- Enhanced OpenCode provider configuration with detailed pricing for various models.
- Updated agent settings to reflect new model assignments and pricing structures.
- Revised testing report to include updated performance metrics and average latencies for agents.
- Adjusted overall success rates and latencies in the report for improved accuracy.
- Added OpenCode provider configuration file with model settings and parameters.
- Updated README to include OpenCode as a supported provider and modified relevant sections for clarity.
- Created a testing report for OpenCode, summarizing agent performance and success rates.
- Enhanced VSCode launch configuration to include OpenCode provider options for testing.
- Updated the README to include xAI as a supported provider, along with pre-configured provider files for testing.
- Added a new configuration file for xAI with detailed model settings and pricing.
- Created a testing report for xAI, summarizing the performance and success rates of various agents.
- Enhanced the VSCode launch configuration to include xAI provider options for testing.
- Replaced all instances of `Qwen3-Coder-Next-FP8` with `MiniMax-M2.7` in the hcnsec provider configuration, adjusting model settings and pricing accordingly.
- Updated the test report to reflect the new model configurations, including success rates and average latencies for various agents using `MiniMax-M2.7`.
- Enhanced the overall structure of the configuration file for clarity and consistency.
- Added new configuration options in `.vscode/launch.json` for vllm and hcnsec providers.
- Updated `deepinfra.provider.yml` to reflect changes in model configurations and pricing.
- Introduced `hcnsec.provider.yml` with detailed model settings and pricing for HCNSec.
- Adjusted various test reports to reflect updated success rates and latencies for different models.
Reworks PR #233 to follow the existing config-path pattern and make an
externally-added Bedrock model fully usable from the web UI.
- BEDROCK_CONFIG_PATH: replace the embedded per-agent config (model
assignments + prices), mirroring OLLAMA_SERVER_CONFIG_PATH /
LLM_SERVER_CONFIG_PATH. DefaultProviderConfig now takes *config.Config
and reads the external file when set, else the embedded config.yml.
- BEDROCK_MODELS_PATH: merge an external model catalog onto the embedded
models.yml so new ids appear and are selectable under Settings ->
Providers. DefaultModels now takes *config.Config and the resolver +
provider construction pass it through; new ids are added, a matching
name overrides the embedded entry.
Wires both through docker-compose, .env.example, config.md and the README,
and ships examples/configs/bedrock-glm-flash.{provider,models}.yml using the
real AWS Bedrock id zai.glm-4.7-flash (In-Region, no inference-profile
prefix, 4K max output).
Dropped from #233: the ProviderConfig.Name field and the SeedDefaultProviders
mechanism (a per-user DB write fired on startup and inside the read-only
SettingsProviders resolver) -- the config already reaches the UI through
DefaultProvidersConfig without any DB rows.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Reworks PR #332 to follow the repo's provider-doc convention instead of
its README-marketing form:
- add examples/configs/atlas.provider.yml, modeled on the existing
aggregator example configs (deepinfra/openrouter/novita)
- list Atlas Cloud in the README aggregators line
- LLM_SERVER_PROVIDER left EMPTY for direct access — it is a LiteLLM
model-name prefix, and #332 incorrectly recommended `openai`, which
would break /models discovery for Atlas's vendor-prefixed model ids
Dropped from #332 (not matching any existing aggregator's docs): vendor
logo/banner, UTM-tracked links, and the static 59-model table.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
DeepSeek V4 thinking mode defaults to enabled on both deepseek-v4-flash
and deepseek-v4-pro; non-thinking behavior requires an explicit toggle.
Per official docs, in thinking mode temperature/top_p/presence_penalty/
frequency_penalty are ignored, so the existing Flash role sampling knobs
would have been silently no-ops without the toggle.
Add extra_body.thinking.type=disabled to the five non-thinking Flash
roles so deepseek-v4-flash actually runs in non-thinking mode and
honors the role's temperature/top_p settings:
- simple, simple_json, adviser, searcher, enricher
Pro roles (primary_agent, assistant, generator, refiner, reflector,
coder, installer, pentester) intentionally keep thinking enabled (the
V4 default) for reasoning, tool-use, and security analysis.
PentAGI provider config already supports extra_body as a first-class
yaml field on AgentConfig and forwards it through openai.WithExtraBody,
which the vxcontrol langchaingo fork serializes at the top level of the
Chat Completions request - the same pattern Kimi uses for tool_choice.
No code, schema, or LiteLLM prefix changes required.
Touches:
- backend/pkg/providers/deepseek/config.yml (embedded production config)
- examples/configs/deepseek.provider.yml (user-facing example)
No change to role-to-model mapping, model metadata, pricing, README
wording, LiteLLM prefix, unrelated providers, lifecycle, queues, or
installer flow.
- Update model descriptions to reflect V4 1M context window (up to 384K output)
instead of legacy 128K wording in models.yml and README.
- Split Flash and Pro pricing per official DeepSeek API docs:
- deepseek-v4-flash: input 0.14 / output 0.28 / cache_hit 0.0028 per 1M tokens
- deepseek-v4-pro: input 0.435 / output 0.87 / cache_hit 0.003625 per 1M tokens
- Apply per-role price split across all 13 role configs in both the embedded
config.yml and the user-facing examples/configs/deepseek.provider.yml.
- Replace stale "cache pricing is 10% of input cost" claim in the README,
which no longer holds for either V4 model.
- No change to LiteLLM prefix behavior, role-to-model mapping, lifecycle,
queues, GraphQL schema, migrations, frontend, or installer flow.
The DeepSeek provider config still defaulted to the legacy
`deepseek-chat` and `deepseek-reasoner` model names, which the
upstream DeepSeek API has announced for deprecation on 2026-07-24.
A first-run install therefore breaks once the legacy names are
removed.
Swap the defaults to the current DeepSeek V4 family:
- non-thinking roles use `deepseek-v4-flash`
- reasoning-heavy roles use `deepseek-v4-pro`
The change is limited to the embedded `config.yml` / `models.yml`
inside `backend/pkg/providers/deepseek`, the matching example at
`examples/configs/deepseek.provider.yml`, the `DeepSeekAgentModel`
fallback constant in `deepseek.go`, and three doc references
(README.md, backend/docs/config.md, backend/docs/llms_how_to.md)
plus one installer help string in
`backend/cmd/installer/wizard/locale/locale.go`. LiteLLM prefix
behavior is untouched.
- Included two new provider YAML files for Qwen 3.6 35B models: `vllm-qwen3.6-35b-a3b-fp8-no-think.provider.yml` and `vllm-qwen3.6-35b-a3b-fp8.provider.yml`.
- Updated Dockerfile to copy the new configuration files into the appropriate directory.
- Added new provider configurations for vLLM Qwen 3.6 in both thinking and non-thinking modes.
- Updated the Dockerfile to include the new configuration files for vLLM Qwen 3.6 and ensure proper setup for deployment.
Dmitry Ng