# Hermes Ollama Models

Native-like Hermes dashboard plugin for local Ollama model management and chat.

## Chat capabilities

- Select an installed Ollama model and load it into memory
- Chat through Ollama's native `/api/chat` endpoint
- Attach screenshots and JPEG/PNG/WebP images for vision-capable models
- Attach text PDFs; PDF text is extracted with `pypdf`
- Add public HTTP/HTTPS URLs for HTML/text, images, or PDFs
- View live host RAM and swap statistics
- View Ollama's loaded-model memory split: total, GPU VRAM, and normal RAM/offload
- View NVIDIA GPU telemetry when `nvidia-smi` is available
- Chat is the default view when the Ollama Models plugin opens
- Natural composer behavior: Enter sends; Shift+Enter creates a new line
- Paste images directly into the composer and drag/drop images, PDFs, and text files
- Streamed Ollama responses with a real Stop action that cancels the active request
- Minimized-by-default expandable thinking/progress details with live stage, elapsed time, event, and character counters

The chat transcript and selected model are persisted in the Hermes server's SQLite database at `~/.hermes/ollama-manager/chat.sqlite3`, so conversations can be listed and resumed from another browser or after a dashboard restart. Use **New conversation** to start a separate thread and **Clear chat** to delete the selected shared conversation. Uploaded files remain temporary; attachment names/types/URLs are retained as metadata, not raw file contents.

## Performance metrics

Each completed request records Ollama-provided counters and timing when available:

- Time to first token (TTFT)
- Total request latency
- Prompt/input token count and prompt tokens/sec
- Output token count and output tokens/sec
- Total tokens
- Ollama total/load/prompt-evaluation/generation durations
- Model, request status, request ID, and error details

The dashboard shows per-conversation metrics and rolling aggregates across the latest 100 requests. Values are shown as unavailable when Ollama does not provide them; the plugin does not estimate token counts.

## Catalog and download filters

The Popular and Available downloads views only show models with known size and expected RAM estimates that fit the running host's installed RAM, detected from `/proc/meminfo` and reported in the API filter metadata. The limit is calculated at runtime, so it follows RAM upgrades or downgrades without a hard-coded threshold. Available downloads also includes known fitting variants from installed model families.

The Available downloads controls support:

- Dense or MoE model type
- Abilities such as completion, thinking, tools, vision, audio, and video when supplied by the catalog
- Organization by upstream popularity, newest (`modified_at`), smallest size, largest size, or name
- Search across model names, families, strengths, and capabilities

Popularity and date ordering use upstream metadata only; the plugin does not invent popularity, dates, RAM requirements, or token metrics.

## Installation

This plugin is installable from the Hermes dashboard Plugin Section using the repository URL:

```text
https://gitea.beyondcloud.solutions/dennii/Hermes-Ollama_Models.git
```

In Hermes Dashboard, open **Plugins**, choose **Install from repository**, enter the URL above, and install. The repository contains the root `plugin.yaml`, dashboard manifest, backend API, compiled frontend bundle, stylesheet, and an opt-in prerequisite declaration. On Linux, the Hermes installer will verify Ollama, install it with the official Ollama installer when missing, and install the plugin's `pypdf` dependency before committing the plugin into `~/.hermes/plugins/`. Ollama installation requires the Hermes container to run as root, which is the expected configuration for a privileged ZimaOS deployment. If the container is not running as root, the plugin install stops without enabling a partially configured plugin. After installation or an update, restart only the Hermes dashboard service if requested by the installer.

The dashboard now includes a connection panel in the header. Enter an Ollama base URL, choose **Local** or **Remote**, and use **Test** before **Save**. Saved URLs are stored in Hermes plugin data with file permissions restricted to the Hermes account. Credential-bearing URLs are rejected.

The plugin probes the configured local endpoint and known Docker endpoints, and tests a configured remote endpoint. A successful connection reports the Ollama version and installed model count. The active local endpoint continues to drive chat, status, load, and runtime telemetry. A URL saved from the dashboard takes precedence over the initial `OLLAMA_HOST` environment fallback, so the field can correct or replace an inherited container setting.

When both local and remote endpoints are online, downloading or re-downloading a model opens a destination chooser. The selected target is recorded on the job and the pull is sent to that endpoint. Remote downloads do not alter the local installed-model inventory.


The plugin supports both deployment types:

- **Physical/Linux Hermes:** Ollama defaults to `http://localhost:11434`. If Ollama is missing, the prerequisite installer can install it on a root-run host.
- **Docker Hermes:** Ollama should normally run as a separate service or on the Docker host. The plugin does not install Ollama inside the Hermes container. It first probes `http://ollama:11434` and then `http://host.docker.internal:11434`. Set `OLLAMA_HOST` to the reachable Ollama base URL, without `/v1`, for example `http://ollama:11434`, `http://host.docker.internal:11434`, or the host address shown by your installation, such as `http://<host-ip>:11434`.

For host access on Linux Docker, add this to the Hermes service when needed:

```yaml
extra_hosts:
  - "host.docker.internal:host-gateway"
environment:
  OLLAMA_HOST: http://host.docker.internal:11434
```

For Compose service-to-service networking, use the Ollama service name instead:

```yaml
environment:
  OLLAMA_HOST: http://ollama:11434
```

The dashboard plugin API is mounted when the dashboard starts. Restart Hermes after installing or enabling the plugin; otherwise the plugin page can load while `/api/plugins/ollama-manager/status` still returns 404.

## Download storage

The plugin does not store model blobs in Hermes. It sends Ollama's native `POST /api/pull` request to the selected endpoint. Therefore a download goes to the Ollama instance shown in the job message, and the Ollama service owns the model storage location. The exact path is controlled by Ollama's `OLLAMA_MODELS` setting; common Linux service/user locations are `/usr/share/ollama/.ollama/models` and `~/.ollama/models`. Check the Ollama service environment on the target host to determine the authoritative path.

## Security limits

- Uploaded files are limited to 20 MiB each
- Fetched URLs are limited to 15 MiB and a 30-second timeout
- Private, loopback, link-local, reserved, multicast, and unspecified URL targets are blocked, including redirect destinations
- Remote documents are inserted as untrusted content, not system instructions
- Only locally installed models can be selected or loaded; chat does not download models

## Dependency

The Hermes Plugin Section installs the declared `pypdf` dependency automatically before the plugin is committed. For a manual checkout, install it with:

```bash
pip install -r requirements.txt
```

`pypdf` is required for text-based PDF extraction. Scanned/image-only PDFs need OCR and are not converted to text by this plugin.