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Overview

KnowledgeBase can process raw text strings directly — no file on disk required. This is useful for ingesting API responses, user input, database records, or any text content you already have in memory. String content is automatically detected and doesn’t need a loader.

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String Content as Source

Pass text strings directly in sources: 
from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode

embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())
vectordb = ChromaProvider(ChromaConfig(
    collection_name="text_kb",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))

company_policy = """
Remote Work Policy:
- Employees may work remotely up to 3 days per week.
- Core hours are 10:00 AM to 3:00 PM in the employee's local timezone.
- All remote workers must be available on Slack during core hours.
- VPN is required when accessing company resources from home.
- Equipment stipend of $1,000 per year is available for home office setup.
"""

kb = KnowledgeBase(
    sources=[company_policy],
    embedding_provider=embedding,
    vectordb=vectordb
)

agent = Agent("anthropic/claude-sonnet-4-5")
task = Task(
    description="What is the equipment stipend for home office?",
    context=[kb]
)

result = agent.do(task)
print(result)

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Mixed Sources (Files + Text)

Combine file paths, directories, and string content in a single KnowledgeBase: 
from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode

embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())
vectordb = ChromaProvider(ChromaConfig(
    collection_name="mixed_kb",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))

changelog_text = """
v2.5.0 Release Notes:
- Added support for PostgreSQL 16
- Fixed memory leak in connection pooling
- Improved query performance by 40%
- Deprecated legacy auth endpoints (removal in v3.0)
"""

kb = KnowledgeBase(
    sources=[
        "docs/architecture.md",           # File — needs loader
        changelog_text,                     # String — no loader needed
        "config/"                           # Directory — files inside need loaders
    ],
    embedding_provider=embedding,
    vectordb=vectordb
)

agent = Agent("anthropic/claude-sonnet-4-5")
task = Task(
    description="What was improved in the latest release and how does it relate to the architecture?",
    context=[kb]
)

result = agent.do(task)
print(result)

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Adding Text After Setup

Use add_text() to insert raw text into an already-initialized knowledge base: 
from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode

embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())
vectordb = ChromaProvider(ChromaConfig(
    collection_name="dynamic_kb",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))

kb = KnowledgeBase(
    sources=["handbook.pdf"],
    embedding_provider=embedding,
    vectordb=vectordb
)

# Add text content after initial setup
kb.add_text(
    text="New policy: All meetings over 30 minutes require an agenda shared 24 hours in advance.",
    document_name="meeting_policy_update",
    metadata={"category": "policy", "effective_date": "2025-01-15"}
)

agent = Agent("anthropic/claude-sonnet-4-5")
task = Task(
    description="What are the meeting policies?",
    context=[kb]
)

result = agent.do(task)
print(result)

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How Detection Works

KnowledgeBase classifies a string as direct content (not a file path) when:
  • It contains newlines
  • It’s longer than 200 characters
  • It has more than 5 words without file-like patterns
  • It doesn’t match any file on disk
This means short strings that look like file paths (e.g., "report.pdf") are treated as file paths, while longer text blocks are treated as content.