Feat/agentic search cosmos retriever - #148
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FastAPI service (POST /search, GET /health) wrapping CosmosRetriever, which runs a multi-turn retrieval agent over a Cosmos DB corpus. Pluggable inference backend: harmony_vllm (fine-tuned pat-jj/harness-1), openai_chat (any OpenAI-compatible chat model), or openai_responses (reasoning models such as gpt-5.4 on Azure AI Foundry). Includes tests for the server and agent loops. The .NET agentic_search tool calls this service over HTTP.
Add a 9th MCP tool, agentic_search, that runs the Cosmos Retriever agent over a Cosmos DB corpus and returns ranked, curated documents. - AgenticSearchExecutor: calls the cosmos-retriever service over HTTP (COSMOS_RETRIEVER_URL, COSMOS_RETRIEVER_TIMEOUT_S); always returns parseable JSON (error envelope on failure). - Wire into Program.cs, MCPProtocolController (tools/list + tools/call), MCPTestController, and McpToolRequestValidator. - CosmosClientFactory: exclude ManagedIdentityCredential (fall through to az login); accept the standard MCP _meta params field. - Docs: docs/AGENTIC_SEARCH.md, README + CHANGELOG + .env.example.
…rness - Move VllmTokenCompleter + run_single_episode into inference/vllm_policy.py - Delete inference/evaluate_harness1_vllm.py (eval/benchmark code) - Repoint retriever.py to vllm_policy; update env_rl docstring - Include pre-existing: pool_doc_ids trajectory pooling (openai_chat), optional baseten import (rerank)
…s to 1-50, de-brand harness references
The datagen/ package deletion was previously only staged, never committed, so it still appeared in the PR. Actually remove it (search_dataset.py, generate_sft_rl_splits.py, BrowseComp-Plus, README, __init__) along with the unit tests folder, the datagen TYPE_CHECKING import in tasks.py, the stale datagen comment in config.py, and the now-dangling pytest/respx dev deps and pytest/ruff test config in pyproject.toml.
…lResult Add a trajectory field to RetrievalResult populated by the harmony_vllm backend: the search queries issued (search_history), per-turn tool calls (turn_tools), programmatic per-turn status summaries (turn_summaries), and the final per-doc importance tags from curation (curated_importance).
…ed retrieval layer - Add schema-driven retrieval package (planner/compiler/executor/strategies/ document-resolvers) decoupled from physical Cosmos paths - Endpoint-only inference (OpenAI chat/responses); drop vLLM/RL runtime - Add foundry-harness and retrieval/agent benchmark scripts
…lt corpus profile); rename LegacyDunderCodec -> DunderChunkCodec
…ratch, endpoint-only backends
…loop.py and ChatSearchResult -> AgentSearchResult (both backends live there); keep backend-id strings
…undry Messages API); refresh backend docs/.env
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Superseded by #150, which adds cross-collection retrieval and live schema discovery on top of this work. |
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