add support for cohere (#1849)

### What problem does this PR solve?

_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

---------

Co-authored-by: Zhedong Cen <cenzhedong2@126.com>

rag/llm/chat_model.py

@@ -900,3 +900,84 @@ class OpenAI_APIChat(Base):
             base_url = os.path.join(base_url, "v1")
         model_name = model_name.split("___")[0]
         super().__init__(key, model_name, base_url)
+
+
+class CoHereChat(Base):
+    def __init__(self, key, model_name, base_url=""):
+        from cohere import Client
+
+        self.client = Client(api_key=key)
+        self.model_name = model_name
+
+    def chat(self, system, history, gen_conf):
+        if system:
+            history.insert(0, {"role": "system", "content": system})
+        if "top_p" in gen_conf:
+            gen_conf["p"] = gen_conf.pop("top_p")
+        if "frequency_penalty" in gen_conf and "presence_penalty" in gen_conf:
+            gen_conf.pop("presence_penalty")
+        for item in history:
+            if "role" in item and item["role"] == "user":
+                item["role"] = "USER"
+            if "role" in item and item["role"] == "assistant":
+                item["role"] = "CHATBOT"
+            if "content" in item:
+                item["message"] = item.pop("content")
+        mes = history.pop()["message"]
+        ans = ""
+        try:
+            response = self.client.chat(
+                model=self.model_name, chat_history=history, message=mes, **gen_conf
+            )
+            ans = response.text
+            if response.finish_reason == "MAX_TOKENS":
+                ans += (
+                    "...\nFor the content length reason, it stopped, continue?"
+                    if is_english([ans])
+                    else "······\n由于长度的原因，回答被截断了，要继续吗？"
+                )
+            return (
+                ans,
+                response.meta.tokens.input_tokens + response.meta.tokens.output_tokens,
+            )
+        except Exception as e:
+            return ans + "\n**ERROR**: " + str(e), 0
+
+    def chat_streamly(self, system, history, gen_conf):
+        if system:
+            history.insert(0, {"role": "system", "content": system})
+        if "top_p" in gen_conf:
+            gen_conf["p"] = gen_conf.pop("top_p")
+        if "frequency_penalty" in gen_conf and "presence_penalty" in gen_conf:
+            gen_conf.pop("presence_penalty")
+        for item in history:
+            if "role" in item and item["role"] == "user":
+                item["role"] = "USER"
+            if "role" in item and item["role"] == "assistant":
+                item["role"] = "CHATBOT"
+            if "content" in item:
+                item["message"] = item.pop("content")
+        mes = history.pop()["message"]
+        ans = ""
+        total_tokens = 0
+        try:
+            response = self.client.chat_stream(
+                model=self.model_name, chat_history=history, message=mes, **gen_conf
+            )
+            for resp in response:
+                if resp.event_type == "text-generation":
+                    ans += resp.text
+                    total_tokens += num_tokens_from_string(resp.text)
+                elif resp.event_type == "stream-end":
+                    if resp.finish_reason == "MAX_TOKENS":
+                        ans += (
+                            "...\nFor the content length reason, it stopped, continue?"
+                            if is_english([ans])
+                            else "······\n由于长度的原因，回答被截断了，要继续吗？"
+                        )
+                yield ans
+
+        except Exception as e:
+            yield ans + "\n**ERROR**: " + str(e)
+
+        yield total_tokens