[Docs] add docs for youtube channel (#1072)
Co-authored-by: Deven Patel <deven298@yahoo.com>
This commit is contained in:
@@ -8,6 +8,7 @@ Embedchain comes with built-in support for various data sources. We handle the c
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<Card title="📰 PDF file" href="/components/data-sources/pdf-file"></Card>
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<Card title="📊 CSV file" href="/components/data-sources/csv"></Card>
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<Card title="📃 JSON file" href="/components/data-sources/json"></Card>
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<Card title="📽️ Youtube Channel" href="/components/data-sources/youtube-channel"></Card>
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<Card title="📺 Youtube" href="/components/data-sources/youtube-video"></Card>
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<Card title="📝 Text" href="/components/data-sources/text"></Card>
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<Card title="📚 Documentation website" href="/components/data-sources/docs-site"></Card>
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20
docs/components/data-sources/youtube-channel.mdx
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20
docs/components/data-sources/youtube-channel.mdx
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@@ -0,0 +1,20 @@
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---
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title: '📽️ Youtube Channel'
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---
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To add all the videos from a youtube channel to your app, use the data_type as `youtube_channel`.
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<Note>
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Make sure you have all the required packages installed before using this data type. You can install them by running the following command in your terminal.
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```bash
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pip install -u "embedchain[youtube]"
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```
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</Note>
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```python
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from embedchain import Pipeline as App
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app = App()
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app.add("@channel_name", data_type="youtube_channel")
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```
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@@ -2,8 +2,7 @@
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title: '📺 Youtube'
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---
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To add any youtube video to your app, use the data_type (first argument to `.add()` method) as `youtube_video`. Eg:
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To add any youtube video to your app, use the data_type as `youtube_video`. Eg:
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```python
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from embedchain import Pipeline as App
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@@ -189,8 +189,7 @@ class EmbedChain(JSONSerializable):
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data_type = detect_datatype(source)
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# `source_hash` is the md5 hash of the source argument
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hash_object = hashlib.md5(str(source).encode("utf-8"))
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source_hash = hash_object.hexdigest()
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source_hash = hashlib.md5(str(source).encode("utf-8")).hexdigest()
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self.user_asks.append([source, data_type.value, metadata])
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@@ -27,6 +27,7 @@ class DirectoryLoader(BaseLoader):
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if not directory_path.is_dir():
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raise ValueError(f"Invalid path: {path}")
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logging.info(f"Loading data from directory: {path}")
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data_list = self._process_directory(directory_path)
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doc_id = hashlib.sha256((str(data_list) + str(directory_path)).encode()).hexdigest()
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@@ -44,6 +45,8 @@ class DirectoryLoader(BaseLoader):
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if file_path.is_file() and (not self.extensions or any(file_path.suffix == ext for ext in self.extensions)):
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loader = self._predict_loader(file_path)
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data_list.extend(loader.load_data(str(file_path))["data"])
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elif file_path.is_dir():
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logging.info(f"Loading data from directory: {file_path}")
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return data_list
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def _predict_loader(self, file_path: Path) -> BaseLoader:
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@@ -358,10 +358,6 @@ def is_valid_json_string(source: str):
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_ = json.loads(source)
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return True
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except json.JSONDecodeError:
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logging.error(
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"Insert valid string format of JSON. \
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Check the docs to see the supported formats - `https://docs.embedchain.ai/data-sources/json`"
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)
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return False
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