Package index
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chat_azure() - Chat with a model hosted on Azure OpenAI
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chat_bedrock() - Chat with an AWS bedrock model
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chat_claude() - Chat with an Anthropic Claude model
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chat_cortex() - Create a chatbot that speaks to the Snowflake Cortex Analyst
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chat_databricks() - Chat with a model hosted on Databricks
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chat_gemini() - Chat with a Google Gemini model
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chat_github() - Chat with a model hosted on the GitHub model marketplace
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chat_groq() - Chat with a model hosted on Groq
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chat_ollama() - Chat with a local Ollama model
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chat_openai() - Chat with an OpenAI model
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chat_perplexity() - Chat with a model hosted on perplexity.ai
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chat_vllm() - Chat with a model hosted by vLLM
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token_usage() - Report on token usage in the current session
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create_tool_def() - Create metadata for a tool
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content_image_url()content_image_file()content_image_plot() - Encode image content for chat input
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live_console()live_browser() - Open a live chat application
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interpolate()interpolate_file() - Helpers for interpolating data into prompts
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tool() - Define a tool
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type_boolean()type_integer()type_number()type_string()type_enum()type_array()type_object() - Type specifications
Objects
These classes abstact across behaviour differences in chat providers so that for typical ellmer use you don’t need to worry about them. You’ll need to learn more about the objects if you’re doing something that’s only supported by one provider, or if you’re implementing a new provider.
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Turn() - A user or assistant turn
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Provider() - A chatbot provider
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Content()ContentText()ContentImage()ContentImageRemote()ContentImageInline()ContentToolRequest()ContentToolResult() - Content types received from and sent to a chatbot
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Chat - A chat
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TypeBasic()TypeEnum()TypeArray()TypeObject() - Type definitions for function calling and structured data extraction.
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contents_text()contents_html()contents_markdown() - Format contents into a textual representation