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CogOS can process multiple input formats, automatically converting them into text suitable for the CM agent.

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Auto-Detection

The simplest approach — auto_convert() handles format detection: 
from cogos.converters import auto_convert

text = auto_convert(any_data)  # handles str, list[dict], dict, JSON strings

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Available Converters

ConverterInput TypeDescription
PlainTextConverterstrPass-through with cleanup
MarkdownConverterstrMarkdown content / files
ChatHistoryConverterlist[dict]OpenAI message format
RAGConverterlist[dict]RAG chunks with metadata
JSONConverterdict / strArbitrary JSON data
auto_convert()anyAuto-detects format

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Chat History

Convert OpenAI-compatible message arrays: 
from cogos.converters import ChatHistoryConverter

messages = [
    {"role": "user", "content": "Hi, I'm Alice"},
    {"role": "assistant", "content": "Hello Alice!"},
]
text = ChatHistoryConverter().convert(messages)

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RAG Chunks

Convert retrieval-augmented generation chunks with metadata: 
from cogos.converters import RAGConverter

chunks = [
    {"text": "Important fact.", "metadata": {"source": "doc.md"}},
]
text = RAGConverter().convert(chunks)

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Custom Converters

Subclass InputConverter and implement convert(): 
from cogos.converters import InputConverter

class MyConverter(InputConverter):
    def can_handle(self, data) -> bool:
        return isinstance(data, MyCustomType)

    def convert(self, data) -> str:
        return str(data)