diff --git a/pyproject.toml b/pyproject.toml
index 0bd8a5bc..9a2dfcd9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -61,7 +61,7 @@ dependencies = [
     "html2text>=2024.2.26",
     "langchain>=0.2.0",
     "langchain-text-splitters>=0.0.1",
-    "chromadb>=0.4.24",
+    "chromadb>=1.0.0,<2.0.0",
     "qdrant-client (>=1.15.1,<2.0.0)",
     "pyseekdb==1.1.0.post3",
     "langbot-plugin==0.3.0",
diff --git a/src/langbot/pkg/vector/vdbs/chroma.py b/src/langbot/pkg/vector/vdbs/chroma.py
index 6cefce13..738e347a 100644
--- a/src/langbot/pkg/vector/vdbs/chroma.py
+++ b/src/langbot/pkg/vector/vdbs/chroma.py
@@ -2,11 +2,14 @@ from __future__ import annotations
 import asyncio
 from typing import Any
 from chromadb import PersistentClient
-from langbot.pkg.vector.vdb import VectorDatabase
+from langbot.pkg.vector.vdb import VectorDatabase, SearchType
 from langbot.pkg.core import app
 import chromadb
 import chromadb.errors
 
+# RRF smoothing constant (standard value from the literature)
+_RRF_K = 60
+
 
 class ChromaVectorDatabase(VectorDatabase):
     def __init__(self, ap: app.Application, base_path: str = './data/chroma'):
@@ -14,6 +17,10 @@ class ChromaVectorDatabase(VectorDatabase):
         self.client = PersistentClient(path=base_path)
         self._collections = {}
 
+    @classmethod
+    def supported_search_types(cls) -> list[SearchType]:
+        return [SearchType.VECTOR, SearchType.FULL_TEXT, SearchType.HYBRID]
+
     async def get_or_create_collection(self, collection: str) -> chromadb.Collection:
         if collection not in self._collections:
             self._collections[collection] = await asyncio.to_thread(
@@ -34,8 +41,8 @@ class ChromaVectorDatabase(VectorDatabase):
         kwargs: dict[str, Any] = dict(embeddings=embeddings_list, ids=ids, metadatas=metadatas)
         if documents is not None:
             kwargs['documents'] = documents
-        await asyncio.to_thread(col.add, **kwargs)
-        self.ap.logger.info(f"Added {len(ids)} embeddings to Chroma collection '{collection}'.")
+        await asyncio.to_thread(col.upsert, **kwargs)
+        self.ap.logger.info(f"Upserted {len(ids)} embeddings to Chroma collection '{collection}'.")
 
     async def search(
         self,
@@ -47,6 +54,23 @@ class ChromaVectorDatabase(VectorDatabase):
         filter: dict[str, Any] | None = None,
     ) -> dict[str, Any]:
         col = await self.get_or_create_collection(collection)
+
+        if search_type == SearchType.FULL_TEXT:
+            return await self._full_text_search(col, collection, k, query_text, filter)
+        elif search_type == SearchType.HYBRID:
+            return await self._hybrid_search(col, collection, query_embedding, k, query_text, filter)
+
+        # Default: vector search
+        return await self._vector_search(col, collection, query_embedding, k, filter)
+
+    async def _vector_search(
+        self,
+        col: chromadb.Collection,
+        collection: str,
+        query_embedding: list[float],
+        k: int,
+        filter: dict[str, Any] | None,
+    ) -> dict[str, Any]:
         query_kwargs: dict[str, Any] = dict(
             query_embeddings=query_embedding,
             n_results=k,
@@ -55,9 +79,137 @@ class ChromaVectorDatabase(VectorDatabase):
         if filter:
             query_kwargs['where'] = filter
         results = await asyncio.to_thread(col.query, **query_kwargs)
-        self.ap.logger.info(f"Chroma search in '{collection}' returned {len(results.get('ids', [[]])[0])} results.")
+        self.ap.logger.info(f"Chroma vector search in '{collection}' returned {len(results.get('ids', [[]])[0])} results.")
         return results
 
+    async def _full_text_search(
+        self,
+        col: chromadb.Collection,
+        collection: str,
+        k: int,
+        query_text: str,
+        filter: dict[str, Any] | None,
+    ) -> dict[str, Any]:
+        if not query_text:
+            return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
+
+        get_kwargs: dict[str, Any] = dict(
+            where_document={'$contains': query_text},
+            include=['metadatas', 'documents'],
+            limit=k,
+        )
+        if filter:
+            get_kwargs['where'] = filter
+        results = await asyncio.to_thread(col.get, **get_kwargs)
+
+        # col.get returns flat lists; wrap into column-major format.
+        # Distances are all 0.0 because Chroma's local $contains is a boolean
+        # filter with no relevance scoring.  Chroma's BM25 sparse embedding
+        # function (ChromaBm25EmbeddingFunction) can generate scored sparse
+        # vectors, but sparse vector *indexing* is only available on Chroma
+        # Cloud, not locally.  For ranked results, use hybrid mode or apply a
+        # reranker in a downstream stage.
+        ids = results.get('ids', [])
+        metadatas = results.get('metadatas', []) or [None] * len(ids)
+        documents = results.get('documents', []) or [None] * len(ids)
+        distances = [0.0] * len(ids)
+
+        self.ap.logger.info(f"Chroma full-text search in '{collection}' returned {len(ids)} results.")
+        return {'ids': [ids], 'metadatas': [metadatas], 'distances': [distances], 'documents': [documents]}
+
+    async def _hybrid_search(
+        self,
+        col: chromadb.Collection,
+        collection: str,
+        query_embedding: list[float],
+        k: int,
+        query_text: str,
+        filter: dict[str, Any] | None,
+    ) -> dict[str, Any]:
+        # Fall back to pure vector search when no text is provided
+        if not query_text:
+            return await self._vector_search(col, collection, query_embedding, k, filter)
+
+        # Run vector search and full-text search in parallel
+        vector_task = self._vector_search(col, collection, query_embedding, k, filter)
+        text_task = self._full_text_search(col, collection, k, query_text, filter)
+        vector_results, text_results = await asyncio.gather(vector_task, text_task)
+
+        vector_ids = vector_results.get('ids', [[]])[0]
+        text_ids = text_results.get('ids', [[]])[0]
+
+        if not vector_ids and not text_ids:
+            return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
+
+        # RRF fusion
+        fused = self._rrf_fuse([vector_ids, text_ids], k)
+        if not fused:
+            return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
+
+        fused_ids = [doc_id for doc_id, _ in fused]
+
+        # Fetch full metadata and documents for fused results
+        fetched = await asyncio.to_thread(
+            col.get, ids=fused_ids, include=['metadatas', 'documents']
+        )
+
+        # col.get returns results in arbitrary order; re-order to match fused ranking
+        fetched_map: dict[str, tuple] = {}
+        for i, fid in enumerate(fetched.get('ids', [])):
+            meta = (fetched.get('metadatas') or [None] * len(fetched['ids']))[i]
+            doc = (fetched.get('documents') or [None] * len(fetched['ids']))[i]
+            fetched_map[fid] = (meta, doc)
+
+        ordered_ids = []
+        ordered_metas = []
+        ordered_docs = []
+        ordered_dists = []
+
+        # Normalize RRF scores to 0~1 distances via min-max scaling.
+        # Raw RRF scores are tiny (e.g. 0.016~0.033 with k=60) so a naive
+        # ``1 - score`` would compress all distances into a narrow 0.96~0.98
+        # band with almost no discriminative power.  Min-max normalization
+        # spreads them across the full 0~1 range (0.0 = best match).
+        max_score = fused[0][1]
+        min_score = fused[-1][1]
+        score_range = max_score - min_score
+
+        for doc_id, score in fused:
+            if doc_id in fetched_map:
+                meta, doc = fetched_map[doc_id]
+                ordered_ids.append(doc_id)
+                ordered_metas.append(meta)
+                ordered_docs.append(doc)
+                if score_range > 0:
+                    ordered_dists.append(1.0 - (score - min_score) / score_range)
+                else:
+                    ordered_dists.append(0.0)
+
+        self.ap.logger.info(
+            f"Chroma hybrid search in '{collection}' returned {len(ordered_ids)} results "
+            f"(vector={len(vector_ids)}, text={len(text_ids)})."
+        )
+        return {
+            'ids': [ordered_ids],
+            'metadatas': [ordered_metas],
+            'distances': [ordered_dists],
+            'documents': [ordered_docs],
+        }
+
+    @staticmethod
+    def _rrf_fuse(result_lists: list[list[str]], k: int) -> list[tuple[str, float]]:
+        """Reciprocal Rank Fusion over multiple ranked ID lists.
+
+        Returns a list of (doc_id, rrf_score) sorted by descending score,
+        truncated to *k* entries.
+        """
+        scores: dict[str, float] = {}
+        for ranked_ids in result_lists:
+            for rank, doc_id in enumerate(ranked_ids):
+                scores[doc_id] = scores.get(doc_id, 0.0) + 1.0 / (_RRF_K + rank + 1)
+        sorted_results = sorted(scores.items(), key=lambda x: x[1], reverse=True)
+        return sorted_results[:k]
+
     async def delete_by_file_id(self, collection: str, file_id: str) -> None:
         col = await self.get_or_create_collection(collection)
         await asyncio.to_thread(col.delete, where={'file_id': file_id})
diff --git a/uv.lock b/uv.lock
index 3c8c1b7c..edf97698 100644
--- a/uv.lock
+++ b/uv.lock
@@ -19,7 +19,7 @@ resolution-markers = [
 [[package]]
 name = "aenum"
 version = "3.1.16"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/09/7a/61ed58e8be9e30c3fe518899cc78c284896d246d51381bab59b5db11e1f3/aenum-3.1.16.tar.gz", hash = "sha256:bfaf9589bdb418ee3a986d85750c7318d9d2839c1b1a1d6fe8fc53ec201cf140", size = 137693, upload-time = "2026-01-12T22:34:38.819Z" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/e3/52/6ad8f63ec8da1bf40f96996d25d5b650fdd38f5975f8c813732c47388f18/aenum-3.1.16-py3-none-any.whl", hash = "sha256:9035092855a98e41b66e3d0998bd7b96280e85ceb3a04cc035636138a1943eaf", size = 165627, upload-time = "2025-04-25T03:17:58.89Z" },
@@ -28,7 +28,7 @@ wheels = [
 [[package]]
 name = "aiocqhttp"
 version = "1.4.4"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "httpx" },
     { name = "quart" },
@@ -38,7 +38,7 @@ sdist = { url = "https://files.pythonhosted.org/packages/c2/91/e4bf8584695b065e2
 [[package]]
 name = "aiofiles"
 version = "25.1.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/41/c3/534eac40372d8ee36ef40df62ec129bee4fdb5ad9706e58a29be53b2c970/aiofiles-25.1.0.tar.gz", hash = "sha256:a8d728f0a29de45dc521f18f07297428d56992a742f0cd2701ba86e44d23d5b2", size = 46354, upload-time = "2025-10-09T20:51:04.358Z" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/bc/8a/340a1555ae33d7354dbca4faa54948d76d89a27ceef032c8c3bc661d003e/aiofiles-25.1.0-py3-none-any.whl", hash = "sha256:abe311e527c862958650f9438e859c1fa7568a141b22abcd015e120e86a85695", size = 14668, upload-time = "2025-10-09T20:51:03.174Z" },
@@ -47,7 +47,7 @@ wheels = [
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
@@ -56,7 +56,7 @@ wheels = [
 [[package]]
 name = "aiohttp"
 version = "3.13.3"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "aiohappyeyeballs" },
     { name = "aiosignal" },
@@ -158,7 +158,7 @@ wheels = [
 [[package]]
 name = "aioshutil"
 version = "1.6"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/d3/bd/dcea5abb1792269e70cc75d5f9ae9adbdfba0f0d08a207eb788ec3b469b6/aioshutil-1.6.tar.gz", hash = "sha256:9eae342b9a4cacc2c2c5877877a2d2f7a2b66c62aa1ab57d7e95c8cfd4ede507", size = 7843, upload-time = "2025-10-21T08:42:23.742Z" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/68/92/7020e67ad83095ecc2ce751c24a63df332fb9a34ebfe14bc12a6b21b8f58/aioshutil-1.6-py3-none-any.whl", hash = "sha256:e0711de25ade421b70094b2a27c69bef6356127013744fec05f019f36732c1bd", size = 4705, upload-time = "2025-10-21T08:42:22.892Z" },
@@ -167,7 +167,7 @@ wheels = [
 [[package]]
 name = "aiosignal"
 version = "1.4.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "frozenlist" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
@@ -180,7 +180,7 @@ wheels = [
 [[package]]
 name = "aiosqlite"
 version = "0.22.1"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/4e/8a/64761f4005f17809769d23e518d915db74e6310474e733e3593cfc854ef1/aiosqlite-0.22.1.tar.gz", hash = "sha256:043e0bd78d32888c0a9ca90fc788b38796843360c855a7262a532813133a0650", size = 14821, upload-time = "2025-12-23T19:25:43.997Z" }
 wheels = [
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@@ -189,7 +189,7 @@ wheels = [
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
 wheels = [
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@@ -198,7 +198,7 @@ wheels = [
 [[package]]
 name = "anthropic"
 version = "0.77.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "anyio" },
     { name = "distro" },
@@ -217,7 +217,7 @@ wheels = [
 [[package]]
 name = "anyio"
 version = "4.12.1"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "idna" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
@@ -230,7 +230,7 @@ wheels = [
 [[package]]
 name = "apscheduler"
 version = "3.11.2"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "tzlocal" },
 ]
@@ -242,7 +242,7 @@ wheels = [
 [[package]]
 name = "argon2-cffi"
 version = "25.1.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "argon2-cffi-bindings" },
 ]
@@ -254,7 +254,7 @@ wheels = [
 [[package]]
 name = "argon2-cffi-bindings"
 version = "25.1.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 dependencies = [
     { name = "cffi" },
 ]
@@ -285,7 +285,7 @@ wheels = [
 [[package]]
 name = "async-lru"
 version = "2.1.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/ef/c3/bbf34f15ea88dfb649ab2c40f9d75081784a50573a9ea431563cab64adb8/async_lru-2.1.0.tar.gz", hash = "sha256:9eeb2fecd3fe42cc8a787fc32ead53a3a7158cc43d039c3c55ab3e4e5b2a80ed", size = 12041, upload-time = "2026-01-17T22:52:18.931Z" }
 wheels = [
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@@ -294,7 +294,7 @@ wheels = [
 [[package]]
 name = "asyncpg"
 version = "0.31.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/fe/cc/d18065ce2380d80b1bcce927c24a2642efd38918e33fd724bc4bca904877/asyncpg-0.31.0.tar.gz", hash = "sha256:c989386c83940bfbd787180f2b1519415e2d3d6277a70d9d0f0145ac73500735", size = 993667, upload-time = "2025-11-24T23:27:00.812Z" }
 wheels = [
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@@ -342,7 +342,7 @@ wheels = [
 [[package]]
 name = "attrs"
 version = "25.4.0"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/6b/5c/685e6633917e101e5dcb62b9dd76946cbb57c26e133bae9e0cd36033c0a9/attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11", size = 934251, upload-time = "2025-10-06T13:54:44.725Z" }
 wheels = [
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@@ -351,7 +351,7 @@ wheels = [
 [[package]]
 name = "audioop-lts"
 version = "0.2.2"
-source = { registry = "https://pypi.org/simple" }
+source = { registry = "https://pypi.org/simple/" }
 sdist = { url = "https://files.pythonhosted.org/packages/38/53/946db57842a50b2da2e0c1e34bd37f36f5aadba1a929a3971c5d7841dbca/audioop_lts-0.2.2.tar.gz", hash = "sha256:64d0c62d88e67b98a1a5e71987b7aa7b5bcffc7dcee65b635823dbdd0a8dbbd0", size = 30686, upload-time = "2025-08-05T16:43:17.409Z" }
 wheels = [
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@@ -407,7 +407,7 @@ wheels = [
 [[package]]
 name = "backoff"
 version = "2.2.1"
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