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Complete MiniMax provider transport and model metadata #3

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9d059b4
Add MiniMax provider preset with global and China endpoints to LLMClient
octo-patch Jul 31, 2026
523e6b9
Add MiniMax Anthropic Messages transport
octo-patch Aug 11, 2026
e0a63f5
Add current MiniMax model metadata
octo-patch Aug 12, 2026
c513421
Fix MiniMax Anthropic request compatibility
octo-patch Aug 12, 2026
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19 changes: 14 additions & 5 deletions docs/api.md
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Expand Up @@ -167,30 +167,39 @@ from molecode.prompts import MARKUSH_SYSTEM_PROMPT # Markush + image→MoleC

## `molecode.llm`

An optional, dependency-free, OpenAI-compatible chat client. You supply the API
key and base URL — nothing is hard-coded.
An optional, dependency-free client for OpenAI Chat Completions and Anthropic
Messages. Supply a base URL directly or select a provider and region preset.

```python
class LLMClient(api_key=None, base_url=None, model=None, *, timeout=120.0, default_temperature=0.0)
class LLMClient(api_key=None, base_url=None, model=None, *, provider=None, region=None,
transport=None, timeout=120.0, default_temperature=0.0)
.chat(user, system=None, *, images=None, model=None, temperature=None, **extra) -> str
.complete(messages, *, model=None, temperature=None, **extra) -> str

call_llm(system, user, *, temperature=0.0, **client_kwargs) -> Optional[str]
image_to_data_uri(path_or_url: str) -> str
DEFAULT_MODEL # 'gemini-3.1-pro-preview'
DEFAULT_BASE_URL # 'https://api.openai.com/v1'
PROVIDER_PRESETS # regional OpenAI and Anthropic base URLs
PROVIDER_MODELS # provider defaults, supported model IDs, and model metadata
```

Credentials fall back to env vars `MOLECODE_API_KEY` / `OPENAI_API_KEY`,
`MOLECODE_BASE_URL`, `MOLECODE_MODEL`. Pass `images=[...]` (file paths or URLs) to
a vision model for OCSR (molecule image → MoleCode).
`MOLECODE_BASE_URL`, `MOLECODE_MODEL`, `MOLECODE_PROVIDER`, `MOLECODE_REGION`,
and `MOLECODE_TRANSPORT`. Anthropic transport also recognizes
`ANTHROPIC_API_KEY`, `ANTHROPIC_AUTH_TOKEN`, and `ANTHROPIC_BASE_URL`. Pass
`images=[...]` (file paths or URLs) to a vision model for OCSR (molecule image ->
MoleCode).

```python
from molecode import LLMClient
from molecode.prompts import MOLECULE_SYSTEM_PROMPT, MARKUSH_SYSTEM_PROMPT

client = LLMClient(api_key="sk-...", base_url="https://api.openai.com/v1", model="gpt-4o")

minimax = LLMClient(api_key="...", provider="minimax", region="global_en",
transport="anthropic", model="MiniMax-M3")

# text task
client.chat("How many carbons are in this molecule? ...", system=MOLECULE_SYSTEM_PROMPT)

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