fixes setup scripts

fixes to env handling in setup script plus other minor fixes
2026-01-20 05:50:58 +00:00 · 2026-01-12 23:48:52 +03:00
parent f1d714b5c1
commit 974d98b94b
5 changed files with 125 additions and 83 deletions
--- a/application/core/model_settings.py
+++ b/application/core/model_settings.py
@@ -6,6 +6,19 @@ from typing import Dict, List, Optional
 logger = logging.getLogger(__name__)


+def _is_valid_api_key(key: Optional[str]) -> bool:
+    """
+    Check if an API key is valid (not None, not empty, not string 'None').
+    Handles Pydantic loading 'None' from .env as string "None".
+    """
+    if key is None:
+        return False
+    if not isinstance(key, str):
+        return False
+    key_stripped = key.strip().lower()
+    return key_stripped != "" and key_stripped != "none"
+
+
 class ModelProvider(str, Enum):
    OPENAI = "openai"
    AZURE_OPENAI = "azure_openai"
@@ -87,40 +100,53 @@ class ModelRegistry:
        # Skip DocsGPT model if using custom OpenAI-compatible endpoint
        if not settings.OPENAI_BASE_URL:
            self._add_docsgpt_models(settings)
-        if settings.OPENAI_API_KEY or (
-            settings.LLM_PROVIDER == "openai" and settings.API_KEY
+        if (
+            _is_valid_api_key(settings.OPENAI_API_KEY)
+            or (settings.LLM_PROVIDER == "openai" and _is_valid_api_key(settings.API_KEY))
+            or settings.OPENAI_BASE_URL
        ):
            self._add_openai_models(settings)
        if settings.OPENAI_API_BASE or (
-            settings.LLM_PROVIDER == "azure_openai" and settings.API_KEY
+            settings.LLM_PROVIDER == "azure_openai" and _is_valid_api_key(settings.API_KEY)
        ):
            self._add_azure_openai_models(settings)
-        if settings.ANTHROPIC_API_KEY or (
-            settings.LLM_PROVIDER == "anthropic" and settings.API_KEY
+        if _is_valid_api_key(settings.ANTHROPIC_API_KEY) or (
+            settings.LLM_PROVIDER == "anthropic" and _is_valid_api_key(settings.API_KEY)
        ):
            self._add_anthropic_models(settings)
-        if settings.GOOGLE_API_KEY or (
-            settings.LLM_PROVIDER == "google" and settings.API_KEY
+        if _is_valid_api_key(settings.GOOGLE_API_KEY) or (
+            settings.LLM_PROVIDER == "google" and _is_valid_api_key(settings.API_KEY)
        ):
            self._add_google_models(settings)
-        if settings.GROQ_API_KEY or (
-            settings.LLM_PROVIDER == "groq" and settings.API_KEY
+        if _is_valid_api_key(settings.GROQ_API_KEY) or (
+            settings.LLM_PROVIDER == "groq" and _is_valid_api_key(settings.API_KEY)
        ):
            self._add_groq_models(settings)
-        if settings.HUGGINGFACE_API_KEY or (
-            settings.LLM_PROVIDER == "huggingface" and settings.API_KEY
+        if _is_valid_api_key(settings.HUGGINGFACE_API_KEY) or (
+            settings.LLM_PROVIDER == "huggingface" and _is_valid_api_key(settings.API_KEY)
        ):
            self._add_huggingface_models(settings)
        # Default model selection
-
-        if settings.LLM_NAME and settings.LLM_NAME in self.models:
-            self.default_model_id = settings.LLM_NAME
-        elif settings.LLM_PROVIDER and settings.API_KEY:
-            for model_id, model in self.models.items():
-                if model.provider.value == settings.LLM_PROVIDER:
-                    self.default_model_id = model_id
+        if settings.LLM_NAME:
+            # Parse LLM_NAME (may be comma-separated)
+            model_names = self._parse_model_names(settings.LLM_NAME)
+            # First model in the list becomes default
+            for model_name in model_names:
+                if model_name in self.models:
+                    self.default_model_id = model_name
                    break
-        else:
+            # Backward compat: try exact match if no parsed model found
+            if not self.default_model_id and settings.LLM_NAME in self.models:
+                self.default_model_id = settings.LLM_NAME
+
+        if not self.default_model_id:
+            if settings.LLM_PROVIDER and _is_valid_api_key(settings.API_KEY):
+                for model_id, model in self.models.items():
+                    if model.provider.value == settings.LLM_PROVIDER:
+                        self.default_model_id = model_id
+                        break
+
+        if not self.default_model_id and self.models:
            self.default_model_id = next(iter(self.models.keys()))
        logger.info(
            f"ModelRegistry loaded {len(self.models)} models, default: {self.default_model_id}"
@@ -132,29 +158,29 @@ class ModelRegistry:
            create_custom_openai_model,
        )

-        # Add standard OpenAI models if API key is present
-        if settings.OPENAI_API_KEY:
-            for model in OPENAI_MODELS:
-                self.models[model.id] = model
+        # Check if using local OpenAI-compatible endpoint (Ollama, LM Studio, etc.)
+        using_local_endpoint = bool(
+            settings.OPENAI_BASE_URL and settings.OPENAI_BASE_URL.strip()
+        )

-        # Add custom model if OPENAI_BASE_URL is configured with a custom LLM_NAME
-        if (
-            settings.LLM_PROVIDER == "openai"
-            and settings.OPENAI_BASE_URL
-            and settings.LLM_NAME
-        ):
-            custom_model = create_custom_openai_model(
-                settings.LLM_NAME, settings.OPENAI_BASE_URL
-            )
-            self.models[settings.LLM_NAME] = custom_model
-            logger.info(
-                f"Registered custom OpenAI model: {settings.LLM_NAME} at {settings.OPENAI_BASE_URL}"
-            )
-
-        # Fallback: add all OpenAI models if none were added
-        if not any(m.provider.value == "openai" for m in self.models.values()):
-            for model in OPENAI_MODELS:
-                self.models[model.id] = model
+        if using_local_endpoint:
+            # When OPENAI_BASE_URL is set, ONLY register custom models from LLM_NAME
+            # Do NOT add standard OpenAI models (gpt-5.1, etc.)
+            if settings.LLM_NAME:
+                model_names = self._parse_model_names(settings.LLM_NAME)
+                for model_name in model_names:
+                    custom_model = create_custom_openai_model(
+                        model_name, settings.OPENAI_BASE_URL
+                    )
+                    self.models[model_name] = custom_model
+                    logger.info(
+                        f"Registered custom OpenAI model: {model_name} at {settings.OPENAI_BASE_URL}"
+                    )
+        else:
+            # Standard OpenAI API usage - add standard models if API key is valid
+            if _is_valid_api_key(settings.OPENAI_API_KEY):
+                for model in OPENAI_MODELS:
+                    self.models[model.id] = model

    def _add_azure_openai_models(self, settings):
        from application.core.model_configs import AZURE_OPENAI_MODELS
@@ -240,6 +266,15 @@ class ModelRegistry:
        )
        self.models[model_id] = model

+    def _parse_model_names(self, llm_name: str) -> List[str]:
+        """
+        Parse LLM_NAME which may contain comma-separated model names.
+        E.g., 'deepseek-r1:1.5b,gemma:2b' -> ['deepseek-r1:1.5b', 'gemma:2b']
+        """
+        if not llm_name:
+            return []
+        return [name.strip() for name in llm_name.split(",") if name.strip()]
+
    def get_model(self, model_id: str) -> Optional[AvailableModel]:
        return self.models.get(model_id)

--- a/application/core/model_utils.py
+++ b/application/core/model_utils.py
@@ -1,6 +1,6 @@
 from typing import Any, Dict, Optional

-from application.core.model_settings import ModelRegistry
+from application.core.model_settings import ModelRegistry, _is_valid_api_key


 def get_api_key_for_provider(provider: str) -> Optional[str]:
@@ -19,9 +19,11 @@ def get_api_key_for_provider(provider: str) -> Optional[str]:
    }

    provider_key = provider_key_map.get(provider)
-    if provider_key:
+    if provider_key and _is_valid_api_key(provider_key):
        return provider_key
-    return settings.API_KEY
+    if _is_valid_api_key(settings.API_KEY):
+        return settings.API_KEY
+    return None


 def get_all_available_models() -> Dict[str, Dict[str, Any]]:
--- a/deployment/docker-compose-hub.yaml
+++ b/deployment/docker-compose-hub.yaml
@@ -16,6 +16,8 @@ services:
  backend:
    user: root
    image: arc53/docsgpt:develop
+    env_file:
+      - ../.env
    environment:
      - API_KEY=$API_KEY
      - EMBEDDINGS_KEY=$API_KEY
@@ -41,6 +43,8 @@ services:
    user: root
    image: arc53/docsgpt:develop
    command: celery -A application.app.celery worker -l INFO -B
+    env_file:
+      - ../.env
    environment:
      - API_KEY=$API_KEY
      - EMBEDDINGS_KEY=$API_KEY
@@ -51,6 +55,7 @@ services:
      - MONGO_URI=mongodb://mongo:27017/docsgpt
      - API_URL=http://backend:7091
      - CACHE_REDIS_URL=redis://redis:6379/2
+      - OPENAI_BASE_URL=$OPENAI_BASE_URL
    volumes:
      - ../application/indexes:/app/indexes
      - ../application/inputs:/app/inputs
--- a/setup.ps1
+++ b/setup.ps1
@@ -398,9 +398,9 @@ function Serve-LocalOllama {
    # Create .env file
    "API_KEY=xxxx" | Out-File -FilePath $ENV_FILE -Encoding utf8 -Force
    "LLM_PROVIDER=openai" | Add-Content -Path $ENV_FILE -Encoding utf8
-    "MODEL_NAME=$model_name" | Add-Content -Path $ENV_FILE -Encoding utf8
+    "LLM_NAME=$model_name" | Add-Content -Path $ENV_FILE -Encoding utf8
    "VITE_API_STREAMING=true" | Add-Content -Path $ENV_FILE -Encoding utf8
-    "OPENAI_BASE_URL=http://host.docker.internal:11434/v1" | Add-Content -Path $ENV_FILE -Encoding utf8
+    "OPENAI_BASE_URL=http://ollama:11434/v1" | Add-Content -Path $ENV_FILE -Encoding utf8
    "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" | Add-Content -Path $ENV_FILE -Encoding utf8
    
    Write-ColorText ".env file configured for Ollama ($($docker_compose_file_suffix.ToUpper()))." -ForegroundColor "Green"
@@ -495,49 +495,49 @@ function Connect-LocalInferenceEngine {
        switch ($engine_choice) {
            "1" {  # LLaMa.cpp
                $script:engine_name = "LLaMa.cpp"
-                $script:openai_base_url = "http://localhost:8000/v1"
+                $script:openai_base_url = "http://host.docker.internal:8000/v1"
                Get-ModelName
                break
            }
            "2" {  # Ollama
                $script:engine_name = "Ollama"
-                $script:openai_base_url = "http://localhost:11434/v1"
+                $script:openai_base_url = "http://host.docker.internal:11434/v1"
                Get-ModelName
                break
            }
            "3" {  # TGI
                $script:engine_name = "TGI"
-                $script:openai_base_url = "http://localhost:8080/v1"
+                $script:openai_base_url = "http://host.docker.internal:8080/v1"
                Get-ModelName
                break
            }
            "4" {  # SGLang
                $script:engine_name = "SGLang"
-                $script:openai_base_url = "http://localhost:30000/v1"
+                $script:openai_base_url = "http://host.docker.internal:30000/v1"
                Get-ModelName
                break
            }
            "5" {  # vLLM
                $script:engine_name = "vLLM"
-                $script:openai_base_url = "http://localhost:8000/v1"
+                $script:openai_base_url = "http://host.docker.internal:8000/v1"
                Get-ModelName
                break
            }
            "6" {  # Aphrodite
                $script:engine_name = "Aphrodite"
-                $script:openai_base_url = "http://localhost:2242/v1"
+                $script:openai_base_url = "http://host.docker.internal:2242/v1"
                Get-ModelName
                break
            }
            "7" {  # FriendliAI
                $script:engine_name = "FriendliAI"
-                $script:openai_base_url = "http://localhost:8997/v1"
+                $script:openai_base_url = "http://host.docker.internal:8997/v1"
                Get-ModelName
                break
            }
            "8" {  # LMDeploy
                $script:engine_name = "LMDeploy"
-                $script:openai_base_url = "http://localhost:23333/v1"
+                $script:openai_base_url = "http://host.docker.internal:23333/v1"
                Get-ModelName
                break
            }
@@ -561,7 +561,7 @@ function Connect-LocalInferenceEngine {
    # Create .env file
    "API_KEY=None" | Out-File -FilePath $ENV_FILE -Encoding utf8 -Force
    "LLM_PROVIDER=openai" | Add-Content -Path $ENV_FILE -Encoding utf8
-    "MODEL_NAME=$model_name" | Add-Content -Path $ENV_FILE -Encoding utf8
+    "LLM_NAME=$model_name" | Add-Content -Path $ENV_FILE -Encoding utf8
    "VITE_API_STREAMING=true" | Add-Content -Path $ENV_FILE -Encoding utf8
    "OPENAI_BASE_URL=$openai_base_url" | Add-Content -Path $ENV_FILE -Encoding utf8
    "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" | Add-Content -Path $ENV_FILE -Encoding utf8
@@ -694,7 +694,7 @@ function Connect-CloudAPIProvider {
    # Create .env file
    "API_KEY=$api_key" | Out-File -FilePath $ENV_FILE -Encoding utf8 -Force
    "LLM_PROVIDER=$llm_name" | Add-Content -Path $ENV_FILE -Encoding utf8
-    "MODEL_NAME=$model_name" | Add-Content -Path $ENV_FILE -Encoding utf8
+    "LLM_NAME=$model_name" | Add-Content -Path $ENV_FILE -Encoding utf8
    "VITE_API_STREAMING=true" | Add-Content -Path $ENV_FILE -Encoding utf8
    
    Write-ColorText ".env file configured for $provider_name." -ForegroundColor "Green"
--- a/setup.sh
+++ b/setup.sh
@@ -173,8 +173,8 @@ prompt_ollama_options() {
 # 1) Use DocsGPT Public API Endpoint (simple and free)
 use_docs_public_api_endpoint() {
    echo -e "\n${NC}Setting up DocsGPT Public API Endpoint...${NC}"
-    echo "LLM_PROVIDER=docsgpt" > .env
-    echo "VITE_API_STREAMING=true" >> .env
+    echo "LLM_PROVIDER=docsgpt" > "$ENV_FILE"
+    echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
    echo -e "${GREEN}.env file configured for DocsGPT Public API.${NC}"

    check_and_start_docker
@@ -240,12 +240,12 @@ serve_local_ollama() {


    echo -e "\n${NC}Configuring for Ollama ($(echo "$docker_compose_file_suffix" | tr '[:lower:]' '[:upper:]'))...${NC}" # Using tr for uppercase - more compatible
-    echo "API_KEY=xxxx" > .env # Placeholder API Key
-    echo "LLM_PROVIDER=openai" >> .env
-    echo "LLM_NAME=$model_name" >> .env
-    echo "VITE_API_STREAMING=true" >> .env
-    echo "OPENAI_BASE_URL=http://ollama:11434/v1" >> .env
-    echo "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" >> .env
+    echo "API_KEY=xxxx" > "$ENV_FILE" # Placeholder API Key
+    echo "LLM_PROVIDER=openai" >> "$ENV_FILE"
+    echo "LLM_NAME=$model_name" >> "$ENV_FILE"
+    echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
+    echo "OPENAI_BASE_URL=http://ollama:11434/v1" >> "$ENV_FILE"
+    echo "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" >> "$ENV_FILE"
    echo -e "${GREEN}.env file configured for Ollama ($(echo "$docker_compose_file_suffix" | tr '[:lower:]' '[:upper:]')${NC}${GREEN}).${NC}"


@@ -308,42 +308,42 @@ connect_local_inference_engine() {
        case "$engine_choice" in
            1) # LLaMa.cpp
                engine_name="LLaMa.cpp"
-                openai_base_url="http://localhost:8000/v1"
+                openai_base_url="http://host.docker.internal:8000/v1"
                get_model_name
                break ;;
            2) # Ollama
                engine_name="Ollama"
-                openai_base_url="http://localhost:11434/v1"
+                openai_base_url="http://host.docker.internal:11434/v1"
                get_model_name
                break ;;
            3) # TGI
                engine_name="TGI"
-                openai_base_url="http://localhost:8080/v1"
+                openai_base_url="http://host.docker.internal:8080/v1"
                get_model_name
                break ;;
            4) # SGLang
                engine_name="SGLang"
-                openai_base_url="http://localhost:30000/v1"
+                openai_base_url="http://host.docker.internal:30000/v1"
                get_model_name
                break ;;
            5) # vLLM
                engine_name="vLLM"
-                openai_base_url="http://localhost:8000/v1"
+                openai_base_url="http://host.docker.internal:8000/v1"
                get_model_name
                break ;;
            6) # Aphrodite
                engine_name="Aphrodite"
-                openai_base_url="http://localhost:2242/v1"
+                openai_base_url="http://host.docker.internal:2242/v1"
                get_model_name
                break ;;
            7) # FriendliAI
                engine_name="FriendliAI"
-                openai_base_url="http://localhost:8997/v1"
+                openai_base_url="http://host.docker.internal:8997/v1"
                get_model_name
                break ;;
            8) # LMDeploy
                engine_name="LMDeploy"
-                openai_base_url="http://localhost:23333/v1"
+                openai_base_url="http://host.docker.internal:23333/v1"
                get_model_name
                break ;;
            b|B) clear; return ;; # Back to Main Menu
@@ -352,19 +352,19 @@ connect_local_inference_engine() {
    done

    echo -e "\n${NC}Configuring for Local Inference Engine: ${BOLD}${engine_name}...${NC}"
-    echo "API_KEY=None" > .env
-    echo "LLM_PROVIDER=openai" >> .env
-    echo "LLM_NAME=$model_name" >> .env
-    echo "VITE_API_STREAMING=true" >> .env
-    echo "OPENAI_BASE_URL=$openai_base_url" >> .env
-    echo "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" >> .env
+    echo "API_KEY=None" > "$ENV_FILE"
+    echo "LLM_PROVIDER=openai" >> "$ENV_FILE"
+    echo "LLM_NAME=$model_name" >> "$ENV_FILE"
+    echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
+    echo "OPENAI_BASE_URL=$openai_base_url" >> "$ENV_FILE"
+    echo "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" >> "$ENV_FILE"
    echo -e "${GREEN}.env file configured for ${BOLD}${engine_name}${NC}${GREEN} with OpenAI API format.${NC}"
    echo -e "${YELLOW}Note: MODEL_NAME is set to '${BOLD}$model_name${NC}${YELLOW}'. You can change it later in the .env file.${NC}"

    check_and_start_docker

    echo -e "\n${NC}Starting Docker Compose...${NC}"
-    docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" pull && docker compose -f "${COMPOSE_FILE}" up -d
+    docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" pull && docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" up -d
    docker_compose_status=$?

    echo "Docker Compose Exit Status: $docker_compose_status" # Debug output
@@ -444,10 +444,10 @@ connect_cloud_api_provider() {
    done

    echo -e "\n${NC}Configuring for Cloud API Provider: ${BOLD}${provider_name}...${NC}"
-    echo "API_KEY=$api_key" > .env
-    echo "LLM_PROVIDER=$llm_provider" >> .env
-    echo "LLM_NAME=$model_name" >> .env
-    echo "VITE_API_STREAMING=true" >> .env
+    echo "API_KEY=$api_key" > "$ENV_FILE"
+    echo "LLM_PROVIDER=$llm_provider" >> "$ENV_FILE"
+    echo "LLM_NAME=$model_name" >> "$ENV_FILE"
+    echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
    echo -e "${GREEN}.env file configured for ${BOLD}${provider_name}${NC}${GREEN}.${NC}"

    check_and_start_docker