{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-diegoomal-ollama-connection","slug":"ollama-connection","name":"Ollama connection","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=diegoomal.ollama-connection","page_url":"https://unfragile.ai/ollama-connection","categories":["code-editors"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-diegoomal-ollama-connection__cap_0","uri":"capability://text.generation.language.local.ollama.model.inference.via.command.palette","name":"local-ollama-model-inference-via-command-palette","description":"Executes inference requests against a locally-running Ollama instance by routing user queries through VS Code's Command Palette interface. The extension marshals natural language input from the user, sends it to the Ollama API endpoint (typically localhost:11434), and streams or returns model responses back into a dedicated chatbot panel within the editor. This approach avoids cloud API calls and keeps model execution on the developer's machine, enabling offline-first LLM interactions without external service dependencies.","intents":["I want to ask an LLM questions about my code without leaving VS Code or sending data to the cloud","I need real-time AI assistance while coding but want to run models locally for privacy","I want to use open-source models (via Ollama) instead of proprietary cloud APIs"],"best_for":["solo developers and small teams prioritizing data privacy and offline capability","developers working in air-gapped or restricted network environments","builders experimenting with open-source LLMs without cloud service costs"],"limitations":["Ollama instance must be running and accessible before extension can function — no fallback to cloud providers if local service is unavailable","Model inference latency depends entirely on local hardware; no optimization or caching layer documented to reduce response times","No documented support for model switching or selection within the extension — users must manage Ollama model lifecycle externally","Single-turn query pattern — no documented conversation history or multi-turn context management within the chatbot panel"],"requires":["Visual Studio Code (minimum version unknown, likely 1.60+)","Ollama tool installed and running locally or on accessible network (https://ollama.ai)","At least one Ollama model pulled and available (e.g., llama2, mistral, neural-chat)"],"input_types":["natural language text (free-form queries)","code snippets (selected text from editor, mechanism unknown)"],"output_types":["natural language text (model response)","code snippets (if model generates code)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-diegoomal-ollama-connection__cap_1","uri":"capability://text.generation.language.code.explanation.and.documentation.generation","name":"code-explanation-and-documentation-generation","description":"Accepts selected code snippets or entire files from the VS Code editor and sends them to the Ollama model to generate natural language explanations, documentation, or code comments. The extension likely captures the current editor context (selected text or full file), formats it as a prompt, and returns the model's explanation into the chatbot panel or as inline comments. This enables developers to understand unfamiliar code or auto-generate documentation without leaving the editor.","intents":["I want to understand what a piece of code does by asking the AI to explain it","I need to generate docstrings or comments for my code automatically","I want to document legacy or unfamiliar code quickly without manual effort"],"best_for":["developers onboarding to new codebases and needing rapid code comprehension","teams maintaining legacy code with minimal documentation","solo developers who want to auto-generate documentation to save time"],"limitations":["No documented mechanism to inject explanations back into the editor as inline comments — output appears only in chatbot panel, requiring manual copy-paste","Model quality and accuracy depend entirely on Ollama model selection; smaller models may produce incomplete or inaccurate explanations","No context awareness of project structure, imports, or external dependencies — explanations are generated from code snippet alone","Explanation length and detail are not configurable; no documented way to request concise vs. detailed explanations"],"requires":["Visual Studio Code with Ollama Connection extension installed","Ollama instance running with a model capable of code understanding (e.g., mistral, neural-chat, or code-specific models)","Code to explain (selected text or open file in editor)"],"input_types":["code (selected text from editor)","code (full file content, mechanism unknown)"],"output_types":["natural language text (explanation)","markdown or plain text (documentation)"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-diegoomal-ollama-connection__cap_2","uri":"capability://code.generation.editing.context.aware.code.completion.suggestions","name":"context-aware-code-completion-suggestions","description":"Monitors the current editor context (cursor position, surrounding code, open file) and generates code completion suggestions by querying the Ollama model with the incomplete code as a prompt. The extension likely uses a trigger mechanism (keystroke, delay, or explicit invocation) to request completions and displays suggestions in a chatbot panel or inline. This enables developers to receive AI-powered code suggestions from local models without relying on cloud-based completion services.","intents":["I want code completion suggestions from a local LLM as I type","I need to complete a function or code block using AI without sending my code to the cloud","I want to explore alternative implementations or patterns suggested by the model"],"best_for":["developers working in privacy-sensitive environments or air-gapped networks","teams using proprietary or confidential codebases that cannot be sent to cloud services","builders experimenting with local LLM-based development workflows"],"limitations":["No documented inline suggestion display — completions appear in chatbot panel, not as autocomplete popups, requiring context switching","Latency of local model inference may make real-time completion impractical on slower hardware; no caching or optimization documented","Model quality varies significantly; smaller Ollama models may produce syntactically incorrect or semantically irrelevant suggestions","No language-specific optimization or syntax awareness — completions are generated as raw text without AST-based validation","No documented filtering or ranking of suggestions; all model output is presented equally without quality scoring"],"requires":["Visual Studio Code with Ollama Connection extension","Ollama instance running with a code-capable model (e.g., mistral, neural-chat, or code-specific models like starcoder if available)","Incomplete code in the editor (function signature, partial statement, etc.)"],"input_types":["code (current file context and cursor position)","code (surrounding lines for context, mechanism unknown)"],"output_types":["code (completion suggestions)","natural language (alternative implementations or explanations)"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-diegoomal-ollama-connection__cap_3","uri":"capability://text.generation.language.interactive.chatbot.panel.for.development.queries","name":"interactive-chatbot-panel-for-development-queries","description":"Provides a dedicated chatbot interface within VS Code (sidebar or panel view) where developers can pose natural language questions about code, architecture, debugging, or development practices. The extension maintains a query-response interface that sends user input to the Ollama model and displays responses in a conversational format. This enables developers to use the editor as a hub for AI-assisted development without context-switching to external chat applications.","intents":["I want to ask the AI questions about my code or development approach without leaving VS Code","I need a conversational interface to explore solutions to coding problems in real-time","I want to use an AI assistant as a development partner while working in the editor"],"best_for":["developers who prefer integrated development environments with minimal context-switching","teams using local Ollama instances and wanting a unified interface for AI assistance","solo developers building custom workflows around local LLM interactions"],"limitations":["No documented conversation history persistence — chat history may be lost on extension reload or VS Code restart","Single-turn or limited multi-turn context — no documented mechanism to maintain conversation state across multiple queries","Panel positioning and UI customization options are not documented; layout may be fixed or limited","No documented support for file attachments, code snippets, or rich media in chat — likely text-only input/output","Model response streaming or chunking behavior is not documented; responses may appear as single blocks rather than progressive text"],"requires":["Visual Studio Code with Ollama Connection extension installed","Ollama instance running with an available model","Natural language input from the developer"],"input_types":["natural language text (free-form questions)","code snippets (if copy-pasted into chat, mechanism unknown)"],"output_types":["natural language text (model response)","code snippets (if model generates code in response)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-diegoomal-ollama-connection__cap_4","uri":"capability://tool.use.integration.ollama.connection.configuration.and.endpoint.management","name":"ollama-connection-configuration-and-endpoint-management","description":"Manages the connection between VS Code and the Ollama service by storing and validating connection parameters (host, port, API endpoint). The extension likely provides a settings or configuration interface where developers specify the Ollama instance location (localhost:11434 by default, or remote endpoints). This enables developers to connect to different Ollama deployments (local, remote, containerized) without modifying code or environment variables.","intents":["I want to configure the extension to connect to my Ollama instance running on a specific host and port","I need to switch between multiple Ollama deployments (local development, remote staging, etc.)","I want to verify that the extension can reach my Ollama service before using it"],"best_for":["developers managing multiple Ollama instances across different environments","teams deploying Ollama on remote servers or containerized infrastructure","solo developers setting up local Ollama for the first time"],"limitations":["No documented settings UI or configuration file format — mechanism for specifying connection parameters is unknown","No documented connection validation or health check — developers may not know if the extension can reach Ollama until attempting to use it","No support for authentication or API key management documented — assumes Ollama runs without authentication (typical for local deployments)","No documented support for TLS/SSL or secure connections — unclear if remote Ollama instances over HTTPS are supported","No fallback or retry logic documented — connection failures may result in silent failures or unclear error messages"],"requires":["Visual Studio Code with Ollama Connection extension","Ollama instance accessible at the configured endpoint (local or remote)","Network connectivity to the Ollama service"],"input_types":["configuration parameters (host, port, API endpoint)","connection credentials (if authentication is required, mechanism unknown)"],"output_types":["connection status (success/failure, mechanism unknown)","error messages (if connection fails)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":33,"verified":false,"data_access_risk":"moderate","permissions":["Visual Studio Code (minimum version unknown, likely 1.60+)","Ollama tool installed and running locally or on accessible network (https://ollama.ai)","At least one Ollama model pulled and available (e.g., llama2, mistral, neural-chat)","Visual Studio Code with Ollama Connection extension installed","Ollama instance running with a model capable of code understanding (e.g., mistral, neural-chat, or code-specific models)","Code to explain (selected text or open file in editor)","Visual Studio Code with Ollama Connection extension","Ollama instance running with a code-capable model (e.g., mistral, neural-chat, or code-specific models like starcoder if available)","Incomplete code in the editor (function signature, partial statement, etc.)","Ollama instance running with an available model"],"failure_modes":["Ollama instance must be running and accessible before extension can function — no fallback to cloud providers if local service is unavailable","Model inference latency depends entirely on local hardware; no optimization or caching layer documented to reduce response times","No documented support for model switching or selection within the extension — users must manage Ollama model lifecycle externally","Single-turn query pattern — no documented conversation history or multi-turn context management within the chatbot panel","No documented mechanism to inject explanations back into the editor as inline comments — output appears only in chatbot panel, requiring manual copy-paste","Model quality and accuracy depend entirely on Ollama model selection; smaller models may produce incomplete or inaccurate explanations","No context awareness of project structure, imports, or external dependencies — explanations are generated from code snippet alone","Explanation length and detail are not configurable; no documented way to request concise vs. detailed explanations","No documented inline suggestion display — completions appear in chatbot panel, not as autocomplete popups, requiring context switching","Latency of local model inference may make real-time completion impractical on slower hardware; no caching or optimization documented","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.45,"quality":0.2,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.118Z","last_scraped_at":"2026-05-03T15:20:33.198Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=ollama-connection","compare_url":"https://unfragile.ai/compare?artifact=ollama-connection"}},"signature":"ebIFmTirK/7gRtO44jeP6CdP84oQxV9fEYw8xcTF1EBTxztUYvALhMgEGpPi3Tb2sXqFrPXx+PTA/NDnB+g8CA==","signedAt":"2026-06-21T03:19:18.398Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/ollama-connection","artifact":"https://unfragile.ai/ollama-connection","verify":"https://unfragile.ai/api/v1/verify?slug=ollama-connection","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}