fleet-memory/hindsight-docs/versioned_docs/version-0.3/developer/api/opinions.mdx
Nicolò Boschi 522b71aab8
doc: mental models (#199)
* doc: mental models

* doc: mental models
2026-01-26 14:27:08 +01:00

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Text

---
sidebar_position: 5
---
# Opinions
How memory banks form, store, and evolve beliefs.
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
import CodeSnippet from '@site/src/components/CodeSnippet';
{/* Import raw source files */}
import opinionsPy from '!!raw-loader!@site/examples/api/legacy/opinions.py';
import opinionsMjs from '!!raw-loader!@site/examples/api/legacy/opinions.mjs';
:::tip Prerequisites
Make sure you've completed the [Quick Start](./quickstart) to install the client and start the server.
:::
## What Are Opinions?
Opinions are beliefs formed by the memory bank based on evidence and disposition. Unlike world facts (objective information received) or experience (conversations and events), opinions are **judgments** with confidence scores.
| Type | Example | Confidence |
|------|---------|------------|
| World Fact | "Python was created in 1991" | — |
| Experience | "I recommended Python to Bob" | — |
| Opinion | "Python is the best language for data science" | 0.85 |
## How Opinions Form
Opinions are created during `reflect` operations when the memory bank:
1. Retrieves relevant facts
2. Applies disposition traits
3. Forms a judgment
4. Assigns a confidence score
```mermaid
graph LR
F[Facts] --> D[Disposition Filter]
D --> J[Judgment]
J --> O[Opinion + Confidence]
O --> S[(Store)]
```
<Tabs>
<TabItem value="python" label="Python">
<CodeSnippet code={opinionsPy} section="opinion-form" language="python" />
</TabItem>
<TabItem value="node" label="Node.js">
<CodeSnippet code={opinionsMjs} section="opinion-form" language="javascript" />
</TabItem>
</Tabs>
## Searching Opinions
<Tabs>
<TabItem value="python" label="Python">
<CodeSnippet code={opinionsPy} section="opinion-search" language="python" />
</TabItem>
<TabItem value="node" label="Node.js">
<CodeSnippet code={opinionsMjs} section="opinion-search" language="javascript" />
</TabItem>
<TabItem value="cli" label="CLI">
```bash
hindsight recall my-bank "programming" --types opinion
```
</TabItem>
</Tabs>
## Opinion Evolution
Opinions change as new evidence arrives:
| Evidence Type | Effect |
|---------------|--------|
| **Reinforcing** | Confidence increases (+0.1) |
| **Weakening** | Confidence decreases (-0.15) |
| **Contradicting** | Opinion revised, confidence reset |
**Example evolution:**
```
t=0: "Python is best for data science" (0.70)
↓ New evidence: Python dominates ML libraries
t=1: "Python is best for data science" (0.85)
↓ New evidence: Julia is 10x faster for numerical computing
t=2: "Python is best for data science, though Julia is faster" (0.75)
↓ New evidence: Most teams still use Python
t=3: "Python is best for data science" (0.82)
```
## Disposition Influence
Different dispositions form different opinions from the same facts:
<Tabs>
<TabItem value="python" label="Python">
<CodeSnippet code={opinionsPy} section="opinion-disposition" language="python" />
</TabItem>
<TabItem value="node" label="Node.js">
<CodeSnippet code={opinionsMjs} section="opinion-disposition" language="javascript" />
</TabItem>
</Tabs>
## Opinions in Reflect Responses
When `reflect` uses opinions, they appear in `based_on`:
<Tabs>
<TabItem value="python" label="Python">
<CodeSnippet code={opinionsPy} section="opinion-in-reflect" language="python" />
</TabItem>
<TabItem value="node" label="Node.js">
<CodeSnippet code={opinionsMjs} section="opinion-in-reflect" language="javascript" />
</TabItem>
</Tabs>
## Confidence Thresholds
Opinions below a confidence threshold may be:
- Excluded from responses
- Marked as uncertain
- Revised more easily
```python
# Low confidence opinions are held loosely
# "I think Python might be good for this" (0.45)
# High confidence opinions are stated firmly
# "Python is definitely the right choice" (0.92)
```