open-webui

Complete Open WebUI API integration for managing LLM models, chat completions, Ollama proxy operations, file uploads, knowledge bases (RAG), image generation, audio processing, and pipelines. Use this skill when interacting with Open WebUI instances via REST API - listing models, chatting with LLMs, uploading files for RAG, managing knowledge collections, or executing Ollama commands through the Open WebUI proxy. Requires OPENWEBUI_URL and OPENWEBUI_TOKEN environment variables or explicit parameters.

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Feb 12, 2026

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Open WebUI API Skill

Complete API integration for Open WebUI - a unified interface for LLMs including Ollama, OpenAI, and other providers.

When to Use

Activate this skill when the user wants to:

List available models from their Open WebUI instance
Send chat completions to models through Open WebUI
Upload files for RAG (Retrieval Augmented Generation)
Manage knowledge collections and add files to them
Use Ollama proxy endpoints (generate, embed, pull models)
Generate images or process audio through Open WebUI
Check Ollama status or manage models (load, unload, delete)
Create or manage pipelines

Do NOT activate for:

Installing or configuring Open WebUI server itself (use system admin skills)
General questions about what Open WebUI is (use general knowledge)
Troubleshooting Open WebUI server issues (use troubleshooting guides)
Local file operations unrelated to Open WebUI API

Prerequisites

Environment Variables (Recommended)

export OPENWEBUI_URL="http://localhost:3000"  # Your Open WebUI instance URL
export OPENWEBUI_TOKEN="your-api-key-here"    # From Settings > Account in Open WebUI

Authentication

Bearer Token authentication required
Token obtained from Open WebUI: Settings > Account
Alternative: JWT token for advanced use cases

Activation Triggers

Example requests that SHOULD activate this skill:

"List all models available in my Open WebUI"
"Send a chat completion to llama3.2 via Open WebUI with prompt 'Explain quantum computing'"
"Upload /path/to/document.pdf to Open WebUI knowledge base"
"Create a new knowledge collection called 'Research Papers' in Open WebUI"
"Generate an embedding for 'Open WebUI is great' using the nomic-embed-text model"
"Pull the llama3.2 model through Open WebUI Ollama proxy"
"Get Ollama status from my Open WebUI instance"
"Chat with gpt-4 using my Open WebUI with RAG enabled on collection 'docs'"
"Generate an image using Open WebUI with prompt 'A futuristic city'"
"Delete the old-model from Open WebUI Ollama"

Example requests that should NOT activate this skill:

"How do I install Open WebUI?" (Installation/Admin)
"What is Open WebUI?" (General knowledge)
"Configure the Open WebUI environment variables" (Server config)
"Troubleshoot why Open WebUI won't start" (Server troubleshooting)
"Compare Open WebUI to other UIs" (General comparison)

Workflow

1. Configuration Check

Verify OPENWEBUI_URL and OPENWEBUI_TOKEN are set
Validate URL format (http/https)
Test connection with GET /api/models or /ollama/api/tags

2. Operation Execution

Use the CLI tool or direct API calls:

# Using the CLI tool (recommended)
python3 scripts/openwebui-cli.py --help
python3 scripts/openwebui-cli.py models list
python3 scripts/openwebui-cli.py chat --model llama3.2 --message "Hello"

# Using curl (alternative)
curl -H "Authorization: Bearer $OPENWEBUI_TOKEN" \
  "$OPENWEBUI_URL/api/models"

3. Response Handling

HTTP 200: Success - parse and present JSON
HTTP 401: Authentication failed - check token
HTTP 404: Endpoint/model not found
HTTP 422: Validation error - check request parameters

Core API Endpoints

Chat & Completions

Endpoint	Method	Description
`/api/chat/completions`	POST	OpenAI-compatible chat completions
`/api/models`	GET	List all available models
`/ollama/api/chat`	POST	Native Ollama chat completion
`/ollama/api/generate`	POST	Ollama text generation

Ollama Proxy

Endpoint	Method	Description
`/ollama/api/tags`	GET	List Ollama models
`/ollama/api/pull`	POST	Pull/download a model
`/ollama/api/delete`	DELETE	Delete a model
`/ollama/api/embed`	POST	Generate embeddings
`/ollama/api/ps`	GET	List loaded models

RAG & Knowledge

Endpoint	Method	Description
`/api/v1/files/`	POST	Upload file for RAG
`/api/v1/files/{id}/process/status`	GET	Check file processing status
`/api/v1/knowledge/`	GET/POST	List/create knowledge collections
`/api/v1/knowledge/{id}/file/add`	POST	Add file to knowledge base

Images & Audio

Endpoint	Method	Description
`/api/v1/images/generations`	POST	Generate images
`/api/v1/audio/speech`	POST	Text-to-speech
`/api/v1/audio/transcriptions`	POST	Speech-to-text

Safety & Boundaries

Confirmation Required

Always confirm before:

Deleting models (DELETE /ollama/api/delete) - Irreversible
Pulling large models - May take significant time/bandwidth
Deleting knowledge collections - Data loss risk
Uploading sensitive files - Privacy consideration

Redaction & Security

Never log the full API token - Redact to sk-...XXXX format
Sanitize file paths - Verify files exist before upload
Validate URLs - Ensure HTTPS for external instances
Handle errors gracefully - Don't expose stack traces with tokens

Workspace Safety

File uploads default to workspace directory
Confirm before accessing files outside workspace
No sudo/root operations required (pure API client)

Examples

List Models

python3 scripts/openwebui-cli.py models list

Chat Completion

python3 scripts/openwebui-cli.py chat \
  --model llama3.2 \
  --message "Explain the benefits of RAG" \
  --stream

Upload File for RAG

python3 scripts/openwebui-cli.py files upload \
  --file /path/to/document.pdf \
  --process

Add File to Knowledge Base

python3 scripts/openwebui-cli.py knowledge add-file \
  --collection-id "research-papers" \
  --file-id "doc-123-uuid"

Generate Embeddings (Ollama)

python3 scripts/openwebui-cli.py ollama embed \
  --model nomic-embed-text \
  --input "Open WebUI is great for LLM management"

Pull Model (Confirmation Required)

python3 scripts/openwebui-cli.py ollama pull \
  --model llama3.2:70b
# Agent must confirm: "This will download ~40GB. Proceed? [y/N]"

Check Ollama Status

python3 scripts/openwebui-cli.py ollama status

Error Handling

Error	Cause	Solution
401 Unauthorized	Invalid or missing token	Verify OPENWEBUI_TOKEN
404 Not Found	Model/endpoint doesn't exist	Check model name spelling
422 Validation Error	Invalid parameters	Check request body format
400 Bad Request	File still processing	Wait for processing completion
Connection refused	Wrong URL	Verify OPENWEBUI_URL

Edge Cases

File Processing Race Condition

Files uploaded for RAG are processed asynchronously. Before adding to knowledge:

Upload file → get file_id
Poll /api/v1/files/{id}/process/status until status: "completed"
Then add to knowledge collection

Large Model Downloads

Pulling models (e.g., 70B parameters) can take hours. Always:

Confirm with user before starting
Show progress if possible
Allow cancellation

Streaming Responses

Chat completions support streaming. Use --stream flag for real-time output or collect full response for non-streaming.

CLI Tool Reference

The included CLI tool (scripts/openwebui-cli.py) provides:

Automatic authentication from environment variables
Structured JSON output with optional formatting
Built-in help for all commands
Error handling with user-friendly messages
Progress indicators for long operations

Run python3 scripts/openwebui-cli.py --help for full usage.

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Open WebUI API Skill

Complete API integration for Open WebUI - a unified interface for LLMs including Ollama, OpenAI, and other providers.

When to Use

Activate this skill when the user wants to:

List available models from their Open WebUI instance
Send chat completions to models through Open WebUI
Upload files for RAG (Retrieval Augmented Generation)
Manage knowledge collections and add files to them
Use Ollama proxy endpoints (generate, embed, pull models)
Generate images or process audio through Open WebUI
Check Ollama status or manage models (load, unload, delete)
Create or manage pipelines

Do NOT activate for:

Installing or configuring Open WebUI server itself (use system admin skills)
General questions about what Open WebUI is (use general knowledge)
Troubleshooting Open WebUI server issues (use troubleshooting guides)
Local file operations unrelated to Open WebUI API

Prerequisites

Environment Variables (Recommended)

export OPENWEBUI_URL="http://localhost:3000"  # Your Open WebUI instance URL
export OPENWEBUI_TOKEN="your-api-key-here"    # From Settings > Account in Open WebUI

Authentication

Bearer Token authentication required
Token obtained from Open WebUI: Settings > Account
Alternative: JWT token for advanced use cases

Activation Triggers

Example requests that SHOULD activate this skill:

"List all models available in my Open WebUI"
"Send a chat completion to llama3.2 via Open WebUI with prompt 'Explain quantum computing'"
"Upload /path/to/document.pdf to Open WebUI knowledge base"
"Create a new knowledge collection called 'Research Papers' in Open WebUI"
"Generate an embedding for 'Open WebUI is great' using the nomic-embed-text model"
"Pull the llama3.2 model through Open WebUI Ollama proxy"
"Get Ollama status from my Open WebUI instance"
"Chat with gpt-4 using my Open WebUI with RAG enabled on collection 'docs'"
"Generate an image using Open WebUI with prompt 'A futuristic city'"
"Delete the old-model from Open WebUI Ollama"

Example requests that should NOT activate this skill:

"How do I install Open WebUI?" (Installation/Admin)
"What is Open WebUI?" (General knowledge)
"Configure the Open WebUI environment variables" (Server config)
"Troubleshoot why Open WebUI won't start" (Server troubleshooting)
"Compare Open WebUI to other UIs" (General comparison)

Workflow

1. Configuration Check

Verify OPENWEBUI_URL and OPENWEBUI_TOKEN are set
Validate URL format (http/https)
Test connection with GET /api/models or /ollama/api/tags

2. Operation Execution

Use the CLI tool or direct API calls:

# Using the CLI tool (recommended)
python3 scripts/openwebui-cli.py --help
python3 scripts/openwebui-cli.py models list
python3 scripts/openwebui-cli.py chat --model llama3.2 --message "Hello"

# Using curl (alternative)
curl -H "Authorization: Bearer $OPENWEBUI_TOKEN" \
  "$OPENWEBUI_URL/api/models"

3. Response Handling

HTTP 200: Success - parse and present JSON
HTTP 401: Authentication failed - check token
HTTP 404: Endpoint/model not found
HTTP 422: Validation error - check request parameters

Core API Endpoints

Chat & Completions

Endpoint	Method	Description
`/api/chat/completions`	POST	OpenAI-compatible chat completions
`/api/models`	GET	List all available models
`/ollama/api/chat`	POST	Native Ollama chat completion
`/ollama/api/generate`	POST	Ollama text generation

Ollama Proxy

Endpoint	Method	Description
`/ollama/api/tags`	GET	List Ollama models
`/ollama/api/pull`	POST	Pull/download a model
`/ollama/api/delete`	DELETE	Delete a model
`/ollama/api/embed`	POST	Generate embeddings
`/ollama/api/ps`	GET	List loaded models

RAG & Knowledge

Endpoint	Method	Description
`/api/v1/files/`	POST	Upload file for RAG
`/api/v1/files/{id}/process/status`	GET	Check file processing status
`/api/v1/knowledge/`	GET/POST	List/create knowledge collections
`/api/v1/knowledge/{id}/file/add`	POST	Add file to knowledge base

Images & Audio

Endpoint	Method	Description
`/api/v1/images/generations`	POST	Generate images
`/api/v1/audio/speech`	POST	Text-to-speech
`/api/v1/audio/transcriptions`	POST	Speech-to-text

Safety & Boundaries

Confirmation Required

Always confirm before:

Deleting models (DELETE /ollama/api/delete) - Irreversible
Pulling large models - May take significant time/bandwidth
Deleting knowledge collections - Data loss risk
Uploading sensitive files - Privacy consideration

Redaction & Security

Never log the full API token - Redact to sk-...XXXX format
Sanitize file paths - Verify files exist before upload
Validate URLs - Ensure HTTPS for external instances
Handle errors gracefully - Don't expose stack traces with tokens

Workspace Safety

File uploads default to workspace directory
Confirm before accessing files outside workspace
No sudo/root operations required (pure API client)

Examples

List Models

python3 scripts/openwebui-cli.py models list

Chat Completion

python3 scripts/openwebui-cli.py chat \
  --model llama3.2 \
  --message "Explain the benefits of RAG" \
  --stream

Upload File for RAG

python3 scripts/openwebui-cli.py files upload \
  --file /path/to/document.pdf \
  --process

Add File to Knowledge Base

python3 scripts/openwebui-cli.py knowledge add-file \
  --collection-id "research-papers" \
  --file-id "doc-123-uuid"

Generate Embeddings (Ollama)

python3 scripts/openwebui-cli.py ollama embed \
  --model nomic-embed-text \
  --input "Open WebUI is great for LLM management"

Pull Model (Confirmation Required)

python3 scripts/openwebui-cli.py ollama pull \
  --model llama3.2:70b
# Agent must confirm: "This will download ~40GB. Proceed? [y/N]"

Check Ollama Status

python3 scripts/openwebui-cli.py ollama status

Error Handling

Error	Cause	Solution
401 Unauthorized	Invalid or missing token	Verify OPENWEBUI_TOKEN
404 Not Found	Model/endpoint doesn't exist	Check model name spelling
422 Validation Error	Invalid parameters	Check request body format
400 Bad Request	File still processing	Wait for processing completion
Connection refused	Wrong URL	Verify OPENWEBUI_URL

Edge Cases

File Processing Race Condition

Files uploaded for RAG are processed asynchronously. Before adding to knowledge:

Upload file → get file_id
Poll /api/v1/files/{id}/process/status until status: "completed"
Then add to knowledge collection

Large Model Downloads

Pulling models (e.g., 70B parameters) can take hours. Always:

Confirm with user before starting
Show progress if possible
Allow cancellation

Streaming Responses

Chat completions support streaming. Use --stream flag for real-time output or collect full response for non-streaming.

CLI Tool Reference

The included CLI tool (scripts/openwebui-cli.py) provides:

Automatic authentication from environment variables
Structured JSON output with optional formatting
Built-in help for all commands
Error handling with user-friendly messages
Progress indicators for long operations

Run python3 scripts/openwebui-cli.py --help for full usage.