Configuration

[anthropic_api]
key = '...'

[openai_api]
api_key = '...'

The Context Engine uses a global config .toml file for configuration. You receive this file during initial installation. Below is a set of configurations that you can modify according to your needs.

Models configuration (required)

The Context Engine requires at least:

One embedding model
One chat model capable of agentic (multi-step) execution

Additional fast models can improve performance but are not required.

Model types

1. Embedding model (required)

Drives chunking and retrieval. May require tuning if replaced. Example: text-embedding-large-3

2. Super-fast model (optional)

A lightweight model for very quick operations. If not provided, the agentic model will handle these tasks, but indexing may become slower. Example: gpt-4.1-nano Recommendation: If no fast or super-fast model is available, it’s best to disable code description during indexing to avoid slowdowns.

[descriptor]
enabled = false

3. Fast chat model (optional)

Used for quick, non-reasoning tasks. If not provided, the agentic model can be used instead, with some performance impact. Example: gpt-4.1-mini

4. Agentic-capable chat model (required)

Runs the core agent workflows and multi-step reasoning. Example: claude-sonnet-4-5

Required models summary

Purpose	Model Example	Required
Embeddings	`text-embedding-large-3`	Yes
Agentic-capable chat	e.g.,`claude-sonnet-4-5`	Yes
Fast chat model	e.g.,`gpt-4.1-mini`	Optional
Super-fast model	e.g.,`gpt-4.1-nano`	Optional

Example model configurations

OpenAI-only example

Role	Model	Embedding
Embedding	`openai/text-embedding-large-3`	Yes
Super-fast model	`openai/gpt-4.1-nano`	Optional
Fast chat model	`openai/gpt-4.1-mini`	Optional
Agentic-capable chat model	`openai/gpt-5.1`	Yes

Bedrock-only example

Role	Model	Embedding
Embedding	`bedrock/amazon.titan-embed-text-v2:0`	Yes
Super-fast model	`bedrock/anthropic.claude-haiku-4-5-20251001-v1:0`	Optional
Fast chat model	`bedrock/anthropic.claude-haiku-4-5-20251001-v1:0`	Optional
Agentic-capable chat model	`bedrock/global.anthropic.claude-sonnet-4-5-20250929-v1:0`	Yes

Default configuration

[anthropic_api]
key = '...'

[openai_api]
api_key = '...'

Bedrock configuration

Set this environment variable to enable Bedrock routing:

AI_MODELS_FILE=ai_models_bedrock.py

[aws]
AWS_ACCESS_KEY_ID = "KEY_ID"
AWS_SECRET_ACCESS_KEY = "SECRET"
AWS_REGION_NAME = "us-east-1"

[deep_ask_research_preview]
llm_model = "bedrock/global.anthropic.claude-sonnet-4-5-20250929-v1:0"

LLM gateway support

Our product supports integration with custom LLM gateways, provided they implement the same API interfaces as the official OpenAI or Anthropic model endpoints. Set this environment variable in all deployments to enable LLM gateway routing:

AI_MODELS_FILE=ai_models_onprem.py

[onprem_models]
[onprem_models.lite]
api_base = "<INSERT_GATEWAY_BASE_URL_HERE>"
[onprem_models.main]
api_base = "<INSERT_GATEWAY_BASE_URL_HERE>"
[onprem_models.remote_rag]
api_base = "<INSERT_GATEWAY_BASE_URL_HERE>"

[deep_ask_research_preview]
llm_base_url = "<INSERT_GATEWAY_BASE_URL_HERE>"

If you have unique integration needs, please reach out to the Qodo team.

Monitoring config (recommended)

Sentry - We use Sentry for error tracking. When enabled, we only emit code crashes and traces.
Mixpanel - Used for analytics only. No user data is sent.
CLIENT_DISPLAY_NAME - Name of your org e.g. "qodo_ai" used as identifier for the above tools

CLIENT_DISPLAY_NAME = "N/A"


[sentry]
dsn = "..."
environment = "PRODUCTION"


[mixpanel]
token = "..."
api_secret = "..."

Core concepts

Onboard Qodo for admins

Git providers

Integrations

Pricing, deployment & support

Models configuration (required)

Model types

1. Embedding model (required)

2. Super-fast model (optional)

3. Fast chat model (optional)

4. Agentic-capable chat model (required)

Required models summary

Example model configurations

OpenAI-only example

Bedrock-only example

Default configuration

Bedrock configuration

LLM gateway support

Monitoring config (recommended)

​Models configuration (required)

​Model types

​1. Embedding model (required)

​2. Super-fast model (optional)

​3. Fast chat model (optional)

​4. Agentic-capable chat model (required)

​Required models summary

​Example model configurations

​OpenAI-only example

​Bedrock-only example

​Default configuration

​Bedrock configuration

​LLM gateway support

​Monitoring config (recommended)

Models configuration (required)

Model types

1. Embedding model (required)

2. Super-fast model (optional)

3. Fast chat model (optional)

4. Agentic-capable chat model (required)

Required models summary

Example model configurations

OpenAI-only example

Bedrock-only example

Default configuration

Bedrock configuration

LLM gateway support

Monitoring config (recommended)