[I] [Feature] Add LiteLLM Router SDK integration for model routing and failover [flink-agents]

["wenjin272 (via GitHub)" <gi...@apache.org>]

wenjin272 opened a new issue, #1324:
URL: https://github.com/apache/flink-agents/issues/1324

   ### Search before asking
   
   - [x] I searched in the [issues](https://github.com/apache/flink-agents/issues) and found nothing similar.
   
   ### Description
   
   Add an optional integration with the **LiteLLM Python Router SDK**, allowing Flink Agents to use multiple model deployments, retries, fallbacks, and routing strategies without running a separate LiteLLM Proxy service.
   
   **Target:** the next release, subject to community agreement and implementation readiness.
   
   #### Motivation
   
   Model rate limits and transient failures can interrupt agent execution. Applications may need to retry a request, switch to another model or deployment, or select a backend based on latency or available capacity. LiteLLM Router provides these capabilities, but Flink Agents currently requires a custom adapter to use it in process.
   
   #### Proposed integration
   
   Reuse the existing Connection / Setup resource model; the names below are illustrative:
   
   - **LiteLLM Router Connection:** declare `model_list`, routing strategy and arguments, retry/timeout settings, fallback chains, and optional Redis-backed shared state.
   - **Chat Model Setup:** reference the connection and a logical model group, together with the existing prompt, tools, skills, and generation settings.
   - **Invocation:** keep the existing chat APIs and tool execution flow. The connection delegates model requests to `litellm.Router` and converts the result to `ChatResult`.
   
   Carry serializable configuration in the resource descriptor and create/reuse/close the live Router at runtime. Custom routing strategies should be declared through an importable class path and arguments rather than a live Router or closure in the job plan.
   
   This complements Flink Agents' existing `MODEL_ROUTER`: framework routing can select a business-level model/setup, while LiteLLM routes requests among backend deployments. Using LiteLLM should not require a `MODEL_ROUTER` resource.
   
   #### Acceptance criteria
   
   - [ ] Provide an optional Python integration and a documented resource declaration API, including built-in routing strategies and a custom strategy example.
   - [ ] Support multiple deployments, rate-limit retries, timeout handling, and cross-model fallback through LiteLLM Router.
   - [ ] Preserve messages, tool calls/results, finish reasons, usage, and actual backend model information where available; define and test structured-output behavior across fallback models.
   - [ ] Define Router lifecycle, concurrent use, and recovery behavior within the framework's existing durable model-call path. Document retry ownership and how parallel instances share quota/cooldown state.
   - [ ] Add deterministic tests for 429 retry, timeout/fallback, exhausted candidates, tool calls, and runtime reconstruction, without requiring live provider credentials.
   - [ ] Document dependencies and Python/Java cross-language support boundaries, and provide a Bailian example using a primary and backup model.
   
   #### References
   
   - [LiteLLM Router](https://docs.litellm.ai/docs/routing)
   - [LangChain ChatLiteLLMRouter](https://docs.langchain.com/oss/python/integrations/chat/litellm)
   - [smolagents LiteLLMRouterModel](https://huggingface.co/docs/smolagents/reference/models#smolagents.LiteLLMRouterModel)
   
   ### Are you willing to submit a PR?
   
   - [ ] I'm willing to submit a PR!
   
   


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Re: [I] [Feature] Add LiteLLM Router SDK integration for model routing and failover [flink-agents]

["noorall (via GitHub)" <gi...@apache.org>]

noorall commented on issue #1324:
URL: https://github.com/apache/flink-agents/issues/1324#issuecomment-6361976441

   Hi @wenjin272 , I’d like to work on this issue. Could you please assign it to me?


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