# fenic 0.7.0: Gemini 3 Flash, Granular Thinking Levels — plus session and docs improvements

> fenic 0.7.0 adds Gemini 3 Flash Preview with four thinking levels, optional usage summary suppression, and a use-case-first README overhaul.

Published 2025-12-19 · By Kostas Pardalis
Source: https://fenic.ai/blog/fenic-0-7-0-gemini-3-flash-granular-thinking-levels-plus-session-and-docs-improvements

---

fenic 0.7.0 adds Google's latest Gemini 3 Flash Preview with granular thinking-level control, quality-of-life improvements for session management, and a repositioned README centered on use cases and context engineering for agents.

## What's in it for you

- **Gemini 3 Flash Preview** support with four thinking levels (`high`, `medium`, `low`, `minimal`) — fine-tune cost/quality tradeoffs per call.
- **Refined thinking-level API** with per-model validation and auto-created profiles for every supported level.
- **Optional usage summary suppression** via `session.stop(skip_usage_summary=True)` for automated environments and testing.
- **Use-case-first README** restructured around what you can build, not library internals.

## Gemini 3 Flash Preview with granular thinking levels

Gemini 3 Flash Preview joins the previously added Gemini 3 Pro Preview. The thinking-level API now supports four distinct levels — `high`, `medium`, `low`, and `minimal` — with per-model validation. Gemini 3 Flash supports all four; Gemini 3 Pro supports `high` and `low`.

fenic auto-creates profiles for every supported thinking level, so switching between cost and quality tradeoffs is a one-line change.

```python
from fenic.api.session.config import GoogleDeveloperLanguageModel

config = SessionConfig(
    semantic=SemanticConfig(
        language_models={
            "gemini-flash": GoogleDeveloperLanguageModel(
                model_name="gemini-3-flash-preview",
                rpm=100,
                tpm=1000,
            )
        }
    )
)

# Auto-created profiles: "high", "medium", "low", "minimal"
df.semantic.extract(
    "content",
    schema=MySchema,
    model=ModelAlias(name="gemini-flash", profile="low")
)
```

Attempting to use an unsupported thinking level now raises a clear error indicating which levels are available for the given model.

## Optional usage summary suppression

`Session.stop()` now accepts `skip_usage_summary` to suppress the default usage summary printout. Useful for automated environments, CI pipelines, or applications that handle metrics reporting separately.

```python
session.stop(skip_usage_summary=True)
```

Works consistently across both local and cloud backends.

## README overhaul

The README has been restructured around **declarative context engineering for agents**. Instead of leading with library internals, it highlights what you can build:

- Memory and personalization pipelines
- Retrieval and knowledge systems
- Context operations (chunking, parsing, embedding)
- Structured context from raw data

Long reference sections are collapsed behind expandable `<details>` blocks for scannability.

## Bug fixes

- **Removed `gpt-5.1-codex`** from the model catalog — fenic does not currently support the responses API required by this model.
- **Cloud session respects `skip_usage_summary`** — the cloud backend now correctly honors this parameter, matching local backend behavior.
- **Fixed module shadowing** — `examples/mcp/` renamed to `examples/mcp_server/` to prevent shadowing the `mcp` Python module.

## Upgrading from v0.6.x

- `CompletionModelParameters.supports_thinking_level` (bool) has been replaced by `supported_thinking_levels` (optional set of thinking level strings). Code that directly accesses model parameter internals will need to be updated.
- Updated `google-genai` dependency and `fastmcp` to v2.13.0 (security fix).

## Try it out and tell us what you build

```bash
pip install --upgrade fenic
```

Read the latest docs at [docs.fenic.ai](https://docs.fenic.ai). Questions or ideas — file an issue with a small reproduction case.