
+    @patch("openai.OpenAI")
+    def test_chat_completion_returns_content(self, mock_openai_cls):
+        """chat_completion returns the message content string."""
+        mock_client = MagicMock()
+        mock_client.chat.completions.create.return_value = _make_openai_response("Portkey response")
+        mock_openai_cls.return_value = mock_client
+
+        provider = PortkeyProvider(api_key="pk-key")
+        result = provider.chat_completion(
+            messages=[{"role": "user", "content": "hello"}],
+            model="gpt-4o",
+        )
+
+        assert result == "Portkey response"
+
+    @patch("openai.OpenAI")
+    def test_chat_completion_with_all_options(self, mock_openai_cls):
+        """Provider works correctly with virtual_key, config, and custom model."""
+        mock_client = MagicMock()
+        mock_client.chat.completions.create.return_value = _make_openai_response("ok")
+        mock_openai_cls.return_value = mock_client
+
+        provider = PortkeyProvider(
+            api_key="pk-key",
+            virtual_key="vk-anthropic",
+            config="pc-fallback-config",
+        )
+        result = provider.chat_completion(
+            messages=[{"role": "user", "content": "test"}],
+            model="claude-3-5-sonnet-20241022",
+            temperature=0.5,
+        )
+
+        assert result == "ok"
+        call_kwargs = mock_client.chat.completions.create.call_args[1]
+        assert call_kwargs["model"] == "claude-3-5-sonnet-20241022"
+        assert call_kwargs["temperature"] == 0.5
+
+
 # ---------------------------------------------------------------------------
 # LiteLLMProvider
 # ---------------------------------------------------------------------------
@@ -444,6 +582,10 @@ class TestGetAIProvider:
             "ollama_base_url": "http://localhost:11434",
             "openrouter_api_key": None,
             "openrouter_base_url": "https://openrouter.ai/api/v1",
+            "portkey_api_key": None,
+            "portkey_virtual_key": None,
+            "portkey_config": None,
+            "portkey_base_url": "https://api.portkey.ai/v1",
         }
         defaults.update(kwargs)
         mock_settings = MagicMock()
@@ -536,6 +678,37 @@ class TestGetAIProvider:
             with pytest.raises(ValueError, match="OPENROUTER_API_KEY"):
                 get_ai_provider()
 
+    @patch("openai.OpenAI")
+    def test_returns_portkey_provider(self, mock_openai_cls):
+        """get_ai_provider returns PortkeyProvider for ai_provider='portkey'."""
+        with patch(
+            "app.utils.ai_provider.settings",
+            self._mock_settings(
+                ai_provider="portkey",
+                portkey_api_key="pk-test",
+                portkey_virtual_key=None,
+                portkey_config=None,
+                portkey_base_url="https://api.portkey.ai/v1",
+            ),
+        ):
+            provider = get_ai_provider()
+        assert isinstance(provider, PortkeyProvider)
+
+    def test_portkey_raises_without_api_key(self):
+        """get_ai_provider raises ValueError when portkey_api_key is missing."""
+        with patch(
+            "app.utils.ai_provider.settings",
+            self._mock_settings(
+                ai_provider="portkey",
+                portkey_api_key=None,
+                portkey_virtual_key=None,
+                portkey_config=None,
+                portkey_base_url="https://api.portkey.ai/v1",
+            ),
+        ):
+            with pytest.raises(ValueError, match="PORTKEY_API_KEY"):
+                get_ai_provider()
+
     def test_returns_litellm_provider(self):
         """get_ai_provider returns LiteLLMProvider for ai_provider='litellm'."""
         with patch(

tests/test_extract_metadata_gpt.py

@@ -67,7 +67,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_successful_metadata_extraction(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test successful metadata extraction with valid AI provider response."""
         mock_provider = MagicMock()
@@ -116,7 +116,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_handles_json_in_backticks(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test extraction handles JSON wrapped in markdown code blocks."""
         mock_provider = MagicMock()
@@ -135,7 +135,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_handles_invalid_json_response(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test handling of invalid JSON in AI provider response."""
         mock_provider = MagicMock()
@@ -154,7 +154,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_handles_api_exception(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test handling of AI provider API exceptions."""
         mock_provider = MagicMock()
@@ -173,7 +173,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     @patch("app.tasks.extract_metadata_with_gpt.SessionLocal")
     def test_retrieves_file_id_from_database_when_not_provided(
         self, mock_session_local, mock_get_provider, mock_log_progress, mock_embed_task
@@ -207,7 +207,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_validates_filename_security(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test filename validation to prevent path traversal."""
         mock_provider = MagicMock()
@@ -227,7 +227,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_validates_filename_with_dots(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test filename validation rejects '..' in filenames."""
         mock_provider = MagicMock()
@@ -245,7 +245,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_accepts_valid_filename(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test that valid filenames are accepted."""
         mock_provider = MagicMock()
@@ -263,7 +263,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_handles_malformed_json_with_valid_structure(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test handling of JSON that's parseable but missing expected fields."""
         mock_provider = MagicMock()
@@ -280,7 +280,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     def test_handles_absolute_path_filename(self, mock_get_provider, mock_log_progress, mock_embed_task):
         """Test handling when filename is provided as an absolute path."""
         mock_provider = MagicMock()
@@ -299,7 +299,7 @@ class TestExtractMetadataWithGpt:
 
     @patch("app.tasks.extract_metadata_with_gpt.embed_metadata_into_pdf")
     @patch("app.tasks.extract_metadata_with_gpt.log_task_progress")
-    @patch("app.utils.ai_provider.get_ai_provider")
+    @patch("app.tasks.extract_metadata_with_gpt.get_ai_provider")
     @patch("app.tasks.extract_metadata_with_gpt.SessionLocal")
     def test_database_lookup_with_existing_file(
         self, mock_session_local, mock_get_provider, mock_log_progress, mock_embed_task

tests/test_ocr_processing.py

@@ -423,7 +423,7 @@ class TestRefineTextWithGPT:
         mock_provider.chat_completion.return_value = cleaned
 
         with (
-            patch("app.utils.ai_provider.get_ai_provider", return_value=mock_provider),
+            patch("app.tasks.refine_text_with_gpt.get_ai_provider", return_value=mock_provider),
             patch.object(metadata_module, "extract_metadata_with_gpt") as mock_extract,
             patch("app.tasks.refine_text_with_gpt.settings") as mock_settings,
         ):
@@ -456,7 +456,7 @@ class TestRefineTextWithGPT:
         mock_provider.chat_completion.side_effect = Exception("OpenAI API error")
 
         with (
-            patch("app.utils.ai_provider.get_ai_provider", return_value=mock_provider),
+            patch("app.tasks.refine_text_with_gpt.get_ai_provider", return_value=mock_provider),
             patch("app.tasks.refine_text_with_gpt.settings") as mock_settings,
         ):
             mock_settings.openai_model = "gpt-4"