diff --git a/.github/workflows/quality.yml b/.github/workflows/quality.yml new file mode 100644 index 0000000..b243082 --- /dev/null +++ b/.github/workflows/quality.yml @@ -0,0 +1,38 @@ +name: Quality + +on: + pull_request: + push: + branches: [main] + +permissions: + contents: read + +jobs: + python: + uses: Sparkience-AI/.github/.github/workflows/reusable-python-quality.yml@adc5b60771b32fbf93f28304fbcf2dd5ad4a0464 + with: + python-version: "3.12" + run-type-check: true + + documentation: + uses: Sparkience-AI/.github/.github/workflows/reusable-docs-geo.yml@adc5b60771b32fbf93f28304fbcf2dd5ad4a0464 + + package: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ["3.11", "3.12", "3.13"] + steps: + - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1 + - uses: actions/setup-python@6d4fd22b20465ccc0f7354476588e8df7c9ca0e0 # v7.1.0 + with: + python-version: ${{ matrix.python-version }} + - uses: astral-sh/setup-uv@68559e99cc807c1eb7e9238fd43a15bba460eec2 # v10.3.3 + - name: Build distributions + run: uv build --no-sources + - name: Smoke-test installed wheel + run: | + python -m venv .wheel-smoke + .wheel-smoke/bin/python -m pip install --disable-pip-version-check dist/*.whl + .wheel-smoke/bin/sparkollama --version diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..ea52b05 --- /dev/null +++ b/.gitignore @@ -0,0 +1,17 @@ +.venv/ +.wheel-smoke/ +.uv-cache/ +dist/ +build/ +*.egg-info/ +__pycache__/ +*.py[cod] +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +.coverage +htmlcov/ +.env +.env.* +!.env.example +.streamlit/secrets.toml diff --git a/.streamlit/config.toml b/.streamlit/config.toml new file mode 100644 index 0000000..511e77e --- /dev/null +++ b/.streamlit/config.toml @@ -0,0 +1,12 @@ +[theme] +base = "dark" +primaryColor = "#e91e63" +backgroundColor = "#070707" +secondaryBackgroundColor = "#1f1f1f" +textColor = "#f5f5f5" + +[server] +address = "127.0.0.1" + +[browser] +gatherUsageStats = false diff --git a/README.md b/README.md index 8232edc..4ccf439 100644 --- a/README.md +++ b/README.md @@ -1,103 +1,103 @@ -# SparkOllama 🤖 -## Your AI, Your Conversations; Powered by Streamlit and Ollama; Developed by Sparkience AI Lab +# SparkOllama -Welcome to **SparkOllama**! This application is a sleek, AI-powered conversational interface built using Ollama's advanced language models. If you're looking for an effortless way to interact with AI through real-time responses, SparkOllama is the tool for you! +SparkOllama is an alpha, privacy-focused chat interface for models running on a local [Ollama](https://ollama.com/) service. It provides model discovery, bounded in-memory conversation history, and streamed responses without adding a cloud provider or hosted backend. ---- +## Who it is for -### Features ✨ -- **Multiple AI Models**: Choose from a list of available Ollama models to tailor your conversation. -- **Real-Time Streaming**: Get dynamic responses in real-time as you type, thanks to the Ollama API. -- **Clear Chat History**: Reset your conversation history at any time. -- **Stylish Dark Mode**: Enjoy a sleek, modern, and dark-themed interface for an immersive experience. - ---- +SparkOllama is for people who already use Ollama and want a small browser interface that keeps ordinary inference on their machine. It is not a public chat service, remote Ollama gateway, model manager, or autonomous agent. -### How It Works ⚙️ +## Capabilities -1. **Model Selection**: - - Choose your AI model from a dropdown list. Ollama provides various models for different use cases. - -2. **Chat with AI**: - - Type your query into the chat box, and the AI will respond in real-time with intelligent, conversational answers. - -3. **Clear Chat**: - - Easily clear your chat history using the "Clear Chat History" button to start fresh at any time. +- Lists models installed in the local Ollama service. +- Streams local model responses into a Streamlit chat interface. +- Keeps conversation content only in the current application session. +- Bounds prompt and history size before sending context to Ollama. +- Clears history when the user requests it or changes models. +- Handles unavailable daemons, empty model lists, malformed responses, timeouts, and interrupted streams with user-facing states. +- Renders user and model content without unsafe HTML interpolation. ---- +SparkOllama does not browse, execute code, access files, call tools, or send prompts to a cloud model. -### Installation 🚀 +## Requirements -1. **Clone the Repository**: - ```bash - git clone https://github.com/your-repo/sparkollama.git - cd sparkollama - ``` +- Windows, macOS, or Linux supported by Ollama and Python. +- Python 3.11, 3.12, or 3.13. +- [uv](https://docs.astral.sh/uv/) for the reproducible Python environment. +- A locally installed [Ollama](https://ollama.com/download) service. +- Enough disk and memory for the model you choose; requirements vary by model and quantization. -2. **Install Dependencies**: - ```bash - pip install -r requirements.txt - ``` +## Local installation -3. **Run the Application**: - ```bash - streamlit run file.py - ``` +```bash +git clone https://github.com/Sparkience-AI/SparkOllama.git +cd SparkOllama +uv sync --locked +``` -4. **Open the App**: - - Visit `http://localhost:8501` in your browser to start interacting with SparkOllama! +Pull a small model if you do not already have one: ---- +```bash +ollama pull llama3.2 +``` -### Key Files 🗂️ +Start the application: -- **`file.py`**: - The main Streamlit app that handles user input, displays messages, and interacts with the Ollama API. - -- **`style.css`**: - Custom CSS to give the application a sleek, modern look with a dark theme. +```bash +uv run --locked sparkollama +``` ---- +Open . The launcher binds Streamlit to loopback and disables Streamlit usage reporting. The original `app.py` and `file.py` launch commands remain available as source-checkout compatibility entry points and use the committed secure Streamlit configuration. -### User Interface 🖥️ +## Local security posture -- **Wide Mode Layout**: Utilizes the full width of your screen for a more spacious experience. -- **Interactive Chat Boxes**: Different color schemes for user and AI responses for clarity and ease of reading. -- **Dark Theme**: Keep it sleek with a modern, dark-themed UI for comfortable use in low-light environments. +SparkOllama connects only to an explicit loopback endpoint, `http://127.0.0.1:11434`, and rejects remote or ambiguous endpoints in its provider boundary. Ollama's local API does not provide application authentication by default. Do not bind port `11434` to `0.0.0.0`, a LAN interface, or the public internet merely to use this application. ---- +Conversation content is untrusted text. The application does not enable unsafe HTML when rendering messages, and models receive no tool authority. See [privacy and data handling](docs/privacy.md) and the [architecture and trust boundary](docs/architecture.md). -### Behind the Scenes 🧠 +## Failure behavior -- **Ollama API**: SparkOllama leverages the Ollama chat API to stream conversational responses in real-time, enhancing the interactivity of the tool. -- **Streamlit**: Used to create a fast, responsive, and user-friendly web app interface. +- **Ollama is unavailable:** start the Ollama service and reload the page. +- **No model is installed:** run `ollama pull llama3.2` or select another model you have installed. +- **A stream is interrupted:** any received partial response remains visible and in the current session; the error does not expose prompt text. +- **History is too large:** older complete turns are removed from both session state and provider context; the UI reports provider-context omissions. +- **The latest prompt is too large:** the application rejects it rather than silently truncating it. ---- +Review the [known limitations](docs/limitations.md) before relying on the application for sensitive or long-running work. -### Contribution Guidelines 🤝 +## Architecture -We welcome contributions! If you'd like to contribute to SparkOllama, feel free to open an issue or submit a pull request. +The Streamlit interface calls a framework-independent `ChatService`, which validates conversation context and uses an `OllamaProvider` adapter. Deterministic tests inject fake clients, so normal CI does not require a daemon, model download, network request, or API key. ---- +```text +Streamlit UI -> ChatService -> loopback-only OllamaProvider -> local Ollama daemon + | | + context policy error translation +``` -### Future Plans 🔮 +## Development -- **Improved Customization**: More model options and fine-tuning capabilities. -- **Saved Conversations**: Allow users to save and revisit past conversations. -- **Enhanced Visuals**: Even more customization for the UI, with options for light mode and font changes. +Run the same checks used by CI: ---- +```bash +uv sync --locked --all-groups +uv run --locked ruff format --check . +uv run --locked ruff check . +uv run --locked mypy src +uv run --locked pytest -q +uv build --no-sources +``` -### License 📜 +The test suite covers endpoint policy, daemon failures, model response compatibility, streaming, partial-stream recovery, complete-turn context bounds, local server configuration, the installed launcher, and safe UI rendering. CI also builds and smoke-tests the wheel on Python 3.11, 3.12, and 3.13. -This project is licensed under the MIT License. See the `LICENSE` file for details. +## Documentation and AI discoverability ---- +- [Privacy and retention](docs/privacy.md) +- [Architecture and trust boundary](docs/architecture.md) +- [Known limitations](docs/limitations.md) +- [`llms.txt`](llms.txt), provided as an experimental machine-readable project summary -### Stay Connected 🌐 +The README and linked documents are the authoritative sources for installation, scope, privacy, and limitations. Generic claims about model intelligence are intentionally avoided because behavior depends on the selected local model. -Made with ❤️ by **Sparkience AI Lab**. Feel free to reach out or follow us for updates! +## License and support -Happy chatting with SparkOllama! 👨‍💻👩‍💻 - ---- +SparkOllama is available under the [MIT License](LICENSE). Use GitHub issues for reproducible bugs and feature proposals. Report security concerns through the Sparkience organization security policy rather than a public issue. diff --git a/app.py b/app.py new file mode 100644 index 0000000..6afa2b0 --- /dev/null +++ b/app.py @@ -0,0 +1,5 @@ +"""Canonical Streamlit entry point.""" + +from sparkollama.ui import run + +run() diff --git a/docs/architecture.md b/docs/architecture.md new file mode 100644 index 0000000..838bcde --- /dev/null +++ b/docs/architecture.md @@ -0,0 +1,16 @@ +# Architecture + +SparkOllama has four small boundaries: + +1. `app.py` and `file.py` launch the Streamlit interface. +2. `sparkollama.ui` owns display and session state but not Ollama protocol handling. +3. `sparkollama.service` validates and bounds conversation context. +4. `sparkollama.providers` enforces the loopback endpoint policy and translates Ollama responses and failures. + +The UI and deterministic tests use the same typed service contracts. Standard tests use fake clients and do not require a running daemon or model download. + +## Trust boundary + +User and model messages are untrusted text. They are rendered through Streamlit without enabling unsafe HTML. The only supported provider endpoint is an explicit loopback HTTP(S) URL with no credentials, query, fragment, or API path. + +SparkOllama does not give the model tools, filesystem access, browsing, code execution, or permission to perform external actions. diff --git a/docs/limitations.md b/docs/limitations.md new file mode 100644 index 0000000..36b4d3c --- /dev/null +++ b/docs/limitations.md @@ -0,0 +1,11 @@ +# Current limitations + +SparkOllama is an alpha local chat client, not a hosted service. + +- Only a loopback Ollama service is supported. +- Conversation history exists only in the current Streamlit session. +- Context is bounded by message and character limits, not a model-specific tokenizer. +- The current Streamlit interface cannot cancel an in-flight request. A 60-second Ollama client timeout bounds stalled requests; slow models may require a future user-configurable local setting. +- Partial streamed output is retained in the session when the connection fails. +- Model quality, safety, licensing, context size, and hardware needs depend on the model selected in Ollama. +- Saved conversations, remote endpoints, cloud models, tool calling, and public hosting are intentionally out of scope. diff --git a/docs/privacy.md b/docs/privacy.md new file mode 100644 index 0000000..0dd01c6 --- /dev/null +++ b/docs/privacy.md @@ -0,0 +1,11 @@ +# Privacy and data handling + +SparkOllama is designed for a local Ollama service on `127.0.0.1` or `localhost`. + +- Prompts and model responses remain in the active Streamlit session and are not saved by SparkOllama. +- Clearing the chat removes the current in-memory application history. +- SparkOllama disables Streamlit usage reporting and has no application telemetry, user accounts, cloud provider, or analytics integration. +- Ollama model downloads require network access, but ordinary inference is local after the model is present. +- Local models and Ollama may have their own files, caches, and logs. Review Ollama's configuration when local retention matters. + +The committed configuration and installed launcher bind the Streamlit interface to `127.0.0.1`. SparkOllama does not treat a browser-accessible Ollama endpoint as authenticated. Keep ports `8501` and `11434` bound to loopback. Do not expose either service on a LAN or the public internet without a separately designed authenticated and encrypted gateway. diff --git a/file.py b/file.py index 1b67837..961b778 100644 --- a/file.py +++ b/file.py @@ -1,58 +1,5 @@ -import streamlit as st -import ollama -from typing import Dict, Generator - -# Set wide mode -st.set_page_config(layout="wide") - -# Load custom CSS for styling -with open("style.css") as css: - st.markdown(f'', unsafe_allow_html=True) - -# Generator function for streaming chat responses from Ollama -def ollama_generator(model_name: str, messages: Dict) -> Generator: - stream = ollama.chat(model=model_name, messages=messages, stream=True) - for chunk in stream: - yield chunk['message']['content'] - -# Page title -st.title("🤖 SparkOllama: Made By Sparkience AI Lab") - -# Initialize session state variables -if "selected_model" not in st.session_state: - st.session_state.selected_model = "" -if "messages" not in st.session_state: - st.session_state.messages = [] - -# Model Selection Dropdown (dark themed) -st.session_state.selected_model = st.selectbox( - "Please select the model:", [model["name"] for model in ollama.list()["models"]]) - -# Clear chat history functionality -if st.button("Clear Chat History"): - st.session_state.messages = [] - -# Display chat messages -for message in st.session_state.messages: - if message["role"] == "user": - with st.chat_message("user"): - st.markdown(f'
{message["content"]}
', - unsafe_allow_html=True) - else: - with st.chat_message("assistant"): - st.markdown(f'
{message["content"]}
', - unsafe_allow_html=True) - -# Chat input functionality -if prompt := st.chat_input("How can I assist you?"): - # Add user message to chat history - st.session_state.messages.append({"role": "user", "content": prompt}) - - # Display user message in chat message container - with st.chat_message("user"): - st.markdown(f'
{prompt}
', unsafe_allow_html=True) - - - with st.chat_message("assistant"): - response = st.write_stream(ollama_generator(st.session_state.selected_model, st.session_state.messages)) - st.session_state.messages.append({"role": "assistant", "content": response}) +"""Compatibility entry point for the original SparkOllama launch command.""" + +from sparkollama.ui import run + +run() diff --git a/llms.txt b/llms.txt new file mode 100644 index 0000000..1b8011b --- /dev/null +++ b/llms.txt @@ -0,0 +1,12 @@ +# SparkOllama + +SparkOllama is an open-source, privacy-focused local conversation client for models served by Ollama. + +Authoritative sources: + +- Project and installation: https://github.com/Sparkience-AI/SparkOllama#readme +- Privacy: https://github.com/Sparkience-AI/SparkOllama/blob/main/docs/privacy.md +- Architecture and trust boundary: https://github.com/Sparkience-AI/SparkOllama/blob/main/docs/architecture.md +- Known limitations: https://github.com/Sparkience-AI/SparkOllama/blob/main/docs/limitations.md + +The complete product runs locally. There is no hosted SparkOllama service, cloud model provider, or agentic tool execution. The Ollama API is unauthenticated by default and must remain loopback-only. diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..27c2026 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,50 @@ +[build-system] +requires = ["hatchling>=1.26,<2"] +build-backend = "hatchling.build" + +[project] +name = "sparkollama" +version = "0.1.0" +description = "A privacy-focused local conversation client for Ollama." +readme = "README.md" +requires-python = ">=3.11,<3.14" +license = { file = "LICENSE" } +authors = [{ name = "Sparkience AI Lab" }] +dependencies = [ + "ollama>=0.4,<1", + "streamlit>=1.37,<2", +] + +[project.scripts] +sparkollama = "sparkollama.cli:main" + +[dependency-groups] +dev = [ + "hatchling>=1.26,<2", + "mypy>=1.13,<2", + "pytest>=8.3,<9", + "ruff>=0.8,<1", +] + +[tool.hatch.build.targets.wheel] +packages = ["src/sparkollama"] + +[tool.pytest.ini_options] +addopts = "-q" +testpaths = ["tests"] + +[tool.ruff] +line-length = 100 +target-version = "py311" + +[tool.ruff.format] +line-ending = "lf" + +[tool.ruff.lint] +select = ["E", "F", "I", "UP", "B"] + +[tool.mypy] +python_version = "3.11" +strict = true +follow_imports = "skip" +packages = ["sparkollama"] diff --git a/src/sparkollama/__init__.py b/src/sparkollama/__init__.py new file mode 100644 index 0000000..c89ebfc --- /dev/null +++ b/src/sparkollama/__init__.py @@ -0,0 +1,8 @@ +"""SparkOllama local chat application.""" + +from sparkollama.models import ChatMessage, ModelInfo +from sparkollama.service import ChatService, ConversationPolicy + +__version__ = "0.1.0" + +__all__ = ["ChatMessage", "ChatService", "ConversationPolicy", "ModelInfo"] diff --git a/src/sparkollama/cli.py b/src/sparkollama/cli.py new file mode 100644 index 0000000..130fd11 --- /dev/null +++ b/src/sparkollama/cli.py @@ -0,0 +1,34 @@ +"""Installed SparkOllama launcher.""" + +from __future__ import annotations + +import argparse +import subprocess +import sys +from collections.abc import Sequence +from pathlib import Path + +from sparkollama import __version__ + + +def main(argv: Sequence[str] | None = None) -> int: + parser = argparse.ArgumentParser(description="Run the local SparkOllama interface.") + parser.add_argument("--version", action="version", version=f"SparkOllama {__version__}") + parser.add_argument("--port", type=int, default=8501, help="Loopback Streamlit port.") + args = parser.parse_args(argv) + if not 1 <= args.port <= 65_535: + parser.error("--port must be between 1 and 65535") + + ui_path = Path(__file__).with_name("ui.py") + return subprocess.call( + [ + sys.executable, + "-m", + "streamlit", + "run", + str(ui_path), + "--server.address=127.0.0.1", + "--browser.gatherUsageStats=false", + f"--server.port={args.port}", + ] + ) diff --git a/src/sparkollama/models.py b/src/sparkollama/models.py new file mode 100644 index 0000000..f098a9c --- /dev/null +++ b/src/sparkollama/models.py @@ -0,0 +1,22 @@ +"""Typed values shared across SparkOllama layers.""" + +from dataclasses import dataclass +from typing import Literal + +ChatRole = Literal["user", "assistant", "system"] + + +@dataclass(frozen=True, slots=True) +class ChatMessage: + role: ChatRole + content: str + + def as_provider_message(self) -> dict[str, str]: + return {"role": self.role, "content": self.content} + + +@dataclass(frozen=True, slots=True) +class ModelInfo: + name: str + digest: str | None = None + size_bytes: int | None = None diff --git a/src/sparkollama/providers.py b/src/sparkollama/providers.py new file mode 100644 index 0000000..ed27b7b --- /dev/null +++ b/src/sparkollama/providers.py @@ -0,0 +1,157 @@ +"""Provider boundary for the loopback Ollama service.""" + +from __future__ import annotations + +import builtins +from collections.abc import Iterable, Iterator, Sequence +from typing import Any, Protocol, cast +from urllib.parse import urlsplit + +import ollama + +from sparkollama.models import ChatMessage, ModelInfo + +DEFAULT_OLLAMA_ENDPOINT = "http://127.0.0.1:11434" + + +class OllamaClient(Protocol): + def list(self) -> Any: ... + + def chat( + self, + *, + model: str, + messages: builtins.list[dict[str, str]], + stream: bool, + ) -> Iterable[Any]: ... + + +class ChatProvider(Protocol): + def list_models(self) -> list[ModelInfo]: ... + + def stream_chat( + self, + model: str, + messages: Sequence[ChatMessage], + ) -> Iterator[str]: ... + + +class SparkOllamaError(RuntimeError): + """Base class for safe, user-displayable application errors.""" + + +class EndpointPolicyError(SparkOllamaError): + pass + + +class OllamaUnavailableError(SparkOllamaError): + pass + + +class OllamaProtocolError(SparkOllamaError): + pass + + +class OllamaGenerationError(SparkOllamaError): + pass + + +def validate_loopback_endpoint(endpoint: str) -> str: + """Accept only an HTTP(S) Ollama endpoint on the local machine.""" + + try: + parsed = urlsplit(endpoint) + port = parsed.port + except ValueError as exc: + raise EndpointPolicyError("The Ollama endpoint contains an invalid host or port.") from exc + if parsed.scheme not in {"http", "https"}: + raise EndpointPolicyError("The Ollama endpoint must use HTTP or HTTPS.") + if parsed.username or parsed.password or parsed.query or parsed.fragment: + raise EndpointPolicyError("The Ollama endpoint must not contain credentials or parameters.") + if parsed.path not in {"", "/"}: + raise EndpointPolicyError("The Ollama endpoint must not contain a path.") + if parsed.hostname not in {"127.0.0.1", "::1", "localhost"}: + raise EndpointPolicyError("SparkOllama supports loopback Ollama endpoints only.") + if port is None or not 1 <= port <= 65_535: + raise EndpointPolicyError("The Ollama endpoint must include a port from 1 to 65535.") + return endpoint.rstrip("/") + + +def _value(item: Any, *names: str) -> Any: + for name in names: + if isinstance(item, dict) and name in item: + return item[name] + value = getattr(item, name, None) + if value is not None: + return value + return None + + +class OllamaProvider: + """Translate the Ollama Python client into the application provider contract.""" + + def __init__( + self, + endpoint: str = DEFAULT_OLLAMA_ENDPOINT, + *, + timeout_seconds: float = 60.0, + client: OllamaClient | None = None, + ) -> None: + self.endpoint = validate_loopback_endpoint(endpoint) + self._client = client or cast( + OllamaClient, + ollama.Client(host=self.endpoint, timeout=timeout_seconds), + ) + + def list_models(self) -> list[ModelInfo]: + try: + response = self._client.list() + raw_models = _value(response, "models") + if raw_models is None: + raise OllamaProtocolError("Ollama returned an unexpected model-list response.") + models: list[ModelInfo] = [] + for raw in raw_models: + name = _value(raw, "model", "name") + if not isinstance(name, str) or not name.strip(): + raise OllamaProtocolError("Ollama returned a model without a valid name.") + digest = _value(raw, "digest") + size = _value(raw, "size") + models.append( + ModelInfo( + name=name, + digest=digest if isinstance(digest, str) else None, + size_bytes=size if isinstance(size, int) else None, + ) + ) + return sorted(models, key=lambda model: model.name.casefold()) + except SparkOllamaError: + raise + except Exception as exc: + raise OllamaUnavailableError( + "Ollama is not reachable on the local loopback endpoint." + ) from exc + + def stream_chat( + self, + model: str, + messages: Sequence[ChatMessage], + ) -> Iterator[str]: + try: + chunks = self._client.chat( + model=model, + messages=[message.as_provider_message() for message in messages], + stream=True, + ) + for chunk in chunks: + message = _value(chunk, "message") + content = _value(message, "content") if message is not None else None + if not isinstance(content, str): + raise OllamaProtocolError("Ollama returned an unexpected streaming response.") + if content: + yield content + except SparkOllamaError: + raise + except Exception as exc: + raise OllamaGenerationError( + "Local generation stopped before a complete response was received." + ) from exc diff --git a/src/sparkollama/service.py b/src/sparkollama/service.py new file mode 100644 index 0000000..9974282 --- /dev/null +++ b/src/sparkollama/service.py @@ -0,0 +1,115 @@ +"""Framework-independent SparkOllama application service.""" + +from __future__ import annotations + +from collections.abc import Iterator, Sequence +from dataclasses import dataclass + +from sparkollama.models import ChatMessage, ModelInfo +from sparkollama.providers import ChatProvider, SparkOllamaError + + +class ConversationValidationError(SparkOllamaError): + pass + + +@dataclass(frozen=True, slots=True) +class PreparedConversation: + messages: tuple[ChatMessage, ...] + dropped_messages: int + + +@dataclass(frozen=True, slots=True) +class ConversationPolicy: + max_messages: int = 25 + max_characters: int = 32_000 + max_prompt_characters: int = 8_000 + max_response_characters: int = 16_000 + + @staticmethod + def _validate_alternating(messages: Sequence[ChatMessage], *, final_role: str) -> None: + if not messages: + raise ConversationValidationError("The conversation cannot be empty.") + expected = "user" + for message in messages: + if message.role != expected: + raise ConversationValidationError( + "Conversation messages must be complete alternating user/assistant turns." + ) + expected = "assistant" if expected == "user" else "user" + if messages[-1].role != final_role: + raise ConversationValidationError( + f"The conversation must end with an {final_role} message." + ) + + def _trim_complete_turns(self, messages: Sequence[ChatMessage]) -> list[ChatMessage]: + selected = list(messages) + while len(selected) > (1 if selected[-1].role == "user" else 2) and ( + len(selected) > self.max_messages + or sum(len(message.content) for message in selected) > self.max_characters + ): + del selected[:2] + return selected + + def prepare(self, messages: Sequence[ChatMessage]) -> PreparedConversation: + if not messages: + raise ConversationValidationError("Enter a message before starting generation.") + self._validate_alternating(messages, final_role="user") + if not messages[-1].content.strip(): + raise ConversationValidationError("The user message cannot be empty.") + if len(messages[-1].content) > self.max_prompt_characters: + raise ConversationValidationError( + f"The latest message exceeds the {self.max_prompt_characters:,}-character limit." + ) + + selected = self._trim_complete_turns(messages) + if sum(len(message.content) for message in selected) > self.max_characters: + raise ConversationValidationError( + f"The latest message exceeds the {self.max_characters:,}-character context limit." + ) + return PreparedConversation( + messages=tuple(selected), + dropped_messages=len(messages) - len(selected), + ) + + def retain_session(self, messages: Sequence[ChatMessage]) -> tuple[ChatMessage, ...]: + """Keep bounded, complete user/assistant turns in Streamlit session state.""" + + self._validate_alternating(messages, final_role="assistant") + selected = self._trim_complete_turns(messages) + if sum(len(message.content) for message in selected) > self.max_characters: + raise ConversationValidationError( + "The latest conversation turn exceeds session limits." + ) + return tuple(selected) + + +class ChatService: + def __init__( + self, + provider: ChatProvider, + policy: ConversationPolicy | None = None, + ) -> None: + self._provider = provider + self._policy = policy or ConversationPolicy() + + def available_models(self) -> list[ModelInfo]: + return self._provider.list_models() + + def stream_reply( + self, + model: str, + messages: Sequence[ChatMessage], + ) -> tuple[PreparedConversation, Iterator[str]]: + if not model.strip(): + raise ConversationValidationError("Select an installed Ollama model.") + prepared = self._policy.prepare(messages) + stream = self._provider.stream_chat(model, prepared.messages) + return prepared, stream + + @property + def response_character_limit(self) -> int: + return self._policy.max_response_characters + + def retain_session(self, messages: Sequence[ChatMessage]) -> tuple[ChatMessage, ...]: + return self._policy.retain_session(messages) diff --git a/src/sparkollama/ui.py b/src/sparkollama/ui.py new file mode 100644 index 0000000..8f29f04 --- /dev/null +++ b/src/sparkollama/ui.py @@ -0,0 +1,111 @@ +"""Streamlit user interface for the tested SparkOllama core.""" + +from __future__ import annotations + +import streamlit as st + +from sparkollama.models import ChatMessage +from sparkollama.providers import OllamaProvider, SparkOllamaError +from sparkollama.service import ChatService + + +def _messages() -> list[ChatMessage]: + raw = st.session_state.setdefault("sparkollama_messages", []) + return [ChatMessage(role=item["role"], content=item["content"]) for item in raw] + + +def _save_messages(messages: list[ChatMessage]) -> None: + st.session_state.sparkollama_messages = [message.as_provider_message() for message in messages] + + +def _render_message(message: ChatMessage) -> None: + with st.chat_message(message.role): + st.markdown(message.content, unsafe_allow_html=False) + + +def run() -> None: + st.set_page_config(page_title="SparkOllama", page_icon="🤖", layout="wide") + st.title("SparkOllama") + st.caption("Private, session-only chat with models running on your local Ollama service.") + + service = ChatService(OllamaProvider()) + try: + models = service.available_models() + except SparkOllamaError as exc: + st.error(str(exc)) + st.info( + "Start Ollama, then reload this page. The default endpoint is http://127.0.0.1:11434." + ) + st.stop() + + if not models: + st.warning("Ollama is running, but no local models are installed.") + st.code("ollama pull llama3.2", language="shell") + st.stop() + + names = [model.name for model in models] + previous_model = st.session_state.get("sparkollama_selected_model") + if previous_model not in names: + previous_model = names[0] + selected_model = st.selectbox( + "Local model", + names, + index=names.index(previous_model), + help="Changing models clears the current conversation to avoid mixing model contexts.", + ) + + messages = _messages() + if st.session_state.get("sparkollama_selected_model") not in {None, selected_model}: + messages = [] + _save_messages(messages) + st.info("The conversation was cleared because the selected model changed.") + st.session_state.sparkollama_selected_model = selected_model + + if st.button("Clear current chat", disabled=not messages): + messages = [] + _save_messages(messages) + st.rerun() + + for message in messages: + _render_message(message) + + prompt = st.chat_input("Message your local model", max_chars=8_000) + if not prompt: + return + + messages.append(ChatMessage(role="user", content=prompt)) + _render_message(messages[-1]) + + partial: list[str] = [] + with st.chat_message("assistant"): + output = st.empty() + try: + prepared, stream = service.stream_reply(selected_model, messages) + if prepared.dropped_messages: + st.caption( + f"Used the newest {len(prepared.messages)} messages; " + f"omitted {prepared.dropped_messages} older messages to bound local context." + ) + for chunk in stream: + remaining = service.response_character_limit - sum(len(part) for part in partial) + if remaining <= 0: + st.warning("The response reached the session character limit and was stopped.") + break + partial.append(chunk[:remaining]) + output.markdown("".join(partial), unsafe_allow_html=False) + if len(chunk) > remaining: + st.warning("The response reached the session character limit and was stopped.") + break + except SparkOllamaError as exc: + if partial: + st.warning(f"{exc} The partial response remains in this session.") + else: + st.error(str(exc)) + + if partial: + messages.append(ChatMessage(role="assistant", content="".join(partial))) + _save_messages(list(service.retain_session(messages))) + + +if __name__ == "__main__": + run() diff --git a/style.css b/style.css deleted file mode 100644 index 2f37ecf..0000000 --- a/style.css +++ /dev/null @@ -1,43 +0,0 @@ -body { - background-color: #070707; -} -.stApp { - background-color: #070707; - padding: 20px; -} -.title { - font-family: 'Arial', sans-serif; - color: #f5f5f5; - text-align: center; -} -.chat-box { - background-color: #333333; - padding: 15px 20px; - border-radius: 10px; - box-shadow: 0px 4px 10px rgba(0, 0, 0, 0.5); - margin-bottom: 10px; -} -.user-message { - background-color: #2196f3; - color: #ffffff; - border-radius: 10px; -} -.assistant-message { - background-color: #4caf50; - color: #ffffff; - border-radius: 10px; -} -.stButton > button { - background-color: #e91e63; - color: #ffffff; -} -.stChatInput { - color: #f5f5f5; -} -.stSelectbox { - background-color: #333333; - color: #f5f5f5; -} -.stMarkdown { - color: #f5f5f5; -} \ No newline at end of file diff --git a/tests/test_cli.py b/tests/test_cli.py new file mode 100644 index 0000000..a1e03bf --- /dev/null +++ b/tests/test_cli.py @@ -0,0 +1,21 @@ +from __future__ import annotations + +from collections.abc import Sequence + +from sparkollama import cli + + +def test_cli_launches_streamlit_with_local_security_flags(monkeypatch) -> None: + command: Sequence[str] = [] + + def fake_call(args: Sequence[str]) -> int: + nonlocal command + command = args + return 0 + + monkeypatch.setattr(cli.subprocess, "call", fake_call) + + assert cli.main(["--port", "8765"]) == 0 + assert "--server.address=127.0.0.1" in command + assert "--browser.gatherUsageStats=false" in command + assert "--server.port=8765" in command diff --git a/tests/test_providers.py b/tests/test_providers.py new file mode 100644 index 0000000..aeef0e0 --- /dev/null +++ b/tests/test_providers.py @@ -0,0 +1,132 @@ +from __future__ import annotations + +from collections.abc import Iterable +from typing import Any + +import pytest + +from sparkollama.models import ChatMessage +from sparkollama.providers import ( + EndpointPolicyError, + OllamaGenerationError, + OllamaProtocolError, + OllamaProvider, + OllamaUnavailableError, + validate_loopback_endpoint, +) + + +class FakeClient: + def __init__(self, models: Any = None, chunks: Iterable[Any] = ()) -> None: + self.models = {"models": []} if models is None else models + self.chunks = chunks + self.received_messages: list[dict[str, str]] | None = None + + def list(self) -> Any: + return self.models + + def chat( + self, + *, + model: str, + messages: list[dict[str, str]], + stream: bool, + ) -> Iterable[Any]: + assert model == "tiny" + assert stream is True + self.received_messages = messages + return self.chunks + + +@pytest.mark.parametrize( + "endpoint", + [ + "http://127.0.0.1:11434", + "http://localhost:11434/", + "https://[::1]:11434", + ], +) +def test_loopback_endpoint_policy_accepts_local_hosts(endpoint: str) -> None: + assert validate_loopback_endpoint(endpoint) + + +@pytest.mark.parametrize( + "endpoint", + [ + "http://0.0.0.0:11434", + "http://192.168.1.5:11434", + "https://ollama.example.com:11434", + "http://localhost:11434/api/chat", + "http://user:secret@localhost:11434", + "http://localhost:not-a-port", + "http://localhost:70000", + "file:///tmp/ollama.sock", + ], +) +def test_loopback_endpoint_policy_rejects_remote_or_ambiguous_hosts(endpoint: str) -> None: + with pytest.raises(EndpointPolicyError): + validate_loopback_endpoint(endpoint) + + +def test_model_list_supports_current_and_legacy_response_names() -> None: + client = FakeClient( + models={ + "models": [ + {"model": "zeta", "digest": "abc", "size": 12}, + {"name": "Alpha"}, + ] + } + ) + + result = OllamaProvider(client=client).list_models() + + assert [model.name for model in result] == ["Alpha", "zeta"] + assert result[1].digest == "abc" + assert result[1].size_bytes == 12 + + +def test_model_list_translates_connection_failures() -> None: + class FailingClient(FakeClient): + def list(self) -> Any: + raise ConnectionError("daemon unavailable") + + with pytest.raises(OllamaUnavailableError, match="loopback"): + OllamaProvider(client=FailingClient()).list_models() + + +def test_model_list_rejects_malformed_response() -> None: + with pytest.raises(OllamaProtocolError): + OllamaProvider(client=FakeClient(models={})).list_models() + + +def test_stream_forwards_typed_messages_and_yields_content() -> None: + client = FakeClient(chunks=[{"message": {"content": "hello"}}, {"message": {"content": ""}}]) + provider = OllamaProvider(client=client) + + result = list(provider.stream_chat("tiny", [ChatMessage("user", "hi")])) + + assert result == ["hello"] + assert client.received_messages == [{"role": "user", "content": "hi"}] + + +def test_stream_preserves_partial_output_then_translates_failure() -> None: + def failing_chunks() -> Iterable[dict[str, dict[str, str]]]: + yield {"message": {"content": "partial"}} + raise ConnectionError("lost connection") + + stream = OllamaProvider(client=FakeClient(chunks=failing_chunks())).stream_chat( + "tiny", [ChatMessage("user", "hi")] + ) + + assert next(stream) == "partial" + with pytest.raises(OllamaGenerationError, match="stopped"): + next(stream) + + +def test_stream_rejects_malformed_chunks() -> None: + stream = OllamaProvider(client=FakeClient(chunks=[{"done": False}])).stream_chat( + "tiny", [ChatMessage("user", "hi")] + ) + + with pytest.raises(OllamaProtocolError): + next(stream) diff --git a/tests/test_service.py b/tests/test_service.py new file mode 100644 index 0000000..9965fa3 --- /dev/null +++ b/tests/test_service.py @@ -0,0 +1,101 @@ +from __future__ import annotations + +from collections.abc import Iterator, Sequence + +import pytest + +from sparkollama.models import ChatMessage, ModelInfo +from sparkollama.service import ChatService, ConversationPolicy, ConversationValidationError + + +class FakeProvider: + def __init__(self) -> None: + self.received: Sequence[ChatMessage] = [] + + def list_models(self) -> list[ModelInfo]: + return [ModelInfo("tiny")] + + def stream_chat( + self, + model: str, + messages: Sequence[ChatMessage], + ) -> Iterator[str]: + self.received = messages + yield f"reply from {model}" + + +def test_policy_keeps_complete_turns_without_orphaning_assistant_messages() -> None: + policy = ConversationPolicy(max_messages=3, max_characters=20, max_prompt_characters=8) + history = [ + ChatMessage("user", "one"), + ChatMessage("assistant", "two"), + ChatMessage("user", "three"), + ChatMessage("assistant", "four"), + ChatMessage("user", "five"), + ] + + result = policy.prepare(history) + + assert result.messages == ( + ChatMessage("user", "three"), + ChatMessage("assistant", "four"), + ChatMessage("user", "five"), + ) + assert result.dropped_messages == 2 + + +def test_policy_bounds_complete_session_turns() -> None: + policy = ConversationPolicy(max_messages=2, max_characters=100) + history = [ + ChatMessage("user", "old"), + ChatMessage("assistant", "answer"), + ChatMessage("user", "new"), + ChatMessage("assistant", "reply"), + ] + + assert policy.retain_session(history) == ( + ChatMessage("user", "new"), + ChatMessage("assistant", "reply"), + ) + + +@pytest.mark.parametrize( + "messages", + [ + [], + [ChatMessage("assistant", "not a user turn")], + [ChatMessage("user", " ")], + ], +) +def test_policy_rejects_invalid_latest_turn(messages: list[ChatMessage]) -> None: + with pytest.raises(ConversationValidationError): + ConversationPolicy().prepare(messages) + + +def test_policy_rejects_oversized_latest_prompt() -> None: + with pytest.raises(ConversationValidationError, match="4-character"): + ConversationPolicy(max_prompt_characters=4).prepare([ChatMessage("user", "12345")]) + + +def test_service_uses_prepared_history() -> None: + provider = FakeProvider() + service = ChatService( + provider, + ConversationPolicy(max_messages=3, max_characters=100, max_prompt_characters=100), + ) + history = [ + ChatMessage("user", "old"), + ChatMessage("assistant", "answer"), + ChatMessage("user", "new"), + ] + + prepared, stream = service.stream_reply("tiny", history) + + assert list(stream) == ["reply from tiny"] + assert provider.received == prepared.messages + assert prepared.dropped_messages == 0 + + +def test_service_requires_a_model() -> None: + with pytest.raises(ConversationValidationError, match="Select"): + ChatService(FakeProvider()).stream_reply(" ", [ChatMessage("user", "hello")]) diff --git a/tests/test_ui_safety.py b/tests/test_ui_safety.py new file mode 100644 index 0000000..1001f14 --- /dev/null +++ b/tests/test_ui_safety.py @@ -0,0 +1,19 @@ +import tomllib +from pathlib import Path + + +def test_ui_never_enables_unsafe_html_for_conversation_content() -> None: + source = (Path(__file__).parents[1] / "src" / "sparkollama" / "ui.py").read_text( + encoding="utf-8" + ) + + assert "unsafe_allow_html=True" not in source + assert "unsafe_allow_html=False" in source + + +def test_streamlit_is_loopback_only_and_usage_reporting_is_disabled() -> None: + config_path = Path(__file__).parents[1] / ".streamlit" / "config.toml" + config = tomllib.loads(config_path.read_text(encoding="utf-8")) + + assert config["server"]["address"] == "127.0.0.1" + assert config["browser"]["gatherUsageStats"] is False diff --git a/uv.lock b/uv.lock new file mode 100644 index 0000000..f74312b --- /dev/null +++ b/uv.lock @@ -0,0 +1,1242 @@ +version = 1 +revision = 3 +requires-python = ">=3.11, <3.14" +resolution-markers = [ + "python_full_version >= '3.12' and sys_platform == 'win32'", + "python_full_version >= '3.12' and sys_platform == 'emscripten'", + "python_full_version >= '3.12' 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