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Merge branch 'main' into clelia/citation-finder-and-interactive-tables

Browse Source
This commit is contained in:
Clelia (Astra) Bertelli
2025-07-09 18:07:12 +02:00
parent f1c8933cab 6f24d1af79
commit 337d055a9a
10 changed files with 1178 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.gitignore
+3
View File
@@ -16,6 +16,9 @@ wheels/
# env files
.env
# image files
static/
# audio files
*.mp3
README.md
+34 -3
View File
@@ -4,7 +4,25 @@
https://github.com/user-attachments/assets/7e9cca45-8a4c-4dfa-98d2-2cef147422f2
This project is aimed at producing a fully open-source, [**LlamaCloud**](https//cloud.llamaindex.ai)-backed alternative to NotebookLM.
This project is aimed at producing a fully open-source, [**LlamaCloud**](https://cloud.llamaindex.ai?utm_source=demo&utm_medium=notebookLM)-backed alternative to NotebookLM.
### Prerequisites
This project uses `uv` to manage dependencies. Before you begin, make sure you have `uv` installed.
On macOS and Linux:
```
curl -LsSf https://astral.sh/uv/install.sh | sh
```
On Windows:
```
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```
For more install options, see `uv`'s [official documentation](https://docs.astral.sh/uv/getting-started/installation/).
### Get it up and running!
@@ -25,7 +43,7 @@ Modify the `.env.example` file with your API keys:
- `OPENAI_API_KEY`: find it [on OpenAI Platform](https://platform.openai.com/api-keys)
- `ELEVENLABS_API_KEY`: find it [on ElevenLabs Settings](https://elevenlabs.io/app/settings/api-keys)
- `LLAMACLOUD_API_KEY`: find it [on LlamaCloud Dashboard](https://cloud.llamaindex.ai/)
- `LLAMACLOUD_API_KEY`: find it [on LlamaCloud Dashboard](https://cloud.llamaindex.ai?utm_source=demo&utm_medium=notebookLM)
Rename the file to `.env`:
@@ -33,6 +51,19 @@ Rename the file to `.env`:
mv .env.example .env
```
Activate the virtual environment
(on Windows):
```bash
.\.venv\Scripts\activate
```
(on mac/unix)
```bash
source .venv/bin/activate
```
Now, you will have to execute the following scripts:
```bash
@@ -64,7 +95,7 @@ streamlit run src/notebookllama/Home.py
>
> _You might need to install `ffmpeg` if you do not have it installed already_
And start exploring the app at `http://localhost:8751/`.
And start exploring the app at `http://localhost:8501/`.
### Contributing
pyproject.toml
+8 -2
View File
@@ -1,6 +1,6 @@
[project]
name = "notebookllama"
version = "0.2.0.post1"
version = "0.2.1"
description = "An OSS and LlamaCloud-backed alternative to NotebookLM"
readme = "README.md"
requires-python = ">=3.13"
@@ -12,6 +12,11 @@ dependencies = [
"llama-cloud>=0.1.29",
"llama-cloud-services>=0.6.38",
"llama-index-core>=0.12.44",
"llama-index-embeddings-azure-inference>=0.3.0",
"llama-index-embeddings-bedrock>=0.5.2",
"llama-index-embeddings-cohere>=0.5.1",
"llama-index-embeddings-gemini>=0.3.2",
"llama-index-embeddings-huggingface-api>=0.3.1",
"llama-index-embeddings-openai>=0.3.1",
"llama-index-indices-managed-llama-cloud>=0.6.11",
"llama-index-llms-openai>=0.4.7",
@@ -29,7 +34,8 @@ dependencies = [
"pytest-asyncio>=1.0.0",
"python-dotenv>=1.1.1",
"pyvis>=0.3.2",
"streamlit>=1.46.1"
"streamlit>=1.46.1",
"textual>=3.7.1"
]
[tool.mypy]
src/notebookllama/instrumentation.py
+1 -1
View File
@@ -37,7 +37,7 @@ class OtelTracesSqlEngine:
limit: Optional[int] = None,
) -> Dict[str, Any]:
url = "http://localhost:16686/api/traces"
params = {
params: Dict[str, Union[str, int]] = {
"service": self.service_name,
"start": start_time
or int(time.time() * 1000000) - (24 * 60 * 60 * 1000000),
tools/cli/stylesheets/input.tcss
+19
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@@ -0,0 +1,19 @@
Screen {
align: center top;
}
Label {
align: center top;
content-align: center middle;
width: 100%;
}
#label1 {
color: rgb(83, 200, 0)
}
Input {
align: center middle;
width: 80;
margin: 2;
}
tools/cli/stylesheets/select.tcss
+19
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@@ -0,0 +1,19 @@
Screen {
align: center top;
}
Select {
align: center middle;
width: 60;
margin: 2;
}
Label {
align: center top;
content-align: center middle;
width: 100%;
}
#label1 {
color: rgb(83, 200, 0)
}
tools/cli/utils.py
+293
View File
@@ -0,0 +1,293 @@
from textual import on
from textual.app import App, ComposeResult
from textual.binding import Binding
from textual.widgets import Select, Input, Label, Footer
class DefaultOrCustomApp(App):
CSS_PATH = "stylesheets/select.tcss"
BINDINGS = [
Binding(
key="ctrl+q", action="quit", description="Submit", key_display="ctrl+q"
),
Binding(
key="ctrl+d",
action="toggle_dark",
description="Toggle Dark Theme",
key_display="ctrl+d",
),
]
def compose(self) -> ComposeResult:
yield Label("How do you wish to proceed?", id="label1")
yield Select(
options=[
("With Default Settings", "With Default Settings"),
("With Custom Settings", "With Custom Settings"),
],
prompt="Please select one of the following",
)
yield Footer()
def action_toggle_dark(self) -> None:
self.theme = (
"textual-dark" if self.theme == "textual-light" else "textual-light"
)
@on(Select.Changed)
def select_changed(self, event: Select.Changed) -> None:
self.title = str(event.value)
class SelectEmbeddingApp(App):
CSS_PATH = "stylesheets/select.tcss"
BINDINGS = [
Binding(
key="ctrl+q", action="quit", description="Submit", key_display="ctrl+q"
),
Binding(
key="ctrl+d",
action="toggle_dark",
description="Toggle Dark Theme",
key_display="ctrl+d",
),
]
def compose(self) -> ComposeResult:
yield Label("Embedding Model Selection", id="label1")
yield Select(
options=[
("OpenAI", "OpenAI"),
("Cohere", "Cohere"),
("HuggingFace API", "HuggingFace API"),
("Bedrock", "Bedrock"),
("Gemini", "Gemini"),
("Azure", "Azure"),
],
prompt="Select the embedding model for your LlamaCloud Index",
)
yield Footer()
def action_toggle_dark(self) -> None:
self.theme = (
"textual-dark" if self.theme == "textual-light" else "textual-light"
)
@on(Select.Changed)
def select_changed(self, event: Select.Changed) -> None:
self.title = str(event.value)
class BedrockEmbeddingApp(App):
CSS_PATH = "stylesheets/input.tcss"
BINDINGS = [
Binding(
key="ctrl+q", action="quit", description="Submit", key_display="ctrl+q"
),
Binding(
key="ctrl+d",
action="toggle_dark",
description="Toggle Dark Theme",
key_display="ctrl+d",
),
]
def __init__(self):
super().__init__()
self.form_data = {}
def compose(self) -> ComposeResult:
yield Label("Model and API key", id="label1")
yield Input(placeholder="AWS Region", type="text", id="region")
yield Input(
placeholder="AWS Secret Access Key", type="text", password=True, id="key_id"
)
yield Input(
placeholder="AWS Secret Key ID", type="text", password=True, id="api_key"
)
yield Input(placeholder="Model", type="text", id="model")
yield Footer()
def action_toggle_dark(self) -> None:
self.theme = (
"textual-dark" if self.theme == "textual-light" else "textual-light"
)
def action_quit(self) -> None:
# Capture form data before quitting
self.form_data = {
"region": self.query_one("#region", Input).value,
"key_id": self.query_one("#key_id", Input).value,
"api_key": self.query_one("#api_key", Input).value,
"model": self.query_one("#model", Input).value,
}
self.exit()
class AzureEmbeddingApp(App):
CSS_PATH = "stylesheets/input.tcss"
BINDINGS = [
Binding(
key="ctrl+q", action="quit", description="Submit", key_display="ctrl+q"
),
Binding(
key="ctrl+d",
action="toggle_dark",
description="Toggle Dark Theme",
key_display="ctrl+d",
),
]
def __init__(self):
super().__init__()
self.form_data = {}
def compose(self) -> ComposeResult:
yield Label("Model and API key", id="label1")
yield Input(placeholder="API key", type="text", password=True, id="api_key")
yield Input(placeholder="Endpoint", type="text", id="target_uri")
yield Footer()
def action_toggle_dark(self) -> None:
self.theme = (
"textual-dark" if self.theme == "textual-light" else "textual-light"
)
def action_quit(self) -> None:
# Capture form data before quitting
self.form_data = {
"api_key": self.query_one("#api_key", Input).value,
"target_uri": self.query_one("#target_uri", Input).value,
}
self.exit()
class GeminiEmbeddingApp(App):
CSS_PATH = "stylesheets/input.tcss"
BINDINGS = [
Binding(
key="ctrl+q", action="quit", description="Submit", key_display="ctrl+q"
),
Binding(
key="ctrl+d",
action="toggle_dark",
description="Toggle Dark Theme",
key_display="ctrl+d",
),
]
def __init__(self):
super().__init__()
self.form_data = {}
def compose(self) -> ComposeResult:
yield Label("Model and API key", id="label1")
yield Input(
placeholder="API key",
type="text",
password=True,
id="api_key",
name="api_key",
)
yield Footer()
def action_toggle_dark(self) -> None:
self.theme = (
"textual-dark" if self.theme == "textual-light" else "textual-light"
)
def action_quit(self) -> None:
# Capture form data before quitting
self.form_data = {
"api_key": self.query_one("#api_key", Input).value,
}
self.exit()
class OtherEmbeddingApp(App):
CSS_PATH = "stylesheets/input.tcss"
BINDINGS = [
Binding(
key="ctrl+q", action="quit", description="Submit", key_display="ctrl+q"
),
Binding(
key="ctrl+d",
action="toggle_dark",
description="Toggle Dark Theme",
key_display="ctrl+d",
),
]
def __init__(self):
super().__init__()
self.form_data = {}
def compose(self) -> ComposeResult:
yield Label("Model and API key", id="label1")
yield Input(
placeholder="API key",
type="text",
password=True,
id="api_key",
name="api_key",
)
yield Input(
placeholder="Model name (or Endpoint URL for HF)",
type="text",
id="model",
name="model",
)
yield Footer()
def action_toggle_dark(self) -> None:
self.theme = (
"textual-dark" if self.theme == "textual-light" else "textual-light"
)
def action_quit(self) -> None:
# Capture form data before quitting
self.form_data = {
"api_key": self.query_one("#api_key", Input).value,
"model": self.query_one("#model", Input).value,
}
self.exit()
if __name__ == "__main__":
def default():
print("Default settings chosen")
app1 = DefaultOrCustomApp()
app1.run()
if app1.title == "With Default Settings":
default()
else:
app2 = SelectEmbeddingApp()
app2.run()
if app2.title == "Azure":
app3 = AzureEmbeddingApp()
app3.run()
print(f"API Key: {app3.form_data.get('api_key', '')}")
print(f"Target URI: {app3.form_data.get('target_uri', '')}")
elif app2.title == "Bedrock":
app4 = BedrockEmbeddingApp()
app4.run()
print(f"API Key: {app4.form_data.get('api_key', '')}")
print(f"Key ID: {app4.form_data.get('key_id', '')}")
print(f"Region: {app4.form_data.get('region', '')}")
print(f"Model: {app4.form_data.get('model', '')}")
elif app2.title == "Gemini":
app5 = GeminiEmbeddingApp()
app5.run()
print(f"API Key: {app5.form_data.get('api_key', '')}")
else:
app6 = OtherEmbeddingApp()
app6.run()
print(f"API Key: {app6.form_data.get('api_key', '')}")
print(f"Model: {app6.form_data.get('model', '')}")
tools/create_llama_cloud_index.py
+127 -3
View File
@@ -1,8 +1,21 @@
import os
from dotenv import load_dotenv
from cli.utils import (
DefaultOrCustomApp,
SelectEmbeddingApp,
AzureEmbeddingApp,
GeminiEmbeddingApp,
BedrockEmbeddingApp,
OtherEmbeddingApp,
)
from llama_cloud import (
PipelineCreateEmbeddingConfig_OpenaiEmbedding,
PipelineCreateEmbeddingConfig_AzureEmbedding,
PipelineCreateEmbeddingConfig_BedrockEmbedding,
PipelineCreateEmbeddingConfig_CohereEmbedding,
PipelineCreateEmbeddingConfig_GeminiEmbedding,
PipelineCreateEmbeddingConfig_HuggingfaceApiEmbedding,
PipelineTransformConfig_Advanced,
AdvancedModeTransformConfigChunkingConfig_Sentence,
AdvancedModeTransformConfigSegmentationConfig_Page,
@@ -10,22 +23,133 @@ from llama_cloud import (
)
from llama_cloud.client import LlamaCloud
from llama_index.embeddings.openai import OpenAIEmbedding
from llama_index.embeddings.azure_inference import AzureAIEmbeddingsModel
from llama_index.embeddings.cohere import CohereEmbedding
from llama_index.embeddings.huggingface_api import HuggingFaceInferenceAPIEmbedding
from llama_index.embeddings.gemini import GeminiEmbedding
from llama_index.embeddings.bedrock import BedrockEmbedding
def main():
def default(client: LlamaCloud):
load_dotenv()
embed_model = OpenAIEmbedding(
model="text-embedding-3-small", api_key=os.getenv("OPENAI_API_KEY")
)
client = LlamaCloud(token=os.getenv("LLAMACLOUD_API_KEY"))
embedding_config = PipelineCreateEmbeddingConfig_OpenaiEmbedding(
type="OPENAI_EMBEDDING",
component=embed_model,
)
segm_config = AdvancedModeTransformConfigSegmentationConfig_Page(mode="page")
chunk_config = AdvancedModeTransformConfigChunkingConfig_Sentence(
chunk_size=1024,
chunk_overlap=200,
separator="<whitespace>",
paragraph_separator="\n\n\n",
mode="sentence",
)
transform_config = PipelineTransformConfig_Advanced(
segmentation_config=segm_config,
chunking_config=chunk_config,
mode="advanced",
)
pipeline_request = PipelineCreate(
name="notebooklm_pipeline",
embedding_config=embedding_config,
transform_config=transform_config,
)
pipeline = client.pipelines.upsert_pipeline(request=pipeline_request)
with open(".env", "a") as f:
f.write(f'\nLLAMACLOUD_PIPELINE_ID="{pipeline.id}"')
return 0
def main():
load_dotenv()
client = LlamaCloud(token=os.getenv("LLAMACLOUD_API_KEY"))
app1 = DefaultOrCustomApp()
app1.run()
if app1.title == "With Default Settings":
default(client=client)
else:
app2 = SelectEmbeddingApp()
app2.run()
if app2.title == "Azure":
app3 = AzureEmbeddingApp()
app3.run()
api_key = app3.form_data.get("api_key", "")
endpoint = app3.form_data.get("target_uri", "")
embed_model = AzureAIEmbeddingsModel(credential=api_key, endpoint=endpoint)
embedding_config = PipelineCreateEmbeddingConfig_AzureEmbedding(
type="AZURE_EMBEDDING",
component=embed_model,
)
elif app2.title == "Bedrock":
app4 = BedrockEmbeddingApp()
app4.run()
api_key = app4.form_data.get("api_key", "")
key_id = app4.form_data.get("key_id", "")
region = app4.form_data.get("region", "")
model = app4.form_data.get("model", "")
embed_model = BedrockEmbedding(
model_name=model,
aws_access_key_id=key_id,
aws_secret_access_key=api_key,
region_name=region,
)
embedding_config = PipelineCreateEmbeddingConfig_BedrockEmbedding(
type="BEDROCK_EMBEDDING",
component=embed_model,
)
elif app2.title == "Gemini":
app5 = GeminiEmbeddingApp()
app5.run()
api_key = app5.form_data.get("api_key", "")
embed_model = GeminiEmbedding(api_key=api_key)
embedding_config = PipelineCreateEmbeddingConfig_GeminiEmbedding(
type="GEMINI_EMBEDDING",
component=embed_model,
)
else:
app6 = OtherEmbeddingApp()
app6.run()
api_key = app6.form_data.get("api_key", "")
model = app6.form_data.get("model", "")
if app2.title == "Cohere":
embed_model = CohereEmbedding(
model_name=model, api_key=api_key, cohere_api_key=api_key
)
embedding_config = PipelineCreateEmbeddingConfig_CohereEmbedding(
type="COHERE_EMBEDDING",
component=embed_model,
)
elif app2.title == "OpenAI":
embed_model = OpenAIEmbedding(model=model, api_key=api_key)
embedding_config = PipelineCreateEmbeddingConfig_OpenaiEmbedding(
type="OPENAI_EMBEDDING",
component=embed_model,
)
else:
embed_model = HuggingFaceInferenceAPIEmbedding(
token=api_key, model_name=model
)
embedding_config = (
PipelineCreateEmbeddingConfig_HuggingfaceApiEmbedding(
type="HUGGINGFACE_API_EMBEDDING",
component=embed_model,
)
)
segm_config = AdvancedModeTransformConfigSegmentationConfig_Page(mode="page")
chunk_config = AdvancedModeTransformConfigChunkingConfig_Sentence(
chunk_size=1024,
tools/test_import.py
View File
uv.lock
Generated
+674 -8
View File
@@ -2,6 +2,51 @@ version = 1
revision = 2
requires-python = ">=3.13"
[[package]]
name = "aioboto3"
version = "15.0.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiobotocore", extra = ["boto3"] },
{ name = "aiofiles" },
]
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]
[[package]]
name = "aiobotocore"
version = "2.23.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiohttp" },
{ name = "aioitertools" },
{ name = "botocore" },
{ name = "jmespath" },
{ name = "multidict" },
{ name = "python-dateutil" },
{ name = "wrapt" },
]
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]
[package.optional-dependencies]
boto3 = [
{ name = "boto3" },
]
[[package]]
name = "aiofiles"
version = "24.1.0"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/0b/03/a88171e277e8caa88a4c77808c20ebb04ba74cc4681bf1e9416c862de237/aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c", size = 30247, upload-time = "2024-06-24T11:02:03.584Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/a5/45/30bb92d442636f570cb5651bc661f52b610e2eec3f891a5dc3a4c3667db0/aiofiles-24.1.0-py3-none-any.whl", hash = "sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5", size = 15896, upload-time = "2024-06-24T11:02:01.529Z" },
]
[[package]]
name = "aiohappyeyeballs"
version = "2.6.1"
@@ -45,6 +90,15 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/9d/47/b11d0089875a23bff0abd3edb5516bcd454db3fefab8604f5e4b07bd6210/aiohttp-3.12.13-cp313-cp313-win_amd64.whl", hash = "sha256:5a178390ca90419bfd41419a809688c368e63c86bd725e1186dd97f6b89c2706", size = 446735, upload-time = "2025-06-14T15:15:02.858Z" },
]
[[package]]
name = "aioitertools"
version = "0.12.0"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/06/de/38491a84ab323b47c7f86e94d2830e748780525f7a10c8600b67ead7e9ea/aioitertools-0.12.0.tar.gz", hash = "sha256:c2a9055b4fbb7705f561b9d86053e8af5d10cc845d22c32008c43490b2d8dd6b", size = 19369, upload-time = "2024-09-02T03:33:40.349Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/85/13/58b70a580de00893223d61de8fea167877a3aed97d4a5e1405c9159ef925/aioitertools-0.12.0-py3-none-any.whl", hash = "sha256:fc1f5fac3d737354de8831cbba3eb04f79dd649d8f3afb4c5b114925e662a796", size = 24345, upload-time = "2024-09-02T03:34:59.454Z" },
]
[[package]]
name = "aiosignal"
version = "1.3.2"
@@ -177,6 +231,50 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/84/29/587c189bbab1ccc8c86a03a5d0e13873df916380ef1be461ebe6acebf48d/authlib-1.6.0-py2.py3-none-any.whl", hash = "sha256:91685589498f79e8655e8a8947431ad6288831d643f11c55c2143ffcc738048d", size = 239981, upload-time = "2025-05-23T00:21:43.075Z" },
]
[[package]]
name = "azure-ai-inference"
version = "1.0.0b9"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "azure-core" },
{ name = "isodate" },
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