diff --git a/README.md b/README.md index ded81f099..827b000a4 100644 --- a/README.md +++ b/README.md @@ -194,7 +194,7 @@ releases! 🌟 # git checkout v0.22.1 # Optional: use a stable tag (see releases: https://github.com/infiniflow/ragflow/releases) - # This steps ensures the **entrypoint.sh** file in the code matches the Docker image version. + # This step ensures the **entrypoint.sh** file in the code matches the Docker image version. # Use CPU for DeepDoc tasks: $ docker compose -f docker-compose.yml up -d diff --git a/agent/tools/code_exec.py b/agent/tools/code_exec.py index e62cace5e..678d56f02 100644 --- a/agent/tools/code_exec.py +++ b/agent/tools/code_exec.py @@ -69,7 +69,7 @@ class CodeExecParam(ToolParamBase): self.meta: ToolMeta = { "name": "execute_code", "description": """ -This tool has a sandbox that can execute code written in 'Python'/'Javascript'. It recieves a piece of code and return a Json string. +This tool has a sandbox that can execute code written in 'Python'/'Javascript'. It receives a piece of code and return a Json string. Here's a code example for Python(`main` function MUST be included): def main() -> dict: \"\"\" diff --git a/api/apps/__init__.py b/api/apps/__init__.py index ea7f559f9..dbcff1d2f 100644 --- a/api/apps/__init__.py +++ b/api/apps/__init__.py @@ -82,6 +82,11 @@ app.url_map.strict_slashes = False app.json_encoder = CustomJSONEncoder app.errorhandler(Exception)(server_error_response) +# Configure Quart timeouts for slow LLM responses (e.g., local Ollama on CPU) +# Default Quart timeouts are 60 seconds which is too short for many LLM backends +app.config["RESPONSE_TIMEOUT"] = int(os.environ.get("QUART_RESPONSE_TIMEOUT", 600)) +app.config["BODY_TIMEOUT"] = int(os.environ.get("QUART_BODY_TIMEOUT", 600)) + ## convince for dev and debug # app.config["LOGIN_DISABLED"] = True app.config["SESSION_PERMANENT"] = False diff --git a/api/apps/document_app.py b/api/apps/document_app.py index bd2262919..4755453d4 100644 --- a/api/apps/document_app.py +++ b/api/apps/document_app.py @@ -706,6 +706,7 @@ async def set_meta(): except Exception as e: return server_error_response(e) + @manager.route("/upload_info", methods=["POST"]) # noqa: F821 async def upload_info(): files = await request.files diff --git a/api/db/services/dialog_service.py b/api/db/services/dialog_service.py index ae79b45a6..d5d0e1664 100644 --- a/api/db/services/dialog_service.py +++ b/api/db/services/dialog_service.py @@ -676,7 +676,11 @@ Please write the SQL, only SQL, without any other explanations or text. if kb_ids: kb_filter = "(" + " OR ".join([f"kb_id = '{kb_id}'" for kb_id in kb_ids]) + ")" if "where" not in sql.lower(): - sql += f" WHERE {kb_filter}" + o = sql.lower().split("order by") + if len(o) > 1: + sql = o[0] + f" WHERE {kb_filter} order by " + o[1] + else: + sql += f" WHERE {kb_filter}" else: sql += f" AND {kb_filter}" @@ -684,10 +688,9 @@ Please write the SQL, only SQL, without any other explanations or text. tried_times += 1 return settings.retriever.sql_retrieval(sql, format="json"), sql - tbl, sql = get_table() - if tbl is None: - return None - if tbl.get("error") and tried_times <= 2: + try: + tbl, sql = get_table() + except Exception as e: user_prompt = """ Table name: {}; Table of database fields are as follows: @@ -701,16 +704,14 @@ Please write the SQL, only SQL, without any other explanations or text. The SQL error you provided last time is as follows: {} - Error issued by database as follows: - {} - Please correct the error and write SQL again, only SQL, without any other explanations or text. - """.format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question, sql, tbl["error"]) - tbl, sql = get_table() - logging.debug("TRY it again: {}".format(sql)) + """.format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question, e) + try: + tbl, sql = get_table() + except Exception: + return - logging.debug("GET table: {}".format(tbl)) - if tbl.get("error") or len(tbl["rows"]) == 0: + if len(tbl["rows"]) == 0: return None docid_idx = set([ii for ii, c in enumerate(tbl["columns"]) if c["name"] == "doc_id"]) diff --git a/api/utils/validation_utils.py b/api/utils/validation_utils.py index a6edadaf2..904ec4293 100644 --- a/api/utils/validation_utils.py +++ b/api/utils/validation_utils.py @@ -14,6 +14,7 @@ # limitations under the License. # from collections import Counter +import string from typing import Annotated, Any, Literal from uuid import UUID @@ -25,6 +26,7 @@ from pydantic import ( StringConstraints, ValidationError, field_validator, + model_validator, ) from pydantic_core import PydanticCustomError from werkzeug.exceptions import BadRequest, UnsupportedMediaType @@ -362,10 +364,9 @@ class CreateDatasetReq(Base): embedding_model: Annotated[str | None, Field(default=None, max_length=255, serialization_alias="embd_id")] permission: Annotated[Literal["me", "team"], Field(default="me", min_length=1, max_length=16)] shared_tenant_id: Annotated[str | None, Field(default=None, max_length=32, description="Specific tenant ID to share with when permission is 'team'")] - chunk_method: Annotated[ - Literal["naive", "book", "email", "laws", "manual", "one", "paper", "picture", "presentation", "qa", "table", "tag"], - Field(default="naive", min_length=1, max_length=32, serialization_alias="parser_id"), - ] + chunk_method: Annotated[str | None, Field(default=None, serialization_alias="parser_id")] + parse_type: Annotated[int | None, Field(default=None, ge=0, le=64)] + pipeline_id: Annotated[str | None, Field(default=None, min_length=32, max_length=32, serialization_alias="pipeline_id")] parser_config: Annotated[ParserConfig | None, Field(default=None)] @field_validator("shared_tenant_id", mode="after") @@ -535,6 +536,93 @@ class CreateDatasetReq(Base): raise PydanticCustomError("string_too_long", "Parser config exceeds size limit (max 65,535 characters). Current size: {actual}", {"actual": len(json_str)}) return v + @field_validator("pipeline_id", mode="after") + @classmethod + def validate_pipeline_id(cls, v: str | None) -> str | None: + """Validate pipeline_id as 32-char lowercase hex string if provided. + + Rules: + - None or empty string: treat as None (not set) + - Must be exactly length 32 + - Must contain only hex digits (0-9a-fA-F); normalized to lowercase + """ + if v is None: + return None + if v == "": + return None + if len(v) != 32: + raise PydanticCustomError("format_invalid", "pipeline_id must be 32 hex characters") + if any(ch not in string.hexdigits for ch in v): + raise PydanticCustomError("format_invalid", "pipeline_id must be hexadecimal") + return v.lower() + + @model_validator(mode="after") + def validate_parser_dependency(self) -> "CreateDatasetReq": + """ + Mixed conditional validation: + - If parser_id is omitted (field not set): + * If both parse_type and pipeline_id are omitted → default chunk_method = "naive" + * If both parse_type and pipeline_id are provided → allow ingestion pipeline mode + - If parser_id is provided (valid enum) → parse_type and pipeline_id must be None (disallow mixed usage) + + Raises: + PydanticCustomError with code 'dependency_error' on violation. + """ + # Omitted chunk_method (not in fields) logic + if self.chunk_method is None and "chunk_method" not in self.model_fields_set: + # All three absent → default naive + if self.parse_type is None and self.pipeline_id is None: + object.__setattr__(self, "chunk_method", "naive") + return self + # parser_id omitted: require BOTH parse_type & pipeline_id present (no partial allowed) + if self.parse_type is None or self.pipeline_id is None: + missing = [] + if self.parse_type is None: + missing.append("parse_type") + if self.pipeline_id is None: + missing.append("pipeline_id") + raise PydanticCustomError( + "dependency_error", + "parser_id omitted → required fields missing: {fields}", + {"fields": ", ".join(missing)}, + ) + # Both provided → allow pipeline mode + return self + + # parser_id provided (valid): MUST NOT have parse_type or pipeline_id + if isinstance(self.chunk_method, str): + if self.parse_type is not None or self.pipeline_id is not None: + invalid = [] + if self.parse_type is not None: + invalid.append("parse_type") + if self.pipeline_id is not None: + invalid.append("pipeline_id") + raise PydanticCustomError( + "dependency_error", + "parser_id provided → disallowed fields present: {fields}", + {"fields": ", ".join(invalid)}, + ) + return self + + @field_validator("chunk_method", mode="wrap") + @classmethod + def validate_chunk_method(cls, v: Any, handler) -> Any: + """Wrap validation to unify error messages, including type errors (e.g. list).""" + allowed = {"naive", "book", "email", "laws", "manual", "one", "paper", "picture", "presentation", "qa", "table", "tag"} + error_msg = "Input should be 'naive', 'book', 'email', 'laws', 'manual', 'one', 'paper', 'picture', 'presentation', 'qa', 'table' or 'tag'" + # Omitted field: handler won't be invoked (wrap still gets value); None treated as explicit invalid + if v is None: + raise PydanticCustomError("literal_error", error_msg) + try: + # Run inner validation (type checking) + result = handler(v) + except Exception: + raise PydanticCustomError("literal_error", error_msg) + # After handler, enforce enumeration + if not isinstance(result, str) or result == "" or result not in allowed: + raise PydanticCustomError("literal_error", error_msg) + return result + class UpdateDatasetReq(CreateDatasetReq): dataset_id: Annotated[str, Field(...)] diff --git a/conf/service_conf.yaml b/conf/service_conf.yaml index 6b3cef80e..07a7b32a9 100644 --- a/conf/service_conf.yaml +++ b/conf/service_conf.yaml @@ -38,6 +38,7 @@ oceanbase: port: 2881 redis: db: 1 + username: '' password: 'infini_rag_flow' host: 'localhost:6379' task_executor: diff --git a/deepdoc/parser/mineru_parser.py b/deepdoc/parser/mineru_parser.py index d4834de39..9670bdcf9 100644 --- a/deepdoc/parser/mineru_parser.py +++ b/deepdoc/parser/mineru_parser.py @@ -190,7 +190,7 @@ class MinerUParser(RAGFlowPdfParser): self._run_mineru_executable(input_path, output_dir, method, backend, lang, server_url, callback) def _run_mineru_api(self, input_path: Path, output_dir: Path, method: str = "auto", backend: str = "pipeline", lang: Optional[str] = None, callback: Optional[Callable] = None): - OUTPUT_ZIP_PATH = os.path.join(str(output_dir), "output.zip") + output_zip_path = os.path.join(str(output_dir), "output.zip") pdf_file_path = str(input_path) @@ -230,16 +230,16 @@ class MinerUParser(RAGFlowPdfParser): response.raise_for_status() if response.headers.get("Content-Type") == "application/zip": - self.logger.info(f"[MinerU] zip file returned, saving to {OUTPUT_ZIP_PATH}...") + self.logger.info(f"[MinerU] zip file returned, saving to {output_zip_path}...") if callback: - callback(0.30, f"[MinerU] zip file returned, saving to {OUTPUT_ZIP_PATH}...") + callback(0.30, f"[MinerU] zip file returned, saving to {output_zip_path}...") - with open(OUTPUT_ZIP_PATH, "wb") as f: + with open(output_zip_path, "wb") as f: f.write(response.content) self.logger.info(f"[MinerU] Unzip to {output_path}...") - self._extract_zip_no_root(OUTPUT_ZIP_PATH, output_path, pdf_file_name + "/") + self._extract_zip_no_root(output_zip_path, output_path, pdf_file_name + "/") if callback: callback(0.40, f"[MinerU] Unzip to {output_path}...") @@ -459,13 +459,36 @@ class MinerUParser(RAGFlowPdfParser): return poss def _read_output(self, output_dir: Path, file_stem: str, method: str = "auto", backend: str = "pipeline") -> list[dict[str, Any]]: - subdir = output_dir / file_stem / method - if backend.startswith("vlm-"): - subdir = output_dir / file_stem / "vlm" - json_file = subdir / f"{file_stem}_content_list.json" + candidates = [] + seen = set() - if not json_file.exists(): - raise FileNotFoundError(f"[MinerU] Missing output file: {json_file}") + def add_candidate_path(p: Path): + if p not in seen: + seen.add(p) + candidates.append(p) + + if backend.startswith("vlm-"): + add_candidate_path(output_dir / file_stem / "vlm") + if method: + add_candidate_path(output_dir / file_stem / method) + add_candidate_path(output_dir / file_stem / "auto") + else: + if method: + add_candidate_path(output_dir / file_stem / method) + add_candidate_path(output_dir / file_stem / "vlm") + add_candidate_path(output_dir / file_stem / "auto") + + json_file = None + subdir = None + for sub in candidates: + jf = sub / f"{file_stem}_content_list.json" + if jf.exists(): + subdir = sub + json_file = jf + break + + if not json_file: + raise FileNotFoundError(f"[MinerU] Missing output file, tried: {', '.join(str(c / (file_stem + '_content_list.json')) for c in candidates)}") with open(json_file, "r", encoding="utf-8") as f: data = json.load(f) @@ -520,7 +543,7 @@ class MinerUParser(RAGFlowPdfParser): method: str = "auto", server_url: Optional[str] = None, delete_output: bool = True, - parse_method: str = "raw" + parse_method: str = "raw", ) -> tuple: import shutil @@ -570,7 +593,7 @@ class MinerUParser(RAGFlowPdfParser): self.logger.info(f"[MinerU] Parsed {len(outputs)} blocks from PDF.") if callback: callback(0.75, f"[MinerU] Parsed {len(outputs)} blocks from PDF.") - + return self._transfer_to_sections(outputs, parse_method), self._transfer_to_tables(outputs) finally: if temp_pdf and temp_pdf.exists(): diff --git a/docker/service_conf.yaml.template b/docker/service_conf.yaml.template index fa85453ab..72e7a6d73 100644 --- a/docker/service_conf.yaml.template +++ b/docker/service_conf.yaml.template @@ -38,6 +38,7 @@ oceanbase: port: ${OCEANBASE_PORT:-2881} redis: db: 1 + username: '${REDIS_USERNAME:-}' password: '${REDIS_PASSWORD:-infini_rag_flow}' host: '${REDIS_HOST:-redis}:6379' user_default_llm: diff --git a/docs/configurations.md b/docs/configurations.md index 7574c6d12..f2602767c 100644 --- a/docs/configurations.md +++ b/docs/configurations.md @@ -89,6 +89,8 @@ RAGFlow utilizes MinIO as its object storage solution, leveraging its scalabilit - `REDIS_PORT` The port used to expose the Redis service to the host machine, allowing **external** access to the Redis service running inside the Docker container. Defaults to `6379`. +- `REDIS_USERNAME` + Optional Redis ACL username when using Redis 6+ authentication. - `REDIS_PASSWORD` The password for Redis. @@ -160,6 +162,13 @@ If you cannot download the RAGFlow Docker image, try the following mirrors. - `password`: The password for MinIO. - `host`: The MinIO serving IP *and* port inside the Docker container. Defaults to `minio:9000`. +### `redis` + +- `host`: The Redis serving IP *and* port inside the Docker container. Defaults to `redis:6379`. +- `db`: The Redis database index to use. Defaults to `1`. +- `username`: Optional Redis ACL username (Redis 6+). +- `password`: The password for the specified Redis user. + ### `oauth` The OAuth configuration for signing up or signing in to RAGFlow using a third-party account. diff --git a/docs/guides/models/deploy_local_llm.mdx b/docs/guides/models/deploy_local_llm.mdx index 8eadfad94..dfee3fc78 100644 --- a/docs/guides/models/deploy_local_llm.mdx +++ b/docs/guides/models/deploy_local_llm.mdx @@ -314,35 +314,3 @@ To enable IPEX-LLM accelerated Ollama in RAGFlow, you must also complete the con 3. [Update System Model Settings](#6-update-system-model-settings) 4. [Update Chat Configuration](#7-update-chat-configuration) -## Deploy a local model using jina - -To deploy a local model, e.g., **gpt2**, using jina: - -### 1. Check firewall settings - -Ensure that your host machine's firewall allows inbound connections on port 12345. - -```bash -sudo ufw allow 12345/tcp -``` - -### 2. Install jina package - -```bash -pip install jina -``` - -### 3. Deploy a local model - -Step 1: Navigate to the **rag/svr** directory. - -```bash -cd rag/svr -``` - -Step 2: Run **jina_server.py**, specifying either the model's name or its local directory: - -```bash -python jina_server.py --model_name gpt2 -``` -> The script only supports models downloaded from Hugging Face. diff --git a/docs/references/http_api_reference.md b/docs/references/http_api_reference.md index 3c73cf58c..7f006ec3d 100644 --- a/docs/references/http_api_reference.md +++ b/docs/references/http_api_reference.md @@ -419,7 +419,15 @@ Creates a dataset. - `"embedding_model"`: `string` - `"permission"`: `string` - `"chunk_method"`: `string` - - `"parser_config"`: `object` + - "parser_config": `object` + - "parse_type": `int` + - "pipeline_id": `string` + +Note: Choose exactly one ingestion mode when creating a dataset. +- Chunking method: provide `"chunk_method"` (optionally with `"parser_config"`). +- Ingestion pipeline: provide both `"parse_type"` and `"pipeline_id"` and do not provide `"chunk_method"`. + +These options are mutually exclusive. If all three of `chunk_method`, `parse_type`, and `pipeline_id` are omitted, the system defaults to `chunk_method = "naive"`. ##### Request example @@ -433,6 +441,26 @@ curl --request POST \ }' ``` +##### Request example (ingestion pipeline) + +Use this form when specifying an ingestion pipeline (do not include `chunk_method`). + +```bash +curl --request POST \ + --url http://{address}/api/v1/datasets \ + --header 'Content-Type: application/json' \ + --header 'Authorization: Bearer ' \ + --data '{ + "name": "test-sdk", + "parse_type": , + "pipeline_id": "" + }' +``` + +Notes: +- `parse_type` is an integer. Replace `` with your pipeline's parse-type value. +- `pipeline_id` must be a 32-character lowercase hexadecimal string. + ##### Request parameters - `"name"`: (*Body parameter*), `string`, *Required* @@ -473,6 +501,7 @@ curl --request POST \ - `"qa"`: Q&A - `"table"`: Table - `"tag"`: Tag + - Mutually exclusive with `parse_type` and `pipeline_id`. If you set `chunk_method`, do not include `parse_type` or `pipeline_id`. - `"parser_config"`: (*Body parameter*), `object` The configuration settings for the dataset parser. The attributes in this JSON object vary with the selected `"chunk_method"`: @@ -509,6 +538,15 @@ curl --request POST \ - Defaults to: `{"use_raptor": false}`. - If `"chunk_method"` is `"table"`, `"picture"`, `"one"`, or `"email"`, `"parser_config"` is an empty JSON object. +- "parse_type": (*Body parameter*), `int` + The ingestion pipeline parse type identifier. Required if and only if you are using an ingestion pipeline (together with `"pipeline_id"`). Must not be provided when `"chunk_method"` is set. + +- "pipeline_id": (*Body parameter*), `string` + The ingestion pipeline ID. Required if and only if you are using an ingestion pipeline (together with `"parse_type"`). + - Must not be provided when `"chunk_method"` is set. + +Note: If none of `chunk_method`, `parse_type`, and `pipeline_id` are provided, the system will default to `chunk_method = "naive"`. + #### Response Success: diff --git a/rag/llm/chat_model.py b/rag/llm/chat_model.py index 9fbc88348..726aecd8b 100644 --- a/rag/llm/chat_model.py +++ b/rag/llm/chat_model.py @@ -33,9 +33,9 @@ from openai.lib.azure import AzureOpenAI from strenum import StrEnum from zhipuai import ZhipuAI +from common.token_utils import num_tokens_from_string, total_token_count_from_response from rag.llm import FACTORY_DEFAULT_BASE_URL, LITELLM_PROVIDER_PREFIX, SupportedLiteLLMProvider from rag.nlp import is_chinese, is_english -from common.token_utils import num_tokens_from_string, total_token_count_from_response # Error message constants @@ -66,7 +66,7 @@ LENGTH_NOTIFICATION_EN = "...\nThe answer is truncated by your chosen LLM due to class Base(ABC): def __init__(self, key, model_name, base_url, **kwargs): - timeout = int(os.environ.get("LM_TIMEOUT_SECONDS", 600)) + timeout = int(os.environ.get("LLM_TIMEOUT_SECONDS", 600)) self.client = OpenAI(api_key=key, base_url=base_url, timeout=timeout) self.model_name = model_name # Configure retry parameters @@ -127,7 +127,7 @@ class Base(ABC): "tool_choice", "logprobs", "top_logprobs", - "extra_headers" + "extra_headers", } gen_conf = {k: v for k, v in gen_conf.items() if k in allowed_conf} @@ -1213,7 +1213,7 @@ class GoogleChat(Base): # Build GenerateContentConfig try: - from google.genai.types import GenerateContentConfig, ThinkingConfig, Content, Part + from google.genai.types import Content, GenerateContentConfig, Part, ThinkingConfig except ImportError as e: logging.error(f"[GoogleChat] Failed to import google-genai: {e}. Please install: pip install google-genai>=1.41.0") raise @@ -1242,14 +1242,14 @@ class GoogleChat(Base): role = "model" if item["role"] == "assistant" else item["role"] content = Content( role=role, - parts=[Part(text=item["content"])] + parts=[Part(text=item["content"])], ) contents.append(content) response = self.client.models.generate_content( model=self.model_name, contents=contents, - config=config + config=config, ) ans = response.text @@ -1299,7 +1299,7 @@ class GoogleChat(Base): # Build GenerateContentConfig try: - from google.genai.types import GenerateContentConfig, ThinkingConfig, Content, Part + from google.genai.types import Content, GenerateContentConfig, Part, ThinkingConfig except ImportError as e: logging.error(f"[GoogleChat] Failed to import google-genai: {e}. Please install: pip install google-genai>=1.41.0") raise @@ -1326,7 +1326,7 @@ class GoogleChat(Base): role = "model" if item["role"] == "assistant" else item["role"] content = Content( role=role, - parts=[Part(text=item["content"])] + parts=[Part(text=item["content"])], ) contents.append(content) @@ -1334,7 +1334,7 @@ class GoogleChat(Base): for chunk in self.client.models.generate_content_stream( model=self.model_name, contents=contents, - config=config + config=config, ): text = chunk.text ans = text @@ -1406,7 +1406,7 @@ class LiteLLMBase(ABC): ] def __init__(self, key, model_name, base_url=None, **kwargs): - self.timeout = int(os.environ.get("LM_TIMEOUT_SECONDS", 600)) + self.timeout = int(os.environ.get("LLM_TIMEOUT_SECONDS", 600)) self.provider = kwargs.get("provider", "") self.prefix = LITELLM_PROVIDER_PREFIX.get(self.provider, "") self.model_name = f"{self.prefix}{model_name}" @@ -1625,6 +1625,7 @@ class LiteLLMBase(ABC): if self.provider == SupportedLiteLLMProvider.OpenRouter: if self.provider_order: + def _to_order_list(x): if x is None: return [] @@ -1633,6 +1634,7 @@ class LiteLLMBase(ABC): if isinstance(x, (list, tuple)): return [str(s).strip() for s in x if str(s).strip()] return [] + extra_body = {} provider_cfg = {} provider_order = _to_order_list(self.provider_order) diff --git a/rag/prompts/citation_prompt.md b/rag/prompts/citation_prompt.md index 55c89c454..ff41ea219 100644 --- a/rag/prompts/citation_prompt.md +++ b/rag/prompts/citation_prompt.md @@ -106,4 +106,4 @@ REMEMBER: - Each citation supports the ENTIRE sentence - When in doubt, ask: "Would a fact-checker need to verify this?" - Place citations at sentence end, before punctuation -- Format likes this is FORBIDDEN: [ID:0, ID:5, ID:...]. It MUST be seperated like, [ID:0][ID:5]... +- Format likes this is FORBIDDEN: [ID:0, ID:5, ID:...]. It MUST be separated like, [ID:0][ID:5]... diff --git a/rag/utils/es_conn.py b/rag/utils/es_conn.py index 5971950cf..cca3fc7c7 100644 --- a/rag/utils/es_conn.py +++ b/rag/utils/es_conn.py @@ -575,9 +575,9 @@ class ESConnection(DocStoreConnection): time.sleep(3) self._connect() continue - except Exception: - logger.exception("ESConnection.sql got exception") - break + except Exception as e: + logger.exception(f"ESConnection.sql got exception. SQL:\n{sql}") + raise Exception(f"SQL error: {e}\n\nSQL: {sql}") logger.error(f"ESConnection.sql timeout for {ATTEMPT_TIME} times!") return None diff --git a/rag/utils/redis_conn.py b/rag/utils/redis_conn.py index a8bc43b57..b7cc15c63 100644 --- a/rag/utils/redis_conn.py +++ b/rag/utils/redis_conn.py @@ -86,6 +86,9 @@ class RedisDB: "db": int(self.config.get("db", 1)), "decode_responses": True, } + username = self.config.get("username") + if username: + conn_params["username"] = username password = self.config.get("password") if password: conn_params["password"] = password diff --git a/web/src/components/embed-dialog/index.tsx b/web/src/components/embed-dialog/index.tsx index 34197ada0..7f0ccd60f 100644 --- a/web/src/components/embed-dialog/index.tsx +++ b/web/src/components/embed-dialog/index.tsx @@ -22,6 +22,7 @@ import { SharedFrom } from '@/constants/chat'; import { LanguageAbbreviation, LanguageAbbreviationMap, + ThemeEnum, } from '@/constants/common'; import { useTranslate } from '@/hooks/common-hooks'; import { IModalProps } from '@/interfaces/common'; @@ -36,6 +37,7 @@ const FormSchema = z.object({ locale: z.string(), embedType: z.enum(['fullscreen', 'widget']), enableStreaming: z.boolean(), + theme: z.enum([ThemeEnum.Light, ThemeEnum.Dark]), }); type IProps = IModalProps & { @@ -61,6 +63,7 @@ function EmbedDialog({ locale: '', embedType: 'fullscreen' as const, enableStreaming: false, + theme: ThemeEnum.Light, }, }); @@ -74,7 +77,7 @@ function EmbedDialog({ }, []); const generateIframeSrc = useCallback(() => { - const { visibleAvatar, locale, embedType, enableStreaming } = values; + const { visibleAvatar, locale, embedType, enableStreaming, theme } = values; const baseRoute = embedType === 'widget' ? Routes.ChatWidget @@ -91,6 +94,9 @@ function EmbedDialog({ if (enableStreaming) { src += '&streaming=true'; } + if (theme && embedType === 'fullscreen') { + src += `&theme=${theme}`; + } return src; }, [beta, from, token, values]); @@ -181,6 +187,41 @@ function EmbedDialog({ )} /> + {values.embedType === 'fullscreen' && ( + ( + + Theme + + +
+ + +
+
+ + +
+ + + + + )} + /> + )} { + if (theme && (theme === ThemeEnum.Light || theme === ThemeEnum.Dark)) { + setTheme(theme as ThemeEnum); + } + }, [theme, setTheme]); +} diff --git a/web/src/pages/agent/hooks/use-send-shared-message.ts b/web/src/pages/agent/hooks/use-send-shared-message.ts index ab7f7d2fc..fe1e34d62 100644 --- a/web/src/pages/agent/hooks/use-send-shared-message.ts +++ b/web/src/pages/agent/hooks/use-send-shared-message.ts @@ -29,6 +29,7 @@ export const useGetSharedChatSearchParams = () => { from: searchParams.get('from') as SharedFrom, sharedId: searchParams.get('shared_id'), locale: searchParams.get('locale'), + theme: searchParams.get('theme'), data: data, visibleAvatar: searchParams.get('visible_avatar') ? searchParams.get('visible_avatar') !== '1' diff --git a/web/src/pages/agent/share/index.tsx b/web/src/pages/agent/share/index.tsx index af3393ad2..039d8e5d5 100644 --- a/web/src/pages/agent/share/index.tsx +++ b/web/src/pages/agent/share/index.tsx @@ -4,6 +4,7 @@ import { NextMessageInput } from '@/components/message-input/next'; import MessageItem from '@/components/next-message-item'; import PdfSheet from '@/components/pdf-drawer'; import { useClickDrawer } from '@/components/pdf-drawer/hooks'; +import { useSyncThemeFromParams } from '@/components/theme-provider'; import { MessageType } from '@/constants/chat'; import { useUploadCanvasFileWithProgress } from '@/hooks/use-agent-request'; import { cn } from '@/lib/utils'; @@ -25,8 +26,10 @@ const ChatContainer = () => { const { sharedId: conversationId, locale, + theme, visibleAvatar, } = useGetSharedChatSearchParams(); + useSyncThemeFromParams(theme); const { visible, hideModal, documentId, selectedChunk, clickDocumentButton } = useClickDrawer(); diff --git a/web/src/pages/next-chats/hooks/use-send-shared-message.ts b/web/src/pages/next-chats/hooks/use-send-shared-message.ts index fb287ff7d..022998e70 100644 --- a/web/src/pages/next-chats/hooks/use-send-shared-message.ts +++ b/web/src/pages/next-chats/hooks/use-send-shared-message.ts @@ -33,6 +33,7 @@ export const useGetSharedChatSearchParams = () => { from: searchParams.get('from') as SharedFrom, sharedId: searchParams.get('shared_id'), locale: searchParams.get('locale'), + theme: searchParams.get('theme'), data: data, visibleAvatar: searchParams.get('visible_avatar') ? searchParams.get('visible_avatar') !== '1' diff --git a/web/src/pages/next-chats/share/index.tsx b/web/src/pages/next-chats/share/index.tsx index e01671eed..c08d14feb 100644 --- a/web/src/pages/next-chats/share/index.tsx +++ b/web/src/pages/next-chats/share/index.tsx @@ -3,6 +3,7 @@ import { NextMessageInput } from '@/components/message-input/next'; import MessageItem from '@/components/message-item'; import PdfSheet from '@/components/pdf-drawer'; import { useClickDrawer } from '@/components/pdf-drawer/hooks'; +import { useSyncThemeFromParams } from '@/components/theme-provider'; import { MessageType, SharedFrom } from '@/constants/chat'; import { useFetchNextConversationSSE } from '@/hooks/chat-hooks'; import { useFetchFlowSSE } from '@/hooks/flow-hooks'; @@ -22,8 +23,10 @@ const ChatContainer = () => { sharedId: conversationId, from, locale, + theme, visibleAvatar, } = useGetSharedChatSearchParams(); + useSyncThemeFromParams(theme); const { visible, hideModal, documentId, selectedChunk, clickDocumentButton } = useClickDrawer(); @@ -52,6 +55,7 @@ const ChatContainer = () => { i18n.changeLanguage(locale); } }, [locale, visibleAvatar]); + const { data: avatarData } = useFetchAvatar(); if (!conversationId) {