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docs: update readme and docs

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Boris Arzentar 2024-03-30 18:30:23 +01:00
parent d315248bfa
commit 348c87ffe9
2 changed files with 34 additions and 71 deletions
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83
README.md
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@ -55,65 +55,37 @@ poetry add "cognee[weaviate]"
### Setup
Create `.env` file in your project root directory in order to store environment variables such as API keys.
Note: Don't push `.env` file to git repo as it will expose those keys to others.
If cognee is installed with Weaviate as a vector database provider, add Weaviate environment variables:
```
WEAVIATE_URL = {YOUR_WEAVIATE_URL}
WEAVIATE_API_KEY = {YOUR_WEAVIATE_API_KEY}
```
import os
Otherwise if cognee is installed with a default (Qdrant) vector database provider, add Qdrant environment variables:
```
QDRANT_URL = {YOUR_QDRANT_URL}
QDRANT_API_KEY = {YOUR_QDRANT_API_KEY}
```
os.environ["WEAVIATE_URL"] = "YOUR_WEAVIATE_URL"
os.environ["WEAVIATE_API_KEY"] = "YOUR_WEAVIATE_API_KEY"
Add OpenAI API Key environment variable:
```
OPENAI_API_KEY = {YOUR_OPENAI_API_KEY}
```
os.environ["OPENAI_API_KEY"] = "YOUR_OPENAI_API_KEY"
Cognee stores data and system files inside the library directory, which is lost if the library folder is removed.
You can change the directories where cognee will store data and system files by calling config functions:
```
import cognee
cognee.config.system_root_directory(absolute_path_to_directory)
cognee.config.data_root_directory(absolute_path_to_directory)
```
### Run
Add a new piece of information to the storage:
```
import cognee
cognee.add("some_text", dataset_name)
text = """Natural language processing (NLP) is an interdisciplinary
subfield of computer science and information retrieval"""
cognee.add(text) # Add a new piece of information
cognee.cognify() # Use LLMs and cognee to create knowledge
search_results = cognee.search("SIMILARITY", "computer science") # Query cognee for the knowledge
for result_text in search_results[0]:
print(result_text)
cognee.add([
"some_text_1",
"some_text_2",
"some_text_3",
...
])
```
Or
Add alternative data types:
```
cognee.add("file://{absolute_path_to_file}", dataset_name)
cognee.add(
[
"file://{absolute_path_to_file_1}",
"file://{absolute_path_to_file_2}",
"file://{absolute_path_to_file_3}",
...
],
dataset_name
)
```
Or
```
@ -132,28 +104,7 @@ cognee.add("data://{absolute_path_to_directory}", dataset_name)
# This will add just directory 2024 under reports.
```
Use LLMs and cognee to create graphs:
```
cognee.cognify(dataset_name)
```
Render the graph with our util function:
```
from cognee.utils import render_graph
graph_url = await render_graph(graph)
print(graph_url)
```
Query the graph for a piece of information:
```
search_results = cognee.search('SIMILARITY', "query_search")
print(search_results)
```
Read more [here](docs/index.md#run).
## Demo

22
docs/index.md
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@ -34,19 +34,19 @@ Note: Don't push `.env` file to git repo as it will expose those keys to others.
If cognee is installed with Weaviate as a vector database provider, add Weaviate environment variables:
```
WEAVIATE_URL = {YOUR_WEAVIATE_URL}
WEAVIATE_API_KEY = {YOUR_WEAVIATE_API_KEY}
WEAVIATE_URL = "YOUR_WEAVIATE_URL"
WEAVIATE_API_KEY = "YOUR_WEAVIATE_API_KEY"
```
Otherwise if cognee is installed with a default (Qdrant) vector database provider, add Qdrant environment variables:
```
QDRANT_URL = {YOUR_QDRANT_URL}
QDRANT_API_KEY = {YOUR_QDRANT_API_KEY}
QDRANT_URL = "YOUR_QDRANT_URL"
QDRANT_API_KEY = "YOUR_QDRANT_API_KEY"
```
Add OpenAI API Key environment variable:
```
OPENAI_API_KEY = {YOUR_OPENAI_API_KEY}
OPENAI_API_KEY = "YOUR_OPENAI_API_KEY"
```
Cognee stores data and system files inside the library directory, which is lost if the library folder is removed.
@ -59,6 +59,18 @@ cognee.config.system_root_directory(absolute_path_to_directory)
cognee.config.data_root_directory(absolute_path_to_directory)
```
#### Without .env file
```
import os
os.environ["WEAVIATE_URL"] = "YOUR_WEAVIATE_URL"
os.environ["WEAVIATE_API_KEY"] = "YOUR_WEAVIATE_API_KEY"
os.environ["OPENAI_API_KEY"] = "YOUR_OPENAI_API_KEY"
```
### Run
Add a new piece of information to the storage: