Merge remote-tracking branch 'upstream/dev' into docling_context_extraction_engine

merge upstream

backend/open_webui/retrieval/loaders/tavily.py

@@ -0,0 +1,98 @@
+import requests
+import logging
+from typing import Iterator, List, Literal, Union
+
+from langchain_core.document_loaders import BaseLoader
+from langchain_core.documents import Document
+from open_webui.env import SRC_LOG_LEVELS
+
+log = logging.getLogger(__name__)
+log.setLevel(SRC_LOG_LEVELS["RAG"])
+
+class TavilyLoader(BaseLoader):
+    """Extract web page content from URLs using Tavily Extract API.
+    
+    This is a LangChain document loader that uses Tavily's Extract API to
+    retrieve content from web pages and return it as Document objects.
+    
+    Args:
+        urls: URL or list of URLs to extract content from.
+        api_key: The Tavily API key.
+        extract_depth: Depth of extraction, either "basic" or "advanced".
+        continue_on_failure: Whether to continue if extraction of a URL fails.
+    """
+    def __init__(
+        self,
+        urls: Union[str, List[str]],
+        api_key: str,
+        extract_depth: Literal["basic", "advanced"] = "basic",
+        continue_on_failure: bool = True,
+    ) -> None:
+        """Initialize Tavily Extract client.
+        
+        Args:
+            urls: URL or list of URLs to extract content from.
+            api_key: The Tavily API key.
+            include_images: Whether to include images in the extraction.
+            extract_depth: Depth of extraction, either "basic" or "advanced".
+                advanced extraction retrieves more data, including tables and 
+                embedded content, with higher success but may increase latency.
+                basic costs 1 credit per 5 successful URL extractions,
+                advanced costs 2 credits per 5 successful URL extractions.
+            continue_on_failure: Whether to continue if extraction of a URL fails.
+        """
+        if not urls:
+            raise ValueError("At least one URL must be provided.")
+            
+        self.api_key = api_key
+        self.urls = urls if isinstance(urls, list) else [urls]
+        self.extract_depth = extract_depth
+        self.continue_on_failure = continue_on_failure
+        self.api_url = "https://api.tavily.com/extract"
+        
+    def lazy_load(self) -> Iterator[Document]:
+        """Extract and yield documents from the URLs using Tavily Extract API."""
+        batch_size = 20
+        for i in range(0, len(self.urls), batch_size):
+            batch_urls = self.urls[i:i + batch_size]
+            try:
+                headers = {
+                    "Content-Type": "application/json",
+                    "Authorization": f"Bearer {self.api_key}"
+                }
+                # Use string for single URL, array for multiple URLs
+                urls_param = batch_urls[0] if len(batch_urls) == 1 else batch_urls
+                payload = {
+                    "urls": urls_param,
+                    "extract_depth": self.extract_depth
+                }
+                # Make the API call
+                response = requests.post(
+                    self.api_url,
+                    headers=headers,
+                    json=payload
+                )
+                response.raise_for_status()
+                response_data = response.json()
+                # Process successful results
+                for result in response_data.get("results", []):
+                    url = result.get("url", "")
+                    content = result.get("raw_content", "")
+                    if not content:
+                        log.warning(f"No content extracted from {url}")
+                        continue
+                    # Add URLs as metadata
+                    metadata = {"source": url}
+                    yield Document(
+                        page_content=content,
+                        metadata=metadata,
+                    )
+                for failed in response_data.get("failed_results", []):
+                    url = failed.get("url", "")
+                    error = failed.get("error", "Unknown error")
+                    log.error(f"Failed to extract content from {url}: {error}")
+            except Exception as e:
+                if self.continue_on_failure:
+                    log.error(f"Error extracting content from batch {batch_urls}: {e}")
+                else:
+                    raise e

backend/open_webui/retrieval/vector/dbs/opensearch.py

@@ -1,4 +1,5 @@
 from opensearchpy import OpenSearch
+from opensearchpy.helpers import bulk
 from typing import Optional
 
 from open_webui.retrieval.vector.main import VectorItem, SearchResult, GetResult
@@ -20,8 +21,14 @@ class OpenSearchClient:
             verify_certs=OPENSEARCH_CERT_VERIFY,
             http_auth=(OPENSEARCH_USERNAME, OPENSEARCH_PASSWORD),
         )
+    
+    def _get_index_name(self, collection_name: str) -> str:
+        return f"{self.index_prefix}_{collection_name}"
 
     def _result_to_get_result(self, result) -> GetResult:
+        if not result["hits"]["hits"]:
+            return None
+        
         ids = []
         documents = []
         metadatas = []
@@ -31,9 +38,12 @@ class OpenSearchClient:
             documents.append(hit["_source"].get("text"))
             metadatas.append(hit["_source"].get("metadata"))
 
-        return GetResult(ids=ids, documents=documents, metadatas=metadatas)
+        return GetResult(ids=[ids], documents=[documents], metadatas=[metadatas])
 
     def _result_to_search_result(self, result) -> SearchResult:
+        if not result["hits"]["hits"]:
+            return None
+        
         ids = []
         distances = []
         documents = []
@@ -46,25 +56,32 @@ class OpenSearchClient:
             metadatas.append(hit["_source"].get("metadata"))
 
         return SearchResult(
-            ids=ids, distances=distances, documents=documents, metadatas=metadatas
+            ids=[ids], distances=[distances], documents=[documents], metadatas=[metadatas]
         )
 
     def _create_index(self, collection_name: str, dimension: int):
         body = {
+            "settings": {
+                "index": {
+                "knn": True
+                }
+            },
             "mappings": {
                 "properties": {
                     "id": {"type": "keyword"},
                     "vector": {
-                        "type": "dense_vector",
-                        "dims": dimension,  # Adjust based on your vector dimensions
-                        "index": true,
+                        "type": "knn_vector",
+                        "dimension": dimension,  # Adjust based on your vector dimensions
+                        "index": True,
                         "similarity": "faiss",
                         "method": {
                             "name": "hnsw",
-                            "space_type": "ip",  # Use inner product to approximate cosine similarity
+                            "space_type": "innerproduct",  # Use inner product to approximate cosine similarity
                             "engine": "faiss",
-                            "ef_construction": 128,
-                            "m": 16,
+                            "parameters": {
+                                "ef_construction": 128,
+                                "m": 16,
+                            }
                         },
                     },
                     "text": {"type": "text"},
@@ -73,7 +90,7 @@ class OpenSearchClient:
             }
         }
         self.client.indices.create(
-            index=f"{self.index_prefix}_{collection_name}", body=body
+            index=self._get_index_name(collection_name), body=body
         )
 
     def _create_batches(self, items: list[VectorItem], batch_size=100):
@@ -84,38 +101,49 @@ class OpenSearchClient:
         # has_collection here means has index.
         # We are simply adapting to the norms of the other DBs.
         return self.client.indices.exists(
-            index=f"{self.index_prefix}_{collection_name}"
+            index=self._get_index_name(collection_name)
         )
 
-    def delete_colleciton(self, collection_name: str):
+    def delete_collection(self, collection_name: str):
         # delete_collection here means delete index.
         # We are simply adapting to the norms of the other DBs.
-        self.client.indices.delete(index=f"{self.index_prefix}_{collection_name}")
+        self.client.indices.delete(index=self._get_index_name(collection_name))
 
     def search(
-        self, collection_name: str, vectors: list[list[float]], limit: int
+        self, collection_name: str, vectors: list[list[float | int]], limit: int
     ) -> Optional[SearchResult]:
-        query = {
-            "size": limit,
-            "_source": ["text", "metadata"],
-            "query": {
-                "script_score": {
-                    "query": {"match_all": {}},
-                    "script": {
-                        "source": "cosineSimilarity(params.vector, 'vector') + 1.0",
-                        "params": {
-                            "vector": vectors[0]
-                        },  # Assuming single query vector
-                    },
-                }
-            },
-        }
+        try:
+            if not self.has_collection(collection_name):
+                return None
+            
+            query = {
+                "size": limit,
+                "_source": ["text", "metadata"],
+                "query": {
+                    "script_score": {
+                        "query": {
+                            "match_all": {}
+                        },
+                        "script": {
+                            "source": "cosineSimilarity(params.query_value, doc[params.field]) + 1.0",
+                            "params": {
+                            "field": "vector",
+                            "query_value": vectors[0]
+                            },  # Assuming single query vector
+                        },
+                    }
+                },
+            }
+            
+            result = self.client.search(
+                index=self._get_index_name(collection_name),
+                body=query
+            )
 
-        result = self.client.search(
-            index=f"{self.index_prefix}_{collection_name}", body=query
-        )
-
-        return self._result_to_search_result(result)
+            return self._result_to_search_result(result)
+        
+        except Exception as e:
+            return None
 
     def query(
         self, collection_name: str, filter: dict, limit: Optional[int] = None
@@ -124,18 +152,26 @@ class OpenSearchClient:
             return None
 
         query_body = {
-            "query": {"bool": {"filter": []}},
+            "query": {
+                "bool": {
+                    "filter": []
+                }
+            },
             "_source": ["text", "metadata"],
         }
 
         for field, value in filter.items():
-            query_body["query"]["bool"]["filter"].append({"term": {field: value}})
+            query_body["query"]["bool"]["filter"].append({
+                "match": {
+                    "metadata." + str(field): value
+                }
+            })
 
         size = limit if limit else 10
 
         try:
             result = self.client.search(
-                index=f"{self.index_prefix}_{collection_name}",
+                index=self._get_index_name(collection_name),
                 body=query_body,
                 size=size,
             )
@@ -146,14 +182,14 @@ class OpenSearchClient:
             return None
 
     def _create_index_if_not_exists(self, collection_name: str, dimension: int):
-        if not self.has_index(collection_name):
+        if not self.has_collection(collection_name):
             self._create_index(collection_name, dimension)
 
     def get(self, collection_name: str) -> Optional[GetResult]:
         query = {"query": {"match_all": {}}, "_source": ["text", "metadata"]}
 
         result = self.client.search(
-            index=f"{self.index_prefix}_{collection_name}", body=query
+            index=self._get_index_name(collection_name), body=query
         )
         return self._result_to_get_result(result)
 
@@ -165,18 +201,18 @@ class OpenSearchClient:
         for batch in self._create_batches(items):
             actions = [
                 {
-                    "index": {
-                        "_id": item["id"],
-                        "_source": {
-                            "vector": item["vector"],
-                            "text": item["text"],
-                            "metadata": item["metadata"],
-                        },
-                    }
+                    "_op_type": "index", 
+                    "_index": self._get_index_name(collection_name),
+                    "_id": item["id"], 
+                    "_source": {
+                        "vector": item["vector"],
+                        "text": item["text"],
+                        "metadata": item["metadata"],
+                    },
                 }
                 for item in batch
             ]
-            self.client.bulk(actions)
+            bulk(self.client, actions)
 
     def upsert(self, collection_name: str, items: list[VectorItem]):
         self._create_index_if_not_exists(
@@ -186,27 +222,47 @@ class OpenSearchClient:
         for batch in self._create_batches(items):
             actions = [
                 {
-                    "index": {
-                        "_id": item["id"],
-                        "_index": f"{self.index_prefix}_{collection_name}",
-                        "_source": {
-                            "vector": item["vector"],
-                            "text": item["text"],
-                            "metadata": item["metadata"],
-                        },
-                    }
+                    "_op_type": "update", 
+                    "_index": self._get_index_name(collection_name),
+                    "_id": item["id"], 
+                    "doc": {
+                        "vector": item["vector"],
+                        "text": item["text"],
+                        "metadata": item["metadata"],
+                    },
+                    "doc_as_upsert": True,
                 }
                 for item in batch
             ]
-            self.client.bulk(actions)
-
-    def delete(self, collection_name: str, ids: list[str]):
-        actions = [
-            {"delete": {"_index": f"{self.index_prefix}_{collection_name}", "_id": id}}
-            for id in ids
-        ]
-        self.client.bulk(body=actions)
+            bulk(self.client, actions)
 
+    def delete(self, collection_name: str, ids: Optional[list[str]] = None, filter: Optional[dict] = None):
+        if ids:
+            actions = [
+                {
+                    "_op_type": "delete",
+                    "_index": self._get_index_name(collection_name),
+                    "_id": id,
+                }
+                for id in ids
+            ]
+            bulk(self.client, actions)
+        elif filter:
+            query_body = {
+                "query": {
+                    "bool": {
+                        "filter": []
+                    }
+                },
+            }
+            for field, value in filter.items():
+                query_body["query"]["bool"]["filter"].append({
+                    "match": {
+                        "metadata." + str(field): value
+                    }
+                })
+            self.client.delete_by_query(index=self._get_index_name(collection_name), body=query_body)
+                
     def reset(self):
         indices = self.client.indices.get(index=f"{self.index_prefix}_*")
         for index in indices:

backend/open_webui/retrieval/web/utils.py

@@ -24,6 +24,7 @@ from langchain_community.document_loaders import PlaywrightURLLoader, WebBaseLoa
 from langchain_community.document_loaders.firecrawl import FireCrawlLoader
 from langchain_community.document_loaders.base import BaseLoader
 from langchain_core.documents import Document
+from open_webui.retrieval.loaders.tavily import TavilyLoader
 from open_webui.constants import ERROR_MESSAGES
 from open_webui.config import (
     ENABLE_RAG_LOCAL_WEB_FETCH,
@@ -31,6 +32,8 @@ from open_webui.config import (
     RAG_WEB_LOADER_ENGINE,
     FIRECRAWL_API_BASE_URL,
     FIRECRAWL_API_KEY,
+    TAVILY_API_KEY,
+    TAVILY_EXTRACT_DEPTH,
 )
 from open_webui.env import SRC_LOG_LEVELS
 
@@ -113,7 +116,47 @@ def verify_ssl_cert(url: str) -> bool:
         return False
 
 
-class SafeFireCrawlLoader(BaseLoader):
+class RateLimitMixin:
+    async def _wait_for_rate_limit(self):
+        """Wait to respect the rate limit if specified."""
+        if self.requests_per_second and self.last_request_time:
+            min_interval = timedelta(seconds=1.0 / self.requests_per_second)
+            time_since_last = datetime.now() - self.last_request_time
+            if time_since_last < min_interval:
+                await asyncio.sleep((min_interval - time_since_last).total_seconds())
+        self.last_request_time = datetime.now()
+
+    def _sync_wait_for_rate_limit(self):
+        """Synchronous version of rate limit wait."""
+        if self.requests_per_second and self.last_request_time:
+            min_interval = timedelta(seconds=1.0 / self.requests_per_second)
+            time_since_last = datetime.now() - self.last_request_time
+            if time_since_last < min_interval:
+                time.sleep((min_interval - time_since_last).total_seconds())
+        self.last_request_time = datetime.now()
+
+
+class URLProcessingMixin:  
+    def _verify_ssl_cert(self, url: str) -> bool:
+        """Verify SSL certificate for a URL."""
+        return verify_ssl_cert(url)
+        
+    async def _safe_process_url(self, url: str) -> bool:
+        """Perform safety checks before processing a URL."""
+        if self.verify_ssl and not self._verify_ssl_cert(url):
+            raise ValueError(f"SSL certificate verification failed for {url}")
+        await self._wait_for_rate_limit()
+        return True
+    
+    def _safe_process_url_sync(self, url: str) -> bool:
+        """Synchronous version of safety checks."""
+        if self.verify_ssl and not self._verify_ssl_cert(url):
+            raise ValueError(f"SSL certificate verification failed for {url}")
+        self._sync_wait_for_rate_limit()
+        return True
+
+
+class SafeFireCrawlLoader(BaseLoader, RateLimitMixin, URLProcessingMixin):
     def __init__(
         self,
         web_paths,
@@ -208,43 +251,120 @@ class SafeFireCrawlLoader(BaseLoader):
                     continue
                 raise e
 
-    def _verify_ssl_cert(self, url: str) -> bool:
-        return verify_ssl_cert(url)
 
-    async def _wait_for_rate_limit(self):
-        """Wait to respect the rate limit if specified."""
-        if self.requests_per_second and self.last_request_time:
-            min_interval = timedelta(seconds=1.0 / self.requests_per_second)
-            time_since_last = datetime.now() - self.last_request_time
-            if time_since_last < min_interval:
-                await asyncio.sleep((min_interval - time_since_last).total_seconds())
-        self.last_request_time = datetime.now()
+class SafeTavilyLoader(BaseLoader, RateLimitMixin, URLProcessingMixin):
+    def __init__(
+        self,
+        web_paths: Union[str, List[str]],
+        api_key: str,
+        extract_depth: Literal["basic", "advanced"] = "basic",
+        continue_on_failure: bool = True,
+        requests_per_second: Optional[float] = None,
+        verify_ssl: bool = True,
+        trust_env: bool = False,
+        proxy: Optional[Dict[str, str]] = None,
+    ):
+        """Initialize SafeTavilyLoader with rate limiting and SSL verification support.
 
-    def _sync_wait_for_rate_limit(self):
-        """Synchronous version of rate limit wait."""
-        if self.requests_per_second and self.last_request_time:
-            min_interval = timedelta(seconds=1.0 / self.requests_per_second)
-            time_since_last = datetime.now() - self.last_request_time
-            if time_since_last < min_interval:
-                time.sleep((min_interval - time_since_last).total_seconds())
-        self.last_request_time = datetime.now()
+        Args:
+            web_paths: List of URLs/paths to process.
+            api_key: The Tavily API key.
+            extract_depth: Depth of extraction ("basic" or "advanced").
+            continue_on_failure: Whether to continue if extraction of a URL fails.
+            requests_per_second: Number of requests per second to limit to.
+            verify_ssl: If True, verify SSL certificates.
+            trust_env: If True, use proxy settings from environment variables.
+            proxy: Optional proxy configuration.
+        """
+        # Initialize proxy configuration if using environment variables
+        proxy_server = proxy.get("server") if proxy else None
+        if trust_env and not proxy_server:
+            env_proxies = urllib.request.getproxies()
+            env_proxy_server = env_proxies.get("https") or env_proxies.get("http")
+            if env_proxy_server:
+                if proxy:
+                    proxy["server"] = env_proxy_server
+                else:
+                    proxy = {"server": env_proxy_server}
+                    
+        # Store parameters for creating TavilyLoader instances
+        self.web_paths = web_paths if isinstance(web_paths, list) else [web_paths]
+        self.api_key = api_key
+        self.extract_depth = extract_depth
+        self.continue_on_failure = continue_on_failure
+        self.verify_ssl = verify_ssl
+        self.trust_env = trust_env
+        self.proxy = proxy
+        
+        # Add rate limiting
+        self.requests_per_second = requests_per_second
+        self.last_request_time = None
 
-    async def _safe_process_url(self, url: str) -> bool:
-        """Perform safety checks before processing a URL."""
-        if self.verify_ssl and not self._verify_ssl_cert(url):
-            raise ValueError(f"SSL certificate verification failed for {url}")
-        await self._wait_for_rate_limit()
-        return True
-
-    def _safe_process_url_sync(self, url: str) -> bool:
-        """Synchronous version of safety checks."""
-        if self.verify_ssl and not self._verify_ssl_cert(url):
-            raise ValueError(f"SSL certificate verification failed for {url}")
-        self._sync_wait_for_rate_limit()
-        return True
+    def lazy_load(self) -> Iterator[Document]:
+        """Load documents with rate limiting support, delegating to TavilyLoader."""
+        valid_urls = []
+        for url in self.web_paths:
+            try:
+                self._safe_process_url_sync(url)
+                valid_urls.append(url)
+            except Exception as e:
+                log.warning(f"SSL verification failed for {url}: {str(e)}")
+                if not self.continue_on_failure:
+                    raise e
+        if not valid_urls:
+            if self.continue_on_failure:
+                log.warning("No valid URLs to process after SSL verification")
+                return
+            raise ValueError("No valid URLs to process after SSL verification")
+        try:
+            loader = TavilyLoader(
+                urls=valid_urls,
+                api_key=self.api_key,
+                extract_depth=self.extract_depth,
+                continue_on_failure=self.continue_on_failure,
+            )
+            yield from loader.lazy_load()
+        except Exception as e:
+            if self.continue_on_failure:
+                log.exception(e, "Error extracting content from URLs")
+            else:
+                raise e
+    
+    async def alazy_load(self) -> AsyncIterator[Document]:
+        """Async version with rate limiting and SSL verification."""
+        valid_urls = []
+        for url in self.web_paths:
+            try:
+                await self._safe_process_url(url)
+                valid_urls.append(url)
+            except Exception as e:
+                log.warning(f"SSL verification failed for {url}: {str(e)}")
+                if not self.continue_on_failure:
+                    raise e
+        
+        if not valid_urls:
+            if self.continue_on_failure:
+                log.warning("No valid URLs to process after SSL verification")
+                return
+            raise ValueError("No valid URLs to process after SSL verification")
+        
+        try:
+            loader = TavilyLoader(
+                urls=valid_urls,
+                api_key=self.api_key,
+                extract_depth=self.extract_depth,
+                continue_on_failure=self.continue_on_failure,
+            )
+            async for document in loader.alazy_load():
+                yield document
+        except Exception as e:
+            if self.continue_on_failure:
+                log.exception(e, "Error loading URLs")
+            else:
+                raise e
 
 
-class SafePlaywrightURLLoader(PlaywrightURLLoader):
+class SafePlaywrightURLLoader(PlaywrightURLLoader, RateLimitMixin, URLProcessingMixin):
     """Load HTML pages safely with Playwright, supporting SSL verification, rate limiting, and remote browser connection.
 
     Attributes:
@@ -356,40 +476,6 @@ class SafePlaywrightURLLoader(PlaywrightURLLoader):
                     raise e
             await browser.close()
 
-    def _verify_ssl_cert(self, url: str) -> bool:
-        return verify_ssl_cert(url)
-
-    async def _wait_for_rate_limit(self):
-        """Wait to respect the rate limit if specified."""
-        if self.requests_per_second and self.last_request_time:
-            min_interval = timedelta(seconds=1.0 / self.requests_per_second)
-            time_since_last = datetime.now() - self.last_request_time
-            if time_since_last < min_interval:
-                await asyncio.sleep((min_interval - time_since_last).total_seconds())
-        self.last_request_time = datetime.now()
-
-    def _sync_wait_for_rate_limit(self):
-        """Synchronous version of rate limit wait."""
-        if self.requests_per_second and self.last_request_time:
-            min_interval = timedelta(seconds=1.0 / self.requests_per_second)
-            time_since_last = datetime.now() - self.last_request_time
-            if time_since_last < min_interval:
-                time.sleep((min_interval - time_since_last).total_seconds())
-        self.last_request_time = datetime.now()
-
-    async def _safe_process_url(self, url: str) -> bool:
-        """Perform safety checks before processing a URL."""
-        if self.verify_ssl and not self._verify_ssl_cert(url):
-            raise ValueError(f"SSL certificate verification failed for {url}")
-        await self._wait_for_rate_limit()
-        return True
-
-    def _safe_process_url_sync(self, url: str) -> bool:
-        """Synchronous version of safety checks."""
-        if self.verify_ssl and not self._verify_ssl_cert(url):
-            raise ValueError(f"SSL certificate verification failed for {url}")
-        self._sync_wait_for_rate_limit()
-        return True
 
 
 class SafeWebBaseLoader(WebBaseLoader):
@@ -499,6 +585,7 @@ RAG_WEB_LOADER_ENGINES = defaultdict(lambda: SafeWebBaseLoader)
 RAG_WEB_LOADER_ENGINES["playwright"] = SafePlaywrightURLLoader
 RAG_WEB_LOADER_ENGINES["safe_web"] = SafeWebBaseLoader
 RAG_WEB_LOADER_ENGINES["firecrawl"] = SafeFireCrawlLoader
+RAG_WEB_LOADER_ENGINES["tavily"] = SafeTavilyLoader
 
 
 def get_web_loader(
@@ -525,6 +612,10 @@ def get_web_loader(
         web_loader_args["api_key"] = FIRECRAWL_API_KEY.value
         web_loader_args["api_url"] = FIRECRAWL_API_BASE_URL.value
 
+    if RAG_WEB_LOADER_ENGINE.value == "tavily":
+        web_loader_args["api_key"] = TAVILY_API_KEY.value
+        web_loader_args["extract_depth"] = TAVILY_EXTRACT_DEPTH.value
+
     # Create the appropriate WebLoader based on the configuration
     WebLoaderClass = RAG_WEB_LOADER_ENGINES[RAG_WEB_LOADER_ENGINE.value]
     web_loader = WebLoaderClass(**web_loader_args)