Merge branch 'master' of github.com:chatchat-space/LangGraph-Chatchat…

… into feature/api

chatchat-server/chatchat/server/agent/graphs_factory/base_rag.py

@@ -163,6 +163,7 @@ class Grade(BaseModel):
 
             If the document contains keyword(s) or semantic meaning related to the user question, grade it as relevant.
             Give a binary score 'yes' or 'no' score to indicate whether the document is relevant to the question.
+            The format of output must be an object contains attribute of 'binary_score', like: '{{"binary_score": "yes"}}.'
             """,
             input_variables=["docs", "history"],
         )
@@ -175,7 +176,7 @@ class Grade(BaseModel):
             logger.warning(f"The scored_result is None. Defaulting to 'yes'. Question: {state['question']}")
             score = "yes"
         else:
-            score = scored_result.binary_score
+            score = scored_result.binary_score if hasattr(scored_result, "binary_score") else None
 
         if score == "yes":
             return "generate"

chatchat-server/chatchat/server/localai_embeddings.py

@@ -17,7 +17,7 @@
 
 from langchain_community.utils.openai import is_openai_v1
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
+from pydantic import BaseModel, Field, model_validator
 from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
 from tenacity import (
     AsyncRetrying,
@@ -171,9 +171,9 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
     class Config:
         """Configuration for this pydantic object."""
 
-        allow_population_by_field_name = True
+        populate_by_name = True
 
-    @root_validator(pre=True)
+    @model_validator(mode='before')
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         """Build extra kwargs from additional params that were passed in."""
         all_required_field_names = get_pydantic_field_names(cls)
@@ -199,7 +199,7 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @model_validator(mode='after')
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["openai_api_key"] = get_from_dict_or_env(

chatchat-server/chatchat/server/utils.py

@@ -259,7 +259,7 @@ def get_Embeddings(
     embed_model: str = None,
     local_wrap: bool = False,  # use local wrapped api
 ) -> Embeddings:
-    from langchain_community.embeddings import OllamaEmbeddings
+    from langchain_ollama import OllamaEmbeddings
     from langchain_openai import OpenAIEmbeddings
 
     from chatchat.server.localai_embeddings import (

chatchat-server/chatchat/startup.py

@@ -17,6 +17,18 @@
 except:
     pass
 
+# 多进程之前配置LangSmith使之生效
+try:
+    from chatchat.settings import Settings
+
+    if Settings.basic_settings.LANG_SMITH["OPEN_LANGSMITH"] is True:
+        os.environ["LANGCHAIN_TRACING_V2"] = "true"
+        os.environ["LANGSMITH_API_KEY"] = Settings.basic_settings.LANG_SMITH["LANGCHAIN_API_KEY"]
+        os.environ["LANGCHAIN_PROJECT"] = Settings.basic_settings.LANG_SMITH["LANGCHAIN_PROJECT"]
+    print(f"LANG_SMITH CONFIG: {Settings.basic_settings.LANG_SMITH}")
+except:
+    pass
+
 import click
 
 from fastapi import FastAPI
@@ -67,12 +79,6 @@ def run_api_server(
     )
     logging.config.dictConfig(logging_conf)  # type: ignore
 
-    if Settings.basic_settings.LANG_SMITH["OPEN_LANGSMITH"] is True:
-        os.environ["LANGCHAIN_TRACING_V2"] = "true"
-        os.environ["LANGSMITH_API_KEY"] = Settings.basic_settings.LANG_SMITH["LANGCHAIN_API_KEY"]
-        os.environ["LANGCHAIN_PROJECT"] = Settings.basic_settings.LANG_SMITH["LANGCHAIN_PROJECT"]
-    logger.info(f"LANG_SMITH CONFIG: {Settings.basic_settings.LANG_SMITH}")
-
     uvicorn.run(app, host=host, port=port)
 
 

chatchat-server/pyproject.toml

@@ -81,6 +81,7 @@ psycopg-pool = "^3.2.3"
 langgraph-checkpoint-postgres = "^2.0.2"
 setuptools = {version = "^75.5.0", allow-prereleases = true}
 pymilvus = "^2.4.9"
+langchain-ollama = ">=0.2,<0.3"
 [tool.poetry.extras]
 xinference = ["xinference_client"]
 zhipuai = ["zhipuai"]