{"id":9566,"library":"byllm","title":"byLLM Python Library","description":"byLLM (byllm) is a Python library providing a unified API for interacting with various Large Language Model (LLM) providers like OpenAI, Anthropic, Ollama, and Google Gemini. It simplifies LLM integration, abstracting away provider-specific client libraries and response formats. Currently at version 0.6.4, it is part of the Jaseci ecosystem and undergoes frequent updates, often alongside releases of `jaclang` and `jaseci` itself, targeting Python 3.11+.","status":"active","version":"0.6.4","language":"en","source_language":"en","source_url":"https://github.com/Jaseci-Labs/jaseci","tags":["LLM","AI","Jaseci","Jaclang","OpenAI","Anthropic","Ollama","Generative AI"],"install":[{"cmd":"pip install byllm","lang":"bash","label":"Install base library"},{"cmd":"pip install byllm[openai,anthropic,ollama]","lang":"bash","label":"Install with common providers"}],"dependencies":[{"reason":"Required for using the Anthropic LLM provider.","package":"anthropic","optional":true},{"reason":"Required for using the OpenAI LLM provider.","package":"openai","optional":true},{"reason":"Required for using the Ollama LLM provider.","package":"ollama","optional":true},{"reason":"Required for using the Cohere LLM provider.","package":"cohere","optional":true},{"reason":"Required for using the Google Generative AI LLM provider.","package":"google-generativeai","optional":true},{"reason":"Required for using the Together AI LLM provider.","package":"together","optional":true},{"reason":"Useful for loading environment variables (e.g., API keys).","package":"python-dotenv","optional":true}],"imports":[{"symbol":"OpenAI","correct":"from byllm.providers.openai import OpenAI"},{"symbol":"Anthropic","correct":"from byllm.providers.anthropic import Anthropic"},{"symbol":"Ollama","correct":"from byllm.providers.ollama import Ollama"},{"note":"Base class is in a submodule, not directly under `byllm`.","wrong":"from byllm import LLMProvider","symbol":"LLMProvider","correct":"from byllm.providers.llm_provider import LLMProvider"}],"quickstart":{"code":"import os\nfrom byllm.providers.openai import OpenAI\n\n# Set your OpenAI API key as an environment variable:\n# export OPENAI_API_KEY=\"your_key_here\"\nopenai_key = os.environ.get(\"OPENAI_API_KEY\")\n\nif not openai_key:\n    print(\"Warning: OPENAI_API_KEY environment variable not set. Requests will likely fail.\")\n    openai_key = \"sk-dummy\" # Use a dummy key to allow instantiation\n\ntry:\n    llm = OpenAI(api_key=openai_key, model_name=\"gpt-3.5-turbo\")\n\n    # Example: Generate text\n    prompt = \"What is the capital of France?\"\n    response = llm.generate(prompt=prompt, max_tokens=50)\n    print(f\"Generated text: {response.text}\\n\")\n\n    # Example: Chat completion\n    messages = [\n        {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n        {\"role\": \"user\", \"content\": \"Tell me a short story about a brave knight.\"}\n    ]\n    chat_response = llm.chat(messages=messages, max_tokens=100)\n    print(f\"Chat response: {chat_response.text}\\n\")\n\nexcept Exception as e:\n    print(f\"An error occurred: {e}\")\n    print(\"Please ensure your API key is correct and the model name is valid.\")","lang":"python","description":"This quickstart demonstrates how to initialize the OpenAI provider, generate text, and use chat completion. It emphasizes retrieving API keys from environment variables and includes basic error handling. Remember to install `byllm[openai]` for this example."},"warnings":[{"fix":"Always review the latest GitHub releases and documentation when upgrading. Pin exact versions of `byllm` in your `requirements.txt` to prevent unexpected breaking changes.","message":"As a pre-1.0.0 library (currently 0.6.4), `byllm`'s API and internal structure are subject to significant changes between minor versions. Upgrading without checking release notes might lead to `ImportError` or `AttributeError` for provider classes or method signatures.","severity":"breaking","affected_versions":"<1.0.0"},{"fix":"Use a dedicated virtual environment for `byllm` projects. If conflicts occur, try installing `byllm` with specific provider extras (e.g., `pip install byllm[openai]`) and resolve conflicts by carefully managing your `requirements.txt`.","message":"`byllm` relies on various upstream LLM client libraries (e.g., `openai`, `anthropic`). If your project uses other packages that require different versions of these underlying clients, dependency conflicts can arise, leading to unexpected behavior or `ImportError`s from the core client libraries.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Ensure the correct API key is set as an environment variable before running your application (e.g., `export OPENAI_API_KEY='your_secret_key'`). For development, consider using `python-dotenv` to load keys from a `.env` file.","message":"Most LLM providers require an API key for authentication. While `byllm` allows passing `api_key` directly, it primarily expects keys to be set as environment variables (e.g., `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`). Forgetting or misconfiguring these will result in authentication failures.","severity":"gotcha","affected_versions":"All versions"}],"env_vars":null,"last_verified":"2026-04-17T00:00:00.000Z","next_check":"2026-07-16T00:00:00.000Z","problems":[{"fix":"Verify your installed `byllm` version and consult the latest documentation or the `byllm/providers` directory in the source code for the correct import path. Ensure you've installed the necessary extra (e.g., `pip install byllm[openai]`).","cause":"The specific import path for a provider class has changed in a new `byllm` version, or the library/provider extra was not installed correctly.","error":"ModuleNotFoundError: No module named 'byllm.providers.openai'"},{"fix":"Set the correct API key as an environment variable (e.g., `export OPENAI_API_KEY='your_secret_key'`) or pass it directly to the provider's constructor (e.g., `OpenAI(api_key=\"your_secret_key\")`). Double-check for typos or expiration.","cause":"The required API key for the LLM provider (e.g., `OPENAI_API_KEY`) is missing, invalid, or incorrectly configured in environment variables or during `byllm` initialization.","error":"openai.AuthenticationError: Incorrect API key provided: ****"},{"fix":"Implement robust error handling around `generate` and `chat` calls. Check logs for underlying API errors, verify network connectivity, ensure correct model names and parameters are used. Check the LLM provider's status page for outages.","cause":"The LLM API call failed, but the `generate` or `chat` method returned `None` or an empty/malformed response object instead of raising an explicit error. This can be due to network issues, rate limits, an invalid model name, or an issue on the LLM provider's side.","error":"AttributeError: 'NoneType' object has no attribute 'text'"}]}