Browse Source

[Docs] Documentation updates (#1014)

Deven Patel 1 year ago
parent
commit
b246d9823e

+ 3 - 0
docs/_snippets/missing-data-source-tip.mdx

@@ -1,6 +1,9 @@
 <p>If you can't find the specific data source, please feel free to request through one of the following channels and help us prioritize.</p>
 
 <CardGroup cols={2}>
+  <Card title="Google Form" icon="file" href="https://forms.gle/NDRCKsRpUHsz2Wcm8" color="#7387d0">
+    Fill out this form
+  </Card>
   <Card title="Slack" icon="slack" href="https://join.slack.com/t/embedchain/shared_invite/zt-22uwz3c46-Zg7cIh5rOBteT_xe1jwLDw" color="#4A154B">
     Let us know on our slack community
   </Card>

+ 19 - 0
docs/api-reference/pipeline/delete.mdx

@@ -0,0 +1,19 @@
+---
+title: 🗑 delete
+---
+
+`delete_chat_history()` method allows you to delete all previous messages in a chat history.
+
+## Usage
+
+```python
+from embedchain import Pipeline as App
+
+app = App()
+
+app.add("https://www.forbes.com/profile/elon-musk")
+
+app.chat("What is the net worth of Elon Musk?")
+
+app.delete_chat_history()
+```

+ 1 - 1
docs/api-reference/pipeline/reset.mdx

@@ -14,4 +14,4 @@ app.add("https://www.forbes.com/profile/elon-musk")
 
 # Reset the app
 app.reset()
-```
+```

+ 31 - 1
docs/get-started/faq.mdx

@@ -4,7 +4,7 @@ description: 'Collections of all the frequently asked questions'
 ---
 <AccordionGroup>
 <Accordion title="Does Embedchain support OpenAI's Assistant APIs?">
-Yes, it does. Please refer to the [OpenAI Assistant docs page](/get-started/openai-assistant).
+Yes, it does. Please refer to the [OpenAI Assistant docs page](/examples/openai-assistant).
 </Accordion>
 <Accordion title="How to use MistralAI language model?">
 Use the model provided on huggingface: `mistralai/Mistral-7B-v0.1`
@@ -116,6 +116,36 @@ embedder:
 ```
 </CodeGroup>
 
+</Accordion>
+<Accordion title="How to stream response while using OpenAI model in Embedchain?">
+You can achieve this by setting `stream` to `true` in the config file.
+
+<CodeGroup>
+```yaml openai.yaml
+llm:
+  provider: openai
+  config:
+    model: 'gpt-3.5-turbo'
+    temperature: 0.5
+    max_tokens: 1000
+    top_p: 1
+    stream: true
+```
+
+```python main.py
+import os
+from embedchain import Pipeline as App
+
+os.environ['OPENAI_API_KEY'] = 'sk-xxx'
+
+app = App.from_config(config_path="openai.yaml")
+
+app.add("https://www.forbes.com/profile/elon-musk")
+
+response = app.query("What is the net worth of Elon Musk?")
+# response will be streamed in stdout as it is generated.
+```
+</CodeGroup>
 </Accordion>
 </AccordionGroup>
 

+ 9 - 2
docs/mint.json

@@ -183,7 +183,8 @@
             "api-reference/pipeline/chat",
             "api-reference/pipeline/search",
             "api-reference/pipeline/deploy",
-            "api-reference/pipeline/reset"
+            "api-reference/pipeline/reset",
+            "api-reference/pipeline/delete"
           ]
         },
         "api-reference/store/openai-assistant",
@@ -233,5 +234,11 @@
   },
   "api": {
     "baseUrl": "http://localhost:8080"
-  }
+  },
+  "redirects": [
+    {
+      "source": "/changelog/command-line",
+      "destination": "/get-started/introduction"
+    }
+  ]
 }

+ 3 - 2
embedchain/embedchain.py

@@ -650,7 +650,7 @@ class EmbedChain(JSONSerializable):
         self.db.reset()
         self.cursor.execute("DELETE FROM data_sources WHERE pipeline_id = ?", (self.config.id,))
         self.connection.commit()
-        self.delete_history()
+        self.delete_chat_history()
         # Send anonymous telemetry
         self.telemetry.capture(event_name="reset", properties=self._telemetry_props)
 
@@ -661,5 +661,6 @@ class EmbedChain(JSONSerializable):
             display_format=display_format,
         )
 
-    def delete_history(self):
+    def delete_chat_history(self):
         self.llm.memory.delete_chat_history(app_id=self.config.id)
+        self.llm.update_history(app_id=self.config.id)

+ 1 - 2
embedchain/llm/base.py

@@ -48,8 +48,7 @@ class BaseLlm(JSONSerializable):
     def update_history(self, app_id: str):
         """Update class history attribute with history in memory (for chat method)"""
         chat_history = self.memory.get_recent_memories(app_id=app_id, num_rounds=10)
-        if chat_history:
-            self.set_history([str(history) for history in chat_history])
+        self.set_history([str(history) for history in chat_history])
 
     def add_history(self, app_id: str, question: str, answer: str, metadata: Optional[Dict[str, Any]] = None):
         chat_message = ChatMessage()