[全量] 初始化项目代码、配置、文档及Agent协同harness

2026-04-02 11:36:05 +08:00
parent 0553309cdf
commit 87e571d9ec
1133 changed files with 221948 additions and 0 deletions
--- a/langchain-chat/server/model_workers/gemini.py
+++ b/langchain-chat/server/model_workers/gemini.py
@@ -0,0 +1,123 @@
+import sys
+from fastchat.conversation import Conversation
+from server.model_workers.base import *
+from server.utils import get_httpx_client
+from fastchat import conversation as conv
+import json, httpx
+from typing import List, Dict
+from configs import logger, log_verbose
+
+
+class GeminiWorker(ApiModelWorker):
+    def __init__(
+            self,
+            *,
+            controller_addr: str = None,
+            worker_addr: str = None,
+            model_names: List[str] = ["gemini-api"],
+            **kwargs,
+    ):
+        kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
+        kwargs.setdefault("context_len", 4096)
+        super().__init__(**kwargs)
+
+    def create_gemini_messages(self, messages) -> json:
+        has_history = any(msg['role'] == 'assistant' for msg in messages)
+        gemini_msg = []
+
+        for msg in messages:
+            role = msg['role']
+            content = msg['content']
+            if role == 'system':
+                continue
+            if has_history:
+                if role == 'assistant':
+                    role = "model"
+                transformed_msg = {"role": role, "parts": [{"text": content}]}
+            else:
+                if role == 'user':
+                    transformed_msg = {"parts": [{"text": content}]}
+
+            gemini_msg.append(transformed_msg)
+
+        msg = dict(contents=gemini_msg)
+        return msg
+
+    def do_chat(self, params: ApiChatParams) -> Dict:
+        params.load_config(self.model_names[0])
+        data = self.create_gemini_messages(messages=params.messages)
+        generationConfig = dict(
+            temperature=params.temperature,
+            topK=1,
+            topP=1,
+            maxOutputTokens=4096,
+            stopSequences=[]
+        )
+
+        data['generationConfig'] = generationConfig
+        url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent" + '?key=' + params.api_key
+        headers = {
+            'Content-Type': 'application/json',
+        }
+        if log_verbose:
+            logger.info(f'{self.__class__.__name__}:url: {url}')
+            logger.info(f'{self.__class__.__name__}:headers: {headers}')
+            logger.info(f'{self.__class__.__name__}:data: {data}')
+
+        text = ""
+        json_string = ""
+        timeout = httpx.Timeout(60.0)
+        client = get_httpx_client(timeout=timeout)
+        with client.stream("POST", url, headers=headers, json=data) as response:
+            for line in response.iter_lines():
+                line = line.strip()
+                if not line or "[DONE]" in line:
+                    continue
+
+                json_string += line
+
+            try:
+                resp = json.loads(json_string)
+                if 'candidates' in resp:
+                    for candidate in resp['candidates']:
+                        content = candidate.get('content', {})
+                        parts = content.get('parts', [])
+                        for part in parts:
+                            if 'text' in part:
+                                text += part['text']
+                                yield {
+                                    "error_code": 0,
+                                    "text": text
+                                }
+                        print(text)
+            except json.JSONDecodeError as e:
+                print("Failed to decode JSON:", e)
+                print("Invalid JSON string:", json_string)
+
+    def get_embeddings(self, params):
+        print("embedding")
+        print(params)
+
+    def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
+        return conv.Conversation(
+            name=self.model_names[0],
+            system_message="You are a helpful, respectful and honest assistant.",
+            messages=[],
+            roles=["user", "assistant"],
+            sep="\n### ",
+            stop_str="###",
+        )
+
+
+if __name__ == "__main__":
+    import uvicorn
+    from server.utils import MakeFastAPIOffline
+    from fastchat.serve.base_model_worker import app
+
+    worker = GeminiWorker(
+        controller_addr="http://127.0.0.1:20001",
+        worker_addr="http://127.0.0.1:21012",
+    )
+    sys.modules["fastchat.serve.model_worker"].worker = worker
+    MakeFastAPIOffline(app)
+    uvicorn.run(app, port=21012)