自定义模型测试

model-providers/model_providers/bootstrap_web/openai_bootstrap_web.py

@@ -185,9 +185,17 @@ class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
                         provider=provider, model_type=model_type
                     )
                 )
+                # 获取预定义模型
                 llm_models.extend(
                     provider_model_bundle.model_type_instance.predefined_models()
                 )
+                # 获取自定义模型
+                for model in provider_model_bundle.configuration.custom_configuration.models:
+
+                    llm_models.append(provider_model_bundle.model_type_instance.get_model_schema(
+                        model=model.model,
+                        credentials=model.credentials,
+                    ))
             except Exception as e:
                 logger.error(
                     f"Error while fetching models for provider: {provider}, model_type: {model_type}"

model-providers/tests/integration_tests/xinference_providers_test/model_providers.yaml

@@ -0,0 +1,15 @@
+
+
+xinference:
+  model_credential:
+    - model: 'chatglm3-6b'
+      model_type: 'llm'
+      model_credentials:
+        server_url: 'http://127.0.0.1:9997/'
+        model_uid: 'chatglm3-6b'
+
+    - model: 'chatglm31-6b'
+      model_type: 'llm'
+      model_credentials:
+        server_url: 'http://127.0.0.1:9997/'
+        model_uid: 'chatglm3-6b'

model-providers/tests/integration_tests/xinference_providers_test/test_service.py

@@ -0,0 +1,37 @@
+from langchain.chains import LLMChain
+from langchain_core.prompts import PromptTemplate
+from langchain_openai import ChatOpenAI, OpenAIEmbeddings
+import pytest
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+@pytest.mark.requires("xinference_client")
+def test_llm(init_server: str):
+    llm = ChatOpenAI(
+
+        model_name="glm-4",
+        openai_api_key="YOUR_API_KEY", openai_api_base=f"{init_server}/xinference/v1")
+    template = """Question: {question}
+    
+    Answer: Let's think step by step."""
+
+    prompt = PromptTemplate.from_template(template)
+
+    llm_chain = LLMChain(prompt=prompt, llm=llm)
+    responses = llm_chain.run("你好")
+    logger.info("\033[1;32m" + f"llm_chain: {responses}" + "\033[0m")
+
+
+@pytest.mark.requires("xinference-client")
+def test_embedding(init_server: str):
+    embeddings = OpenAIEmbeddings(model="text_embedding",
+                                  openai_api_key="YOUR_API_KEY",
+                                  openai_api_base=f"{init_server}/xinference/v1")
+
+    text = "你好"
+
+    query_result = embeddings.embed_query(text)
+
+    logger.info("\033[1;32m" + f"embeddings: {query_result}" + "\033[0m")

model-providers/tests/unit_tests/deepseek/test_provider_manager_models.py

@@ -1,18 +1,19 @@
 import asyncio
 import logging
+from typing import List
 
 import pytest
 from omegaconf import OmegaConf
 
 from model_providers import BootstrapWebBuilder, _to_custom_provide_configuration
 from model_providers.core.model_manager import ModelManager
-from model_providers.core.model_runtime.entities.model_entities import ModelType
+from model_providers.core.model_runtime.entities.model_entities import ModelType, AIModelEntity
 from model_providers.core.provider_manager import ProviderManager
 
 logger = logging.getLogger(__name__)
 
 
-def test_ollama_provider_manager_models(logging_conf: dict, providers_file: str) -> None:
+def test_provider_manager_models(logging_conf: dict, providers_file: str) -> None:
     logging.config.dictConfig(logging_conf)  # type: ignore
     # 读取配置文件
     cfg = OmegaConf.load(
@@ -32,8 +33,17 @@ def test_ollama_provider_manager_models(logging_conf: dict, providers_file: str)
     provider_model_bundle_llm = provider_manager.get_provider_model_bundle(
         provider="deepseek", model_type=ModelType.LLM
     )
-    predefined_models = (
+    llm_models: List[AIModelEntity] = []
+    for model in provider_model_bundle_llm.configuration.custom_configuration.models:
+
+        llm_models.append(provider_model_bundle_llm.model_type_instance.get_model_schema(
+            model=model.model,
+            credentials=model.credentials,
+        ))
+
+    # 获取预定义模型
+    llm_models.extend(
         provider_model_bundle_llm.model_type_instance.predefined_models()
     )
 
-    logger.info(f"predefined_models: {predefined_models}")
+    logger.info(f"predefined_models: {llm_models}")

model-providers/tests/unit_tests/ollama/test_provider_manager_models.py

@@ -12,7 +12,7 @@ from model_providers.core.provider_manager import ProviderManager
 logger = logging.getLogger(__name__)
 
 
-def test_ollama_provider_manager_models(logging_conf: dict, providers_file: str) -> None:
+def test_provider_manager_models(logging_conf: dict, providers_file: str) -> None:
     logging.config.dictConfig(logging_conf)  # type: ignore
     # 读取配置文件
     cfg = OmegaConf.load(
@@ -32,11 +32,18 @@ def test_ollama_provider_manager_models(logging_conf: dict, providers_file: str)
     provider_model_bundle_llm = provider_manager.get_provider_model_bundle(
         provider="ollama", model_type=ModelType.LLM
     )
-    provider_model_bundle_emb = provider_manager.get_provider_model_bundle(
-        provider="ollama", model_type=ModelType.TEXT_EMBEDDING
-    )
-    predefined_models = (
+    llm_models: List[AIModelEntity] = []
+    for model in provider_model_bundle_llm.configuration.custom_configuration.models:
+
+        llm_models.append(provider_model_bundle_llm.model_type_instance.get_model_schema(
+            model=model.model,
+            credentials=model.credentials,
+        ))
+
+    # 获取预定义模型
+    llm_models.extend(
         provider_model_bundle_llm.model_type_instance.predefined_models()
     )
 
-    logger.info(f"predefined_models: {predefined_models}")
+    logger.info(f"predefined_models: {llm_models}")
+

model-providers/tests/unit_tests/openai/model_providers.yaml

@@ -17,17 +17,3 @@ openai:
     openai_api_key: 'sk-'
     openai_organization: ''
     openai_api_base: ''
-
-xinference:
-  model_credential:
-    - model: 'chatglm3-6b'
-      model_type: 'llm'
-      model_credentials:
-        server_url: 'http://127.0.0.1:9997/'
-        model_uid: 'chatglm3-6b'
-
-
-zhipuai:
-
-  provider_credential:
-    api_key: 'd4fa0690b6dfa205204cae2e12aa6fb6.1'

model-providers/tests/unit_tests/openai/test_provider_manager_models.py

@@ -32,11 +32,17 @@ def test_provider_manager_models(logging_conf: dict, providers_file: str) -> Non
     provider_model_bundle_llm = provider_manager.get_provider_model_bundle(
         provider="openai", model_type=ModelType.LLM
     )
-    provider_model_bundle_emb = provider_manager.get_provider_model_bundle(
-        provider="openai", model_type=ModelType.TEXT_EMBEDDING
-    )
-    predefined_models = (
-        provider_model_bundle_emb.model_type_instance.predefined_models()
+    llm_models: List[AIModelEntity] = []
+    for model in provider_model_bundle_llm.configuration.custom_configuration.models:
+
+        llm_models.append(provider_model_bundle_llm.model_type_instance.get_model_schema(
+            model=model.model,
+            credentials=model.credentials,
+        ))
+
+    # 获取预定义模型
+    llm_models.extend(
+        provider_model_bundle_llm.model_type_instance.predefined_models()
     )
 
-    logger.info(f"predefined_models: {predefined_models}")
+    logger.info(f"predefined_models: {llm_models}")

model-providers/tests/unit_tests/xinference/model_providers.yaml

@@ -0,0 +1,9 @@
+
+
+xinference:
+  model_credential:
+    - model: 'chatglm3-6b'
+      model_type: 'llm'
+      model_credentials:
+        server_url: 'http://127.0.0.1:9997/'
+        model_uid: 'chatglm3-6b'

model-providers/tests/unit_tests/xinference/test_provider_manager_models.py

@@ -0,0 +1,48 @@
+import asyncio
+import logging
+
+import pytest
+from omegaconf import OmegaConf
+
+from model_providers import BootstrapWebBuilder, _to_custom_provide_configuration
+from model_providers.core.model_manager import ModelManager
+from model_providers.core.model_runtime.entities.model_entities import ModelType
+from model_providers.core.provider_manager import ProviderManager
+
+logger = logging.getLogger(__name__)
+
+
+def test_provider_manager_models(logging_conf: dict, providers_file: str) -> None:
+    logging.config.dictConfig(logging_conf)  # type: ignore
+    # 读取配置文件
+    cfg = OmegaConf.load(
+        providers_file
+    )
+    # 转换配置文件
+    (
+        provider_name_to_provider_records_dict,
+        provider_name_to_provider_model_records_dict,
+    ) = _to_custom_provide_configuration(cfg)
+    # 创建模型管理器
+    provider_manager = ProviderManager(
+        provider_name_to_provider_records_dict=provider_name_to_provider_records_dict,
+        provider_name_to_provider_model_records_dict=provider_name_to_provider_model_records_dict,
+    )
+
+    provider_model_bundle_llm = provider_manager.get_provider_model_bundle(
+        provider="xinference", model_type=ModelType.LLM
+    )
+    llm_models: List[AIModelEntity] = []
+    for model in provider_model_bundle_llm.configuration.custom_configuration.models:
+
+        llm_models.append(provider_model_bundle_llm.model_type_instance.get_model_schema(
+            model=model.model,
+            credentials=model.credentials,
+        ))
+
+    # 获取预定义模型
+    llm_models.extend(
+        provider_model_bundle_llm.model_type_instance.predefined_models()
+    )
+
+    logger.info(f"predefined_models: {llm_models}")

model-providers/tests/unit_tests/zhipuai/model_providers.yaml

@@ -0,0 +1,6 @@
+
+
+zhipuai:
+
+  provider_credential:
+    api_key: 'd4fa0690b6dfa205204cae2e12aa6fb6.1'

model-providers/tests/unit_tests/zhipuai/test_provider_manager_models.py

@@ -0,0 +1,48 @@
+import asyncio
+import logging
+
+import pytest
+from omegaconf import OmegaConf
+
+from model_providers import BootstrapWebBuilder, _to_custom_provide_configuration
+from model_providers.core.model_manager import ModelManager
+from model_providers.core.model_runtime.entities.model_entities import ModelType
+from model_providers.core.provider_manager import ProviderManager
+
+logger = logging.getLogger(__name__)
+
+
+def test_provider_manager_models(logging_conf: dict, providers_file: str) -> None:
+    logging.config.dictConfig(logging_conf)  # type: ignore
+    # 读取配置文件
+    cfg = OmegaConf.load(
+        providers_file
+    )
+    # 转换配置文件
+    (
+        provider_name_to_provider_records_dict,
+        provider_name_to_provider_model_records_dict,
+    ) = _to_custom_provide_configuration(cfg)
+    # 创建模型管理器
+    provider_manager = ProviderManager(
+        provider_name_to_provider_records_dict=provider_name_to_provider_records_dict,
+        provider_name_to_provider_model_records_dict=provider_name_to_provider_model_records_dict,
+    )
+
+    provider_model_bundle_llm = provider_manager.get_provider_model_bundle(
+        provider="zhipuai", model_type=ModelType.LLM
+    )
+    llm_models: List[AIModelEntity] = []
+    for model in provider_model_bundle_llm.configuration.custom_configuration.models:
+
+        llm_models.append(provider_model_bundle_llm.model_type_instance.get_model_schema(
+            model=model.model,
+            credentials=model.credentials,
+        ))
+
+    # 获取预定义模型
+    llm_models.extend(
+        provider_model_bundle_llm.model_type_instance.predefined_models()
+    )
+
+    logger.info(f"predefined_models: {llm_models}")