Merge remote-tracking branch 'origin/adding_ollama' into adding_ollama
This commit is contained in:
Boris Arzentar
commit
fde01fec7b
12 changed files with 159 additions and 55 deletions
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@ -50,4 +50,4 @@ async def add_standalone(
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def is_data_path(data: str) -> bool:
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return False if not isinstance(data, str) else data.startswith("file://")
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return False if not isinstance(data, str) else data.startswith("file://")
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@ -18,4 +18,4 @@ async def remember(user_id: str, memory_name: str, payload: List[str]):
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if await is_existing_memory(memory_name) is False:
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raise MemoryException(f"Memory with the name \"{memory_name}\" doesn't exist.")
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await create_information_points(memory_name, payload)
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await create_information_points(memory_name, payload)
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@ -202,4 +202,4 @@ if __name__ == "__main__":
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print(graph_url)
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asyncio.run(main())
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asyncio.run(main())
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@ -46,8 +46,9 @@ class Config:
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# Model parameters
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llm_provider: str = "openai" #openai, or custom or ollama
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custom_endpoint: str = "" # pass claude endpoint
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custom_key: Optional[str] = "custom"
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custom_model: str = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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custom_endpoint: str = "https://api.endpoints.anyscale.com/v1" # pass claude endpoint
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custom_key: Optional[str] = os.getenv("ANYSCALE_API_KEY")
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ollama_endpoint: str = "http://localhost:11434/v1"
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ollama_key: Optional[str] = "ollama"
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ollama_model: str = "mistral:instruct"
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@ -6,6 +6,7 @@ from .EmbeddingEngine import EmbeddingEngine
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config = Config()
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config.load()
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class DefaultEmbeddingEngine(EmbeddingEngine):
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async def embed_text(self, text: List[str]) -> List[float]:
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embedding_model = TextEmbedding(model_name = config.embedding_model, cache_dir = get_absolute_path("cache/embeddings"))
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0
cognee/infrastructure/llm/anthropic/__init__.py
Normal file
0
cognee/infrastructure/llm/anthropic/__init__.py
Normal file
57
cognee/infrastructure/llm/anthropic/adapter.py
Normal file
57
cognee/infrastructure/llm/anthropic/adapter.py
Normal file
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@ -0,0 +1,57 @@
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import asyncio
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import aiohttp
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from typing import List, Type
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from pydantic import BaseModel
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import instructor
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from tenacity import retry, stop_after_attempt
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import anthropic
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import openai
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from cognee.infrastructure.llm.llm_interface import LLMInterface
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from cognee.infrastructure.llm.prompts import read_query_prompt
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class AnthropicAdapter(LLMInterface):
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"""Adapter for Ollama's API"""
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def __init__(self, ollama_endpoint, api_key: str, model: str):
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self.aclient = instructor.patch(
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create=anthropic.Anthropic().messages.create,
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mode=instructor.Mode.ANTHROPIC_TOOLS
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)
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self.model = model
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@retry(stop=stop_after_attempt(5))
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async def acreate_structured_output(self, text_input: str, system_prompt: str,
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response_model: Type[BaseModel]) -> BaseModel:
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"""Generate a response from a user query."""
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return await self.aclient(
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model=self.model,
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max_tokens=4096,
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max_retries=0,
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messages=[
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{
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"role": "user",
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"content": f"""Use the given format to
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extract information from the following input: {text_input}. {system_prompt}""",
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}
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],
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response_model=response_model,
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)
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def show_prompt(self, text_input: str, system_prompt: str) -> str:
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"""Format and display the prompt for a user query."""
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if not text_input:
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text_input = "No user input provided."
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if not system_prompt:
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raise ValueError("No system prompt path provided.")
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system_prompt = read_query_prompt(system_prompt)
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formatted_prompt = f"""System Prompt:\n{system_prompt}\n\nUser Input:\n{text_input}\n""" if system_prompt else None
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return formatted_prompt
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@ -12,7 +12,7 @@ from cognee.infrastructure.llm.llm_interface import LLMInterface
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from cognee.infrastructure.llm.prompts import read_query_prompt
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class OllamaAPIAdapter(LLMInterface):
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class GenericAPIAdapter(LLMInterface):
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"""Adapter for Ollama's API"""
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def __init__(self, ollama_endpoint, api_key: str, model: str):
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@ -89,9 +89,8 @@ class OllamaAPIAdapter(LLMInterface):
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{
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"role": "user",
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"content": f"""Use the given format to
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extract information from the following input: {text_input}. """,
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},
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{"role": "system", "content": system_prompt},
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extract information from the following input: {text_input}. {system_prompt} """,
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}
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],
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response_model=response_model,
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)
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@ -1,8 +1,9 @@
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"""Get the LLM client."""
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from enum import Enum
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from cognee.config import Config
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from .anthropic.adapter import AnthropicAdapter
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from .openai.adapter import OpenAIAdapter
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from .ollama.adapter import OllamaAPIAdapter
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from .generic_llm_api.adapter import GenericAPIAdapter
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import logging
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logging.basicConfig(level=logging.INFO)
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@ -10,6 +11,7 @@ logging.basicConfig(level=logging.INFO)
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class LLMProvider(Enum):
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OPENAI = "openai"
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OLLAMA = "ollama"
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ANTHROPIC = "anthropic"
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CUSTOM = "custom"
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config = Config()
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@ -24,10 +26,13 @@ def get_llm_client():
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return OpenAIAdapter(config.openai_key, config.model)
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elif provider == LLMProvider.OLLAMA:
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print("Using Ollama API")
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return OllamaAPIAdapter(config.ollama_endpoint, config.ollama_key, config.ollama_model)
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return GenericAPIAdapter(config.ollama_endpoint, config.ollama_key, config.ollama_model)
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elif provider == LLMProvider.ANTHROPIC:
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print("Using Anthropic API")
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return AnthropicAdapter(config.custom_endpoint, config.custom_endpoint, config.custom_model)
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elif provider == LLMProvider.CUSTOM:
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print("Using Custom API")
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return OllamaAPIAdapter(config.custom_endpoint, config.custom_key, config.model)
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return GenericAPIAdapter(config.custom_endpoint, config.custom_key, config.custom_model)
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# Add your custom LLM provider here
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else:
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raise ValueError(f"Unsupported LLM provider: {provider}")
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@ -6,20 +6,20 @@ from pydantic import BaseModel
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class LLMInterface(Protocol):
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""" LLM Interface """
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@abstractmethod
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async def async_get_embedding_with_backoff(self, text, model="text-embedding-ada-002"):
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"""To get text embeddings, import/call this function"""
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raise NotImplementedError
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@abstractmethod
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def get_embedding_with_backoff(self, text: str, model: str = "text-embedding-ada-002"):
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"""To get text embeddings, import/call this function"""
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raise NotImplementedError
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@abstractmethod
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async def async_get_batch_embeddings_with_backoff(self, texts: List[str], models: List[str]):
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"""To get multiple text embeddings in parallel, import/call this function"""
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raise NotImplementedError
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# @abstractmethod
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# async def async_get_embedding_with_backoff(self, text, model="text-embedding-ada-002"):
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# """To get text embeddings, import/call this function"""
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# raise NotImplementedError
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#
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# @abstractmethod
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# def get_embedding_with_backoff(self, text: str, model: str = "text-embedding-ada-002"):
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# """To get text embeddings, import/call this function"""
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# raise NotImplementedError
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#
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# @abstractmethod
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# async def async_get_batch_embeddings_with_backoff(self, texts: List[str], models: List[str]):
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# """To get multiple text embeddings in parallel, import/call this function"""
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# raise NotImplementedError
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# """ Get completions """
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# async def acompletions_with_backoff(self, **kwargs):
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95
poetry.lock
generated
95
poetry.lock
generated
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@ -150,6 +150,30 @@ files = [
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|||
{file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
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]
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[[package]]
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name = "anthropic"
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version = "0.21.3"
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description = "The official Python library for the anthropic API"
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optional = false
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||||
python-versions = ">=3.7"
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||||
files = [
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||||
{file = "anthropic-0.21.3-py3-none-any.whl", hash = "sha256:5869115453b543a46ded6515c9f29b8d610b6e94bbba3230ad80ac947d2b0862"},
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||||
{file = "anthropic-0.21.3.tar.gz", hash = "sha256:02f1ab5694c497e2b2d42d30d51a4f2edcaca92d2ec86bb64fe78a9c7434a869"},
|
||||
]
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||||
|
||||
[package.dependencies]
|
||||
anyio = ">=3.5.0,<5"
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distro = ">=1.7.0,<2"
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||||
httpx = ">=0.23.0,<1"
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pydantic = ">=1.9.0,<3"
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||||
sniffio = "*"
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||||
tokenizers = ">=0.13.0"
|
||||
typing-extensions = ">=4.7,<5"
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||||
|
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[package.extras]
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bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
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vertex = ["google-auth (>=2,<3)"]
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||||
|
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[[package]]
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||||
name = "anyio"
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version = "4.3.0"
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|
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@ -518,17 +542,17 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
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|
||||
[[package]]
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||||
name = "boto3"
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||||
version = "1.34.70"
|
||||
version = "1.34.73"
|
||||
description = "The AWS SDK for Python"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "boto3-1.34.70-py3-none-any.whl", hash = "sha256:8d7902e2c0c62837457ba18146e3feaf1dec62018617edc5c0336b65b305b682"},
|
||||
{file = "boto3-1.34.70.tar.gz", hash = "sha256:54150a52eb93028b8e09df00319e8dcb68be7459333d5da00d706d75ba5130d6"},
|
||||
{file = "boto3-1.34.73-py3-none-any.whl", hash = "sha256:4d68e7c7c1339e251c661fd6e2a34e31d281177106326712417fed839907fa84"},
|
||||
{file = "boto3-1.34.73.tar.gz", hash = "sha256:f45503333286c03fb692a3ce497b6fdb4e88c51c98a3b8ff05071d7f56571448"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
botocore = ">=1.34.70,<1.35.0"
|
||||
botocore = ">=1.34.73,<1.35.0"
|
||||
jmespath = ">=0.7.1,<2.0.0"
|
||||
s3transfer = ">=0.10.0,<0.11.0"
|
||||
|
||||
|
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@ -537,13 +561,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
|
|||
|
||||
[[package]]
|
||||
name = "botocore"
|
||||
version = "1.34.70"
|
||||
version = "1.34.73"
|
||||
description = "Low-level, data-driven core of boto 3."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "botocore-1.34.70-py3-none-any.whl", hash = "sha256:c86944114e85c8a8d5da06fb84f2609ed3bd23cd2fc06b30250bef7e37e8c589"},
|
||||
{file = "botocore-1.34.70.tar.gz", hash = "sha256:fa03d4972cd57d505e6c0eb5d7c7a1caeb7dd49e84f963f7ebeca41fe8ab736e"},
|
||||
{file = "botocore-1.34.73-py3-none-any.whl", hash = "sha256:88d660b711cc5b5b049e15d547cb09526f86e48c15b78dacad78522109502b91"},
|
||||
{file = "botocore-1.34.73.tar.gz", hash = "sha256:8df020b6682b9f1e9ee7b0554d5d0c14b7b23e3de070c85bcdf07fb20bfe4e2b"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1891,13 +1915,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "httpcore"
|
||||
version = "1.0.4"
|
||||
version = "1.0.5"
|
||||
description = "A minimal low-level HTTP client."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "httpcore-1.0.4-py3-none-any.whl", hash = "sha256:ac418c1db41bade2ad53ae2f3834a3a0f5ae76b56cf5aa497d2d033384fc7d73"},
|
||||
{file = "httpcore-1.0.4.tar.gz", hash = "sha256:cb2839ccfcba0d2d3c1131d3c3e26dfc327326fbe7a5dc0dbfe9f6c9151bb022"},
|
||||
{file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
|
||||
{file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1908,7 +1932,7 @@ h11 = ">=0.13,<0.15"
|
|||
asyncio = ["anyio (>=4.0,<5.0)"]
|
||||
http2 = ["h2 (>=3,<5)"]
|
||||
socks = ["socksio (==1.*)"]
|
||||
trio = ["trio (>=0.22.0,<0.25.0)"]
|
||||
trio = ["trio (>=0.22.0,<0.26.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "httpx"
|
||||
|
|
@ -2030,13 +2054,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "instructor"
|
||||
version = "0.6.7"
|
||||
version = "0.6.8"
|
||||
description = "structured outputs for llm"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.10"
|
||||
files = [
|
||||
{file = "instructor-0.6.7-py3-none-any.whl", hash = "sha256:bb2cdc4b56ba9af763e01e590e051b13168038537a9ef12648142cec53472e53"},
|
||||
{file = "instructor-0.6.7.tar.gz", hash = "sha256:cbae44db8c71796a6237432f8c929b15d021b13c82b5474dc2921b2cdcfe647f"},
|
||||
{file = "instructor-0.6.8-py3-none-any.whl", hash = "sha256:f2099e49b21232ddb50ce9ba27e13159dcb3af17e8ede7cbcd93ce990fe6bc82"},
|
||||
{file = "instructor-0.6.8.tar.gz", hash = "sha256:e261d73deb3535d62ee775c437b82aeb6e9c2b2f63bb533b53a9fa6a47dbb95a"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2048,15 +2072,18 @@ rich = ">=13.7.0,<14.0.0"
|
|||
tenacity = ">=8.2.3,<9.0.0"
|
||||
typer = ">=0.9.0,<0.10.0"
|
||||
|
||||
[package.extras]
|
||||
anthropic = ["anthropic (>=0.18.1,<0.19.0)", "xmltodict (>=0.13.0,<0.14.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "ipykernel"
|
||||
version = "6.29.3"
|
||||
version = "6.29.4"
|
||||
description = "IPython Kernel for Jupyter"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "ipykernel-6.29.3-py3-none-any.whl", hash = "sha256:5aa086a4175b0229d4eca211e181fb473ea78ffd9869af36ba7694c947302a21"},
|
||||
{file = "ipykernel-6.29.3.tar.gz", hash = "sha256:e14c250d1f9ea3989490225cc1a542781b095a18a19447fcf2b5eaf7d0ac5bd2"},
|
||||
{file = "ipykernel-6.29.4-py3-none-any.whl", hash = "sha256:1181e653d95c6808039c509ef8e67c4126b3b3af7781496c7cbfb5ed938a27da"},
|
||||
{file = "ipykernel-6.29.4.tar.gz", hash = "sha256:3d44070060f9475ac2092b760123fadf105d2e2493c24848b6691a7c4f42af5c"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4660,26 +4687,26 @@ cffi = {version = "*", markers = "implementation_name == \"pypy\""}
|
|||
|
||||
[[package]]
|
||||
name = "qdrant-client"
|
||||
version = "1.8.0"
|
||||
version = "1.8.2"
|
||||
description = "Client library for the Qdrant vector search engine"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "qdrant_client-1.8.0-py3-none-any.whl", hash = "sha256:fa28d3eb64c0c57ec029c7c85c71f6c72c197f92502022655741f3632c518e29"},
|
||||
{file = "qdrant_client-1.8.0.tar.gz", hash = "sha256:2a1a3f2cbacc7adba85644cf6cfdee20401cf25764b32da479c81fb63e178d15"},
|
||||
{file = "qdrant_client-1.8.2-py3-none-any.whl", hash = "sha256:ee5341c0486d09e4346b0f5ef7781436e6d8cdbf1d5ecddfde7adb3647d353a8"},
|
||||
{file = "qdrant_client-1.8.2.tar.gz", hash = "sha256:65078d5328bc0393f42a46a31cd319a989b8285bf3958360acf1dffffdf4cc4e"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
grpcio = ">=1.41.0"
|
||||
grpcio-tools = ">=1.41.0"
|
||||
httpx = {version = ">=0.14.0", extras = ["http2"]}
|
||||
httpx = {version = ">=0.20.0", extras = ["http2"]}
|
||||
numpy = {version = ">=1.21", markers = "python_version >= \"3.8\" and python_version < \"3.12\""}
|
||||
portalocker = ">=2.7.0,<3.0.0"
|
||||
pydantic = ">=1.10.8"
|
||||
urllib3 = ">=1.26.14,<3"
|
||||
|
||||
[package.extras]
|
||||
fastembed = ["fastembed (==0.2.2)"]
|
||||
fastembed = ["fastembed (==0.2.5)"]
|
||||
|
||||
[[package]]
|
||||
name = "redis"
|
||||
|
|
@ -4839,17 +4866,18 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
|
|||
|
||||
[[package]]
|
||||
name = "requirements-parser"
|
||||
version = "0.5.0"
|
||||
version = "0.7.0"
|
||||
description = "This is a small Python module for parsing Pip requirement files."
|
||||
optional = false
|
||||
python-versions = ">=3.6,<4.0"
|
||||
python-versions = "<4.0,>=3.7"
|
||||
files = [
|
||||
{file = "requirements-parser-0.5.0.tar.gz", hash = "sha256:3336f3a3ae23e06d3f0f88595e4052396e3adf91688787f637e5d2ca1a904069"},
|
||||
{file = "requirements_parser-0.5.0-py3-none-any.whl", hash = "sha256:e7fcdcd04f2049e73a9fb150d8a0f9d51ce4108f5f7cbeac74c484e17b12bcd9"},
|
||||
{file = "requirements_parser-0.7.0-py3-none-any.whl", hash = "sha256:80569baa23b13cf0980fb2ceb5dc2e3b7ee05df203a26d83e3ed56c155c6597a"},
|
||||
{file = "requirements_parser-0.7.0.tar.gz", hash = "sha256:33f1b1c668fa85df8c6a638c479ac743ea8541f5d8d56011591068757ce1a201"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
types-setuptools = ">=57.0.0"
|
||||
setuptools = ">=59.7.0"
|
||||
types-setuptools = ">=59.7.0"
|
||||
|
||||
[[package]]
|
||||
name = "rfc3339-validator"
|
||||
|
|
@ -6065,6 +6093,17 @@ files = [
|
|||
[package.extras]
|
||||
dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "xmltodict"
|
||||
version = "0.13.0"
|
||||
description = "Makes working with XML feel like you are working with JSON"
|
||||
optional = false
|
||||
python-versions = ">=3.4"
|
||||
files = [
|
||||
{file = "xmltodict-0.13.0-py2.py3-none-any.whl", hash = "sha256:aa89e8fd76320154a40d19a0df04a4695fb9dc5ba977cbb68ab3e4eb225e7852"},
|
||||
{file = "xmltodict-0.13.0.tar.gz", hash = "sha256:341595a488e3e01a85a9d8911d8912fd922ede5fecc4dce437eb4b6c8d037e56"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "yarl"
|
||||
version = "1.9.4"
|
||||
|
|
@ -6196,4 +6235,4 @@ weaviate = ["weaviate-client"]
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "~3.10"
|
||||
content-hash = "d929caab2d4114374cf2c36e1d956a7950476ff6e0a550e50011702c568f9195"
|
||||
content-hash = "35ad50753694260acc7e34b3c85e869e310fe2fb614fb5da3a1f3c1df4e82b1a"
|
||||
|
|
|
|||
|
|
@ -26,7 +26,7 @@ boto3 = "^1.26.125"
|
|||
gunicorn = "^20.1.0"
|
||||
sqlalchemy = "^2.0.21"
|
||||
asyncpg = "^0.28.0"
|
||||
instructor = "^0.6.7"
|
||||
instructor = "^0.6.8"
|
||||
networkx = "^3.2.1"
|
||||
graphviz = "^0.20.1"
|
||||
langdetect = "^1.0.9"
|
||||
|
|
@ -52,6 +52,8 @@ weaviate-client = "^4.5.4"
|
|||
scikit-learn = "^1.4.1.post1"
|
||||
fastembed = "^0.2.5"
|
||||
pypdf = "^4.1.0"
|
||||
anthropic = "^0.21.3"
|
||||
xmltodict = "^0.13.0"
|
||||
|
||||
[tool.poetry.extras]
|
||||
dbt = ["dbt-core", "dbt-redshift", "dbt-bigquery", "dbt-duckdb", "dbt-snowflake", "dbt-athena-community", "dbt-databricks"]
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue