Merge pull request #304 from azdolinski/main

Add examples/pipelines/integrations for DifyAI and N8N

examples/pipelines/integrations/dify_pipeline.py

@@ -0,0 +1,84 @@
+from typing import List, Union, Generator, Iterator, Optional
+from pprint import pprint
+import requests, json, warnings
+
+# Uncomment to disable SSL verification warnings if needed.
+# warnings.filterwarnings('ignore', message='Unverified HTTPS request')
+
+class Pipeline:
+    def __init__(self):
+        self.name = "Dify Agent Pipeline"
+        self.api_url = "http://dify.hostname/v1/workflows/run"     # Set correct hostname
+        self.api_key = "app-dify-key"                              # Insert your actual API key here.v 
+        self.api_request_stream = True                             # Dify support stream
+        self.verify_ssl = True
+        self.debug = False
+
+    async def on_startup(self):
+        # This function is called when the server is started.
+        print(f"on_startup: {__name__}")
+        pass
+
+    async def on_shutdown(self): 
+        # This function is called when the server is shutdown.
+        print(f"on_shutdown: {__name__}")
+        pass
+
+    async def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
+        # This function is called before the OpenAI API request is made. You can modify the form data before it is sent to the OpenAI API.
+        print(f"inlet: {__name__}")
+        if self.debug:
+            print(f"inlet: {__name__} - body:")
+            pprint(body)
+            print(f"inlet: {__name__} - user:")
+            pprint(user)
+        return body
+
+    async def outlet(self, body: dict, user: Optional[dict] = None) -> dict:
+        # This function is called after the OpenAI API response is completed. You can modify the messages after they are received from the OpenAI API.
+        print(f"outlet: {__name__}")
+        if self.debug:
+            print(f"outlet: {__name__} - body:")
+            pprint(body)
+            print(f"outlet: {__name__} - user:")
+            pprint(user)
+        return body
+
+    def pipe(self, user_message: str, model_id: str, messages: List[dict], body: dict) -> Union[str, Generator, Iterator]:
+        print(f"pipe: {__name__}")
+
+        if self.debug:
+            print(f"pipe: {__name__} - received message from user: {user_message}")
+
+        # Set reponse mode Dify API parameter
+        if self.api_request_stream is True:
+            response_mode = "streaming"
+        else:
+            response_mode = "blocking"
+
+        # This function triggers the workflow using the specified API.
+        headers = {
+            'Authorization': f'Bearer {self.api_key}',
+            'Content-Type': 'application/json'
+        }
+        data = {
+            "inputs": {"prompt": user_message},
+            "response_mode": response_mode,
+            "user": body["user"]["email"]
+        }
+
+        response = requests.post(self.api_url, headers=headers, json=data, stream=self.api_request_stream, verify=self.verify_ssl)
+        if response.status_code == 200:
+            # Process and yield each chunk from the response
+            for line in response.iter_lines():
+                if line:
+                    try:
+                        # Remove 'data: ' prefix and parse JSON
+                        json_data = json.loads(line.decode('utf-8').replace('data: ', ''))
+                        # Extract and yield only the 'text' field from the nested 'data' object
+                        if 'data' in json_data and 'text' in json_data['data']:
+                            yield json_data['data']['text']
+                    except json.JSONDecodeError:
+                        print(f"Failed to parse JSON: {line}")
+        else:
+            yield f"Workflow request failed with status code: {response.status_code}"

examples/pipelines/integrations/n8n_pipeline.py

@@ -0,0 +1,79 @@
+from typing import List, Union, Generator, Iterator, Optional
+from pprint import pprint
+import requests, json, warnings
+
+# Uncomment to disable SSL verification warnings if needed.
+# warnings.filterwarnings('ignore', message='Unverified HTTPS request')
+
+class Pipeline:
+    def __init__(self):
+        self.name = "N8N Agent Pipeline"
+        self.api_url = "https://n8n.host/webhook/myflow"     # Set correct hostname
+        self.api_key = ""                                    # Insert your actual API key here
+        self.verify_ssl = True
+        self.debug = False
+        # Please note that N8N do not support stream reponses
+
+    async def on_startup(self):
+        # This function is called when the server is started.
+        print(f"on_startup: {__name__}")
+        pass
+
+    async def on_shutdown(self): 
+        # This function is called when the server is shutdown.
+        print(f"on_shutdown: {__name__}")
+        pass
+
+    async def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
+        # This function is called before the OpenAI API request is made. You can modify the form data before it is sent to the OpenAI API.
+        print(f"inlet: {__name__}")
+        if self.debug:
+            print(f"inlet: {__name__} - body:")
+            pprint(body)
+            print(f"inlet: {__name__} - user:")
+            pprint(user)
+        return body
+
+    async def outlet(self, body: dict, user: Optional[dict] = None) -> dict:
+        # This function is called after the OpenAI API response is completed. You can modify the messages after they are received from the OpenAI API.
+        print(f"outlet: {__name__}")
+        if self.debug:
+            print(f"outlet: {__name__} - body:")
+            pprint(body)
+            print(f"outlet: {__name__} - user:")
+            pprint(user)
+        return body
+
+    def pipe(self, user_message: str, model_id: str, messages: List[dict], body: dict) -> Union[str, Generator, Iterator]:
+        # This is where you can add your custom pipelines like RAG.
+        print(f"pipe: {__name__}")
+
+        if self.debug:
+            print(f"pipe: {__name__} - received message from user: {user_message}")
+
+        # This function triggers the workflow using the specified API.
+        headers = {
+            'Authorization': f'Bearer {self.api_key}',
+            'Content-Type': 'application/json'
+        }
+        data = {
+            "inputs": {"prompt": user_message},
+            "user": body["user"]["email"]
+        }
+
+        response = requests.post(self.api_url, headers=headers, json=data, verify=self.verify_ssl)
+        if response.status_code == 200:
+            # Process and yield each chunk from the response
+            try:
+                for line in response.iter_lines():
+                    if line:
+                        # Decode each line assuming UTF-8 encoding and directly parse it as JSON
+                        json_data = json.loads(line.decode('utf-8'))
+                        # Check if 'output' exists in json_data and yield it
+                        if 'output' in json_data:
+                            yield json_data['output']
+            except json.JSONDecodeError as e:
+                print(f"Failed to parse JSON from line. Error: {str(e)}")
+                yield "Error in JSON parsing."
+        else:
+            yield f"Workflow request failed with status code: {response.status_code}"