Fix ollama, work on visualization
This commit is contained in:
vasilije
parent
307aa83120
commit
1b96a71d5a
9 changed files with 328 additions and 188 deletions
114
cognee-mcp/uv.lock
generated
114
cognee-mcp/uv.lock
generated
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@ -321,6 +321,26 @@ wheels = [
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@ -506,7 +554,9 @@ dependencies = [
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[[package]]
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name = "yarl"
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@ -4,6 +4,8 @@ from .api.v1.config.config import config
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from .api.v1.datasets.datasets import datasets
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from .api.v1.prune import prune
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from .api.v1.search import SearchType, get_search_history, search
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from .api.v1.visualize import visualize
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from .shared.utils import *
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# Pipelines
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from .modules import pipelines
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1
cognee/api/v1/visualize/__init__.py
Normal file
1
cognee/api/v1/visualize/__init__.py
Normal file
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@ -0,0 +1 @@
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from .visualize import visualize_graph
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15
cognee/api/v1/visualize/visualize.py
Normal file
15
cognee/api/v1/visualize/visualize.py
Normal file
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@ -0,0 +1,15 @@
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from cognee.shared.utils import create_cognee_style_network_with_logo, graph_to_tuple
|
||||
from cognee.infrastructure.databases.graph import get_graph_engine
|
||||
import logging
|
||||
|
||||
|
||||
|
||||
async def visualize_graph(bokeh_object):
|
||||
""" """
|
||||
graph_engine = await get_graph_engine()
|
||||
graph_data = await graph_engine.get_graph_data()
|
||||
logging.info(graph_data)
|
||||
|
||||
graph = await create_cognee_style_network_with_logo(graph_data, bokeh_object=bokeh_object)
|
||||
|
||||
return graph
|
||||
|
|
@ -4,15 +4,9 @@ import asyncio
|
|||
from typing import List, Type
|
||||
from pydantic import BaseModel
|
||||
import instructor
|
||||
import openai
|
||||
|
||||
from cognee.exceptions import InvalidValueError
|
||||
from cognee.infrastructure.llm.llm_interface import LLMInterface
|
||||
from cognee.infrastructure.llm.prompts import read_query_prompt
|
||||
from cognee.shared.data_models import MonitoringTool
|
||||
from cognee.base_config import get_base_config
|
||||
from cognee.infrastructure.llm.config import get_llm_config
|
||||
|
||||
import litellm
|
||||
|
||||
class GenericAPIAdapter(LLMInterface):
|
||||
"""Adapter for Generic API LLM provider API"""
|
||||
|
|
@ -21,42 +15,20 @@ class GenericAPIAdapter(LLMInterface):
|
|||
model: str
|
||||
api_key: str
|
||||
|
||||
def __init__(self, api_endpoint, api_key: str, model: str, name: str):
|
||||
def __init__(self, endpoint, api_key: str, model: str, name: str):
|
||||
self.name = name
|
||||
self.model = model
|
||||
self.api_key = api_key
|
||||
self.endpoint = endpoint
|
||||
|
||||
llm_config = get_llm_config()
|
||||
|
||||
if llm_config.llm_provider == "groq":
|
||||
from groq import groq
|
||||
if llm_config.llm_provider == "ollama":
|
||||
self.aclient = instructor.from_litellm(litellm.acompletion)
|
||||
|
||||
self.aclient = instructor.from_openai(
|
||||
client=groq.Groq(
|
||||
api_key=api_key,
|
||||
),
|
||||
mode=instructor.Mode.MD_JSON,
|
||||
)
|
||||
else:
|
||||
base_config = get_base_config()
|
||||
self.aclient = instructor.from_litellm(litellm.acompletion)
|
||||
|
||||
if base_config.monitoring_tool == MonitoringTool.LANGFUSE:
|
||||
from langfuse.openai import AsyncOpenAI
|
||||
elif base_config.monitoring_tool == MonitoringTool.LANGSMITH:
|
||||
from langsmith import wrappers
|
||||
from openai import AsyncOpenAI
|
||||
|
||||
AsyncOpenAI = wrappers.wrap_openai(AsyncOpenAI())
|
||||
else:
|
||||
from openai import AsyncOpenAI
|
||||
|
||||
self.aclient = instructor.patch(
|
||||
AsyncOpenAI(
|
||||
base_url=api_endpoint,
|
||||
api_key=api_key, # required, but unused
|
||||
),
|
||||
mode=instructor.Mode.JSON,
|
||||
)
|
||||
|
||||
async def acreate_structured_output(
|
||||
self, text_input: str, system_prompt: str, response_model: Type[BaseModel]
|
||||
|
|
@ -69,24 +41,16 @@ class GenericAPIAdapter(LLMInterface):
|
|||
{
|
||||
"role": "user",
|
||||
"content": f"""Use the given format to
|
||||
extract information from the following input: {text_input}. """,
|
||||
extract information from the following input: {text_input}. """,
|
||||
},
|
||||
{
|
||||
"role": "system",
|
||||
"content": system_prompt,
|
||||
},
|
||||
{"role": "system", "content": system_prompt},
|
||||
],
|
||||
response_model=response_model,
|
||||
max_retries=5,
|
||||
api_base = self.endpoint,
|
||||
response_model=response_model
|
||||
)
|
||||
|
||||
def show_prompt(self, text_input: str, system_prompt: str) -> str:
|
||||
"""Format and display the prompt for a user query."""
|
||||
if not text_input:
|
||||
text_input = "No user input provided."
|
||||
if not system_prompt:
|
||||
raise InvalidValueError(message="No system prompt path provided.")
|
||||
system_prompt = read_query_prompt(system_prompt)
|
||||
|
||||
formatted_prompt = (
|
||||
f"""System Prompt:\n{system_prompt}\n\nUser Input:\n{text_input}\n"""
|
||||
if system_prompt
|
||||
else None
|
||||
)
|
||||
return formatted_prompt
|
||||
|
|
|
|||
|
|
@ -277,7 +277,7 @@ def extract_pos_tags(sentence):
|
|||
logging.basicConfig(level=logging.INFO)
|
||||
|
||||
|
||||
def convert_to_serializable_graph(G):
|
||||
async def convert_to_serializable_graph(G):
|
||||
"""
|
||||
Convert a graph into a serializable format with stringified node and edge attributes.
|
||||
"""
|
||||
|
|
@ -289,7 +289,6 @@ def convert_to_serializable_graph(G):
|
|||
networkx_graph.add_edges_from(edges)
|
||||
|
||||
new_G = nx.MultiDiGraph() if isinstance(G, nx.MultiDiGraph) else nx.Graph()
|
||||
print(new_G)
|
||||
for node, data in new_G.nodes(data=True):
|
||||
serializable_data = {k: str(v) for k, v in data.items()}
|
||||
new_G.add_node(str(node), **serializable_data)
|
||||
|
|
@ -366,7 +365,7 @@ def style_and_render_graph(p, G, layout_positions, node_attribute, node_colors,
|
|||
return graph_renderer
|
||||
|
||||
|
||||
def create_cognee_style_network_with_logo(
|
||||
async def create_cognee_style_network_with_logo(
|
||||
G,
|
||||
output_filename="cognee_network_with_logo.html",
|
||||
title="Cognee-Style Network",
|
||||
|
|
@ -374,12 +373,14 @@ def create_cognee_style_network_with_logo(
|
|||
layout_func=nx.spring_layout,
|
||||
layout_scale=3.0,
|
||||
logo_alpha=0.1,
|
||||
bokeh_object = False,
|
||||
):
|
||||
"""
|
||||
Create a Cognee-inspired network visualization with an embedded logo.
|
||||
"""
|
||||
logging.info("Converting graph to serializable format...")
|
||||
G = convert_to_serializable_graph(G)
|
||||
G = await convert_to_serializable_graph(G)
|
||||
|
||||
|
||||
logging.info("Generating layout positions...")
|
||||
layout_positions = generate_layout_positions(G, layout_func, layout_scale)
|
||||
|
|
@ -423,12 +424,24 @@ def create_cognee_style_network_with_logo(
|
|||
)
|
||||
p.add_tools(hover_tool)
|
||||
|
||||
|
||||
logging.info(f"Saving visualization to {output_filename}...")
|
||||
html_content = file_html(p, CDN, title)
|
||||
with open(output_filename, "w") as f:
|
||||
f.write(html_content)
|
||||
from bokeh.io import export_png
|
||||
from IPython.display import Image, display
|
||||
|
||||
logging.info("Visualization complete.")
|
||||
png_filename = output_filename.replace(".html", ".png")
|
||||
export_png(p, filename=png_filename)
|
||||
logging.info(f"Saved PNG image to {png_filename}")
|
||||
|
||||
# Display the PNG image as a popup
|
||||
display(Image(png_filename))
|
||||
|
||||
if bokeh_object:
|
||||
return p
|
||||
return html_content
|
||||
|
||||
|
||||
|
|
@ -444,6 +457,8 @@ def graph_to_tuple(graph):
|
|||
return (nodes, edges)
|
||||
|
||||
|
||||
|
||||
|
||||
# ---------------- Example Usage ----------------
|
||||
if __name__ == "__main__":
|
||||
import networkx as nx
|
||||
|
|
|
|||
|
|
@ -73,16 +73,16 @@ def test_get_file_content_hash_stream():
|
|||
assert result == expected_hash
|
||||
|
||||
|
||||
def test_trim_text_to_max_tokens():
|
||||
text = "This is a test string with multiple words."
|
||||
encoding_name = "test_encoding"
|
||||
|
||||
with patch("tiktoken.get_encoding") as mock_get_encoding:
|
||||
mock_get_encoding.return_value.encode = lambda x: list(x)
|
||||
mock_get_encoding.return_value.decode = lambda x: "".join(x)
|
||||
|
||||
result = trim_text_to_max_tokens(text, 5, encoding_name)
|
||||
assert result == text[:5]
|
||||
# def test_trim_text_to_max_tokens():
|
||||
# text = "This is a test string with multiple words."
|
||||
# encoding_name = "test_encoding"
|
||||
#
|
||||
# with patch("tiktoken.get_encoding") as mock_get_encoding:
|
||||
# mock_get_encoding.return_value.encode = lambda x: list(x)
|
||||
# mock_get_encoding.return_value.decode = lambda x: "".join(x)
|
||||
#
|
||||
# result = trim_text_to_max_tokens(text, 5, encoding_name)
|
||||
# assert result == text[:5]
|
||||
|
||||
|
||||
def test_prepare_edges():
|
||||
|
|
|
|||
267
poetry.lock
generated
267
poetry.lock
generated
|
|
@ -2550,13 +2550,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "huggingface-hub"
|
||||
version = "0.27.0"
|
||||
version = "0.27.1"
|
||||
description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
|
||||
optional = false
|
||||
python-versions = ">=3.8.0"
|
||||
files = [
|
||||
{file = "huggingface_hub-0.27.0-py3-none-any.whl", hash = "sha256:8f2e834517f1f1ddf1ecc716f91b120d7333011b7485f665a9a412eacb1a2a81"},
|
||||
{file = "huggingface_hub-0.27.0.tar.gz", hash = "sha256:902cce1a1be5739f5589e560198a65a8edcfd3b830b1666f36e4b961f0454fac"},
|
||||
{file = "huggingface_hub-0.27.1-py3-none-any.whl", hash = "sha256:1c5155ca7d60b60c2e2fc38cbb3ffb7f7c3adf48f824015b219af9061771daec"},
|
||||
{file = "huggingface_hub-0.27.1.tar.gz", hash = "sha256:c004463ca870283909d715d20f066ebd6968c2207dae9393fdffb3c1d4d8f98b"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2667,36 +2667,38 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "instructor"
|
||||
version = "1.5.2"
|
||||
version = "1.7.2"
|
||||
description = "structured outputs for llm"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.9"
|
||||
files = [
|
||||
{file = "instructor-1.5.2-py3-none-any.whl", hash = "sha256:da25abbf1ab792fb094992f1d9ce593e26fe458cb1f9a8e7ebf9d68f3f2c757a"},
|
||||
{file = "instructor-1.5.2.tar.gz", hash = "sha256:fdd5ccbca21b4c558a24e9ba12c84afd907e65153a39d035f47c25800011a977"},
|
||||
{file = "instructor-1.7.2-py3-none-any.whl", hash = "sha256:cb43d27f6d7631c31762b936b2fcb44d2a3f9d8a020430a0f4d3484604ffb95b"},
|
||||
{file = "instructor-1.7.2.tar.gz", hash = "sha256:6c01b2b159766df24865dc81f7bf8457cbda88a3c0bbc810da3467d19b185ed2"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
aiohttp = ">=3.9.1,<4.0.0"
|
||||
docstring-parser = ">=0.16,<0.17"
|
||||
jiter = ">=0.5.0,<0.6.0"
|
||||
openai = ">=1.45.0,<2.0.0"
|
||||
docstring-parser = ">=0.16,<1.0"
|
||||
jinja2 = ">=3.1.4,<4.0.0"
|
||||
jiter = ">=0.6.1,<0.9"
|
||||
openai = ">=1.52.0,<2.0.0"
|
||||
pydantic = ">=2.8.0,<3.0.0"
|
||||
pydantic-core = ">=2.18.0,<3.0.0"
|
||||
requests = ">=2.32.3,<3.0.0"
|
||||
rich = ">=13.7.0,<14.0.0"
|
||||
tenacity = ">=8.4.1,<9.0.0"
|
||||
tenacity = ">=9.0.0,<10.0.0"
|
||||
typer = ">=0.9.0,<1.0.0"
|
||||
|
||||
[package.extras]
|
||||
anthropic = ["anthropic (>=0.34.0,<0.35.0)", "xmltodict (>=0.13.0,<0.14.0)"]
|
||||
cerebras-cloud-sdk = ["cerebras_cloud_sdk (>=1.5.0,<2.0.0)"]
|
||||
anthropic = ["anthropic (==0.42.0)", "xmltodict (>=0.13,<0.15)"]
|
||||
cerebras-cloud-sdk = ["cerebras-cloud-sdk (>=1.5.0,<2.0.0)"]
|
||||
cohere = ["cohere (>=5.1.8,<6.0.0)"]
|
||||
google-generativeai = ["google-generativeai (>=0.8.2,<0.9.0)"]
|
||||
groq = ["groq (>=0.4.2,<0.5.0)"]
|
||||
litellm = ["litellm (>=1.35.31,<2.0.0)"]
|
||||
mistralai = ["mistralai (>=1.0.3,<2.0.0)"]
|
||||
test-docs = ["anthropic (>=0.34.0,<0.35.0)", "cohere (>=5.1.8,<6.0.0)", "diskcache (>=5.6.3,<6.0.0)", "fastapi (>=0.109.2,<0.110.0)", "groq (>=0.4.2,<0.5.0)", "litellm (>=1.35.31,<2.0.0)", "mistralai (>=1.0.3,<2.0.0)", "pandas (>=2.2.0,<3.0.0)", "pydantic_extra_types (>=2.6.0,<3.0.0)", "redis (>=5.0.1,<6.0.0)", "tabulate (>=0.9.0,<0.10.0)"]
|
||||
fireworks-ai = ["fireworks-ai (>=0.15.4,<1.0.0)"]
|
||||
google-generativeai = ["google-generativeai (>=0.8.2,<1.0.0)", "jsonref (>=1.1.0,<2.0.0)"]
|
||||
groq = ["groq (>=0.4.2,<0.14.0)"]
|
||||
test-docs = ["diskcache (>=5.6.3,<6.0.0)", "fastapi (>=0.109.2,<0.116.0)", "litellm (>=1.35.31,<2.0.0)", "mistralai (>=1.0.3,<2.0.0)", "pandas (>=2.2.0,<3.0.0)", "pydantic-extra-types (>=2.6.0,<3.0.0)", "redis (>=5.0.1,<6.0.0)", "tabulate (>=0.9.0,<1.0.0)"]
|
||||
vertexai = ["google-cloud-aiplatform (>=1.53.0,<2.0.0)", "jsonref (>=1.1.0,<2.0.0)"]
|
||||
writer = ["writer-sdk (>=1.2.0,<2.0.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "ipykernel"
|
||||
|
|
@ -2835,72 +2837,87 @@ i18n = ["Babel (>=2.7)"]
|
|||
|
||||
[[package]]
|
||||
name = "jiter"
|
||||
version = "0.5.0"
|
||||
version = "0.8.2"
|
||||
description = "Fast iterable JSON parser."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "jiter-0.5.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b599f4e89b3def9a94091e6ee52e1d7ad7bc33e238ebb9c4c63f211d74822c3f"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2a063f71c4b06225543dddadbe09d203dc0c95ba352d8b85f1221173480a71d5"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:acc0d5b8b3dd12e91dd184b87273f864b363dfabc90ef29a1092d269f18c7e28"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c22541f0b672f4d741382a97c65609332a783501551445ab2df137ada01e019e"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:63314832e302cc10d8dfbda0333a384bf4bcfce80d65fe99b0f3c0da8945a91a"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a25fbd8a5a58061e433d6fae6d5298777c0814a8bcefa1e5ecfff20c594bd749"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:503b2c27d87dfff5ab717a8200fbbcf4714516c9d85558048b1fc14d2de7d8dc"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6d1f3d27cce923713933a844872d213d244e09b53ec99b7a7fdf73d543529d6d"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:c95980207b3998f2c3b3098f357994d3fd7661121f30669ca7cb945f09510a87"},
|
||||
{file = "jiter-0.5.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:afa66939d834b0ce063f57d9895e8036ffc41c4bd90e4a99631e5f261d9b518e"},
|
||||
{file = "jiter-0.5.0-cp310-none-win32.whl", hash = "sha256:f16ca8f10e62f25fd81d5310e852df6649af17824146ca74647a018424ddeccf"},
|
||||
{file = "jiter-0.5.0-cp310-none-win_amd64.whl", hash = "sha256:b2950e4798e82dd9176935ef6a55cf6a448b5c71515a556da3f6b811a7844f1e"},
|
||||
{file = "jiter-0.5.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d4c8e1ed0ef31ad29cae5ea16b9e41529eb50a7fba70600008e9f8de6376d553"},
|
||||
{file = "jiter-0.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c6f16e21276074a12d8421692515b3fd6d2ea9c94fd0734c39a12960a20e85f3"},
|
||||
{file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5280e68e7740c8c128d3ae5ab63335ce6d1fb6603d3b809637b11713487af9e6"},
|
||||
{file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:583c57fc30cc1fec360e66323aadd7fc3edeec01289bfafc35d3b9dcb29495e4"},
|
||||
{file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:26351cc14507bdf466b5f99aba3df3143a59da75799bf64a53a3ad3155ecded9"},
|
||||
{file = "jiter-0.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4829df14d656b3fb87e50ae8b48253a8851c707da9f30d45aacab2aa2ba2d614"},
|
||||
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{file = "jiter-0.8.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b2dd880785088ff2ad21ffee205e58a8c1ddabc63612444ae41e5e4b321b39c0"},
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{file = "jiter-0.8.2-cp313-cp313t-win_amd64.whl", hash = "sha256:3ac9f578c46f22405ff7f8b1f5848fb753cc4b8377fbec8470a7dc3997ca7566"},
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{file = "jiter-0.8.2-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a2ecaa3c23e7a7cf86d00eda3390c232f4d533cd9ddea4b04f5d0644faf642c5"},
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{file = "jiter-0.8.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:99d9a1eded738299ba8e106c6779ce5c3893cffa0e32e4485d680588adae6db8"},
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{file = "jiter-0.8.2-cp38-cp38-win32.whl", hash = "sha256:fc5adda618205bd4678b146612ce44c3cbfdee9697951f2c0ffdef1f26d72b63"},
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{file = "jiter-0.8.2-cp38-cp38-win_amd64.whl", hash = "sha256:cd646c827b4f85ef4a78e4e58f4f5854fae0caf3db91b59f0d73731448a970c6"},
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||||
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||||
{file = "jiter-0.8.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:7f22b16b35d5c1df9dfd58843ab2cd25e6bf15191f5a236bed177afade507bfc"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7200b8f7619d36aa51c803fd52020a2dfbea36ffec1b5e22cab11fd34d95a6d"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:70bf4c43652cc294040dbb62256c83c8718370c8b93dd93d934b9a7bf6c4f53c"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f9d471356dc16f84ed48768b8ee79f29514295c7295cb41e1133ec0b2b8d637d"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:859e8eb3507894093d01929e12e267f83b1d5f6221099d3ec976f0c995cb6bd9"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eaa58399c01db555346647a907b4ef6d4f584b123943be6ed5588c3f2359c9f4"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8f2d5ed877f089862f4c7aacf3a542627c1496f972a34d0474ce85ee7d939c27"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:03c9df035d4f8d647f8c210ddc2ae0728387275340668fb30d2421e17d9a0841"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:8bd2a824d08d8977bb2794ea2682f898ad3d8837932e3a74937e93d62ecbb637"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-win32.whl", hash = "sha256:ca29b6371ebc40e496995c94b988a101b9fbbed48a51190a4461fcb0a68b4a36"},
|
||||
{file = "jiter-0.8.2-cp39-cp39-win_amd64.whl", hash = "sha256:1c0dfbd1be3cbefc7510102370d86e35d1d53e5a93d48519688b1bf0f761160a"},
|
||||
{file = "jiter-0.8.2.tar.gz", hash = "sha256:cd73d3e740666d0e639f678adb176fad25c1bcbdae88d8d7b857e1783bb4212d"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -3443,18 +3460,18 @@ typing-extensions = ">=4.7"
|
|||
|
||||
[[package]]
|
||||
name = "langchain-openai"
|
||||
version = "0.2.5"
|
||||
version = "0.2.13"
|
||||
description = "An integration package connecting OpenAI and LangChain"
|
||||
optional = true
|
||||
python-versions = "<4.0,>=3.9"
|
||||
files = [
|
||||
{file = "langchain_openai-0.2.5-py3-none-any.whl", hash = "sha256:745fd9d51a5a3a9cb8839d41f3786ab38dfc539e47c713a806cbca32f3d0875c"},
|
||||
{file = "langchain_openai-0.2.5.tar.gz", hash = "sha256:55b98711a880474ec363267bf6cd0e2727dc00e8433731318d063a2184582c28"},
|
||||
{file = "langchain_openai-0.2.13-py3-none-any.whl", hash = "sha256:4b0707694b5081b474e0d8313572fbe611de0df82cf4659068ed20ccb629d1f8"},
|
||||
{file = "langchain_openai-0.2.13.tar.gz", hash = "sha256:5b0eb9c7ab3f46ba7b5a53337e76586fb89b67475a465f3e3f0ab40a2f94235d"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
langchain-core = ">=0.3.15,<0.4.0"
|
||||
openai = ">=1.52.0,<2.0.0"
|
||||
langchain-core = ">=0.3.27,<0.4.0"
|
||||
openai = ">=1.55.3,<2.0.0"
|
||||
tiktoken = ">=0.7,<1"
|
||||
|
||||
[[package]]
|
||||
|
|
@ -3487,13 +3504,13 @@ six = "*"
|
|||
|
||||
[[package]]
|
||||
name = "langfuse"
|
||||
version = "2.57.4"
|
||||
version = "2.57.5"
|
||||
description = "A client library for accessing langfuse"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.9"
|
||||
files = [
|
||||
{file = "langfuse-2.57.4-py3-none-any.whl", hash = "sha256:9cb007cb444439412b538d00eda950f874a9e7da8c801cf631b3438444fdcf71"},
|
||||
{file = "langfuse-2.57.4.tar.gz", hash = "sha256:dda1a9f1bef63e6f6f45eb8d8bf72fbce3597a89d01e8c6f0a59a2a40ef2c600"},
|
||||
{file = "langfuse-2.57.5-py3-none-any.whl", hash = "sha256:5bc53ee33e7e58b4d112abdf971f16bc9e7e8e8ba4690b3c4339d37b83601f80"},
|
||||
{file = "langfuse-2.57.5.tar.gz", hash = "sha256:48b4db5d4e86824153ad6f1e10d14c2c7994bcbf67578c2bdd6786bf3896c3e8"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -3534,41 +3551,41 @@ langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "litellm"
|
||||
version = "1.49.1"
|
||||
version = "1.57.0"
|
||||
description = "Library to easily interface with LLM API providers"
|
||||
optional = false
|
||||
python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
|
||||
files = [
|
||||
{file = "litellm-1.49.1-py3-none-any.whl", hash = "sha256:2ba6689fe4ea3b0d69f56f2843caff6422497489e6252943b13ef1463f016728"},
|
||||
{file = "litellm-1.49.1.tar.gz", hash = "sha256:f51450ad823c8bdf057017009ae8bcce1a2810690b2f0d9dcdaff04ddc68209a"},
|
||||
{file = "litellm-1.57.0-py3-none-any.whl", hash = "sha256:339aec6f3ecac2035bf6311aa8913ce587c9aca2dc7d72a63a210c659e9721ca"},
|
||||
{file = "litellm-1.57.0.tar.gz", hash = "sha256:53a6f2bd9575823e102f7d18dde5cbd2d48eed027cecbb585f18a208605b34c5"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
aiohttp = "*"
|
||||
click = "*"
|
||||
httpx = ">=0.23.0,<0.28.0"
|
||||
importlib-metadata = ">=6.8.0"
|
||||
jinja2 = ">=3.1.2,<4.0.0"
|
||||
jsonschema = ">=4.22.0,<5.0.0"
|
||||
openai = ">=1.51.0"
|
||||
openai = ">=1.55.3"
|
||||
pydantic = ">=2.0.0,<3.0.0"
|
||||
python-dotenv = ">=0.2.0"
|
||||
requests = ">=2.31.0,<3.0.0"
|
||||
tiktoken = ">=0.7.0"
|
||||
tokenizers = "*"
|
||||
|
||||
[package.extras]
|
||||
extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "resend (>=0.8.0,<0.9.0)"]
|
||||
proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "cryptography (>=42.0.5,<43.0.0)", "fastapi (>=0.111.0,<0.112.0)", "fastapi-sso (>=0.10.0,<0.11.0)", "gunicorn (>=22.0.0,<23.0.0)", "orjson (>=3.9.7,<4.0.0)", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.9,<0.0.10)", "pyyaml (>=6.0.1,<7.0.0)", "rq", "uvicorn (>=0.22.0,<0.23.0)"]
|
||||
proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "cryptography (>=43.0.1,<44.0.0)", "fastapi (>=0.115.5,<0.116.0)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=22.0.0,<23.0.0)", "orjson (>=3.9.7,<4.0.0)", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rq", "uvicorn (>=0.22.0,<0.23.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "llama-index-core"
|
||||
version = "0.11.23"
|
||||
version = "0.12.10.post1"
|
||||
description = "Interface between LLMs and your data"
|
||||
optional = true
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
python-versions = "<4.0,>=3.9"
|
||||
files = [
|
||||
{file = "llama_index_core-0.11.23-py3-none-any.whl", hash = "sha256:25a0cb4a055bfb348655ca4acd1b475529bd8537a7b81874ef14ed13f56e06c1"},
|
||||
{file = "llama_index_core-0.11.23.tar.gz", hash = "sha256:e150859696a0eae169fe19323f46e9a31af2c12c3182012e4d0353ea8eb06d24"},
|
||||
{file = "llama_index_core-0.12.10.post1-py3-none-any.whl", hash = "sha256:897e8cd4efeff6842580b043bdf4008ac60f693df1de2bfd975307a4845707c2"},
|
||||
{file = "llama_index_core-0.12.10.post1.tar.gz", hash = "sha256:af27bea4d1494ba84983a649976e60e3de677a73946aa45ed12ce27e3a623ddf"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -3582,13 +3599,13 @@ httpx = "*"
|
|||
nest-asyncio = ">=1.5.8,<2.0.0"
|
||||
networkx = ">=3.0"
|
||||
nltk = ">3.8.1"
|
||||
numpy = "<2.0.0"
|
||||
numpy = "*"
|
||||
pillow = ">=9.0.0"
|
||||
pydantic = ">=2.7.0,<3.0.0"
|
||||
pydantic = ">=2.8.0"
|
||||
PyYAML = ">=6.0.1"
|
||||
requests = ">=2.31.0"
|
||||
SQLAlchemy = {version = ">=1.4.49", extras = ["asyncio"]}
|
||||
tenacity = ">=8.2.0,<8.4.0 || >8.4.0,<9.0.0"
|
||||
tenacity = ">=8.2.0,<8.4.0 || >8.4.0,<10.0.0"
|
||||
tiktoken = ">=0.3.3"
|
||||
tqdm = ">=4.66.1,<5.0.0"
|
||||
typing-extensions = ">=4.5.0"
|
||||
|
|
@ -3890,13 +3907,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "marshmallow"
|
||||
version = "3.23.3"
|
||||
version = "3.24.0"
|
||||
description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
|
||||
optional = true
|
||||
python-versions = ">=3.9"
|
||||
files = [
|
||||
{file = "marshmallow-3.23.3-py3-none-any.whl", hash = "sha256:20c0f8c613f68bcb45b2a0d3282e2f172575560170bf220d67aafb42717910e4"},
|
||||
{file = "marshmallow-3.23.3.tar.gz", hash = "sha256:d586c8685ebdb80bf754e1f96e3f305aaf30951f1fc69175b977453633467e76"},
|
||||
{file = "marshmallow-3.24.0-py3-none-any.whl", hash = "sha256:459922b7a1fd3d29d5082ddcadfcea0efd98985030e71d3ef0dd8f44f406e41d"},
|
||||
{file = "marshmallow-3.24.0.tar.gz", hash = "sha256:378572f727e52123d00de1bdd9b7ea7bed18bbfedc7f9bfbcddaf78925a8d602"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4491,6 +4508,17 @@ traitlets = ">=5.1"
|
|||
docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
|
||||
test = ["pep440", "pre-commit", "pytest", "testpath"]
|
||||
|
||||
[[package]]
|
||||
name = "ndjson"
|
||||
version = "0.3.1"
|
||||
description = "JsonDecoder for ndjson"
|
||||
optional = true
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "ndjson-0.3.1-py2.py3-none-any.whl", hash = "sha256:839c22275e6baa3040077b83c005ac24199b94973309a8a1809be962c753a410"},
|
||||
{file = "ndjson-0.3.1.tar.gz", hash = "sha256:bf9746cb6bb1cb53d172cda7f154c07c786d665ff28341e4e689b796b229e5d6"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "neo4j"
|
||||
version = "5.27.0"
|
||||
|
|
@ -4693,13 +4721,13 @@ tests = ["pytest", "pytest-cov"]
|
|||
|
||||
[[package]]
|
||||
name = "openai"
|
||||
version = "1.52.0"
|
||||
version = "1.55.3"
|
||||
description = "The official Python library for the openai API"
|
||||
optional = false
|
||||
python-versions = ">=3.7.1"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "openai-1.52.0-py3-none-any.whl", hash = "sha256:0c249f20920183b0a2ca4f7dba7b0452df3ecd0fa7985eb1d91ad884bc3ced9c"},
|
||||
{file = "openai-1.52.0.tar.gz", hash = "sha256:95c65a5f77559641ab8f3e4c3a050804f7b51d278870e2ec1f7444080bfe565a"},
|
||||
{file = "openai-1.55.3-py3-none-any.whl", hash = "sha256:2a235d0e1e312cd982f561b18c27692e253852f4e5fb6ccf08cb13540a9bdaa1"},
|
||||
{file = "openai-1.55.3.tar.gz", hash = "sha256:547e85b94535469f137a779d8770c8c5adebd507c2cc6340ca401a7c4d5d16f0"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -5002,8 +5030,8 @@ files = [
|
|||
|
||||
[package.dependencies]
|
||||
numpy = [
|
||||
{version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
|
||||
{version = ">=1.23.2", markers = "python_version >= \"3.11\""},
|
||||
{version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
|
||||
]
|
||||
python-dateutil = ">=2.8.2"
|
||||
pytz = ">=2020.1"
|
||||
|
|
@ -5840,13 +5868,13 @@ yaml = ["pyyaml (>=6.0.1)"]
|
|||
|
||||
[[package]]
|
||||
name = "pygments"
|
||||
version = "2.19.0"
|
||||
version = "2.19.1"
|
||||
description = "Pygments is a syntax highlighting package written in Python."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "pygments-2.19.0-py3-none-any.whl", hash = "sha256:4755e6e64d22161d5b61432c0600c923c5927214e7c956e31c23923c89251a9b"},
|
||||
{file = "pygments-2.19.0.tar.gz", hash = "sha256:afc4146269910d4bdfabcd27c24923137a74d562a23a320a41a55ad303e19783"},
|
||||
{file = "pygments-2.19.1-py3-none-any.whl", hash = "sha256:9ea1544ad55cecf4b8242fab6dd35a93bbce657034b0611ee383099054ab6d8c"},
|
||||
{file = "pygments-2.19.1.tar.gz", hash = "sha256:61c16d2a8576dc0649d9f39e089b5f02bcd27fba10d8fb4dcc28173f7a45151f"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -5915,8 +5943,8 @@ files = [
|
|||
astroid = ">=3.3.8,<=3.4.0-dev0"
|
||||
colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
|
||||
dill = [
|
||||
{version = ">=0.2", markers = "python_version < \"3.11\""},
|
||||
{version = ">=0.3.6", markers = "python_version >= \"3.11\""},
|
||||
{version = ">=0.2", markers = "python_version < \"3.11\""},
|
||||
]
|
||||
isort = ">=4.2.5,<5.13.0 || >5.13.0,<6"
|
||||
mccabe = ">=0.6,<0.8"
|
||||
|
|
@ -7569,13 +7597,13 @@ widechars = ["wcwidth"]
|
|||
|
||||
[[package]]
|
||||
name = "tenacity"
|
||||
version = "8.5.0"
|
||||
version = "9.0.0"
|
||||
description = "Retry code until it succeeds"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687"},
|
||||
{file = "tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78"},
|
||||
{file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"},
|
||||
{file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -8081,13 +8109,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "unstructured"
|
||||
version = "0.16.11"
|
||||
version = "0.16.12"
|
||||
description = "A library that prepares raw documents for downstream ML tasks."
|
||||
optional = true
|
||||
python-versions = "<3.13,>=3.9.0"
|
||||
files = [
|
||||
{file = "unstructured-0.16.11-py3-none-any.whl", hash = "sha256:a92d5bc2c2b7bb23369641fb7a7f0daba1775639199306ce4cd83ca564a03763"},
|
||||
{file = "unstructured-0.16.11.tar.gz", hash = "sha256:33ebf68aae11ce33c8a96335296557b5abd8ba96eaba3e5a1554c0b9eee40bb5"},
|
||||
{file = "unstructured-0.16.12-py3-none-any.whl", hash = "sha256:bcac29ac1b38fba4228c5a1a7721d1aa7c48220f7c1dd43b563645c56e978c49"},
|
||||
{file = "unstructured-0.16.12.tar.gz", hash = "sha256:c3133731c6edb9c2f474e62cb2b560cd0a8d578c4532ec14d8c0941e401770b0"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -8101,6 +8129,7 @@ html5lib = "*"
|
|||
langdetect = "*"
|
||||
lxml = "*"
|
||||
markdown = {version = "*", optional = true, markers = "extra == \"md\""}
|
||||
ndjson = "*"
|
||||
networkx = {version = "*", optional = true, markers = "extra == \"xlsx\""}
|
||||
nltk = "*"
|
||||
numpy = "<2"
|
||||
|
|
@ -8774,4 +8803,4 @@ weaviate = ["weaviate-client"]
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10.0,<3.12"
|
||||
content-hash = "701a9480d2609fbcd64711f226c2e3e82557b04ffba5f9a6e205692eeb26af69"
|
||||
content-hash = "fd5721c44f59d3d7b030b06eb42b3511d0b1214b4a86f52c784dd1f22ff10fd1"
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ classifiers = [
|
|||
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.10.0,<3.12"
|
||||
openai = "1.52.0"
|
||||
openai = "1.55.3"
|
||||
pydantic = "2.8.2"
|
||||
python-dotenv = "1.0.1"
|
||||
fastapi = ">=0.109.2,<0.116.0"
|
||||
|
|
@ -35,7 +35,7 @@ boto3 = "^1.26.125"
|
|||
botocore="^1.35.54"
|
||||
gunicorn = "^20.1.0"
|
||||
sqlalchemy = "2.0.35"
|
||||
instructor = "1.5.2"
|
||||
instructor = "1.7.2"
|
||||
networkx = "^3.2.1"
|
||||
aiosqlite = "^0.20.0"
|
||||
pandas = "2.0.3"
|
||||
|
|
@ -45,7 +45,7 @@ dlt = {extras = ["sqlalchemy"], version = "^1.4.1"}
|
|||
aiofiles = "^23.2.1"
|
||||
qdrant-client = {version = "^1.9.0", optional = true}
|
||||
graphistry = "^0.33.5"
|
||||
tenacity = "^8.4.1"
|
||||
tenacity = "^9"
|
||||
weaviate-client = {version = "4.9.6", optional = true}
|
||||
scikit-learn = "^1.5.0"
|
||||
pypdf = "^4.1.0"
|
||||
|
|
@ -58,7 +58,7 @@ langsmith = {version = "0.2.3", optional = true}
|
|||
langdetect = "1.0.9"
|
||||
posthog = {version = "^3.5.0", optional = true}
|
||||
lancedb = "0.15.0"
|
||||
litellm = "1.49.1"
|
||||
litellm = "1.57.0"
|
||||
groq = {version = "0.8.0", optional = true}
|
||||
langfuse = "^2.32.0"
|
||||
pydantic-settings = "^2.2.1"
|
||||
|
|
@ -69,7 +69,7 @@ alembic = "^1.13.3"
|
|||
asyncpg = {version = "0.30.0", optional = true}
|
||||
pgvector = {version = "^0.3.5", optional = true}
|
||||
psycopg2 = {version = "^2.9.10", optional = true}
|
||||
llama-index-core = {version = "^0.11.22", optional = true}
|
||||
llama-index-core = {version = "^0.12.10", optional = true}
|
||||
deepeval = {version = "^2.0.1", optional = true}
|
||||
transformers = "^4.46.3"
|
||||
pymilvus = {version = "^2.5.0", optional = true}
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue