Perplexity API Fix

Perplexity API Fix

examples/pipelines/providers/perplexity_manifold_pipeline.py

@@ -0,0 +1,140 @@
+from typing import List, Union, Generator, Iterator
+from pydantic import BaseModel
+import os
+import requests
+
+class Pipeline:
+    class Valves(BaseModel):
+        PERPLEXITY_API_BASE_URL: str = "https://api.perplexity.ai"
+        PERPLEXITY_API_KEY: str = ""
+        pass
+
+    def __init__(self):
+        self.type = "manifold"
+        self.name = "Perplexity: "
+
+        self.valves = self.Valves(
+            **{
+                "PERPLEXITY_API_KEY": os.getenv(
+                    "PERPLEXITY_API_KEY", "your-perplexity-api-key-here"
+                )
+            }
+        )
+
+        # Debugging: print the API key to ensure it's loaded
+        print(f"Loaded API Key: {self.valves.PERPLEXITY_API_KEY}")
+
+        # List of models
+        self.pipelines = [
+            {"id": "llama-3-sonar-large-32k-online", "name": "Llama 3 Sonar Large 32K Online"},
+            {"id": "llama-3-sonar-small-32k-online", "name": "Llama 3 Sonar Small 32K Online"},
+            {"id": "llama-3-sonar-large-32k-chat", "name": "Llama 3 Sonar Large 32K Chat"},
+            {"id": "llama-3-sonar-small-32k-chat", "name": "Llama 3 Sonar Small 32K Chat"},
+            {"id": "llama-3-8b-instruct", "name": "Llama 3 8B Instruct"},
+            {"id": "llama-3-70b-instruct", "name": "Llama 3 70B Instruct"},
+            {"id": "mixtral-8x7b-instruct", "name": "Mixtral 8x7B Instruct"},
+            {"id": "related", "name": "Related"}
+        ]
+        pass
+
+    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 stopped.
+        print(f"on_shutdown:{__name__}")
+        pass
+
+    async def on_valves_updated(self):
+        # This function is called when the valves are updated.
+        print(f"on_valves_updated:{__name__}")
+        # No models to fetch, static setup
+        pass
+
+    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__}")
+
+        print(messages)
+        print(user_message)
+
+        headers = {
+            "Authorization": f"Bearer {self.valves.PERPLEXITY_API_KEY}",
+            "Content-Type": "application/json",
+            "accept": "application/json"
+        }
+
+        payload = {
+            "model": model_id,
+            "messages": [
+                {"role": "system", "content": "Be precise and concise."},
+                {"role": "user", "content": user_message}
+            ],
+            "stream": body.get("stream", True),
+            "return_citations": True,
+            "return_images": True
+        }
+
+        if "user" in payload:
+            del payload["user"]
+        if "chat_id" in payload:
+            del payload["chat_id"]
+        if "title" in payload:
+            del payload["title"]
+
+        print(payload)
+
+        try:
+            r = requests.post(
+                url=f"{self.valves.PERPLEXITY_API_BASE_URL}/chat/completions",
+                json=payload,
+                headers=headers,
+                stream=True,
+            )
+
+            r.raise_for_status()
+
+            if body.get("stream", False):
+                return r.iter_lines()
+            else:
+                response = r.json()
+                formatted_response = {
+                    "id": response["id"],
+                    "model": response["model"],
+                    "created": response["created"],
+                    "usage": response["usage"],
+                    "object": response["object"],
+                    "choices": [
+                        {
+                            "index": choice["index"],
+                            "finish_reason": choice["finish_reason"],
+                            "message": {
+                                "role": choice["message"]["role"],
+                                "content": choice["message"]["content"]
+                            },
+                            "delta": {"role": "assistant", "content": ""}
+                        } for choice in response["choices"]
+                    ]
+                }
+                return formatted_response
+        except Exception as e:
+            return f"Error: {e}"
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser(description="Perplexity API Client")
+    parser.add_argument("--api-key", type=str, required=True, help="API key for Perplexity")
+    parser.add_argument("--prompt", type=str, required=True, help="Prompt to send to the Perplexity API")
+
+    args = parser.parse_args()
+
+    pipeline = Pipeline()
+    pipeline.valves.PERPLEXITY_API_KEY = args.api_key
+    response = pipeline.pipe(user_message=args.prompt, model_id="llama-3-sonar-large-32k-online", messages=[], body={"stream": False})
+
+    print("Response:", response)