2. Config

[anthropic_api]
key = '...'

[openai_api]
api_key = '...'

Aware uses a global config .toml file for configuration. The file is provided during initial installation. For clarity, below is a set of configurations that can be modified according to your needs.

Models Configuration (Mandatory)

Aware 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	openai/text-embedding-large-3
Super-fast model	openai/gpt-4.1-nano
Fast chat model	openai/gpt-4.1-mini
Agentic-capable chat model	openai/gpt-5.1

---

Bedrock-Only Example

Role	Model
Embedding	bedrock/amazon.titan-embed-text-v2:0
Super-fast, low-cost model	bedrock/anthropic.claude-haiku-4-5-20251001-v1:0
Fast, non-reasoning chat model	bedrock/anthropic.claude-haiku-4-5-20251001-v1:0
Agentic-capable chat model	bedrock/global.anthropic.claude-sonnet-4-5-20250929-v1:0

Default Configuration

[anthropic_api]
key = '...'

[openai_api]
api_key = '...'

Bedrock Configuration

Environment variable that must be set 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.

Environment variable that must be set 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, there user data is not sent at all

• 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 = "..."